A method and device for early warning of lithium battery dendrite growth

Abstract

The present application relates to the technical field of battery management, and provides a lithium battery dendrite growth early warning method, which comprises the following steps: performing real-time simulation on a lithium battery through an electrochemical model to determine whether lithium dendrites are generated in the lithium battery; when it is determined that lithium dendrites are generated in the lithium battery, simulating the growth trend of the lithium dendrites; and based on the simulated growth trend of the lithium dendrites, judging and early warning the lithium battery dendrite growth. The present application avoids the growth of lithium battery dendrites by early warning and simulation of dendrite formation, thereby protecting the safety of the lithium battery system.

Description

Technical Field

[0001] This invention relates to the field of battery management technology, and more particularly to a method and apparatus for early warning of dendrite growth in lithium batteries. Background Technology

[0002] Against the backdrop of global carbon neutrality, the search for clean energy sources to replace petroleum continues to heat up. Solar, tidal, wind, and hydropower are clean and sustainable energy sources, but the controllability of the energy-generating medium is relatively weak. Lithium-ion batteries are currently the next generation of rechargeable batteries, possessing high energy density and cycle life. They are widely used in mobile communications, digital technology, electric vehicles, and energy storage, and the future demand for lithium batteries and their materials is immeasurable, with a huge market for their supporting upstream and downstream industrial chains.

[0003] With the continuous expansion of lithium battery applications, the safety hazards of lithium batteries are attracting increasing attention. From mobile phones and laptops to electric vehicles, there have been incidents of lithium-ion batteries overheating and even catching fire. Moreover, this phenomenon is no longer limited to counterfeit electronic products. Many lithium-ion battery safety incidents have involved domestic and international brand companies such as Nikon, Panasonic, Samsung, Xiaomi, Lenovo, and Tesla.

[0004] Lithium dendrite formation is one of the fundamental problems affecting the safety and stability of lithium-ion batteries, and a major pain point in the industry. The formation of lithium dendrites leads to instability at the electrode-electrolyte interface during battery cycling; the growth of lithium dendrites damages the solid electrolyte interphase (SEI) film, continuously consumes electrolyte during formation, and causes irreversible deposition of metallic lithium, forming dead lithium, resulting in low coulombic efficiency, and may even puncture the separator, causing internal short circuits in the lithium-ion battery, leading to thermal runaway and combustion or explosion. Lithium dendrite formation is one of the fundamental problems affecting the safety and stability of lithium-ion batteries, and a major pain point in the industry.

[0005] There is still much controversy regarding the growth mechanism of lithium dendrites, and how to monitor the growth mechanism of lithium dendrites and provide timely early warning has become an urgent problem to be solved. Summary of the Invention

[0006] The purpose of this invention is to provide a method and apparatus for early warning of dendrite growth in lithium batteries, in order to solve the above-mentioned problems.

[0007] The technical solution provided by this invention is as follows:

[0008] In some embodiments, the present invention provides a method for early warning of dendrite growth in lithium batteries, comprising:

[0009] The lithium battery was simulated in real time using an electrochemical model to determine whether lithium dendrites were generated in the battery.

[0010] When it is determined that lithium dendrites are generated in the lithium battery, the growth trend of the lithium dendrites is simulated.

[0011] Based on the simulated growth trend of lithium dendrites, the growth of lithium battery dendrites is judged and an early warning is given.

[0012] In some embodiments, simulating the growth trend of lithium dendrites when it is determined that the lithium battery produces lithium dendrites includes:

[0013] The growth and stripping formula of lithium dendrites is coupled into the electrochemical model to obtain a simulation model of the generation direction of lithium dendrites and a simulation model of the stripping of lithium dendrites.

[0014] The growth trend of lithium dendrites is simulated based on the simulation model of the formation direction of lithium dendrites and the simulation model of the stripping of lithium dendrites.

[0015] In some embodiments, the simulation model based on the formation direction of the lithium dendrites simulates the growth trend of the lithium dendrites, including:

[0016] Simulations were performed based on the time-varying function of the phase parameter at the phase transition point along the lithium dendrite formation direction. The time-varying function of the phase parameter at the phase transition point along the lithium dendrite formation direction is as follows:

[0017]

[0018] in, The phase parameter time-varying function represents the phase transition point of the lithium dendrite formation direction; ξ represents the degree of phase evolution of lithium participating in the lithium dendrite growth reaction at a certain point in space; t is the current time; T is the current temperature; Li + The positive electrode represents the solid-phase lithium metal state; f0 characterizes the ease with which the two phases abruptly change; η is the reaction overpotential; c0 is the lithium-ion concentration in the reference electrolyte; α and 1-α are the anode-cathode electrochemical conversion factors; f ns (ξ)=h'(ξ)χψ,f ns χ is the noise random term; χ is a 0-1 random value; ψ is the amplitude; κ is the gradient coefficient; δ is the anisotropy intensity; ω is the anisotropic mode; θ is the relative angle of the interface normal vector; L σ L is the interface migration capability parameter. η is the forward reaction parameter; F is the Faraday constant; R is the universal gas constant.

