Material proportioning parameter forming method of high-voltage-resistant high-specific-energy lithium ion battery

Abstract

The invention discloses a method for forming material proportioning parameters of a high-voltage-resistant high-specific-energy lithium ion battery, belongs to the technical field of lithium ions, and aims to solve the problem that the energy density and the working voltage of the battery are limited due to the fact that too high voltage is difficult to bear, and comprises the steps of selecting and optimizing a positive electrode material, selecting a ternary material NCM811 and selecting and optimizing a negative electrode material. The method comprises the following steps: selecting a graphite and silicon composite material, selecting and optimizing a conductive additive, selecting a carbon nanotube as the conductive additive, selecting and optimizing an electrolyte, selecting and optimizing a diaphragm material and selecting a polyolefin diaphragm; the influence of different material ratios on the battery performance is predicted through simulation calculation, and battery assembling and testing are carried out; the specific energy and the high-voltage resistance of the lithium ion battery can be remarkably improved through accurate proportioning and parameter optimization of the positive and negative electrode materials, the electrolyte, the conductive additive and the diaphragm material.

Description

Technical Field

[0001] The invention belongs to the technical field of lithium ions, and in particular relates to a method for forming material ratio parameters of a high-voltage-resistant and high-energy-density lithium ion battery. Background Art

[0002] Lithium-ion batteries have outstanding advantages such as high energy density, long cycle life and no pollution. They have become the mainstream of the battery market and have begun to be used to drive electric vehicles. However, with the large-scale application of lithium-ion batteries, people are increasingly concerned about the price and limited resources of lithium. In recent years, many new alternative energy storage batteries have emerged and developed rapidly, mainly including secondary batteries such as sodium ions, potassium ions, magnesium ions, and calcium ions. Potassium-ion batteries have many advantages, among which potassium sources are cheap and abundant in the earth's crust. The standard reduction potential of potassium-ion batteries is closest to that of lithium-ion batteries, so the energy density is high, and the high electrochemical activity of potassium-ion battery electrolytes is conducive to the transmission of ions and electrons.

[0003] Existing lithium-ion batteries have a narrow voltage range and a short cycle life. Traditional lithium batteries cannot withstand excessively high voltages due to electrolyte decomposition and electrode material degradation, which limits the battery's energy density and operating voltage.

[0004] Therefore, a method for forming material ratio parameters of a high-voltage-resistant and high-energy-density lithium-ion battery is needed to solve the problem in the prior art that the battery is difficult to withstand excessively high voltages, thereby limiting the energy density and operating voltage of the battery. Summary of the invention

[0005] The object of the present invention is to provide a method for forming material ratio parameters of a high-voltage-resistant and high-energy-density lithium-ion battery, so as to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solution: a method for forming material ratio parameters of a high-voltage-resistant high-energy-density lithium-ion battery, comprising:

[0007] S1. Select and optimize the positive electrode material, and choose the ternary material NCM811;

[0008] S2. Select and optimize the negative electrode material, and choose a composite material of graphite and silicon;

[0009] S3, selecting and optimizing the conductive additive, and selecting carbon nanotubes as the conductive additive;

[0010] S4. Select and optimize the electrolyte;

[0011] S5. Select and optimize the diaphragm material and choose polyolefin diaphragm;

[0012] S6. Based on the material performance data of the selected positive and negative electrode materials, electrolyte, conductive additives, and separators, the effects of different material ratios on battery performance are predicted through simulation calculations;

[0013] S7, battery assembly and testing, assemble the optimized materials and verify the performance of the battery cells.

[0014] It should be noted that the S6 method predicts the effects of different material ratios on battery performance based on the selected positive and negative electrode materials, electrolyte, conductive additives, and separator material performance data through simulation calculation, including:

[0015] S61. Build a battery model and create a simplified physical model of the battery, taking into account the electrochemical behavior of the battery;

[0016] S62. Input of material parameters: Input the parameters of each material, including the kinetics of electrochemical reaction, thermodynamic properties, ionic conductivity, electrical conductivity, porosity, etc.;

[0017] S63, based on the charge and discharge behavior simulation of electrode materials, by simulating the behavior of electrode materials during the charge and discharge process, the theoretical capacity, voltage platform and its attenuation trend of the battery can be calculated;

[0018] S64, battery performance prediction, based on the electrochemical performance of each component, simulate and calculate the energy density and power density; simulate the capacity decay of the battery after multiple charge and discharge cycles, and combine factors such as temperature and charge and discharge rate to predict the cycle life of the battery; use thermal analysis models to predict the thermal stability of the battery under extreme working conditions;

[0019] S65, parameter tuning and multi-objective optimization. During the simulation process, there are multiple objectives that need to be optimized, such as maximizing energy density, improving cycle life, reducing internal resistance, optimizing safety, and optimizing cost. By using optimization algorithms, a balance can be found among multiple objectives.

