A method for fast charging lithium ion battery under low temperature environment to inhibit lithium precipitation

Abstract

The application relates to a lithium-ion battery rapid charging method for inhibiting lithium precipitation under a low-temperature environment and belongs to the technical field of new energy automobile power battery management. The method comprises the following steps: firstly, an electrochemical-thermal coupling model is established, and a lithium precipitation safety threshold is set; secondly, a bidirectional pulse heating strategy for inhibiting negative electrode lithium precipitation is adopted, the maximum safety current is dynamically called through a 1Hz bidirectional pulse current and a temperature / SOC three-dimensional safety current atlas; then, a multi-stage constant current charging strategy for inhibiting negative electrode lithium precipitation is adopted, the maximum safety charging current is applied in sections, and an adaptive current reduction compensation mechanism is introduced; finally, a PSO-GA hybrid algorithm is adopted, the heating-charging switching temperature is optimized for a single heating-charging working condition, and the switching temperature and the switching SOC threshold are optimized for a heating-charging-second heating cycle, so that the total time, the total energy consumption and the highest charging SOC are balanced. The application can realize safe and rapid charging without lithium precipitation under a low-temperature environment.

Description

Technical Field

[0001] This invention belongs to the field of power battery management technology for new energy vehicles, and relates to a fast charging method for lithium-ion batteries that suppresses lithium plating under low-temperature conditions. Background Technology

[0002] At low temperatures, the viscosity of the electrolyte inside a lithium-ion battery increases, leading to a significant decrease in ion migration rate. Simultaneously, the electrolyte interphase (SEI) becomes more robust, and charge transfer resistance increases exponentially. These factors collectively cause a sharp drop in usable battery capacity and limited power output. Especially during charging, lithium plating (lithium deposition) is highly likely to occur on the negative electrode surface. This lithium plating side reaction not only accelerates the irreversible loss of active lithium and electrolyte decomposition, resulting in a rapid decline in battery life, but the generated needle-like lithium dendrites can also pierce the separator, inducing serious safety hazards such as internal short circuits, thermal runaway, and even explosions.

[0003] To address this issue, existing external heating technologies (such as heating films and PTC heating) suffer from drawbacks such as long heat conduction paths, low energy utilization, and uneven temperature distribution. While conventional internal heating (such as DC heating) has a high heat generation rate, it is prone to severe capacity decay. Regarding charging strategies, simply reducing the charging current significantly prolongs charging time, failing to meet fast charging requirements. Existing preheating and post-charging solutions often lack systematic constraints on the coupling mechanisms of multiple physical field parameters (such as negative electrode potential and SOC), making it difficult to maximize charging efficiency while ensuring safety. Summary of the Invention

[0004] In view of this, the purpose of this invention is to provide a fast charging method for lithium-ion batteries that suppresses lithium plating in low-temperature environments. Based on an electrochemical-thermal coupling model and lithium plating criteria, and combining a bidirectional pulse heating strategy and a multi-stage constant current charging strategy, a low-temperature fast charging strategy that can effectively suppress lithium plating at the negative electrode is proposed, thereby achieving safe and fast charging of lithium-ion batteries in low-temperature environments.

[0005] To achieve the above objectives, the present invention provides the following technical solution: A fast charging method for lithium-ion batteries that suppresses lithium plating at low temperatures, specifically including the following steps: S1: Construct an electrochemical-thermal coupling model and establish lithium plating criteria; S2: Based on the electrochemical-thermal coupling model and lithium plating criterion, establish safe current amplitude boundaries under different temperatures and states of charge (SOC), including safe current boundaries for heating conditions and safe current boundaries for charging conditions. S3: Based on the safe current amplitude boundary, a bidirectional pulse heating strategy (PP-BPH) and a multi-stage constant current charging strategy (PP-MSCC) to suppress lithium plating on the negative electrode are formulated respectively, forming a complete low-temperature fast charging control method; S4: A multi-objective optimization method for low-temperature fast charging based on the PSO-GA hybrid algorithm is adopted to determine the optimal parameters for heating-charging switching to adapt to different thermal safety constraints.

[0006] Furthermore, in step S1, the electrochemical-thermal coupling model includes an electrochemical mechanism model and a thermal model of the lithium-ion battery; the coupling mechanism between the electrochemical mechanism model and the thermal model is achieved through bidirectional feedback coupling of electrode reaction rate constant, lithium-ion diffusion coefficient, electrolyte ionic conductivity, and temperature parameters via the Arrhenius equation.

[0007] Furthermore, in step S1, the coupling mechanism between the electrochemical mechanism model and the thermal model specifically includes: (1) Parameter transfer from thermal model to electrochemical mechanism model: The thermal model calculates the internal temperature of the battery in real time based on the heat generation (including Joule heat, polarization heat, reaction heat, etc.) and heat dissipation conditions of the battery. T ;temperature T It is input into the electrochemical mechanism model to correct for temperature-dependent electrochemical parameters, including the electrode reaction rate constant. k (Describe the rate of charge transfer reaction), lithium-ion diffusion coefficients in solid and liquid phases. D s , D e Electrolyte ionic conductivity k e ; (2) Parameter correction of the Arrhenius equation: The change of the electrochemical parameters with temperature follows the Arrhenius relation; (3) Update of the electrochemical mechanism model and calculation of heat generation: The corrected electrochemical parameters are substituted into the electrochemical mechanism model to recalculate the key electrical responses of the battery, such as voltage, current distribution, polarization state, and negative electrode potential; at the same time, the electrochemical mechanism model calculates various heat generation sources (reversible entropy heat, polarization heat, ohmic heat, etc.) based on the current temperature and polarization state, and calculates the total heat generation power. Feedback is given to the thermal model; (4) Temperature update of the thermal model: The thermal model uses the total received heat generation power. Solve the heat balance equation and update the battery internal temperature.T And then the electrical parameters for the next time step are corrected again by the Arrhenius formula; this process is repeated in a loop to achieve bidirectional electrothermal coupling.

[0008] Furthermore, in step S1, the lithium plating criterion is: the potential safety threshold for preventing lithium plating on the negative electrode is set to 0.005 V, that is, in order to suppress lithium plating on the negative electrode, the potential difference between the solid and liquid phases at the negative electrode-separator interface is greater than 0.005 V.

