Optimization Method and System for High Rate Discharge Characteristics of Power Batteries

Abstract

The present invention relates to the technical field of power batteries, and discloses a method and system for optimizing the high-rate discharge characteristics of a power battery, including: analyzing the material crystal structure corresponding to the electrode material, calculating the material ion migration rate corresponding to the electrode material, and designing a microscopic structure optimization blueprint corresponding to the electrode material; calculating the discharge energy dissipation degree of the power battery; calculating the material loss coefficient corresponding to the electrode material, calculating the stable confidence level corresponding to the electrode material, and calculating the material health quotient corresponding to the electrode material; determining the discharge optimization parameters of the power battery, planning the discharge control strategy of the power battery, performing optimization management on the high-rate discharge of the power battery, and obtaining a discharge optimization result. The main purpose of the present invention is to solve the problem of poor optimization effect of the high-rate discharge characteristics of power batteries.

Description

Technical Field

[0001] The present invention relates to a method and system for optimizing the high-rate discharge characteristics of a power battery, belonging to the technical field of power batteries. Background Art

[0002] With the rapid development of modern technology, power batteries are increasingly widely used in many fields, especially in electric vehicles, electric tools, and energy storage systems. The market's performance requirements for power batteries are also constantly rising. Among them, the high-rate discharge characteristics, as a key indicator to measure the ability of a power battery to quickly release a large amount of electrical energy in a short time, its optimization has become a research hotspot and a key task in the industry.

[0003] Currently, in the optimization of the high-rate discharge characteristics of power batteries, the traditional method of combining empirical formulas with limited experimental data is mainly adopted. First, based on existing electrochemical theories and accumulated engineering experience, a series of factors that may affect the high-rate discharge characteristics are determined. Through designing and conducting a limited number of experimental tests, the high-rate discharge performance data of the battery under different values of these factors are obtained. Based on these data, a simple mathematical model is established using statistical analysis methods, attempting to reveal the correlation between each factor and the high-rate discharge characteristics, and accordingly, the battery design and manufacturing process are adjusted and optimized.

[0004] However, this traditional method has many limitations. Due to the limited number of experiments, the obtained data sample size is often small, making it difficult to comprehensively and accurately reflect the complex non-linear relationship between each factor and the high-rate discharge characteristics. Moreover, this optimization method based on experience and limited data lacks dynamic adaptability and is difficult to cope with situations such as fluctuations in the characteristics of raw materials and minor changes in the production process during the battery production process, resulting in poor optimization effects on the high-rate discharge characteristics of power batteries. Summary of the Invention

[0005] The present invention provides a method and system for optimizing the high-rate discharge characteristics of a power battery, and its main purpose is to solve the problem of poor optimization effect of the high-rate discharge characteristics of a power battery.

[0006] To achieve the above object, a method for optimizing the high-rate discharge characteristics of a power battery provided by the present invention includes:

[0007] Obtain the electrode material of the power battery, analyze the material crystal structure corresponding to the electrode material, measure the material ion migration rate corresponding to the electrode material, and design an optimized blueprint for the microstructure corresponding to the electrode material according to the material crystal structure and the material ion migration rate;

[0008] Measure the variation amplitude of the internal resistance corresponding to the power battery, measure the polarization potential difference of the power battery during high-rate discharge, and calculate the discharge energy dissipation degree of the power battery by combining the variation amplitude of the internal resistance and the polarization potential difference;

[0009] Record the current parameter set and temperature parameter set of the power battery during discharge respectively. Based on the current parameter set, calculate the material loss coefficient corresponding to the electrode material. Based on the temperature parameter set, calculate the stable confidence level corresponding to the electrode material. Calculate the material health quotient corresponding to the electrode material by combining the material loss coefficient and the stable confidence level;

[0010] Determine the discharge optimization parameters of the power battery by combining the material ion migration rate and the discharge energy dissipation degree. Plan the discharge control strategy of the power battery according to the material health quotient and the discharge optimization parameters. Perform the optimization management of the high-rate discharge of the power battery based on the discharge control strategy and the microstructure optimization blueprint to obtain the discharge optimization result.

[0011] Optionally, the analysis of the material crystal structure corresponding to the electrode material includes:

[0012] Take a sample of the electrode material to obtain an electrode material sample;

[0013] Use a preset X-ray diffractometer to irradiate the electrode material sample to obtain a material X-ray diffraction pattern;

[0014] Identify the peak positions of the material X-ray diffraction pattern to obtain the material diffraction peak positions;

[0015] Extract the peak position map information corresponding to the material diffraction peak positions in the material X-ray diffraction pattern;

[0016] Analyze the material crystal structure corresponding to the electrode material based on the material diffraction peak positions and the peak position map information.

[0017] Optionally, the design of the microstructure optimization blueprint corresponding to the electrode material according to the material crystal structure and the material ion migration rate includes:

[0018] Analyze the characteristics of the material crystal structure to obtain crystal structure characteristics;

[0019] Analyze the ion migration characteristics in the material crystal structure based on the material ion migration rate;

[0020] Construct a material simulation model corresponding to the electrode material by combining the crystal structure characteristics and the ion migration characteristics;

[0021] Perform iterative optimization on the material simulation model to obtain an optimized material simulation model;

[0022] Based on the optimized material simulation model, design an optimized blueprint for the microstructure corresponding to the electrode material.