[0020] S66. Obtain the best preliminary proportion of materials.

[0021] It is further worth noting that the parameter tuning and multi-objective optimization in S65 include:

[0022] S651. Determine optimization objectives and constraints, including maximizing specific energy (energy density), maximizing cycle life, minimizing internal resistance, optimizing safety, optimizing cost, etc.;

[0023] S652. Combination of weight assignment and objective function. In multi-objective optimization, different objectives usually need to be weighted according to their importance. Through weight assignment, multiple objective functions can be combined into a single objective function, so that the optimization algorithm can find a balance between different objectives.

[0024] Multiple objective functions are weighted and summed to form a comprehensive objective function:

[0025] F(x)=w 1 f 1 ·(x)+w 2 ·f 2 (x)+…+w n ·f n (x)

[0026] Among them, F(x) is the comprehensive objective function, f i (x) is the i-th objective function, w i is the weight of the i-th objective function, n is the total number of objective functions, and x is the parameter that needs to be adjusted during the optimization process

[0027] By adjusting the weights, the optimization algorithm can find the best balance between different objectives;

[0028] S653, iterative optimization and convergence analysis, through multiple generations of iterations, the optimization algorithm continuously adjusts the ratio parameters to approach the optimal solution; eventually, the algorithm will give a set of balanced solutions, each of which achieves the optimal balance between multiple objectives, thus obtaining the best.

[0029] It should be further explained that the battery assembly and testing in S7, assembling the optimized materials and verifying the performance of the battery cells, includes:

[0030] S71. Selecting the best preliminary ratio based on the simulation calculation results;

[0031] S72. Conduct experiments according to the initially optimized ratio, prepare battery cells, and perform standardized tests on them;

[0032] S73, testing the actual capacity, cycle life, discharge efficiency, etc. of the battery, and comparing them with the predicted results of the simulation calculation;

[0033] S74. The experimental results can be fed back into the simulation calculation as input to adjust the parameters of the simulation model to optimize the battery design.

[0034] As a preferred embodiment, the positive electrode material is NCM811 coated with aluminum, and 2% to 5% manganese is added to NCM811. The NCM811 (nickel cobalt oxide) material has a higher energy density (theoretical capacity is 200mAh / g) and a nickel content of 81%, which helps to improve the specific energy of the battery. Compared with traditional NCM 532, NCM 811 has a higher capacity and a higher operating voltage platform, which is suitable for high specific energy battery requirements.

[0035] In addition, NCM 811 is coated with aluminum (Al) to improve its electrochemical stability and avoid irreversible side reactions under high voltage environments.

[0036] Through coating and doping modification technology, the stability of NCM 811 under high voltage is improved, so that it will not experience significant capacity decay under high voltage environment, thereby improving the battery life and safety.

[0037] As a preferred embodiment, the graphite and silicon composite material contains 30% silicon in the composite material. The specific capacity of silicon is very high (theoretical value is 4200 mAh / g), but it will undergo a large volume expansion during the charge and discharge process. By compounding silicon with graphite, the problem of silicon expansion can be alleviated, while improving the specific capacity and cycle stability of the negative electrode.

[0038] Silicon accounts for 30% of the composite material, thereby improving the specific capacity while ensuring stability; the composite design of silicon and graphite takes advantage of the high capacity of silicon and optimizes the overall performance of the battery, especially for high current discharge and high specific energy applications.

[0039] As a preferred embodiment, the carbon nanotubes are added in a proportion of 2% to 5% in the positive and negative electrode materials. Conductive additives are essential for the high rate performance of the battery, especially when the instantaneous discharge capacity of the battery needs to be improved. Carbon nanotubes are selected as conductive additives due to their excellent conductivity and mechanical strength. The addition of carbon nanotubes CNT can significantly reduce the internal resistance of the battery and improve the discharge capacity of the battery.