[0009] Furthermore, in step S2, establishing the safety boundary of the heating current specifically targets low-temperature heating scenarios. This involves traversing a multi-dimensional environmental mesh and iteratively optimizing the model to find the maximum pulse heating current matrix that the battery can withstand in each state without any negative electrode lithium plating. Specific steps include: (1) Set the heating condition test grid: Set the ambient temperature conditions of the battery and divide the SOC test range and battery temperature distribution test range of the battery into discrete grid nodes; (2) Apply pulse excitation and iterative search: For each grid node, apply a bidirectional pulse current of a preset frequency; (3) Boundary locking and heating spectrum generation: Record the maximum acceptable heating current ratio that can ensure the negative electrode potential is greater than the potential safety threshold at each node; traverse all grid nodes to form a two-dimensional sample matrix, and generate a three-dimensional spectrum of heating current amplitude boundaries containing different battery temperature dimensions and different SOC dimensions through interpolation calculation.

[0010] Furthermore, in step S2, establishing the charging current safety boundary specifically targets multi-stage constant current charging scenarios. Under the dual safety constraints of potential and voltage, it searches for and generates the maximum safe charging current matrix under different states. Specific steps include: (1) Set the charging condition test grid: Set the ambient temperature conditions of the battery and divide the charging process into discrete grid nodes according to the SOC test range and the preset battery temperature range; (2) Apply constant current charging and dual safety constraints: Apply a constant charging current to the current in the electrochemical-thermal coupling model; in the process of finding the maximum current, if the battery terminal voltage reaches the set charging cutoff voltage in advance within the current SOC stage, the current charging current is reduced to half of the previous current and charging continues. (3) Boundary locking and extreme value handling: Find and record the highest acceptable charging current rate that can ensure the negative electrode potential is greater than the potential safety threshold under each battery temperature and SOC node; when the found highest acceptable charging rate is lower than the preset extremely low current threshold, set the charging current of this interval to a fixed small current and no longer divide it into stages until the charging cut-off voltage is reached. (4) Charging map generation: Summarize the maximum charging current ratio obtained at each node to generate a three-dimensional map of the charging current amplitude boundary under different battery temperatures and different states of charge (SOC).

[0011] Furthermore, in step S3, the bidirectional pulse heating strategy for suppressing lithium plating on the negative electrode specifically includes: (1) Selection of heating waveform and frequency: The frequency range is limited based on a comprehensive consideration of battery impedance characteristics, polarization mechanism and hardware and software control capabilities; (2) Step-by-step dynamic amplitude adjustment based on temperature range: When implementing bidirectional pulse heating, the internal temperature and SOC of the battery are collected in real time, and the safe current amplitude is obtained by looking up the table according to the spectrum generated in step S2.

[0012] Furthermore, in step S3, the multi-stage constant current charging strategy for suppressing lithium plating on the negative electrode specifically includes: (1) Charging stage step size division: The preset SOC span is used as the switching step size for each constant current charging stage; (2) Limit current preset and voltage reduction intervention at each stage: During the maximum constant current charging process according to the graph in step S2, in order to ensure the charging capacity, if the voltage reaches the charging cutoff voltage in advance before the battery SOC reaches 90%, the charging current will be reduced to half of the previous value to continue charging the battery, thereby increasing the charging capacity. (3) Extremely low current smoothing: Real-time monitoring of the maximum acceptable charging rate. When the calculated maximum allowable charging rate is lower than 0.2C, the system no longer divides the battery into 10% SOC stages, but directly charges the battery with a fixed constant small current of 0.1C until the charging cutoff voltage is reached.

[0013] Furthermore, in step S4, the low-temperature fast charging multi-objective optimization method based on the PSO-GA hybrid algorithm specifically includes: (1) Extract the total heating-charging time, total energy consumption and the highest SOC during charging as core evaluation indicators and normalize them; (2) Introduce weighting coefficients to construct a multi-objective optimization function that includes three evaluation indicators: total time, total energy consumption, and highest charging SOC; (3) Use the PSO-GA hybrid algorithm to perform global iterative optimization of the multi-objective optimization function and output the optimal switching threshold for multiple working conditions.

[0014] Furthermore, in step S4, the optimal switching threshold for multiple operating conditions is output, specifically including: (1) For a single heating-charging operation, the "switching temperature from heating to charging" is used as the only decision variable, and the optimal switching temperature threshold for a single heating operation is output. (2) For the secondary heating-charging operation, the switching temperature of the first heating-charging, the switching SOC threshold of the first charging-second heating, and the switching temperature of the second heating-charging are used as decision variables to perform joint optimization and output the best three-dimensional parameter combination.

[0015] The beneficial effects of this invention are as follows: (1) The proposed bidirectional pulse heating strategy (PP-BPH) for suppressing lithium plating on the negative electrode aims to suppress lithium plating and rapidly increase the temperature. The current waveform and frequency are optimized. Based on the electrochemical-thermal coupling model, the three-dimensional boundary of pulse current amplitude under different temperatures and charging states is established with the negative electrode potential safety threshold as a constraint. During heating, the maximum safe current within the boundary is dynamically called according to the real-time status, so as to achieve maximum heat generation and rapid temperature increase under the premise of completely avoiding the risk of lithium plating.

[0016] Based on the electrochemical-thermal coupling model, online monitoring of the negative electrode potential can be achieved, providing accurate physical boundaries and theoretical support with a strict lithium plating threshold.

[0017] The bidirectional pulse heating strategy can dynamically adjust the current amplitude to the maximum safe limit based on real-time temperature and SOC, maximizing self-heating power, significantly improving the low-temperature heating rate without damaging battery health.

[0018] (2) The multi-stage constant current charging strategy (PP-MSCC) proposed in this scheme to suppress lithium plating on the negative electrode makes full use of the high rate acceptance capability under low charge state in the charging condition after low temperature heating. The maximum charging current of each stage is determined by the negative electrode potential threshold as a constraint, and an adaptive current reduction compensation mechanism is introduced. When the terminal voltage reaches the cutoff voltage in advance, the current is halved and charging continues, thereby maximizing the charging capacity without lithium plating or overvoltage, and achieving the best balance between charging efficiency and life protection.

[0019] The multi-stage constant current charging strategy utilizes the high current acceptance capability in the low SOC stage, combined with stepped current and adaptive current reduction compensation, to shorten charging time and increase actual charging capacity without lithium plating.