[0019] In some embodiments, the simulation model based on the stripping of lithium dendrites simulates the growth trend of lithium dendrites, including:

[0020] The time-varying function of the phase parameter at the phase transition point of the lithium dendrite exfoliation was simulated, and the time-varying function of the phase parameter at the phase transition point of the lithium dendrite exfoliation is as follows:

[0021]

[0022] Among them, f d =f step (-φ e / φ d ) represents the electric field activation state of lithium metal; φ d f is the reference potential value. step f is a step function; d These are the state parameters of metallic lithium; is the lithium-ion active concentration; h is a function of lithium-ion concentration.

[0023] In some embodiments, the real-time simulation of the lithium battery using an electrochemical model to determine whether lithium dendrites are generated in the lithium battery includes:

[0024] The real-time operating information of the lithium battery and the physicochemical parameters of the lithium battery are loaded into the electrochemical model of the battery to be simulated.

[0025] The electrochemical model is used to simulate the real-time operating conditions and physicochemical parameters of the lithium battery in order to determine whether lithium dendrites are generated in the lithium battery.

[0026] In some embodiments, the present invention also provides an early warning device for the growth of dendrites in lithium batteries, comprising:

[0027] The judgment module is used to perform real-time simulation of the lithium battery using an electrochemical model to determine whether the lithium battery produces lithium dendrites.

[0028] The simulation module is used to simulate the growth trend of lithium dendrites when it is determined that the lithium battery produces lithium dendrites.

[0029] The early warning module is used to judge and issue early warnings about the growth trend of lithium dendrites in lithium batteries based on the simulated growth trend.

[0030] In some embodiments, the simulation module is further configured to:

[0031] The growth and stripping formula of lithium dendrites is coupled into the electrochemical model to obtain a simulation model of the generation direction of lithium dendrites and a simulation model of the stripping of lithium dendrites.

[0032] The growth trend of lithium dendrites is simulated based on the simulation model of the formation direction of lithium dendrites and the simulation model of the stripping of lithium dendrites.

[0033] In some embodiments, the simulation module is further configured to:

[0034] Simulations were performed based on the time-varying function of the phase parameter at the phase transition point along the lithium dendrite formation direction. The time-varying function of the phase parameter at the phase transition point along the lithium dendrite formation direction is as follows:

[0035]

[0036] Where ξ represents the degree of phase evolution of lithium participating in the growth reaction of lithium dendrites at a certain point in space; t is the current time; T is the current temperature; Li + The positive electrode represents the solid-phase lithium metal state; f0 characterizes the ease with which the two phases abruptly change; η is the reaction overpotential; c0 is the lithium-ion concentration in the reference electrolyte; α and 1-α are the anode-cathode electrochemical conversion factors; f ns (ξ)=h'(ξ)χψ,f ns χ is the noise random term; χ is a 0-1 random value; ψ is the amplitude; κ is the gradient coefficient; δ is the anisotropy intensity; ω is the anisotropic mode; θ is the relative angle of the interface normal vector; L σ L is the interface migration capability parameter. η These are the parameters for the forward reaction.

[0037] In some embodiments, the simulation module is further configured to:

[0038] The time-varying function of the phase parameter at the phase transition point of the lithium dendrite exfoliation was simulated, and the time-varying function of the phase parameter at the phase transition point of the lithium dendrite exfoliation is as follows:

[0039]

[0040] Among them, f d =f step (-φ e / φ d ) represents the electric field activation state of lithium metal; φ d f is the reference potential value. step f is a step function; d These are the state parameters of metallic lithium; is the lithium-ion active concentration; h is a function of lithium-ion concentration.

[0041] In some embodiments, the determining module is further configured to:

[0042] The real-time operating information of the lithium battery and the physicochemical parameters of the lithium battery are loaded into the electrochemical model of the battery to be simulated.

[0043] The electrochemical model is used to simulate the real-time operating conditions and physicochemical parameters of the lithium battery in order to determine whether lithium dendrites are generated in the lithium battery.