[0040] As a preferred embodiment, the electrolyte is selected as a mixed solution of 1.2M lithium hexafluorophosphate, a mixed solvent of dimethyl carbonate and ethylene carbonate in a ratio of 1:1 and 0.5% lithium fluoride additive. The selection of the electrolyte is directly related to the cycle performance and safety of the battery. Especially under high voltage conditions, traditional electrolytes may have stability problems, so it is necessary to select an electrolyte with high voltage stability.

[0041] By adding lithium fluoride to the electrolyte and using a high-voltage stable solvent system, the stability and ion conductivity of the electrolyte at high voltage are improved, significantly improving the safety and long life of the battery when operating at high voltage.

[0042] As a preferred embodiment, the diaphragm material is a polyolefin diaphragm with a pore size of 1.0-1.5 μm and a ceramic coating. The diaphragm is an important component of the lithium-ion battery. It not only provides good ion conductivity, but also has good stability under high temperature and high voltage environment.

[0043] Ceramic-coated polyolefin separators not only provide the mechanical strength of traditional polyolefin separators, but also improve the safety of batteries under high voltage and high temperature environments.

[0044] Compared with the prior art, the present invention provides a method for forming material ratio parameters of a high-voltage-resistant and high-energy-density lithium-ion battery, which has at least the following beneficial effects:

[0045] By precisely matching and optimizing the parameters of positive and negative electrode materials, electrolytes, conductive additives and diaphragm materials, the specific energy and high-voltage resistance of lithium-ion batteries can be significantly improved. By rationally selecting the material ratio and optimizing the operating voltage range, the capacity retention and cycle stability of the battery are effectively improved. At the same time, the safety of the battery is also enhanced, and it can operate stably under high-voltage environments, making it suitable for high-energy-density application scenarios such as electric vehicles and high-performance energy storage systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 A flow chart of a method for forming material ratio parameters of a high-voltage-resistant high-energy-density lithium-ion battery of the present invention;

[0047] Figure 2 This is a flow chart of a method for predicting the effects of different material ratios on battery performance through simulation calculations of the present invention;

[0048] Figure 3 It is a flow chart of the battery assembly and testing method of the present invention. DETAILED DESCRIPTION

[0049] The present invention will be further described below in conjunction with the embodiments.

[0050] Reference Figure 1 As shown, the present invention provides a method for forming material ratio parameters of a high-voltage resistant high-energy lithium-ion battery, comprising:

[0051] S1. Select and optimize the positive electrode material, and choose the ternary material NCM811;

[0052] S2. Select and optimize the negative electrode material, and choose a composite material of graphite and silicon;

[0053] S3, selecting and optimizing the conductive additive, and selecting carbon nanotubes as the conductive additive;

[0054] S4. Select and optimize the electrolyte;

[0055] S5. Select and optimize the diaphragm material and choose polyolefin diaphragm;

[0056] S6. Based on the material performance data of the selected positive and negative electrode materials, electrolyte, conductive additives, and separators, the effects of different material ratios on battery performance are predicted through simulation calculations;

[0057] S7, battery assembly and testing, assemble the optimized materials and verify the performance of the battery cells.

[0058] Reference Figure 2 As shown, the S6 predicts the influence of different material ratios on battery performance through simulation calculation based on the material performance data of the selected positive and negative electrode materials, electrolyte, conductive additive, and separator, including:

[0059] S61. Build a battery model and create a simplified physical model of the battery, taking into account the electrochemical behavior of the battery;

[0060] This model usually includes the physical and chemical properties of the battery's positive electrode, negative electrode, conductive additives, electrolyte, and separator. Based on different material properties, we define corresponding electrochemical models for each component. For example, the charging and discharging process of the positive electrode material, the volume expansion model of the negative electrode material, and the ion mobility in the electrolyte

[0061] Molecular dynamics methods are used to simulate the interactions between materials, especially the stability of materials under high voltage, interface reactions, and ion diffusion behavior. This helps to determine the stability of different materials under high voltage or high temperature environments, especially the compatibility of the electrochemical reactions of the positive and negative electrodes with the solvent system.