[0020] (3) The low-temperature fast charging multi-objective optimization method based on the PSO-GA hybrid algorithm proposed in this scheme is aimed at extreme low temperature environment. It constructs a "heating-charging-secondary heating" cyclic switching procedure, with total time, total energy consumption and the highest charging SOC as optimization objectives. It integrates the fast convergence of PSO and the global search capability of GA to accurately solve the optimal heating-charging switching temperature threshold and charging-secondary heating switching SOC threshold under thermal safety constraints, and outputs the optimal scheduling instruction.

[0021] The PSO-GA hybrid algorithm is used to optimize the switching temperature and SOC threshold of the "heating-charging-secondary heating" cycle. Under thermal safety constraints, the total time, total energy consumption and the maximum SOC of charging are balanced to achieve the lowest energy consumption and lithium-free safe fast charging in low temperature environments.

[0022] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0023] To make the objectives, technical solutions, and advantages of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein: Figure 1 The coupling mechanism is an electrochemical-thermal coupling model. Figure 2 The safe current amplitude boundary for heating and charging conditions; Figure 3 To suppress lithium plating on the negative electrode, a low-temperature fast charging process is required; Figure 4 A typical EIS curve for a lithium-ion battery; Figure 5 The flowchart is for the PSO-GA hybrid optimization algorithm. Detailed Implementation

[0024] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0025] Please see Figures 1-5The fast charging method for suppressing lithium plating in lithium-ion batteries under low-temperature conditions proposed in this invention is a complete technical solution consisting of multiple steps connected in series. Its core process includes: first, constructing an electrochemical-thermal coupling model and establishing lithium plating criteria (step 1); based on this, obtaining the safe current amplitude boundary at different temperatures and SOCs through model simulation (step 2); then, based on this safety boundary, formulating a bidirectional pulse heating strategy and a multi-stage constant current charging strategy to suppress lithium plating on the negative electrode, forming a complete low-temperature fast charging control method (step 3); finally, to adapt to different thermal safety constraints, using a multi-objective optimization method to determine the optimal parameters for heating-charging switching (step 4). The following steps are described in the order of this technical logic, together constituting the complete implementation of the method.

[0026] The implementation of each step is explained in detail below: Step 1: Establishment and Validation of the Electrochemical-Thermal Coupling Model To more accurately characterize the internal electrochemical reactions and thermal behavior of batteries under low-temperature conditions and to effectively predict lithium plating at the negative electrode, establishing a multi-physics coupled numerical model is particularly necessary. Among these, the electrochemical-thermal coupled model can not only accurately simulate key processes such as electrode reaction kinetics, lithium-ion transport, and heat generation and diffusion, but also assess the risk of lithium plating by calculating the local potential of the negative electrode and determining whether it falls below the lithium metal deposition threshold. Its coupling mechanism is as follows: Figure 1 As shown.

[0027] 1. Electrochemical Mechanism Model of Lithium-ion Batteries Given that the P2D electrochemical model involves multiple partial differential equations, the calculation process is relatively complex. Furthermore, relevant research indicates that under non-extremely harsh conditions, some internal side reactions of the battery have limited impact on its charge-discharge behavior and heat generation. Therefore, to improve simulation efficiency and model convergence, a series of reasonable simplification assumptions were made in the initial stage of model construction. These are as follows: ① Neglect the double-layer effect; ② Neglect the contact resistance between the current collector and the electrode material; ③ Assume that no gas is generated during the charging and discharging process; ④ The volume change caused by the reaction and the resulting internal stress effect are not considered; ⑤ Assume that the active particles inside the positive and negative electrodes are spherical structures of uniform size and distribution.

[0028] The core control system of the P2D model comprises five types of equations: the solid-phase diffusion equation describes the evolution of the lithium concentration gradient within the active particles; the liquid-phase mass conservation equation characterizes ion migration behavior in the electrolyte; the solid / liquid phase potential equations respectively analyze the electron conduction path and ion transport characteristics; and the interfacial reaction kinetic equation quantifies the charge transfer process on the electrode surface. The transport characteristics of porous media are corrected using porosity and tortuosity parameters, and a cross-scale coupled solution is achieved using the volume averaging method. The following sections provide a detailed explanation of each governing equation in the P2D model: (1) Solid-phase lithium ion concentration equation Within solid-phase active material particles, the migration process of lithium ions follows Fick's second law, and its diffusion process in spherical coordinates can be described by the following partial differential equation: (1.1) In the formula, Indicates the concentration of solid-phase lithium ions inside the electrode; t Represents time coordinates; Indicates the solid-phase lithium-ion diffusion coefficient; r This represents the radial coordinates of the spherical particle.

[0029] In this process, lithium ions are embedded in the surface of spherical particles and then extracted from the active material. The initial and boundary conditions are as follows: (1.2) In the formula, Indicates the initial concentration of lithium ions in the solid phase; Indicates the radius of a spherical particle; Indicates the positive and negative terminals of the current source; Indicates the specific surface area of ​​the positive and negative electrodes; F This represents the Faraday constant.

[0030] (2) Solid-state potential equation (Ohm's law) Solid-phase positive and negative electrode potentials The distribution of follows Ohm's law, and its governing equation is: (1.3) In the formula, Indicates the effective ionic conductivity of the solid phase; x Indicates the coordinates along the battery thickness direction; This represents the current density at the positive and negative electrodes of the solid phase.

[0031] The increase in solid-phase current density originates from the current source from the liquid phase entering the solid phase. (1.4) Furthermore, if the current collector side of the solid-phase negative electrode is defined as the potential reference, then the boundary conditions for the potential equations of the solid-phase positive and negative electrodes are: (1.5) In the formula, Indicates the battery input current density; L The total thickness of the battery is indicated; the subscripts n, sep, and p represent the negative electrode, separator, and positive electrode, respectively, and the same applies below.

[0032] (3) Equation for lithium ion concentration in liquid phase (conservation of mass) The governing equation for the lithium ion concentration distribution in the electrolyte is: (1.6) In the formula, It represents the volume fraction of the liquid phase, i.e., porosity; Indicates the lithium-ion mobility coefficient; The effective diffusion coefficient of liquid-phase lithium ions, considering the effect of porosity on the diffusion coefficient, is calculated using the following equation: (1.7) In the formula, represents the diffusion coefficient of the liquid electrolyte; Brugg represents the Bruggeman coefficient, which is usually taken as 1.5.

[0033] Since there is no current source in the diaphragm region, then: (1.8) The initial and boundary conditions for the liquid phase concentration are as follows: (1.9) In the formula, This indicates the initial concentration of lithium ions in the liquid phase.