[0044] Compared with the prior art, the early warning method and apparatus for lithium battery dendrite growth provided by the present invention can bring the following beneficial effects:

[0045] This invention provides early warning and simulation of dendrite formation, thereby preventing the growth of dendrites in lithium batteries and protecting the safety of lithium battery systems. Attached Figure Description

[0046] The preferred embodiments will be described below in a clear and easy-to-understand manner, with reference to the accompanying drawings, to further explain the above-mentioned characteristics, technical features, advantages, and implementation methods of a method and apparatus for early warning of dendrite growth in lithium batteries.

[0047] Figure 1 This is a flowchart of an embodiment of a method for early warning of dendrite growth in lithium batteries according to the present invention;

[0048] Figure 2 This is a flowchart of another embodiment of the early warning method for dendrite growth in lithium batteries according to the present invention;

[0049] Figure 3 This is a schematic diagram of the coupled simulation of the lithium dendrite model and the electrochemical model of the present invention;

[0050] Figure 4 This is a schematic diagram illustrating the selection of the time-varying function of the phase transition point in this invention;

[0051] Figure 5 This is a schematic diagram of an embodiment of an early warning device for dendrite growth in lithium batteries according to the present invention. Detailed Implementation

[0052] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the specific implementation methods of the present invention will be described below with reference to the accompanying drawings. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings and other implementation methods can be obtained based on these drawings without any creative effort.

[0053] To keep the drawings concise, only the parts relevant to the invention are shown schematically in each figure, and they do not represent the actual structure of the product. Furthermore, for ease of understanding, in some figures, only one of components with the same structure or function is shown schematically, or only one is labeled. In this document, "one" can mean not only "only one" but also "more than one".

[0054] In one embodiment, such as Figure 1 As shown, the present invention provides a method for early warning of dendrite growth in lithium batteries, comprising:

[0055] S101 uses an electrochemical model to simulate the lithium battery in real time to determine whether the lithium battery produces lithium dendrites.

[0056] In this embodiment, an electrochemical model is used to perform calculations and simulations based on the real-time operating conditions and electrochemical parameters of the lithium battery to analyze and obtain the deposition results of the lithium battery. Based on the deposition results of the lithium battery, it is determined whether lithium dendrites have formed in the lithium battery.

[0057] Specifically, real-time operating condition information and physicochemical parameters identified from lithium battery parameters are loaded into the battery electrochemical model that needs to be simulated.

[0058] In this embodiment, the electrochemical model performs real-time simulation of the parameters that have just been loaded.

[0059] It's important to note that lithium deposition on the negative electrode usually precedes the formation of lithium dendrites, and lithium dendrites are a special form of lithium deposition. The transition from moss-like lithium deposition to lithium dendrites occurs when the mass transfer rate cannot keep up with the electrochemical reaction rate, resulting in uneven lithium deposition. At this point, the liquid phase concentration near the lithium deposition site may be 0 or close to 0. The deposition growth, previously guided by a concentration field, transforms into one guided by an electric field, leading to uneven growth, which manifests as dendrites.

[0060] Before determining dendrite formation, lithium deposition must be considered in the electrochemical model. Therefore, the electrochemical model of this invention does not have to be a full-order model or coupled with other fields, but it must be coupled with the effect of lithium deposition.

[0061] S102 When it is determined that lithium dendrites are generated in the lithium battery, the growth trend of the lithium dendrites is simulated.

[0062] In this embodiment, after obtaining the segmented results of lithium dendrite formation in the lithium battery through the deposition results of the lithium battery, if it is determined that the lithium battery produces lithium dendrites, the growth trend of the lithium dendrites is simulated.

[0063] The simulation of lithium dendrite growth includes simulating the direction of lithium dendrite formation and simulating the lithium glass reaction.

[0064] S103 judges and provides early warnings on the growth trend of lithium dendrites obtained from simulation.

[0065] In this embodiment, the dendrite growth at each point of the lithium battery is judged. If the dendrite parameter of the lithium battery reaches the separator, an internal short circuit and electrical breakdown will begin to occur.

[0066] Specifically, each point in the computational domain of a lithium battery simulation has a ξ value. If the ξ value at a point is close to 1, the state at that point is close to the metallic state, i.e., dendrites. If it is close to 0, it is lithium in the electrolyte state.

[0067] If a point in the lithium battery with a dendrite parameter of 1 reaches the separator, that is, if there is a point in the space near the separator with a parameter equal to 1, then it is judged that there is a physical breakdown or potential danger.