[0023] Optionally, calculating the discharge energy dissipation degree of the power battery by combining the internal resistance amplitude variation and the polarization potential difference includes:

[0024] Statistical the full discharge cycle corresponding to the power battery and measure the discharge current corresponding to the polarization potential difference;

[0025] Sort the internal resistance amplitude variation to obtain a sequence of internal resistance amplitude variation;

[0026] Combining the sequence of internal resistance amplitude variation and the full discharge cycle, calculate the equivalent average internal resistance of the power battery;

[0027] Combining the polarization potential difference, the discharge current, and the full discharge cycle, calculate the average polarization power of the power battery through the following formula:

[0028]

[0029] Where A represents the average polarization power of the power battery, T represents the full discharge cycle, I represents the discharge current, and U represents the polarization potential difference;

[0030] Combining the equivalent average internal resistance, the discharge current, the average polarization power, and the full discharge cycle, the discharge energy dissipation degree of the power battery can be calculated through the following formula:

[0031]

[0032] Where D represents the discharge energy dissipation degree of the power battery, T represents the full discharge cycle, I represents the discharge current, represents the equivalent average internal resistance, and A represents the discharge current.

[0033] Optionally, combining the sequence of internal resistance amplitude variation and the full discharge cycle to calculate the equivalent average internal resistance of the power battery includes:

[0034] Identify the amplitude variation timestamp corresponding to the sequence of internal resistance amplitude variation, and based on the amplitude variation timestamp, calculate the amplitude variation duration period corresponding to the sequence of internal resistance amplitude variation;

[0035] Combining the amplitude variation duration period and the full discharge cycle, calculate the amplitude variation weight corresponding to the sequence of internal resistance amplitude variation;

[0036] Combined with the sequence internal resistance variation range and the variation weight, the equivalent average internal resistance of the power battery is calculated through the following formula:

[0037]

[0038] Among them, represents the equivalent average internal resistance of the power battery, represents the variation weight corresponding to the a-th internal resistance variation in the sequence internal resistance variation range, represents the a-th internal resistance variation in the sequence internal resistance variation range, a represents the serial number corresponding to the sequence internal resistance variation range, and q represents the quantity corresponding to the sequence internal resistance variation range.

[0039] Optionally, calculating the material loss coefficient corresponding to the electrode material based on the current parameter set includes:

[0040] Performing parameter cleaning on the current parameter set to obtain a target current parameter set;

[0041] Querying the material molar mass corresponding to the electrode material, and based on the material molar mass, determining the reaction molar mass corresponding to the electrode material;

[0042] Combining the target current parameter set and the reaction molar mass to calculate the electrode reaction mass corresponding to the electrode material;

[0043] Determining the initial electrode mass corresponding to the electrode material, and combining the electrode reaction mass and the initial electrode mass to calculate the material loss coefficient corresponding to the electrode material.

[0044] Optionally, combining the target current parameter set and the reaction molar mass to calculate the electrode reaction mass corresponding to the electrode material includes:

[0045] Querying the electrode reaction formula corresponding to the electrode material, and based on the electrode reaction formula, determining the number of electron transfers during the reaction of the electrode material;

[0046] Combining the number of electron transfers, the target current parameter set, and the reaction molar mass, and calculating the electrode reaction mass corresponding to the electrode material through the following formula:

[0047]

[0048] Among them, E represents the electrode reaction mass corresponding to the electrode material, F represents the reaction molar mass, represents the b-th current value in the target current parameter set, represents the time period corresponding to the b-th current value in the target current parameter set, n represents the number of electron transfers, G represents the Faraday constant, and b represents the current serial number in the target current parameter set.

[0049] Optionally, calculating the stable confidence level corresponding to the electrode material based on the temperature parameter set includes:

[0050] Performing smoothing processing on the temperature parameter set to obtain smoothed temperature parameters;

[0051] Based on the smoothed temperature parameters, calculating the temperature change amount corresponding to the electrode material;

[0052] Measuring the material thermal expansion coefficient and the corresponding material reference volume corresponding to the electrode material respectively;

[0053] Combining the temperature change amount, the material thermal expansion coefficient and the material reference volume, and calculating the volume change amount corresponding to the electrode material through the following formula:

[0054]

[0055] wherein, H represents the volume change amount corresponding to the electrode material, represents the material reference volume, represents the material thermal expansion coefficient, represents the temperature change amount;

[0056] Combining the volume change amount and the material reference volume, and calculating the stable confidence level corresponding to the electrode material.

[0057] Optionally, combining the material loss coefficient and the stable confidence level, and calculating the material health quotient corresponding to the electrode material includes:

[0058] Querying the battery application scenario corresponding to the power battery, and analyzing the power load characteristics in the battery application scenario;

[0059] Based on the power load characteristics, determining the electrode performance correlation factors of the power battery;

[0060] According to the electrode performance correlation factors, allocating the key degree ratios corresponding to the material loss coefficient and the stable confidence level to obtain a first key degree coefficient and a second key degree coefficient;

[0061] Combining the first key degree coefficient, the second key degree coefficient, the material loss coefficient and the stable confidence level, and calculating the material health quotient corresponding to the electrode material.