[0034] (4) Liquid phase potential equation The liquid phase potential consists of two parts: one part is the potential difference caused by Ohm's law, i.e., the Ohmic voltage drop in the liquid phase. ,have: (1.10) In the formula, Indicates the liquid phase current density; The effective conductivity of the liquid phase, considering the effect of porosity on conductivity, is governed by the following equation: (1.11) In the formula, This represents the liquid phase conductivity function.

[0035] Another part of the potential difference is caused by the difference in lithium-ion concentration in the liquid phase, i.e., the concentration polarization potential in the liquid phase. ,have: (1.12) In the formula, Represents the gas constant; This represents the activity coefficient, which is usually taken as 1; Indicates the liquid-phase average molar activity coefficient; This indicates the average battery temperature.

[0036] Therefore, liquid phase potential satisfy: (1.13) Since the increase in liquid current density comes from the current source of the solid phase entering the liquid phase, then: (1.14) The boundary conditions for the liquid phase potential equation are: (1.15) (5) Interface dynamics equations The lithium-ion behavior at the solid-liquid interface can be described by the Butler-Volmer kinetic equation: (1.16) In the formula, This indicates the exchange current density between the positive and negative electrodes; This indicates the overpotential at the positive and negative terminals.

[0037] Among them, the exchange current density satisfy: (1.17) In the formula, Represents the kinetic reaction rate constant. This represents the maximum solid-phase lithium-ion concentration. Lithium ion concentration at the solid-liquid interface, anode-cathode transfer coefficient and The value of is related to the number of electrons in the reaction, and is usually taken as 0.5.

[0038] The overpotentials at the positive and negative terminals satisfy the following: (1.18) In the formula, It is the solid-phase equilibrium potential function of the positive and negative electrodes.

[0039] (6) Terminal voltage equation in P2D model Battery terminal voltage This is the difference in solid-state potential at the current collectors on both sides of the battery, i.e.: (1.19) 2. Thermal Model of Lithium-ion Batteries The macroscopic thermal behavior of lithium-ion batteries mainly involves three aspects: heat generation, heat conduction, and heat dissipation. A three-dimensional thermal model of the battery is established based on the law of conservation of energy to describe the heat generation and transfer processes during charging and discharging. The energy conservation relationship inside the battery can be expressed by the following heat conduction control equation: (1.20) In the formula, Indicates the average density of the battery; This indicates the average specific heat capacity of the battery; , , They represent batteries x, y, z Anisotropic thermal conductivity in three directions; It is the total heat generation rate inside the battery, which includes reversible heat and irreversible heat, i.e.: (1.21) In the formula, This refers to the irreversible polarization heat caused by polarization phenomena in the battery's electrochemical reaction; This represents the reversible entropic heat accompanying the insertion and extraction of lithium ions between the positive and negative electrodes. To represent the solid-phase ohmic heat caused by electron conduction in the solid phase and the liquid-phase ohmic heat caused by impaired ion migration in the electrolyte, their specific expressions are given by the following formulas: (1.22) (1.23) (1.24) In the formula, d U ocv / d T This represents the entropy thermal coefficient of the battery.

[0040] Given that the thermal radiation effect of the battery is usually negligible under most typical operating conditions, the model only considers the convective heat transfer process between the battery system and the ambient medium. Following Newton's law of cooling, its boundary heat transfer condition can be expressed as: (1.25) In the formula, This represents the average convective heat transfer coefficient between the battery system and the ambient medium. This indicates the specific surface area of ​​the battery. Indicates ambient temperature.

[0041] 3. Electrochemical-thermal model coupling mechanism In the electrothermal coupling modeling of batteries, the electrical sub-model and the thermal sub-model form a two-way feedback through temperature-sensitive parameters. The Arrhenius equation, as the core mathematical tool describing the relationship between the reaction rate constant and temperature dependence, is the key bridge to achieve this coupling.

[0042] Specifically, the coupling mechanism is as follows: (1) Parameter transfer from thermal model to electrical model The thermal model calculates the internal temperature of the battery in real time based on the battery's heat generation (including Joule heat, polarization heat, reaction heat, etc.) and heat dissipation conditions. T .temperature T These parameters are input into the electrochemical model to correct for those that are strongly temperature-dependent, including: ①Electrode reaction rate constant k (Describe the speed of the charge transfer reaction); ② Lithium-ion diffusion coefficient between solid and liquid phases D s , D e ; ③ Electrolyte ionic conductivity k e .

[0043] (2) Parameter correction of Arrhenius formula The changes of the above parameters with temperature follow the Arrhenius relation, which has the general form as: (1.26) In the formula, Current temperature T The parameter values ​​below; Reference temperature (Typically, the parameter value at 25°C); The activation energy of the corresponding process is expressed in J·mol⁻¹. -1 ; R Let J be the ideal gas constant. -1 ·K -1 The activation energies corresponding to different parameters can be obtained through experimental measurements or literature. For example, the activation energy of the reaction rate constant is usually much higher than that of the diffusion coefficient, indicating that the charge transfer process is more sensitive to temperature.

[0044] (3) Update of the electrical model and calculation of heat generation The corrected electrochemical parameters were substituted into the electrochemical model to recalculate key electrical responses of the battery, such as voltage and current distribution, polarization state, and negative electrode potential. Simultaneously, based on the current temperature and polarization state, the model calculated various heat generation components (reversible entropic heat, polarization heat, ohmic heat, etc.) and included the total heat generation power. Feedback is given to the thermal model.

[0045] (4) Temperature update of thermal model The thermal model utilizes the received Solve the heat balance equation and update the battery temperature. T This process, along with the Arrhenius formula, drives the correction of electrical parameters for the next time step. This iterative cycle achieves bidirectional electrothermal coupling.

[0046] 4. Validation of the electrochemical-thermal coupling model Verification content: The consistency between the model simulation results and the actual battery test results, specifically verifying the battery's voltage characteristics, temperature rise characteristics, and response characteristics under dynamic operating conditions.

[0047] Verification conditions: (1) Constant current charging condition: Under an ambient temperature of 25℃, constant current charging was performed at 1C, 2C and 3C rates respectively, and the voltage and temperature curves of the simulation and actual measurement were compared.

[0048] (2) Dynamic operating conditions: The dynamic stress test (DST) condition is adopted to simulate the alternating current situation during vehicle operation and compare the voltage curves of simulation and actual measurement.