[0068] This invention provides early warning and simulation of dendrite formation, thereby preventing the growth of dendrites in lithium batteries and protecting the safety of lithium battery systems.

[0069] In one embodiment, simulating the growth trend of lithium dendrites when it is determined that the lithium battery produces lithium dendrites includes:

[0070] The growth and stripping formula of lithium dendrites is coupled into the electrochemical model to obtain a simulation model of the generation direction of lithium dendrites and a simulation model of the stripping of lithium dendrites.

[0071] The growth trend of lithium dendrites is simulated based on the simulation model of the formation direction of lithium dendrites and the simulation model of the stripping of lithium dendrites.

[0072] In this embodiment, a reversible reaction of lithium dendrite growth and stripping occurs in the lithium dendrite reaction:

[0073] Here, ξ represents the degree of phase evolution of lithium participating in this reaction at a certain point in space. ξ being 0 represents the lithium-ion state in a fully electrolyted solution, i.e., the left side of the chemical reaction equation; Li being the positive electrode in a solid-phase lithium metal state represents the solid-phase lithium metal state, i.e., the right side of the chemical reaction equation. The change of ξ from 0 to 1 at the phase transition interface characterizes the spatial variation of phase evolution.

[0074] Since the overall framework of this embodiment is the numerical simulation framework of the electrochemical model, and the problem studied and simulated is the lithium dendrite problem in lithium batteries, the simulation of lithium dendrite growth needs to be coupled with the numerical simulation framework of the electrochemical model. The following formula can be used to embed the lithium dendrite growth-stripping formula into the simulation of the electrochemical model.

[0075] It is worth noting that dendrites in sodium batteries can actually be simulated using similar formulas. The difference lies in the different material parameters representing material properties, and the fact that dendrite problems in sodium-ion batteries are not their biggest drawback, while dendrite problems in lithium-ion batteries are quite serious.

[0076] In one embodiment, the simulation model based on the formation direction of the lithium dendrites simulates the growth trend of the lithium dendrites, including:

[0077] Simulations were performed based on the time-varying function of the phase parameter at the phase transition point along the lithium dendrite formation direction. The time-varying function of the phase parameter at the phase transition point along the lithium dendrite formation direction is as follows:

[0078]

[0079] Where ξ represents the degree of phase evolution of lithium participating in the growth reaction of lithium dendrites at a certain point in space; t is the current time; T is the current temperature; Li + The positive electrode represents the solid-phase lithium metal state; f0 characterizes the ease with which the two phases abruptly change; η is the reaction overpotential; c0 is the lithium-ion concentration in the reference electrolyte; α and 1-α are the anode-cathode electrochemical conversion factors; f ns (ξ)=h'(ξ)χψ,f ns χ is the noise random term; χ is a 0-1 random value; ψ is the amplitude; κ is the gradient coefficient; δ is the anisotropy intensity; ω is the anisotropic mode; θ is the relative angle of the interface normal vector; L σ L is the interface migration capability parameter. η These are the parameters for the forward reaction.

[0080] In one embodiment, the simulation model based on the stripping of lithium dendrites simulates the growth trend of the lithium dendrites, including:

[0081] The time-varying function of the phase parameter at the phase transition point of the lithium dendrite exfoliation was simulated, and the time-varying function of the phase parameter at the phase transition point of the lithium dendrite exfoliation is as follows:

[0082]

[0083] Among them, f d =f step (-φ e / φ d ) represents the electric field activation state of lithium metal; φ d f is the reference potential value. step f is a step function; d These are the state parameters of metallic lithium; is the lithium-ion active concentration; h is a function of lithium-ion concentration.

[0084] Specifically, the simulation of the formation direction of lithium dendrites and the simulation of the stripping of lithium dendrites are simulations of two antagonistic reactions, which ultimately affect the ξ value at every point in space.

[0085] In this embodiment, the ξ value at each point in space is calculated using the formula corresponding to the simulation model of the lithium dendrite generation direction and the formula corresponding to the simulation model of lithium dendrite stripping, and then it is determined whether the ξ value near the separator is close to 1.

[0086] In one embodiment, the real-time simulation of the lithium battery using an electrochemical model to determine whether lithium dendrites are generated in the lithium battery includes:

[0087] The real-time operating information of the lithium battery and the physicochemical parameters of the lithium battery are loaded into the electrochemical model of the battery to be simulated.

[0088] The electrochemical model is used to simulate the real-time operating conditions and physicochemical parameters of the lithium battery in order to determine whether lithium dendrites are generated in the lithium battery.