[0062] A high-rate discharge characteristic optimization system for a power battery, characterized in that the system includes:

[0063] An optimized blueprint design module for obtaining the electrode material of a power battery, analyzing the material crystal structure corresponding to the electrode material, measuring the material ion migration rate corresponding to the electrode material, and designing an optimized blueprint for the microstructure corresponding to the electrode material according to the material crystal structure and the material ion migration rate;

[0064] An energy dissipation degree calculation module for measuring the internal resistance amplitude change corresponding to the power battery and measuring the polarization potential difference of the power battery during high-rate discharge, and calculating the discharge energy dissipation degree of the power battery by combining the internal resistance amplitude change and the polarization potential difference;

[0065] A health quotient calculation module for respectively recording the current parameter set and the temperature parameter set of the power battery during discharge, calculating the material loss coefficient corresponding to the electrode material based on the current parameter set, calculating the stable confidence level corresponding to the electrode material based on the temperature parameter set, and calculating the material health quotient corresponding to the electrode material by combining the material loss coefficient and the stable confidence level;

[0066] A discharge optimization processing module for determining the discharge optimization parameters of the power battery by combining the material ion migration rate and the discharge energy dissipation degree, planning the discharge control strategy of the power battery according to the material health quotient and the discharge optimization parameters, and performing optimized management of the high-rate discharge of the power battery based on the discharge control strategy and the microstructure optimization blueprint to obtain a discharge optimization result.

[0067] Compared with the problems described in the background art, the present invention analyzes the material crystal structure corresponding to the electrode material, measures the material ion migration rate corresponding to the electrode material, and can assist in designing a more reasonable microscopic structure optimization blueprint based on the material crystal structure and the material ion migration rate, effectively reducing energy loss, improving the overall discharge efficiency and stability of the battery. By combining the internal resistance variation range and the polarization potential difference, the present invention calculates the discharge energy dissipation degree of the power battery, which can accurately quantify the energy loss degree during the discharge of the power battery, helping to optimize the discharge parameters subsequently, improving the overall energy utilization efficiency of the power battery and enhancing its high-rate discharge performance. By calculating the material loss coefficient corresponding to the electrode material based on the current parameter set, the present invention can accurately quantify the loss degree of the electrode material under the action of current, intuitively reflecting the influence of current on the electrode material, and providing a basis for the subsequent calculation of the material health quotient corresponding to the electrode material. By combining the material ion migration rate and the discharge energy dissipation degree, the present invention determines the discharge optimization parameters of the power battery. Through the discharge optimization parameters, excessive internal loss of the battery caused by unreasonable discharge can be avoided, the aging of components such as electrodes can be slowed down, and according to the material health quotient and the discharge optimization parameters, the discharge control strategy of the power battery is planned to maximize the performance of the power battery and ensure operation stability, thereby improving the optimization effect of the high-rate discharge characteristics of the power battery. Therefore, the present invention proposes an optimization method and system for the high-rate discharge characteristics of a power battery to improve the optimization effect of the high-rate discharge characteristics of the power battery. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 It is a schematic flowchart of an optimization method for the high-rate discharge characteristics of a power battery provided by an embodiment of the present invention;

[0069] Figure 2 It is a functional module diagram of a system for optimizing the high-rate discharge characteristics of a power battery provided by an embodiment of the present invention.

[0070] The realization, functional features and advantages of the present invention will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0071] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0072] The embodiments of the present application provide a method for optimizing the high-rate discharge characteristics of a power-type battery. The execution subject of the method for optimizing the high-rate discharge characteristics of the power-type battery includes, but is not limited to, at least one of electronic devices such as a server, a terminal, etc. that can be configured to execute the method provided by the embodiments of the present application. In other words, the method for optimizing the high-rate discharge characteristics of the power-type battery can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to: a single server, a server cluster, a cloud server, or a cloud server cluster, etc.

[0073] Embodiment 1:

[0074] Referring to Figure 1 As shown, it is a schematic flowchart of the method for optimizing the high-rate discharge characteristics of a power-type battery provided by an embodiment of the present invention. In this embodiment, the method for optimizing the high-rate discharge characteristics of the power-type battery includes:

[0075] S1. Obtain the electrode material of the power-type battery, analyze the material crystal structure corresponding to the electrode material, measure the material ion migration rate corresponding to the electrode material, and design a microscopic structure optimization blueprint corresponding to the electrode material according to the material crystal structure and the material ion migration rate.

[0076] By analyzing the material crystal structure corresponding to the electrode material and measuring the material ion migration rate corresponding to the electrode material, the present invention can assist in designing a more reasonable microscopic structure optimization blueprint based on the material crystal structure and the material ion migration rate, effectively reducing energy loss, and improving the overall discharge efficiency and stability of the battery. It should be explained that the power-type battery is an electric energy storage device that provides a power source for various electric devices and needs to have high energy conversion and fast charge and discharge capabilities. The electrode material is a key component of the power-type battery that participates in the electrochemical reaction to realize the mutual conversion of electric energy and chemical energy. The material crystal structure is a specific structural form formed by the atoms corresponding to the electrode material arranged periodically in three-dimensional space. The material ion migration rate is the speed of the ions corresponding to the electrode material moving inside the crystal or at the interface under the action of an electric field. Further, the measurement of the material ion migration rate corresponding to the electrode material can be realized by the potential step method.

[0077] Specifically, the analysis of the material crystal structure corresponding to the electrode material includes:

[0078] Sampling the electrode material to obtain an electrode material sample;

[0079] Using a preset X-ray diffractometer to irradiate the electrode material sample to obtain a material X-ray diffraction pattern;

[0080] Perform peak position identification on the X-ray diffraction pattern of the material to obtain the diffraction peak positions of the material;

[0081] Extract the peak position map information corresponding to the diffraction peak positions of the material from the X-ray diffraction pattern of the material;

[0082] Based on the diffraction peak positions of the material and the peak position map information, analyze the crystal structure of the material corresponding to the electrode material.