[0049] Step 2: Obtaining the safe current amplitude 1. Lithium plating criteria By establishing a virtual physical model that reflects the internal electrochemical reaction state of the battery and defining a safety baseline for preventing lithium plating at the negative electrode, a reliable basis for determining the subsequent dynamic search of the safety current boundary is provided. It is generally believed that when the potential difference between the solid and liquid phases of the negative electrode is lower than the lithium plating potential (usually considered to be 0 V vs. Li+ / Li), metallic lithium plating will be induced on the surface of the negative electrode.

[0050] Therefore, in order to suppress lithium plating at the negative electrode, the negative electrode potential at the negative electrode-separator interface should be: (2.1) In the formula, , These represent the solid and liquid phase potentials at the negative electrode-diaphragm interface, respectively.

[0051] Furthermore, the present invention sets the safe potential threshold for preventing lithium plating on the negative electrode to 0.005 V (vs. Li). + The V value ( / Li), rather than the theoretical critical value of 0 V, is essentially a safety compensation introduced by physical polarization and engineering errors. Specific reasons include: ① Polarization error compensation: The impedance of the SEI film increases significantly at extremely low temperatures. Reserving this potential margin can effectively compensate for the micro potential drop of the SEI film that was not taken into account in the model, and avoid the calculated solid-liquid phase potential difference being too high. ② Transient fluctuation buffer: Under bidirectional pulse high-frequency alternating excitation, the lithium ion concentration gradient at the solid-liquid interface changes drastically. This margin can serve as a buffer zone to prevent the local potential from transiently dropping below the lithium plating threshold at the peak of the pulse wave. ③ System engineering margin: Used to cover sensor sampling noise, model discretization bias and system communication delay during the actual operation of the battery management system (BMS), ensuring the thermodynamic conditions that continuously block lithium metal deposition under the closed-loop control strategy.

[0052] 2. Safety boundary matrix for heating current For low-temperature heating scenarios, by traversing a multi-dimensional environmental grid and iteratively optimizing the model, the maximum pulse heating current matrix that the battery can withstand in each state is found under the premise that lithium plating on the negative electrode will not occur.

[0053] The specific implementation steps are as follows: ① Setting the heating condition test grid: First, set the ambient temperature conditions of the battery. In this embodiment, -15℃ is used as an example. Under the ambient temperature conditions, the battery's state of charge (SOC) test range is set to 10% to 90%, with an interval of 10%. The battery temperature distribution test range is set to -20℃ to 40℃. To balance model accuracy and computational efficiency, the battery temperature scanning interval can preferably be 1℃ to 5℃. In this embodiment, 2.5℃ is used as an example. It should be noted that the temperature scanning interval here is the discretization step size used to generate the safe current boundary map. It has a different physical meaning from the temperature switching threshold mentioned in step 3 (which can be the same numerically): the former determines the resolution of the map, while the latter determines the frequency of current updates during the heating process.

[0054] ② Applying Pulse Excitation and Iterative Search: In the electrochemical-thermal coupling model, a bidirectional pulse current of a preset frequency is applied to each set battery temperature and SOC grid node. The selection of this frequency should take into account both heat generation efficiency and polarization suppression. Based on the battery's electrochemical impedance spectroscopy characteristics, it can be selected in the range of 0.1 Hz to 10 Hz. In this embodiment, 1 Hz is used as an example. For detailed argumentation on this frequency range and the method for determining the optimal frequency, please refer to step 3 below.

[0055] ③ Boundary Locking and Heating Map Generation: Record the maximum acceptable heating current ratio that ensures the negative electrode potential is greater than 0.005V at each node; traverse all nodes to form a two-dimensional sample matrix, and generate a three-dimensional boundary map of heating current amplitude containing different battery temperatures and different SOC dimensions through interpolation calculations (e.g., Figure 2 (as shown in (a)).

[0056] 3. Obtaining the safety boundary of charging current For multi-stage constant current charging scenarios, under the dual safety constraints of potential and voltage, the maximum safe charging current matrix under different states is searched and generated.

[0057] The specific implementation steps are as follows: ① Setting the charging condition test grid: First, set the ambient temperature conditions of the battery. In this embodiment, -15℃ is used as an example. Under the ambient temperature conditions, the charging process is divided into intervals according to SOC. The SOC test range is 10% to 90%, and the interval is set to 10%. The battery temperature range is set to 20℃ to 40℃ (this range corresponds to the typical operating temperature range reached by the battery after bidirectional pulse heating in the scenario of heating before charging in this invention). To balance model accuracy and computational efficiency, the temperature scanning interval can preferably be 0.5℃ to 2℃. In this embodiment, 1℃ is used as an example. It should be noted that the SOC stage division here is the simulation scanning step size used to generate the safe current boundary spectrum. It can be numerically consistent with the SOC switching step size of the actual charging stage in the control strategy (see step 3 below), but the physical meaning is different: the former determines the discrete resolution of the spectrum, and the latter determines the current update frequency in the charging process.

[0058] ② Apply constant current charging and dual safety constraints: Apply a constant charging current to the battery in the electrochemical-thermal coupling model. During the search for the maximum current, if the battery terminal voltage reaches the set charging cutoff voltage of 4.19V before reaching 90% SOC, the current charging current is reduced to half of the previous value to continue charging and ensure the charging capacity is achieved.

[0059] ③ Boundary Locking and Extreme Value Handling: Find and record the highest acceptable charging current rate that ensures the negative electrode potential is greater than 0.005V at each battery temperature and SOC node. When the found acceptable charging rate is lower than 0.2C, to reduce the complexity of actual operation, the charging current in this range is directly set to 0.1C and no further stage division is performed until the charging cutoff voltage is reached.

[0060] ④ Charging current map generation: Summarize the maximum charging current rate obtained at each node to generate a three-dimensional charging current boundary map under different battery temperatures and different SOCs (e.g., Figure 2 (as shown in (b)).

[0061] Step 3: Low-Temperature Fast Charging Control Method to Suppress Lithium Plating on the Negative Electrode This step aims to safely and rapidly raise the battery temperature at low temperatures using pulse excitation, based on a preset safe potential threshold and model observation results. Then, it completes constant current charging through staged dynamic current control, thereby suppressing lithium plating on the negative electrode and maximizing charge-discharge efficiency throughout the entire process. Specifically, it consists of two execution stages: "bidirectional pulse heating control" and "multi-stage constant current charging control," as shown in Figure 3.