[0062] S62. Input of material parameters: Input the parameters of each material, including the kinetics of electrochemical reaction, thermodynamic properties, ionic conductivity, electrical conductivity, porosity, etc.;

[0063] These parameters can be obtained from literature, experimental data or theoretical calculations, for example, the capacity, voltage platform, cycle stability of NCM 811 materials, volume expansion and charge-discharge efficiency of graphite and silicon composites, etc.

[0064] S63, based on the charge and discharge behavior simulation of electrode materials, by simulating the behavior of electrode materials during the charge and discharge process, the theoretical capacity, voltage platform and its attenuation trend of the battery can be calculated;

[0065] Specifically, the battery performance at high discharge rates can be evaluated by simulating the charge and discharge curves of the battery at different rates; the changes in the internal resistance of the battery can be simulated, including the conductivity of the electrolyte, the electronic conductivity, and the electrode interface impedance. The increase in internal resistance often leads to greater losses in the battery at high discharge rates. Through simulation, the ratio of conductive additives can be optimized to reduce internal resistance.

[0066] S64, battery performance prediction, based on the electrochemical performance of each component, simulate and calculate the energy density and power density; simulate the capacity decay of the battery after multiple charge and discharge cycles, and combine factors such as temperature and charge and discharge rate to predict the cycle life of the battery; use thermal analysis models to predict the thermal stability of the battery under extreme working conditions;

[0067] For example, by increasing the proportion of high-energy-density NCM811, its contribution to relative energy can be evaluated; by simulating different electrolyte systems and negative electrode material ratios, its impact on battery cycle life can be predicted. This process can calculate negative / positive electrode material loss, interface side reactions, etc. through electrochemical models; during high-current discharge, the temperature change of the battery and possible thermal runaway phenomena can be simulated to help optimize the ratio of the separator and electrolyte.

[0068] S65, parameter tuning and multi-objective optimization. During the simulation process, there are multiple objectives that need to be optimized, such as maximizing energy density, improving cycle life, reducing internal resistance, optimizing safety, and optimizing cost. By using optimization algorithms, a balance can be found among multiple objectives.

[0069] S66. Obtain the best preliminary proportion of materials.

[0070] The parameter tuning and multi-objective optimization in S65 include:

[0071] S651. Determine optimization objectives and constraints, including maximizing specific energy (energy density), maximizing cycle life, minimizing internal resistance, optimizing safety, optimizing cost, etc.;

[0072] S652. Combination of weight assignment and objective function. In multi-objective optimization, different objectives usually need to be weighted according to their importance. Through weight assignment, multiple objective functions can be combined into a single objective function, so that the optimization algorithm can find a balance between different objectives.

[0073] Multiple objective functions are weighted and summed to form a comprehensive objective function:

[0074] F(x)=w 1 f 1 ·(x)+w 2 ·f 2 (x)+…+wn ·f n (x)

[0075] Among them, F(x) is the comprehensive objective function, f i (x) is the i-th objective function, w i is the weight of the i-th objective function, n is the total number of objective functions, and x is the parameter that needs to be adjusted during the optimization process

[0076] By adjusting the weights, the optimization algorithm can find the best balance between different objectives;

[0077] S653, iterative optimization and convergence analysis, through multiple generations of iterations, the optimization algorithm continuously adjusts the ratio parameters to approach the optimal solution; eventually, the algorithm will give a set of balanced solutions, each of which achieves the optimal balance between multiple objectives, thus obtaining the best.

[0078] Reference Figure 3 As shown, the battery assembly and testing in S7 assembles the optimized materials and verifies the performance of the battery cells, including:

[0079] S71. Selecting the best preliminary ratio based on the simulation calculation results;

[0080] S72. Conduct experiments according to the initially optimized ratio, prepare battery cells, and perform standardized tests on them;

[0081] S73, testing the actual capacity, cycle life, discharge efficiency, etc. of the battery, and comparing them with the predicted results of the simulation calculation;

[0082] S74. The experimental results can be fed back into the simulation calculation as input to adjust the parameters of the simulation model to optimize the battery design.

[0083] It can be understood that the positive electrode material is NCM811 coated with aluminum, and 2% to 5% manganese is added to NCM811. The NCM811 (nickel cobalt oxide) material has a higher energy density (theoretical capacity is 200mAh / g) and a nickel content of 81%, which helps to improve the specific energy of the battery. Compared with the traditional NCM 532, NCM 811 has a higher capacity and a higher operating voltage platform, which is suitable for high specific energy battery requirements.