[0083] It should be explained that the electrode material sample is a physical sample of the electrode material for detection and analysis. The X-ray diffractometer is an instrument that irradiates the electrode material sample with X-rays to obtain information related to its internal crystal structure. The X-ray diffraction pattern of the material is a pattern that reflects the crystal structure characteristics presented after the X-ray diffractometer irradiates the electrode material sample. The diffraction peak positions of the material are the positions of the peak-shaped features representing specific crystal structure information in the X-ray diffraction pattern of the material. The peak position map information is the detailed data content such as the intensity, shape, and position relationship of the peaks reflected by the diffraction peak positions of the material in the X-ray diffraction pattern of the material, which can be used to analyze the crystal structure of the electrode material.

[0084] Furthermore, the electrode material can be sampled by a professional electrode material sampling device to obtain an electrode material sample, such as a handheld sampler; the peak positions of the X-ray diffraction pattern of the material can be identified by a high-precision image analysis software combined with a diffraction peak identification algorithm to obtain the diffraction peak positions of the material, such as Image-Pro Plus software; the peak position map information corresponding to the diffraction peak positions of the material can be extracted from the X-ray diffraction pattern of the material by a data extraction tool, and the data extraction tool is compiled by a scripting language, such as the JS scripting language; based on the diffraction peak positions of the material and the peak position map information, analyze the crystal structure of the material corresponding to the electrode material. The position, number, and relative intensity of the diffraction peak positions of the material reflect the arrangement spacing and periodic law of atoms in the crystal, and the characteristics such as the peak shape in the peak position map information imply the crystallinity, grain size, and orientation distribution of the crystal. By comprehensively interpreting the diffraction peak positions of the material and the peak position map information and applying crystallographic theories and analysis methods, the type, symmetry, defect conditions, etc. of the crystal structure of the material corresponding to the electrode material can be accurately inferred.

[0085] Based on the crystal structure of the material and the ion migration rate of the material, an optimized blueprint for the microstructure corresponding to the electrode material is designed. According to the characteristics of the crystal structure and the ion migration speed, an appropriate microstructure can be accurately constructed to reduce the ion transport resistance and greatly improve the charge-discharge efficiency of the battery. It should be noted that the optimized blueprint for the microstructure is a planned and guiding scheme corresponding to the electrode material, which is formulated based on the analysis of the characteristics of the crystal structure, internal pore distribution, atomic arrangement and other microscopic aspects of the material, aiming to improve the electrode performance, battery discharge efficiency and stability.

[0086] Specifically, the design of the optimized blueprint for the microstructure corresponding to the electrode material according to the crystal structure of the material and the ion migration rate of the material includes:

[0087] Analyze the characteristics of the crystal structure of the material to obtain crystal structure characteristics;

[0088] Based on the ion migration rate of the material, analyze the ion migration characteristics in the crystal structure of the material;

[0089] Combine the crystal structure characteristics and the ion migration characteristics to construct a material simulation model corresponding to the electrode material;

[0090] Perform iterative optimization on the material simulation model to obtain an optimized material simulation model;

[0091] Based on the optimized material simulation model, design an optimized blueprint for the microstructure corresponding to the electrode material.

[0092] It should be noted that the crystal structure characteristics are the relevant characteristics reflecting the internal microscopic structure characteristics of the crystal structure of the material, such as lattice type, unit cell parameters, atomic arrangement, symmetry and the presence of defects. The ion migration characteristics are the characteristics affecting ion transport, such as diffusion channels, diffusion difficulty, and migration direction preference of ions in the crystal structure, obtained by analyzing the crystal structure of the material based on the ion migration rate of the material. The material simulation model is a virtual model corresponding to the electrode material, which is constructed based on various factors such as crystal structure characteristics and ion migration characteristics to digitally present the physical and chemical behaviors and performance of the electrode material. The optimized material simulation model is an improved virtual model that can more accurately reflect the actual situation of the electrode material after optimization means such as adjusting parameters and improving the structure, and is used to guide the improvement of electrode performance and the optimization of battery-related performance.

[0093] Further, the crystal structure of the material can be characterized by X-ray diffraction analysis technology to obtain crystal structure characteristics; based on the ion migration rate of the material, the ion migration characteristics in the crystal structure of the material can be analyzed by molecular dynamics simulation method; combining the crystal structure characteristics and the ion migration characteristics, a material simulation model corresponding to the electrode material can be constructed by computational materials science simulation software (such as Materials Studio software); the material simulation model can be iteratively optimized by genetic algorithm to obtain an optimized material simulation model; based on the optimized material simulation model, a microscopic structure optimization blueprint corresponding to the electrode material can be designed by multi-objective optimization analysis of microscopic structure parameters and combining with electrode performance requirements.

[0094] S2. Measure the internal resistance variation amplitude corresponding to the power battery, and measure the polarization potential difference of the power battery during high-rate discharge. Combine the internal resistance variation amplitude and the polarization potential difference to calculate the discharge energy dissipation degree of the power battery.

[0095] In the present invention, by combining the internal resistance variation amplitude and the polarization potential difference, the discharge energy dissipation degree of the power battery is calculated, which can accurately quantify the energy loss degree during the discharge of the power battery, help to optimize the discharge parameters subsequently, improve the overall energy utilization efficiency of the power battery and enhance its high-rate discharge performance. It should be noted that the internal resistance variation amplitude is the amplitude of the internal resistance change of the power battery corresponding to different working conditions (such as charge and discharge processes, temperature changes, etc.), reflecting the stability of the internal resistance of the battery; the polarization potential difference is the difference between the electrode potential and the equilibrium potential due to the electrode polarization phenomenon during the high-rate discharge of the power battery, reflecting the deviation degree of the electrode reaction during the high-load discharge of the battery; the discharge energy dissipation degree is the degree of energy dissipation in the form of heat, etc. during the discharge process of the power battery, used to measure the discharge efficiency and energy loss of the battery. Further, the measurement of the internal resistance variation amplitude corresponding to the power battery can be realized by AC impedance spectroscopy (EIS) technology, and the measurement of the polarization potential difference of the power battery during high-rate discharge can be realized by linear sweep voltammetry.