[0062] 1. Bidirectional pulse heating control to suppress lithium plating on the negative electrode (1) Selection of heating waveform and frequency A bidirectional pulse waveform with excellent heat generation effect is selected as the heating excitation source. Based on the typical EIS curve of a lithium-ion battery (as shown in Figure 4) and the heating test results at different frequencies, preferably, the operating frequency range of the bidirectional pulse current is set to 0.1 Hz ~ 10 Hz; more preferably, the operating frequency range is set to 0.5 Hz ~ 5 Hz; in this embodiment, the optimal operating frequency is selected as 1 Hz.

[0063] The above frequency range is limited based on a comprehensive consideration of battery impedance characteristics, polarization mechanism, and software and hardware control capabilities: ① Avoiding heat generation decay and control burden caused by high frequency: According to the Bernardi heat generation rate equation (3.1), the irreversible Joule heat generated by ohmic internal resistance and polarization internal resistance is positively correlated with the overall battery impedance. As the pulse frequency increases, the battery impedance gradually decreases; and under high-frequency alternation, the current preferentially passes through the double-layer capacitance of the solid-liquid interface, causing the polarization internal resistance, which plays a major role in heat generation, to be "bypassed". Both of these factors together cause a significant decrease in the actual heat generation rate per unit current. In addition, excessively high frequencies have extremely limited effect on improving the upper limit of the safe current for non-lithium plating (there is a marginal diminishing effect), but instead will multiply the switching losses and hardware response burden of the BMS.

[0064] ② Avoiding increased polarization and current limitation caused by low frequencies: When the pulse frequency is too low (e.g., below 0.1 Hz), although the battery is in a high-impedance state, the duration of the single half-wave is prolonged, leading to a significant accumulation of concentration polarization inside the battery. To ensure that the negative electrode potential does not fall below the lithium plating safety threshold, the system will be forced to drastically reduce the maximum pulse current amplitude that the battery can withstand. This precipitous drop in current amplitude will ultimately cause the total heating power to decrease instead of increase, severely weakening the rapid heating effect.

[0065] Therefore, limiting the operating frequency to the range of 0.1 Hz to 10 Hz (1 Hz is the optimal choice) can avoid the polarization current limiting problem at low frequencies and overcome the heat attenuation and hardware overload at high frequencies, thus achieving the optimal solution for the system between ensuring safe input of large current and maximizing Joule heat generation.

[0066] (3.1) In the formula, Battery temperature; and These represent the irreversible Joule heat generated during battery charging and discharging; This represents the reversible heat of reaction generated by the electrochemical reaction during charging and discharging. N The order of the equivalent circuit model.

[0067] (2) Stepped dynamic amplitude adjustment based on temperature range The design aims to dynamically increase the heating current based on the real-time temperature rise of the battery during actual low-temperature heating processes, while avoiding the risk of lithium plating caused by frequent current fluctuations in the system.

[0068] Specific implementation: During bidirectional pulse heating, the battery's internal temperature and SOC are collected in real time, and the safe current amplitude is obtained by looking up the pre-generated spectrum in step 2. Preferably, the temperature switching threshold range is set to 1℃~5℃, more preferably 2℃~3.5℃, and in this embodiment, 2.5℃ is optimally selected. That is, the maximum allowable pulse current amplitude of the next step is switched and called only when the battery temperature rises by a preset threshold.

[0069] The advantages of using the aforementioned threshold range are as follows: a range that is too small will trigger high-frequency and ineffective amplitude modulation commands from the BMS, increasing the system communication load; a range that is too large will cause current step lag, limiting the heating power that could be further increased with rising temperature. This range achieves a balance between increasing the self-heating rate and reducing the hardware control load.

[0070] 2. Multi-stage constant current charging control to suppress lithium plating on the negative electrode (1) Step division of the charging stage The design aims to address the charging conditions after heating at low temperatures by rationally dividing the constant current stage and fully utilizing the high current heat generation effect in the low SOC range to offset the battery cooling caused by the low temperature environment.

[0071] Specific implementation: A preset SOC span is used as the switching step size for each constant current charging stage. Preferably, the SOC switching step size range for the constant current charging stage is set to 5% ~ 20%; more preferably, the step size range is set to 8% ~ 15%; in this embodiment, the optimal switching step size is selected as 10% SOC.

[0072] The above-mentioned step size range is based on a comprehensive consideration of electrochemical safety boundary constraints, battery thermal management requirements, and system control load: ① Avoid excessively large step sizes leading to current limitation and insufficient heat generation: The maximum charging current that a battery can withstand without lithium plating gradually decreases as the State of Charge (SOC) increases. In constant current charging control, if the step size is too large (e.g., above 20% SOC), to ensure absolute no lithium plating throughout the entire range, the system must use the lowest safe current corresponding to the end of that range (i.e., the highest SOC point) as the upper limit of constant current control for the entire stage. This will result in the battery's inability to fully release its inherent high current-accepting capacity in the initial charging stage, severely prolonging the total charging time and weakening the self-heating effect brought by the high current in the low SOC stage, thus failing to effectively maintain the battery's internal temperature.

[0073] ② Avoid high-frequency switching and hardware burden caused by excessively small step sizes: If the step size is too small (e.g., below 5% SOC), theoretically, the stepped control current can more finely match the continuous three-dimensional safety current boundary curve. However, overly dense step divisions will drastically increase the BMS's lookup and optimization frequency. Frequent current jumps and level switching not only cause unnecessary current surges to the charging and discharging equipment hardware, but also, in practical engineering applications, this overly fine division makes a negligible marginal contribution to further shortening charging time.

[0074] Therefore, limiting the SOC switching step size to the range of 5% to 20% (10% SOC is the optimal choice) can make full use of the high rate acceptance capability of the low SOC stage to achieve rapid charging and self-heating, while effectively controlling the hardware switching stress of the system. This achieves the optimal solution between maximizing charging and heat generation efficiency and reducing engineering implementation complexity.

[0075] (2) Limiting current preset and voltage current reduction intervention at each stage During the maximum constant current charging process according to the graph in step 2, in order to ensure the charging capacity, if the voltage reaches the charging cutoff voltage before the battery SOC reaches 90%, the charging current will be reduced to half of the previous value to continue charging the battery, thereby increasing the charging capacity.