[0089] In this embodiment, real-time operating condition information refers to the operating condition information controlling battery charging and discharging.

[0090] For example, real-time operating information includes current-time information, voltage-time information, and power-time information.

[0091] In real-world scenarios, if battery charging and discharging is controlled by current, then the real-time operating information is current-time information. If battery charging and discharging is controlled by voltage, then the real-time operating information is voltage-time information. If battery charging and discharging is controlled by power, then the real-time operating information is power-time information.

[0092] In this embodiment, the lithium battery electrochemical parameters refer to the physicochemical parameters identified by the lithium battery parameters, which, for the electrochemical model, are the electrochemical parameters of the electrochemical model used.

[0093] The deposition results of the lithium battery are obtained by performing calculations and simulations based on the real-time operating information and the electrochemical parameters using an electrochemical model.

[0094] Specifically, real-time operating condition information and physicochemical parameters identified from lithium battery parameters are loaded into the battery electrochemical model that needs to be simulated.

[0095] In this embodiment, the electrochemical model performs real-time simulation of the parameters that have just been loaded.

[0096] It's important to note that lithium deposition on the negative electrode usually precedes the formation of lithium dendrites, and lithium dendrites are a special form of lithium deposition. The transition from moss-like lithium deposition to lithium dendrites occurs when the mass transfer rate cannot keep up with the electrochemical reaction rate, resulting in uneven lithium deposition. At this point, the liquid phase concentration near the lithium deposition site may be 0 or close to 0. The deposition growth, previously guided by a concentration field, transforms into one guided by an electric field, leading to uneven growth, which manifests as dendrites.

[0097] Before determining dendrite formation, lithium deposition must be considered in the electrochemical model. Therefore, the electrochemical model of this invention does not have to be a full-order model or coupled with other fields, but it must be coupled with the effect of lithium deposition.

[0098] In one embodiment, the present invention also provides a method for early warning of dendrite growth in lithium batteries, such as... Figure 2 As shown, it specifically includes:

[0099] This invention provides a numerical simulation and early warning method for dendrite growth in lithium batteries. First, the battery operating conditions, parameters, and physicochemical parameters are loaded. Then, it is determined whether dendrites have formed. Subsequently, dendrite growth is simulated. Finally, the severity of internal short circuits is determined for each point based on the distance of that point from the separator and the length of the dendrite. According to a method for establishing a digital twin system for a lithium battery module based on this invention, the following steps are included:

[0100] Step S1: Loading parameters

[0101] Real-time operating condition information and physicochemical parameters identified from lithium battery parameters are loaded into the battery electrochemical model that needs to be simulated.

[0102] Step S2: Real-time electrochemical simulation and determination of lithium dendrite formation.

[0103] Step S3, Simulation of Lithium Dendrite Growth

[0104] The lithium dendrite reaction involves a reversible process of lithium dendrite growth and exfoliation:

[0105] In this embodiment, ξ is used to represent the degree of phase evolution of lithium participating in the reaction at a certain point in this space. ξ of 0 represents the lithium-ion state in a fully electrolyted solution, i.e., the left side of the chemical reaction equation; ξ of 1 represents the solid-phase lithium metal state, i.e., the right side of the chemical reaction equation. The change of ξ from 0 to 1 at the phase transition interface characterizes the spatial change of phase evolution.

[0106] Since the overall framework of this embodiment is the numerical simulation framework of the electrochemical model, and the problem studied in the simulation is the lithium dendrite problem in lithium batteries, the simulation of lithium dendrite growth needs to be coupled with the numerical simulation framework of the electrochemical model. This can be achieved by embedding the lithium dendrite growth-stripping formula into the electrochemical model simulation according to the following equation. It is worth noting that dendrites in sodium batteries can also be simulated using a similar formula. The difference lies in two aspects: firstly, the material parameters representing material properties will be different; secondly, the dendrite problem in sodium-ion batteries is not their biggest limitation, while the dendrite problem in lithium-ion batteries is quite severe.

[0107] Specifically, such as Figure 3 As shown, the simulation in this embodiment is performed by coupling the lithium dendrite model with the electrochemical model to simulate the growth of lithium dendrites. Figure 3The leftmost diagram in the middle is the voltage simulation diagram of the battery, and the three diagrams on the right are the liquid phase concentration, overpotential, and liquid phase potential diagrams inside at a certain second during the simulation process. The second diagram on the left is the actual growth diagram of lithium dendrites, and the third diagram on the left is the simulated growth diagram.