[0096] Specifically, the combination of the internal resistance variation amplitude and the polarization potential difference to calculate the discharge energy dissipation degree of the power battery includes:

[0097] Statistically analyze the full discharge cycle corresponding to the power battery, and measure the discharge current corresponding to the polarization potential difference;

[0098] Sort the internal resistance variation amplitude to obtain a sequence of internal resistance variation amplitude;

[0099] Calculate the equivalent average internal resistance of the power battery by combining the internal resistance amplitude variation of the sequence and the full discharge cycle.

[0100] Calculate the average polarization power of the power battery by combining the polarization potential difference, the discharge current, and the full discharge cycle through the following formula:

[0101]

[0102] Wherein, A represents the average polarization power of the power battery, T represents the full discharge cycle, I represents the discharge current, and U represents the polarization potential difference.

[0103] Calculate the discharge energy dissipation degree of the power battery by combining the equivalent average internal resistance, the discharge current, the average polarization power, and the full discharge cycle through the following formula:

[0104]

[0105] Wherein, D represents the discharge energy dissipation degree of the power battery, T represents the full discharge cycle, I represents the discharge current, represents the equivalent average internal resistance, and A represents the discharge current.

[0106] It should be explained that the full discharge cycle is the time corresponding to the power battery from the start of discharge to the end of discharge. The discharge current is the physical quantity of the charge flow formed due to the potential difference generated by the polarization phenomenon during the battery discharge corresponding to the polarization potential difference. The internal resistance amplitude variation of the sequence is the internal resistance amplitude variation of the arranged change amplitude according to time or discharge stage, etc. The equivalent average internal resistance is the equivalent average value of the internal resistance of the power battery during the entire discharge process. The average polarization power is the average power loss generated by the polarization phenomenon during the discharge of the power battery, which is used to measure the degree of influence of polarization on the battery performance.

[0107] Furthermore, the full discharge cycle corresponding to the power battery can be counted by the timing module in the power battery. The measurement of the discharge current corresponding to the polarization potential difference can be realized by the direct measurement method of an ammeter. The internal resistance amplitude variation of the sequence can be obtained by sorting according to the time series corresponding to the internal resistance amplitude variation.

[0108] Furthermore, as an optional embodiment of the present invention, the step of calculating the equivalent average internal resistance of the power battery by combining the internal resistance amplitude variation of the sequence and the full discharge cycle includes:

[0109] Identify the amplitude variation timestamp corresponding to the internal resistance amplitude variation of the sequence, and calculate the amplitude variation duration period corresponding to the internal resistance amplitude variation of the sequence based on the amplitude variation timestamp.

[0110] Combined with the amplitude change duration period and the full discharge period, calculate the amplitude change weight corresponding to the sequence internal resistance amplitude change;

[0111] Combined with the sequence internal resistance amplitude change and the amplitude change weight, calculate the equivalent average internal resistance of the power battery through the following formula:

[0112]

[0113] Wherein, represents the equivalent average internal resistance of the power battery, represents the amplitude change weight corresponding to the a-th internal resistance amplitude change in the sequence internal resistance amplitude change, represents the a-th internal resistance amplitude change in the sequence internal resistance amplitude change, a represents the serial number corresponding to the sequence internal resistance amplitude change, and q represents the quantity corresponding to the sequence internal resistance amplitude change.

[0114] It should be explained that the amplitude change timestamp is an identifier for recording the time point of occurrence of each internal resistance amplitude change corresponding to the sequence internal resistance amplitude change; the amplitude change duration period is the time period corresponding to the sequence internal resistance amplitude change from the start of internal resistance change to the end of change, reflecting the time span of internal resistance change; the amplitude change weight represents a quantitative index corresponding to the sequence internal resistance amplitude change for measuring the overall influence degree of each internal resistance amplitude change on the battery performance determined according to factors such as the magnitude and duration of the internal resistance amplitude change. Further, the amplitude change timestamp corresponding to the sequence internal resistance amplitude change can be identified by a timestamp identification tool, and the timestamp identification tool is compiled by a programming language; the amplitude change duration period corresponding to the sequence internal resistance amplitude change can be obtained by subtracting the start time point from the end time point in the amplitude change timestamp; calculate the period ratio of the amplitude change duration period and the full discharge period, and use the period ratio as the amplitude change weight corresponding to the sequence internal resistance amplitude change.

[0115] S3. Respectively record the current parameter set and the temperature parameter set of the power battery during the discharge process. Based on the current parameter set, calculate the material loss coefficient corresponding to the electrode material. Based on the temperature parameter set, calculate the stable confidence level corresponding to the electrode material. Combined with the material loss coefficient and the stable confidence level, calculate the material health quotient corresponding to the electrode material.

[0116] Based on the current parameter set, the present invention calculates the material loss coefficient corresponding to the electrode material, which can accurately quantify the loss degree of the electrode material under the action of current, intuitively reflect the influence of current on the electrode material, and provide a basis for the subsequent calculation of the material health quotient corresponding to the electrode material. It should be explained that the current parameter set and the temperature parameter set are respectively a series of relevant data sets reflecting the magnitude of current and the level of temperature recorded during the discharge process of the power battery over time. The material loss coefficient represents a quantitative value of the loss degree corresponding to the electrode material. Further, the recording of the current parameter set and the temperature parameter set during the discharge process of the power battery can be realized by a current sensor and a temperature sensor respectively.