[0076] (3) Extremely low current smoothing process It is designed to address the problem of excessive control complexity caused by extremely low temperature conditions or the end of charging, where the allowable charging current is extremely small.

[0077] Specific implementation: Real-time monitoring of the maximum acceptable charging rate. When the calculated maximum allowable charging rate is lower than 0.2C, the system no longer divides the battery into 10% SOC stages, but directly charges the battery with a fixed constant small current of 0.1C until the charging cutoff voltage is reached.

[0078] Step 4: Multi-objective optimization of low-temperature fast charging strategy This step aims to determine the optimal timing (temperature or SOC threshold) for switching between "heating" and "charging" modes in a low-temperature environment, based on the aforementioned established safe current boundary and charging / heating execution strategy, and by comprehensively considering the three mutually constraining physical objectives of "time, energy consumption, and charging power". It employs a particle swarm optimization algorithm combined with a genetic algorithm (PSO-GA) to determine the optimal timing (temperature or SOC threshold) for switching between "heating" and "charging" modes, thereby outputting the optimal global control parameters.

[0079] The specific implementation details are as follows: 1. Evaluation Indicators Establishment and Normalization Three core performance indicators (SCIs) were extracted to evaluate the entire process of low-temperature fast charging: total heating-charging time, total energy consumption, and maximum state of charge (SOC). To eliminate calculation differences caused by different physical dimensions and orders of magnitude, the three indicators were normalized mathematically, mapping their eigenvalues ​​to the interval [0, 1] (0 representing the optimal value and 1 representing the worst). The normalization expressions are shown below: (4.1) In the formula, , , These are the normalized total time, total energy consumption, and maximum state of charge (SOC). , , , , and These represent the maximum and minimum values ​​of the total heating-charging time, total energy consumption, and maximum and minimum SOC during charging within the selected switching temperature range.

[0080] The total time in the heating-charging process consists of the sum of the time consumed in the heating phase and the charging phase, and its expression is as follows: (4.2) In the formula, and These represent the time required for heating and the time required for charging, respectively.

[0081] The total energy consumption during the heating-charging process includes the energy consumed by the battery's internal resistance during both the heating and charging processes. The calculation formula is as follows: (4.3) In the formula, and These are the energy consumption during the heating phase and the energy consumption during the charging phase, respectively.

[0082] The energy loss caused by the battery's internal resistance during heating can be expressed as: (4.4) In the formula, , and These are the battery terminal voltage, battery open-circuit voltage, and heating current, respectively.

[0083] The energy loss during the charging phase due to the battery's internal resistance is expressed as: (4.5) In the formula, This is the charging current.

[0084] Under the low-temperature charging procedure of heating-charging, the actual capacity charged into the battery can be expressed as the total capacity charged into the battery, and its expression is: (4.6) In the formula, and These are the initial SOC of the battery before heating and the nominal capacity of the lithium-ion battery, respectively.

[0085] 2. Construct a comprehensive objective function with weighted coefficients. When performing a heating-charging procedure, the ideal strategy should simultaneously achieve a short total time, low energy consumption, and a high maximum state of charge (SOC). However, there are significant contradictions among these three factors, making it difficult to judge using a single indicator. Therefore, to achieve a reasonable trade-off among these three factors, this invention introduces weighting coefficients and constructs a unified multi-objective optimization function as follows: (4.7) Here, λ1 and λ2 are weighting coefficients, with values ​​ranging from 0 to 1, and satisfying λ1 + λ2 ≤ 1. Based on different application requirements, the weighting coefficients are adjusted to flexibly optimize the strategy and determine the most suitable heating-charging switching temperature, achieving a comprehensive improvement in charging efficiency and energy efficiency at low temperatures.

[0086] 3. Global Iterative Optimization Based on PSO-GA Hybrid Algorithm After determining the weight coefficients, the PSO-GA hybrid optimization algorithm (as shown in Figure 5) is selected. First, the fast convergence speed of the PSO algorithm is utilized to quickly lock the approximate range of the optimal solution, realizing the first stage of optimization and obtaining an initial population with high fitness. Subsequently, the powerful global search capability of the genetic algorithm is combined to further evolve the initial population, enhance the diversity of solutions, improve the ability to escape local optima, and thus improve the overall optimization effect.

[0087] 4. Optimal switching threshold output for multiple operating conditions For different battery thermal safety constraints, parameter optimization is performed for the corresponding operating conditions: (1) Single heating-charging condition: For scenarios with good battery heat dissipation, the "switching temperature from heating to charging" is used as the only decision variable (e.g., finding the optimal value within the range of 20℃~40℃), and the optimal switching temperature threshold for single heating is output.

[0088] (2) Secondary heating-charging condition: For scenarios with high battery thermal safety requirements and low permissible switching temperature, three decision variables are set for joint optimization. The final output is the optimal combination of three-dimensional parameters: ① First heating - charging temperature switching; ② The SOC threshold for switching between the first charge and the second heating; ③ Second heating-charging switching temperature.

[0089] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for fast charging lithium-ion batteries to suppress lithium plating under low-temperature conditions, characterized in that, The method includes the following steps: S1: Construct an electrochemical-thermal coupling model and establish lithium plating criteria; S2: Based on the electrochemical-thermal coupling model and lithium plating criterion, establish safe current amplitude boundaries under different temperatures and charging states, including the safe current boundary under heating conditions and the safe current boundary under charging conditions. S3: Based on the safe current amplitude boundary, a bidirectional pulse heating strategy and a multi-stage constant current charging strategy to suppress lithium plating on the negative electrode are formulated to form a complete low-temperature fast charging control method. S4: A multi-objective optimization method for low-temperature fast charging based on the PSO-GA hybrid algorithm is adopted to determine the optimal parameters for heating-charging switching to adapt to different thermal safety constraints.

2. The lithium-ion battery fast charging method according to claim 1, characterized in that, In step S1, the electrochemical-thermal coupling model includes an electrochemical mechanism model and a thermal model of a lithium-ion battery; the coupling mechanism between the electrochemical mechanism model and the thermal model is achieved through bidirectional feedback coupling of electrode reaction rate constant, lithium-ion diffusion coefficient, electrolyte ionic conductivity and temperature parameters via the Arrhenius equation.