[0084] In addition, NCM 811 is coated with aluminum (Al) to improve its electrochemical stability and avoid irreversible side reactions under high voltage environments.

[0085] Through coating and doping modification technology, the stability of NCM 811 under high voltage is improved, so that it will not experience significant capacity decay under high voltage environment, thereby improving the battery life and safety.

[0086] It can be understood that in the graphite and silicon composite material, silicon accounts for 30% of the composite material, and the specific capacity of silicon is very high (theoretical value is 4200mAh / g), but it will undergo a large volume expansion during the charge and discharge process. By compounding silicon with graphite, the problem of silicon expansion can be alleviated, while improving the specific capacity and cycle stability of the negative electrode.

[0087] Silicon accounts for 30% of the composite material, thereby improving the specific capacity while ensuring stability; the composite design of silicon and graphite takes advantage of the high capacity of silicon and optimizes the overall performance of the battery, especially for high current discharge and high specific energy applications.

[0088] It is understandable that the carbon nanotubes are added in a ratio of 2% to 5% in the positive and negative electrode materials. Conductive additives are essential for the high rate performance of the battery, especially when the instantaneous discharge capacity of the battery needs to be improved. Due to its excellent conductivity and mechanical strength, carbon nanotubes are selected as conductive additives. The addition of carbon nanotubes CNT can significantly reduce the internal resistance of the battery and improve the discharge capacity of the battery.

[0089] It can be understood that the electrolyte is a mixed solution of 1.2M lithium hexafluorophosphate, a mixed solvent of dimethyl carbonate and ethylene carbonate in a ratio of 1:1, and 0.5% lithium fluoride additive. The selection of electrolyte is directly related to the cycle performance and safety of the battery, especially under high voltage conditions, traditional electrolytes may have stability problems, so it is necessary to select an electrolyte with high voltage stability.

[0090] By adding lithium fluoride to the electrolyte and using a high-voltage stable solvent system, the stability and ion conductivity of the electrolyte at high voltage are improved, significantly improving the safety and long life of the battery when operating at high voltage.

[0091] It is understandable that the diaphragm material is a polyolefin diaphragm with a pore size of 1.0-1.5 μm and a ceramic coating. The diaphragm is an important component of the lithium-ion battery. It not only provides good ion conductivity, but also has good stability under high temperature and high voltage environment.

[0092] Ceramic-coated polyolefin separators not only provide the mechanical strength of traditional polyolefin separators, but also improve the safety of batteries under high voltage and high temperature environments.

[0093] In summary, the advantages of the present invention are: by accurately matching and optimizing the parameters of positive and negative electrode materials, electrolytes, conductive additives and diaphragm materials, the specific energy and high-voltage resistance of lithium-ion batteries can be significantly improved. By rationally selecting the ratio of materials and optimizing the operating voltage range, the capacity retention and cycle stability of the battery are effectively improved. At the same time, the safety of the battery is also enhanced, and it can operate stably under high-voltage environments, and is suitable for high-energy-density application scenarios such as electric vehicles and high-performance energy storage systems.

[0094] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for forming material ratio parameters of a high-voltage-resistant high-energy lithium-ion battery, characterized in that: include: S1. Select and optimize the positive electrode material, and choose the ternary material NCM811; S2. Select and optimize the negative electrode material, and choose a composite material of graphite and silicon; S3, selecting and optimizing the conductive additive, and selecting carbon nanotubes as the conductive additive; S4. Select and optimize electrolyte materials; S5. Select and optimize the diaphragm material and choose polyolefin diaphragm; S6. Based on the material performance data of the selected positive and negative electrode materials, electrolyte, conductive additives, and separators, the effects of different material ratios on battery performance are predicted through simulation calculations; S7, battery assembly and testing, assemble the optimized materials and verify the performance of the battery cells.