[0117] Specifically, the calculation of the material loss coefficient corresponding to the electrode material based on the current parameter set includes:

[0118] Perform parameter cleaning on the current parameter set to obtain a target current parameter set;

[0119] Query the molar mass of the material corresponding to the electrode material, and based on the molar mass of the material, determine the reaction molar mass corresponding to the electrode material;

[0120] Combine the target current parameter set and the reaction molar mass to calculate the electrode reaction mass corresponding to the electrode material;

[0121] Determine the initial mass of the electrode corresponding to the electrode material, and combine the electrode reaction mass and the initial mass of the electrode to calculate the material loss coefficient corresponding to the electrode material.

[0122] It should be explained that the target current parameter set is the current parameter set obtained after removing the invalid data in the current parameter set; the molar mass of the material is the mass of the electrode material per unit amount of substance corresponding to each material in the electrode material, reflecting its basic stoichiometric characteristics; the reaction molar mass is the mass corresponding to the unit amount of substance of the substance involved in the electrode reaction process corresponding to the electrode material according to the stoichiometric relationship; the electrode reaction mass is the mass of the part of the material that actually participates in the reaction during the chemical reaction of the electrode corresponding to the electrode material; the initial mass of the electrode is the mass of the electrode material itself before starting the relevant electrochemical process (such as discharging, charging, etc.).

[0123] Further, the current parameter set can be processed for parameter cleaning by the box plot method to obtain a target current parameter set; the material molar mass corresponding to the electrode material can be queried from the Internet through a human-computer interaction method; based on the material molar mass, the reaction molar mass corresponding to the motor material is determined. First, clarify the chemical equation of the electrode reaction and find the stoichiometric coefficient of the substance related to the electrode material in the reaction. For example, in a certain battery electrode reaction, the stoichiometric coefficient of a certain electrode material substance x is s. Then, given that the material molar mass of substance x is p, the reaction molar mass corresponding to this electrode material is the product of the stoichiometric coefficient and the material molar mass, that is, sp, which reflects the actual situation of the molar mass of this material participating in the reaction in a specific electrode reaction; the initial mass of the electrode corresponding to the motor material can be determined by the direct weighing method; by calculating (the electrode reaction mass - the initial mass of the electrode) / the initial mass of the electrode, the material loss coefficient corresponding to the electrode material is obtained.

[0124] Further, as an optional embodiment of the present invention, calculating the electrode reaction mass corresponding to the electrode material by combining the target current parameter set and the reaction molar mass includes:

[0125] Query the electrode reaction formula corresponding to the electrode material, and based on the electrode reaction formula, determine the number of electron transfers of the electrode material during the reaction;

[0126] Combining the number of electron transfers, the target current parameter set and the reaction molar mass, calculate the electrode reaction mass corresponding to the electrode material through the following formula:

[0127]

[0128] where E represents the electrode reaction mass corresponding to the electrode material, F represents the reaction molar mass, represents the b-th current value in the target current parameter set, represents the time period corresponding to the b-th current value in the target current parameter set, n represents the number of electron transfers, G represents the Faraday constant, and b represents the current serial number in the target current parameter set.

[0129] Among them, the electrode reaction formula is the chemical equation representing the oxidation or reduction reaction of the electrode material during the electrochemical process (such as the charge and discharge of a battery). It clearly shows the reactants, products, and the direction of the reaction; the number of electron transfers is the number of electrons transferred from one substance to another by the electrode material during the reaction, which is used to measure the degree of oxidation-reduction during the electrode reaction process. The Faraday constant is a fundamental physical constant, with a value of approximately 96485 C / mol, representing the electric charge carried by each mole of electrons. Further, the electrode reaction formula corresponding to the electrode material can be queried through an electrochemical database. Based on the electrode reaction formula, the number of electron transfers of the electrode material during the reaction can be determined. For example, in a zinc-copper primary battery, the zinc electrode undergoes an oxidation reaction: , and the reduction reaction occurring at the copper electrode is: . In the oxidation reaction of the zinc electrode, each zinc atom loses 2 electrons, so the number of electron transfers is 2; in the reduction reaction of the copper electrode, each copper ion gains 2 electrons, and the number of electron transfers is also 2.

[0130] By calculating the stability confidence level corresponding to the electrode material based on the temperature parameter set, the present invention can understand the stability degree of the performance of the electrode material in different temperature environments, providing a basis for optimizing the discharge characteristics of the power battery and ensuring the stable operation of the power battery. It should be explained that the stability confidence level represents the stability degree of the performance of the electrode material in different temperature environments.

[0131] Specifically, calculating the stability confidence level corresponding to the electrode material based on the temperature parameter set includes:

[0132] Performing smoothing processing on the temperature parameter set to obtain smoothed temperature parameters;

[0133] Based on the smoothed temperature parameters, calculating the temperature change amount corresponding to the electrode material;

[0134] Respectively measuring the material thermal expansion coefficient and the corresponding reference volume of the electrode material;

[0135] Combining the temperature change amount, the material thermal expansion coefficient, and the reference volume of the material, calculating the volume change amount corresponding to the electrode material through the following formula:

[0136]

[0137] Among them, H represents the volume change amount corresponding to the electrode material, represents the reference volume of the material, represents the material thermal expansion coefficient, represents the temperature change amount;

[0138] Calculate the stable confidence level corresponding to the electrode material by combining the volume change amount and the reference volume of the material.