[0108] Regarding the direction of dendrite generation:

[0109]

[0110] L σ is the interfacial migration ability parameter, and L η is the forward reaction parameter.

[0111] Specifically, ξ at each point in space is calculated according to two PDEs. During visualization, the ξ value is characterized by the shade of color to show the growth of lithium dendrites, but it can be directly judged by the ξ value in the computer.

[0112] f0(ξ) = Wξ 2 (1 - ξ) 2 is an energy barrier functional and can be selected as the characteristic form. Here, a double well is selected. At this time, W / 16 represents the size of the energy barrier between two equilibrium states in the electrode and the electrolyte. A relatively simple one can also be selected as f0 = Wξ(1 - ξ) or f0 = Wξln(1 - ξ), and its physical meaning is to characterize the difficulty of the mutation between two phase states. In fact, when considering the model with thermal coupling, the influence of temperature needs to be considered. At this time, the main situation is that W is a function of T. At this time, there is a reference temperature Tc, and its physical meaning is the phase transition point, that is, without external stimulation, the potential energies of the two states are equal, which can be approximately considered as the phase transition point of water and ice, 0°C. And at other temperatures, there is always a tendency for water to become ice more easily or ice to become water more easily. What appears in the functional for this temperature is

[0113] Specifically, as Figure 4 shown in a), Φ is ξ in the formula, and it is the Landau free energy phase diagram of a simple binary mixture. As Figure 4 shown in B), when T < Tc, it changes from one phase to two phases. The dashed line is the spinodal line.

[0114] Looking at the left side, when T - Tc > 0, the lowest point of the free energy isotherm is one, and when T - Tc < 0, it is two, which represents the number of stable phase states at different temperatures.

[0115] h(ξ) = ξ 3 (ξ - ξ a )(ξ - ξ b ) is an interpolation function that characterizes the influence of the concentration field and the electric field on the dendrite reaction.

[0116] α and 1 - α are the anodic and cathodic electroconversion factors.

[0117] η=φ s -φ e -U eq It is the reaction overpotential, φ s For solid-state potential, φ e U is the liquid phase potential. eq The equilibrium voltage for this reaction is generally taken as 0V at room temperature. c_0 is the reference lithium-ion concentration in the electrolyte, typically taken as 1000 mol / L.

[0118] f ns (ξ)=h'(ξ)χψ,fns is the noise random term, χ is a random value of 0-1, and ψ is the amplitude.

[0119] κ can be extended to κ(θ), where κ(θ) = κ_0[1 + δcosωθ] is related to the anisotropy of surface energy, and κ_0, δ, ω, and θ are the gradient coefficients, anisotropy intensity, anisotropic modes, and relative angles of the interface normal vector, respectively.

[0120] For lithium stripping reaction:

[0121]

[0122] f d =f step (-φ e / φ d ) represents the electric field activation state of lithium metal, φ d For reference potential values, the visual model and environment settings are generally set to 1.0mV, which is actually a function of temperature and pressure, f. step The step function can be used, but the sigmoid function, softmax function, or ReLU function can also be chosen. fd = 1 represents active lithium metal, and fd = 0 represents dead lithium.

[0123] Let h be the lithium-ion active concentration, which is a function of the lithium-ion concentration. Generally, if the lithium-ion concentration is around 1 mol / L or lower, h = 1. After that, the higher the lithium-ion concentration, the smaller h becomes, which characterizes the actual lithium-ion activity level.

[0124] Conversely, dendrite growth affects the electric field:

[0125]

[0126] The effect of dendrite growth on the concentration field:

[0127]

[0128] σ eff It is electrical conductivity. is the lithium-ion liquid-phase diffusion coefficient, F is the Farady constant, Ce is the lithium-ion liquid-phase concentration, Cs is the lithium-ion solid-phase concentration, R is the universal gas constant, T is the Kelvin temperature, and n is the number of lithium moles in the active material compound.

[0129] Step S4: Growth Assessment and Early Warning

[0130] For each point, dendrite growth is assessed. If the dendrite parameter ξ is not 0, an internal short circuit and electrical breakdown will begin to occur when the point reaches the diaphragm.

[0131] If a point with a dendrite parameter ξ of 1 reaches the diaphragm, that is, if there is a point in the space near the diaphragm with a parameter ξ equal to 1, then it is judged that there is physical breakdown or potential danger.

[0132] In one embodiment, such as Figure 5 As shown, the present invention also provides an early warning device for the growth of dendrites in lithium batteries, comprising:

[0133] The judgment module 101 is used to perform real-time simulation of the lithium battery using an electrochemical model to determine whether the lithium battery produces lithium dendrites.