2. The method for forming material ratio parameters of a high-voltage-resistant and high-energy-density lithium-ion battery according to claim 1, characterized in that: The method of S6 predicts the influence of different material ratios on battery performance based on the material performance data of the selected positive and negative electrode materials, electrolyte, conductive additive, and separator through simulation calculation, including: S61. Build a battery model and create a simplified physical model of the battery, taking into account the electrochemical behavior of the battery; S62. Input of material parameters: Input the parameters of each material, including the kinetics of electrochemical reaction, thermodynamic properties, ionic conductivity, electrical conductivity, porosity, etc.; S63, based on the charge and discharge behavior simulation of electrode materials, by simulating the behavior of electrode materials during the charge and discharge process, the theoretical capacity, voltage platform and its attenuation trend of the battery can be calculated; S64, battery performance prediction, based on the electrochemical performance of each component, simulate and calculate the energy density and power density; simulate the capacity decay of the battery after multiple charge and discharge cycles, and combine factors such as temperature and charge and discharge rate to predict the cycle life of the battery; use thermal analysis models to predict the thermal stability of the battery under extreme working conditions; S65, parameter tuning and multi-objective optimization. During the simulation process, there are multiple objectives that need to be optimized, such as maximizing energy density, improving cycle life, reducing internal resistance, optimizing safety, and optimizing cost. By using optimization algorithms, a balance can be found among multiple objectives. S66. Obtain the best preliminary proportion of materials.

3. The method for forming material ratio parameters of a high-voltage-resistant and high-energy-density lithium-ion battery according to claim 2, characterized in that: The parameter tuning and multi-objective optimization in S65 include: S651. Determine optimization objectives and constraints, including maximizing specific energy (energy density), maximizing cycle life, minimizing internal resistance, optimizing safety, optimizing cost, etc.; S652. Combination of weight assignment and objective function. In multi-objective optimization, different objectives usually need to be weighted according to their importance. Through weight assignment, multiple objective functions can be combined into a single objective function, so that the optimization algorithm can find a balance between different objectives. Multiple objective functions are weighted and summed to form a comprehensive objective function: F(x)=w1f1·(x)+w2·f2(x)+…+w n ·f n (x) Among them, F(x) is the comprehensive objective function, f i (x) is the i-th objective function, w i is the weight of the i-th objective function, n is the total number of objective functions, and x is the parameter that needs to be adjusted during the optimization process By adjusting the weights, the optimization algorithm can find the best balance between different objectives; S653, iterative optimization and convergence analysis, through multiple generations of iterations, the optimization algorithm continuously adjusts the ratio parameters to approach the optimal solution; eventually, the algorithm will give a set of balanced solutions, each of which achieves the optimal balance between multiple objectives, thus obtaining the best.

4. The method for forming material ratio parameters of a high-voltage-resistant and high-energy-density lithium-ion battery according to claim 3, characterized in that: The battery assembly and testing in S7 assembles the optimized materials and verifies the performance of the battery cells, including: S71. Selecting the best preliminary ratio based on the simulation calculation results; S72. Conduct experiments according to the initially optimized ratio, prepare battery cells, and perform standardized tests on them; S73, testing the actual capacity, cycle life, discharge efficiency, etc. of the battery, and comparing them with the predicted results of the simulation calculation; S74. The experimental results can be fed back into the simulation calculation as input to adjust the parameters of the simulation model to optimize the battery design.

5. The method for forming material ratio parameters of a high-voltage-resistant and high-energy-density lithium-ion battery according to claim 4, characterized in that: In the positive electrode material, NCM811 is coated with aluminum, and 2% to 5% of manganese is added into the NCM811.

6. The method for forming material ratio parameters of a high-voltage-resistant and high-energy-density lithium-ion battery according to claim 5, characterized in that: In the graphite and silicon composite material, silicon accounts for 30% of the composite material.

7. The method for forming material ratio parameters of a high-voltage-resistant and high-energy-density lithium-ion battery according to claim 6, characterized in that: The carbon nanotubes are added in a proportion of 2% to 5% in the positive electrode and negative electrode materials.

8. The method for forming material ratio parameters of a high-voltage-resistant and high-energy-density lithium-ion battery according to claim 7, characterized in that: The electrolyte is a mixed solution of 1.2M lithium hexafluorophosphate, a mixed solvent of dimethyl carbonate and ethylene carbonate in a ratio of 1:1, and 0.5% lithium fluoride additive.

9. The method for forming material ratio parameters of a high-voltage-resistant and high-energy-density lithium-ion battery according to claim 8, characterized in that: The membrane material is a polyolefin membrane with a pore size of 1.0-1.5 μm and a ceramic coating.

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