[0139] It should be explained that the smoothed temperature parameter is a temperature-related parameter obtained by performing data smoothing on the recorded temperature parameter; the temperature change amount is the change value of the temperature corresponding to the electrode material, reflecting the dynamic change of the temperature of the environment where the electrode is located; the coefficient of thermal expansion of the material is the proportionality coefficient corresponding to the electrode material that causes the volume expansion (or contraction) of the material per unit temperature change when the temperature changes; the reference volume of the material is the volume of the electrode material corresponding to a certain initial state, serving as a reference for measuring the volume change; the volume change amount is the numerical value of the change in the volume of the electrode material caused by factors such as temperature change and physicochemical processes.

[0140] Furthermore, the temperature parameter set can be smoothed by a moving average filtering algorithm to obtain the smoothed temperature parameter; based on the smoothed temperature parameter, the temperature change amount corresponding to the electrode material can be calculated by calculating the difference between the smoothed temperature values at different times; the coefficient of thermal expansion of the material and the corresponding reference volume of the material corresponding to the electrode material can be measured by a dilatometer and a volume measuring instrument respectively; calculate the ratio between the volume change amount and the reference volume of the material to obtain the volume change rate, calculate the average change rate corresponding to the volume change rate, and combine the volume change rate and the average change rate to calculate the volume change standard deviation, and the volume change standard deviation is the stable confidence level corresponding to the electrode material.

[0141] The present invention calculates the material health quotient corresponding to the electrode material by combining the material loss coefficient and the stable confidence level, and can accurately understand the health state corresponding to the electrode material, improving the accuracy of the subsequent discharge control strategy planning of the power battery. It should be explained that the material health quotient represents a measurement value of the health state corresponding to the electrode material.

[0142] Specifically, the calculating the material health quotient corresponding to the electrode material by combining the material loss coefficient and the stable confidence level includes:

[0143] Query the battery application scenario corresponding to the power battery and analyze the power load characteristics in the battery application scenario;

[0144] Based on the power load characteristics, determine the electrode performance correlation factors of the power battery;

[0145] According to the electrode performance correlation factors, allocate the key degree ratios corresponding to the material loss coefficient and the stable confidence level to obtain the first key degree coefficient and the second key degree coefficient;

[0146] Combined with the first criticality coefficient, the second criticality coefficient, the material loss coefficient, and the stability confidence level, calculate the material health quotient corresponding to the electrode material.

[0147] It should be explained that the battery application scenario is the specific environment and usage situation of the power battery in actual use, such as different application fields like electric vehicles and energy storage power stations; the power load characteristic is the relevant characteristics such as the power change that the battery can withstand and output under different working conditions in the battery application scenario, reflecting the battery's ability to cope with load changes; the electrode performance related factors are various factors related to and affecting the electrode performance of the power battery, such as the electrode material composition, structure, reaction environment, etc.; the first criticality coefficient and the second criticality coefficient are respectively quantitative indicators corresponding to the material loss coefficient and the stability confidence level for measuring their importance in evaluating the overall performance, stability, etc. of the battery or electrode.

[0148] Furthermore, the battery application scenario corresponding to the power battery can be queried through the product manual, and the power load characteristics in the battery application scenario can be analyzed through the actual working condition simulation test method; based on the power load characteristics, the electrode performance related factors of the power battery can be determined by associating the mutual influence relationship between the electrode reaction mechanism, electrode material characteristics, and power load; a hierarchical analysis model (AHP) can be constructed to score the electrode performance related factors, the material loss coefficient, and the stability confidence level respectively according to their importance in affecting the battery performance, and the correlation degree of the material loss coefficient and the stability confidence level in the electrode performance related factors can be determined according to the scoring values, and the criticality ratios corresponding to the material loss coefficient and the stability confidence level can be allocated according to the correlation degree to obtain the first criticality coefficient and the second criticality coefficient; multiply the first criticality coefficient and the second criticality coefficient by the material loss coefficient and the stability confidence level respectively and sum them up to obtain the material health quotient corresponding to the electrode material.

[0149] S4. Determine the discharge optimization parameters of the power battery in combination with the material ion migration rate and the discharge energy dissipation degree, plan the discharge control strategy of the power battery according to the material health quotient and the discharge optimization parameters, and perform the optimization management of the high-rate discharge of the power battery based on the discharge control strategy and the microstructure optimization blueprint to obtain the discharge optimization result.