3. The lithium-ion battery fast charging method according to claim 2, characterized in that, In step S1, the coupling mechanism between the electrochemical mechanism model and the thermal model specifically includes: (1) Parameter transfer from thermal model to electrochemical mechanism model: The thermal model calculates the internal temperature of the battery in real time based on the heat generation (including Joule heat, polarization heat, reaction heat, etc.) and heat dissipation conditions of the battery. T ;temperature T It is input into the electrochemical mechanism model to correct electrochemical parameters that are strongly correlated with temperature, including electrode reaction rate constant, lithium-ion diffusion coefficient in solid and liquid phases, and electrolyte ionic conductivity; (2) Parameter correction of the Arrhenius equation: The change of the electrochemical parameters with temperature follows the Arrhenius relation; (3) Update of electrochemical mechanism model and heat generation calculation: The corrected electrochemical parameters are substituted into the electrochemical mechanism model to recalculate the battery voltage, current distribution, polarization state and negative electrode potential; at the same time, the electrochemical mechanism model calculates various heat generation source terms based on the current temperature and polarization state, and feeds back the total heat generation power to the thermal model. (4) Temperature update of thermal model: The thermal model uses the total received heat generation power to solve the heat balance equation and update the internal temperature of the battery. T And then the electrical parameters for the next time step are corrected again by the Arrhenius formula; this process is repeated in a loop to achieve bidirectional electrothermal coupling.

4. The lithium-ion battery fast charging method according to claim 1, characterized in that, In step S1, the lithium plating criterion is: the potential safety threshold for preventing lithium plating on the negative electrode is set to 0.005 V, that is, in order to suppress lithium plating on the negative electrode, the potential difference between the solid and liquid phases at the interface between the negative electrode and the separator must be greater than 0.005 V.

5. The lithium-ion battery fast charging method according to claim 1, characterized in that, In step S2, establishing the safety boundary of the heating current specifically targets low-temperature heating scenarios. This involves traversing a multi-dimensional environmental mesh and iteratively optimizing the model to find the maximum pulse heating current matrix that the battery can withstand in each state without any negative electrode lithium plating. Specific steps include: (1) Set the heating condition test grid: Set the ambient temperature conditions of the battery and divide the battery state of charge (SOC) test range and battery temperature distribution test range into discrete grid nodes; (2) Apply pulse excitation and iterative search: For each grid node, apply a bidirectional pulse current of a preset frequency; (3) Boundary locking and heating spectrum generation: Record the maximum acceptable heating current ratio that can ensure the negative electrode potential is greater than the electric potential safety threshold at each node; traverse all grid nodes to form a two-dimensional sample matrix, and generate a three-dimensional spectrum of heating current amplitude boundaries containing different battery temperature dimensions and different charge state dimensions through interpolation calculation.

6. The lithium-ion battery fast charging method according to claim 1, characterized in that, In step S2, establishing the charging current safety boundary specifically targets the multi-stage constant current charging scenario. Under the dual safety constraints of potential and voltage, the maximum safe charging current matrix under different states is searched and generated. The specific steps include: (1) Set the charging condition test grid: Set the ambient temperature conditions of the battery and divide the charging process into discrete grid nodes according to the state of charge test range and the preset battery temperature range; (2) Apply constant current charging and dual safety constraints: Apply a constant charging current to the current in the electrochemical-thermal coupling model; in the process of finding the maximum current, if the battery terminal voltage reaches the set charging cutoff voltage in advance during the current state of charge stage, the current charging current is reduced to half of the previous current and charging continues. (3) Boundary locking and extreme value handling: Find and record the highest acceptable charging current rate that can ensure the negative electrode potential is greater than the electrical potential safety threshold under each battery temperature and state of charge node; when the found highest acceptable charging rate is lower than the preset extremely low current threshold, set the charging current of this interval to a fixed small current and no longer divide it into stages until the charging cut-off voltage is reached. (4) Charging map generation: Summarize the maximum charging current ratio obtained at each node to generate a three-dimensional map of the charging current amplitude boundary under different battery temperatures and different charging states.

7. The lithium-ion battery fast charging method according to claim 1, characterized in that, In step S3, the bidirectional pulse heating strategy for suppressing lithium plating on the negative electrode specifically includes: (1) Selection of heating waveform and frequency: The frequency range is limited based on a comprehensive consideration of battery impedance characteristics, polarization mechanism and hardware and software control capabilities; (2) Step-by-step dynamic amplitude adjustment based on temperature range: When implementing bidirectional pulse heating, the internal temperature and state of charge of the battery are collected in real time, and the safe current amplitude is obtained by looking up the table according to the spectrum generated in step S2.

8. The lithium-ion battery fast charging method according to claim 1, characterized in that, In step S3, the multi-stage constant current charging strategy for suppressing lithium plating on the negative electrode specifically includes: (1) Charging stage step size division: The preset SOC span is used as the switching step size for each constant current charging stage; (2) Limit current preset and voltage reduction intervention at each stage: During the maximum constant current charging process according to the graph in step S2, in order to ensure the charging capacity, if the voltage reaches the charging cutoff voltage in advance before the battery SOC reaches 90%, the charging current will be reduced to half of the previous value to continue charging the battery, thereby increasing the charging capacity. (3) Extremely low current smoothing: Real-time monitoring of the maximum acceptable charging rate; When the calculated maximum allowable charging rate is lower than 0.2C, the system no longer divides the 10% state of charge stage, but directly charges the battery with a fixed constant small current of 0.1C until the charging cutoff voltage is reached.

9. The lithium-ion battery fast charging method according to claim 1, characterized in that, In step S4, the low-temperature fast charging multi-objective optimization method based on the PSO-GA hybrid algorithm specifically includes: (1) Extract the total heating-charging time, total energy consumption and the highest state of charge during charging as evaluation indicators and normalize them; (2) Introduce weighting coefficients to construct a multi-objective optimization function that includes three evaluation indicators: total time, total energy consumption, and maximum state of charge. (3) Use the PSO-GA hybrid algorithm to perform global iterative optimization of the multi-objective optimization function and output the optimal switching threshold for multiple working conditions.

10. The lithium-ion battery fast charging method according to claim 9, characterized in that, In step S4, the optimal switching threshold for multiple operating conditions is output, specifically including: (1) For a single heating-charging operation, the "switching temperature from heating to charging" is used as the only decision variable, and the optimal switching temperature threshold for a single heating operation is output. (2) For the secondary heating-charging operation, the switching temperature of the first heating-charging, the switching state of charge threshold of the first charging-second heating, and the switching temperature of the second heating-charging are used as decision variables to perform joint optimization and output the best three-dimensional parameter combination.

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