[0134] The simulation module 102 is used to simulate the growth trend of lithium dendrites when it is determined that the lithium battery produces lithium dendrites.

[0135] The early warning module 103 is used to judge and warn of the growth of lithium dendrites in lithium batteries based on the simulated growth trend of the lithium dendrites.

[0136] In one embodiment, the simulation module is further configured to:

[0137] The growth and stripping formula of lithium dendrites is coupled into the electrochemical model to obtain a simulation model of the generation direction of lithium dendrites and a simulation model of the stripping of lithium dendrites.

[0138] The growth trend of lithium dendrites is simulated based on the simulation model of the formation direction of lithium dendrites and the simulation model of the stripping of lithium dendrites.

[0139] In one embodiment, the simulation module is further configured to:

[0140] Simulations were performed based on the time-varying function of the phase parameter at the phase transition point along the lithium dendrite formation direction. The time-varying function of the phase parameter at the phase transition point along the lithium dendrite formation direction is as follows:

[0141]

[0142] Where ξ represents the degree of phase evolution of lithium participating in the growth reaction of lithium dendrites at a certain point in space; t is the current time; T is the current temperature; Li +The positive electrode represents the solid-phase lithium metal state; f0 characterizes the ease with which the two phases abruptly change; η is the reaction overpotential; c0 is the lithium-ion concentration in the reference electrolyte; α and 1-α are the anode-cathode electrochemical conversion factors; f ns (ξ)=h'(ξ)χψ,f ns χ is the noise random term; χ is a 0-1 random value; ψ is the amplitude; κ is the gradient coefficient; δ is the anisotropy intensity; ω is the anisotropic mode; θ is the relative angle of the interface normal vector; L σ L is the interface migration capability parameter. η These are the parameters for the forward reaction.

[0143] In one embodiment, the simulation module is further configured to:

[0144] The time-varying function of the phase parameter at the phase transition point of the lithium dendrite exfoliation was simulated, and the time-varying function of the phase parameter at the phase transition point of the lithium dendrite exfoliation is as follows:

[0145]

[0146] Among them, f d =f step (-φ e / φ d ) represents the electric field activation state of lithium metal; φ d f is the reference potential value. step f is a step function; d These are the state parameters of metallic lithium; is the lithium-ion active concentration; h is a function of lithium-ion concentration.

[0147] In one embodiment, the determining module is further configured to:

[0148] The real-time operating information of the lithium battery and the physicochemical parameters of the lithium battery are loaded into the electrochemical model of the battery to be simulated.

[0149] The electrochemical model is used to simulate the real-time operating conditions and physicochemical parameters of the lithium battery in order to determine whether lithium dendrites are generated in the lithium battery.

[0150] This invention provides early warning and simulation of dendrite formation, thereby preventing the growth of dendrites in lithium batteries and protecting the safety of lithium battery systems.

[0151] It should be noted that the above embodiments can be freely combined as needed. The above description is only a preferred embodiment of the present invention. It should be pointed out that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for early warning of dendrite growth in lithium batteries, characterized in that, include: The lithium battery was simulated in real time using an electrochemical model to determine whether lithium dendrites were generated in the battery. When it is determined that lithium dendrites are generated in the lithium battery, the growth trend of the lithium dendrites is simulated. Based on the simulated growth trend of lithium dendrites, the growth of lithium battery dendrites is judged and an early warning is given. The step of simulating the growth trend of lithium dendrites when it is determined that the lithium battery produces lithium dendrites includes: The growth and stripping formula of lithium dendrites is coupled into the electrochemical model to obtain a simulation model of the generation direction of lithium dendrites and a simulation model of the stripping of lithium dendrites. The growth trend of lithium dendrites is simulated based on the simulation model of the formation direction of lithium dendrites and the simulation model of the stripping of lithium dendrites. The simulation model based on the formation direction of the lithium dendrites simulates the growth trend of the lithium dendrites, including: Simulations were performed based on the time-varying function of the phase parameter at the phase transition point along the lithium dendrite formation direction. The time-varying function of the phase parameter at the phase transition point along the lithium dendrite formation direction is as follows: ； in, The time-varying function of the phase parameter representing the phase transition point of the lithium dendrite formation direction. This indicates the degree of phase evolution of lithium participating in the growth reaction of lithium dendrites at a certain location in space; t is the current time; T is the current temperature; It is a solid-phase lithium metal state that is the positive electrode; Characterizes the ease or difficulty of a sudden transition between two phases; This is the reaction overpotential; For reference electrolyte lithium ion concentration; and The anode-cathode electrical conversion factor; , For noise random terms; It is a random value between 0 and 1. κ is the amplitude; κ is the gradient coefficient; The strength of anisotropy; It is an anisotropic mode; The relative angle between the interface normal vector and the surface normal vector; For interface migration capability parameters, is the forward reaction parameter; F is the Faraday constant; R is the universal gas constant.

2. The early warning method for dendrite growth in lithium batteries according to claim 1, characterized in that, The simulation model based on the stripping of lithium dendrites simulates the growth trend of lithium dendrites, including: The time-varying function of the phase parameter at the phase transition point of the lithium dendrite exfoliation was simulated, and the time-varying function of the phase parameter at the phase transition point of the lithium dendrite exfoliation is as follows: ； in, This is the electric field activated state of metallic lithium; For reference potential value; It is a step function; These are the state parameters of metallic lithium; is the lithium-ion active concentration; h is a function of lithium-ion concentration.

3. The early warning method for dendrite growth in lithium batteries according to claim 2, characterized in that, The method for judging and providing early warning of lithium battery dendrite growth based on the simulated growth trend of lithium dendrites includes: Based on the simulated growth trend of the lithium dendrites, the influence of the lithium dendrite growth on the electric field is calculated. Based on the simulated growth trend of the lithium dendrites, the influence of the lithium dendrite growth on the concentration length was calculated. Based on the data on the influence of lithium dendrite growth on the electric field and the data on the influence of lithium dendrite growth on the concentration, the growth of lithium dendrites in lithium batteries is judged and an early warning is issued.

4. The early warning method for dendrite growth in lithium batteries according to any one of claims 1 to 3, characterized in that, The method of performing real-time simulation of a lithium battery using an electrochemical model to determine whether lithium dendrites are generated in the lithium battery includes: The real-time operating information of the lithium battery and the physicochemical parameters of the lithium battery are loaded into the electrochemical model of the battery to be simulated. The electrochemical model is used to simulate the real-time operating conditions and physicochemical parameters of the lithium battery in order to determine whether lithium dendrites are generated in the lithium battery.

5. An early warning device for dendrite growth in lithium batteries, characterized in that, include: The judgment module is used to perform real-time simulation of the lithium battery using an electrochemical model to determine whether the lithium battery produces lithium dendrites. The simulation module is used to simulate the growth trend of lithium dendrites when it is determined that the lithium battery produces lithium dendrites. The early warning module is used to judge and warn of the growth of lithium dendrites in lithium batteries based on the simulated growth trend of the lithium dendrites. The simulation module is further configured to: The growth and stripping formula of lithium dendrites is coupled into the electrochemical model to obtain a simulation model of the generation direction of lithium dendrites and a simulation model of the stripping of lithium dendrites. The growth trend of lithium dendrites is simulated based on the simulation model of the formation direction of lithium dendrites and the simulation model of the stripping of lithium dendrites. The simulation module is also used for: Simulations were performed based on the time-varying function of the phase parameter at the phase transition point along the lithium dendrite formation direction. The time-varying function of the phase parameter at the phase transition point along the lithium dendrite formation direction is as follows: ； in, The time-varying function of the phase parameter representing the phase transition point of the lithium dendrite formation direction. This indicates the degree of phase evolution of lithium participating in the growth reaction of lithium dendrites at a certain location in space; t is the current time; T is the current temperature; It is a solid-phase lithium metal state that is the positive electrode; Characterizes the ease or difficulty of a sudden transition between two phases; This is the reaction overpotential; For reference electrolyte lithium ion concentration; and The anode-cathode electrical conversion factor; , For noise random terms; It is a random value between 0 and 1. κ is the amplitude; κ is the gradient coefficient; The strength of anisotropy; It is an anisotropic mode; The relative angle between the interface normal vector and the surface normal vector; For interface migration capability parameters, is the forward reaction parameter; F is the Faraday constant; R is the universal gas constant.

6. The early warning device for lithium battery dendrite growth according to claim 5, characterized in that, The simulation module is also used for: The time-varying function of the phase parameter at the phase transition point of the lithium dendrite exfoliation was simulated, and the time-varying function of the phase parameter at the phase transition point of the lithium dendrite exfoliation is as follows: ； in, This is the electric field activated state of metallic lithium; For reference potential value; It is a step function; These are the state parameters of metallic lithium; is the lithium-ion active concentration; h is a function of lithium-ion concentration.

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