[0150] The present invention determines the discharge optimization parameters of the power battery by combining the ion migration rate of the material and the discharge energy dissipation degree. Through the discharge optimization parameters, the excessive internal loss of the battery caused by unreasonable discharge can be avoided, the aging of components such as electrodes can be slowed down, and according to the material health quotient and the discharge optimization parameters, the discharge control strategy of the power battery is planned to maximize the performance of the power battery and ensure operation stability, thereby improving the optimization effect of the high-rate discharge characteristics of the power battery. It should be noted that the discharge optimization parameters are the key adjustment indicators for improving the discharge efficiency determined based on the ion migration rate of the material and the discharge energy dissipation degree of the power battery, and the discharge control strategy is the specific discharge operation plan of the power battery based on the material health quotient and the discharge optimization parameters. Further, by combining the ion migration rate of the material and the discharge energy dissipation degree, the discharge optimization parameters of the power battery are determined. By deeply analyzing the ion migration rate of the material, the speed of ion transmission inside the battery can be clarified, which is closely related to the discharge efficiency. At the same time, by studying the discharge energy dissipation degree, the energy loss situation during the discharge process can be understood. By combining the two, optimization parameters such as the discharge current magnitude and the discharge cut-off voltage can be determined to balance the energy output and loss and achieve an efficient and stable discharge process, improving the comprehensive performance of the battery; according to the material health quotient and the discharge optimization parameters, the discharge control strategy of the power battery is planned. First, based on the material health quotient, the health status and remaining life of the electrode material are judged. If the health quotient is high, it indicates that the electrode state is good. Combining the discharge optimization parameters, the discharge power and current can be appropriately increased to give full play to the battery performance. On the contrary, if the health quotient is low, to protect the electrode and extend the battery life, the discharge intensity should be reduced, such as reducing the discharge current and increasing the discharge cut-off voltage. At the same time, during the discharge process, the material health quotient and the actual discharge effect are continuously monitored, and the discharge control strategy is dynamically adjusted to ensure that the battery can discharge safely, efficiently and stably under different working conditions;Based on the above-mentioned discharge control strategy and the microstructure optimization blueprint, the optimization management of the high-rate discharge of the power-type battery is carried out to obtain the discharge optimization result. First, according to the discharge control strategy, key parameters such as current and voltage during the high-rate discharge of the power-type battery are set to ensure that the discharge process is carried out within a safe and efficient range. For example, according to the material health quotient and discharge optimization parameters, the discharge current is limited within a reasonable range to prevent the battery from overheating or electrode damage caused by excessive current. Then, referring to the microstructure optimization blueprint, the internal microstructure of the battery, such as the crystal structure and pore distribution of the electrode material, is regulated. For example, the electrode is specially treated according to the blueprint to make the ion migration channel smoother, reduce the ion diffusion resistance, and improve the reaction rate during high-rate discharge. During the discharge process, various performance indicators of the battery are continuously monitored, and the discharge control strategy and microstructure optimization measures are fine-tuned according to the actual situation. The final discharge optimization result may be that under high-rate discharge, the energy output of the battery is more stable, the capacity retention rate is higher, and the heating phenomenon is effectively controlled, thereby improving the overall performance and service life of the power-type battery in high-power demand scenarios.;

[0151] Compared with the problems described in the background art, the present invention can assist in designing a more reasonable microstructure optimization blueprint by analyzing the crystal structure of the electrode material corresponding to the electrode material and calculating the ion migration rate of the electrode material corresponding to the electrode material, effectively reducing energy loss and improving the overall discharge efficiency and stability of the battery. By combining the internal resistance amplitude and the polarization potential difference, the present invention calculates the discharge energy dissipation degree of the power-type battery, which can accurately quantify the energy loss degree during the discharge of the power-type battery, helping to optimize the discharge parameters subsequently, improving the overall energy utilization efficiency of the power-type battery and enhancing its high-rate discharge performance. By calculating the material loss coefficient corresponding to the electrode material based on the current parameter set, the present invention can accurately quantify the loss degree of the electrode material under the action of current, intuitively reflecting the influence of current on the electrode material, and providing a basis for the subsequent calculation of the material health quotient corresponding to the electrode material. By combining the ion migration rate of the material and the discharge energy dissipation degree, the present invention determines the discharge optimization parameters of the power-type battery. Through the discharge optimization parameters, excessive internal loss of the battery caused by unreasonable discharge can be avoided, the aging of components such as electrodes can be slowed down, and according to the material health quotient and the discharge optimization parameters, the discharge control strategy of the power-type battery is planned to maximize the performance of the power-type battery and ensure operation stability, thereby improving the optimization effect of the high-rate discharge characteristics of the power-type battery. Therefore, the present invention proposes a method for optimizing the high-rate discharge characteristics of a power-type battery to improve the optimization effect of the high-rate discharge characteristics of the power-type battery.

[0152] Example 2:

[0153] As Figure 2 shown, it is a functional block diagram of a system for optimizing the high-rate discharge characteristics of a power battery provided by an embodiment of the present invention.

[0154] The high-rate discharge characteristic optimization system 100 of a power battery according to the present invention can be installed in an electronic device. According to the functions achieved, the high-rate discharge characteristic optimization system 100 of a power battery can include an optimization blueprint design module 101, an energy dissipation degree calculation module 102, a health quotient calculation module 103, and a discharge optimization processing module 104. The modules in the present invention can also be referred to as units, which refer to a series of computer program segments that can be executed by a processor of an electronic device and can complete fixed functions, and are stored in the memory of the electronic device.

[0155] In this embodiment, the functions of each module / unit are as follows:

[0156] The optimization blueprint design module 101 is used to obtain the electrode material of the power battery, analyze the material crystal structure corresponding to the electrode material, measure the material ion migration rate corresponding to the electrode material, and design a microstructure optimization blueprint corresponding to the electrode material according to the material crystal structure and the material ion migration rate;

[0157] The energy dissipation degree calculation module 102 is used to measure the internal resistance variation range corresponding to the power battery, measure the polarization potential difference when the power battery is discharging at a high rate, and calculate the discharge energy dissipation degree of the power battery by combining the internal resistance variation range and the polarization potential difference;

[0158] The health quotient calculation module 103 is used to respectively record the current parameter set and the temperature parameter set during the discharge process of the power battery, calculate the material loss coefficient corresponding to the electrode material based on the current parameter set, calculate the stable confidence level corresponding to the electrode material based on the temperature parameter set, and calculate the material health quotient corresponding to the electrode material by combining the material loss coefficient and the stable confidence level;

[0159] The discharge optimization processing module 104 is used to determine the discharge optimization parameters of the power battery by combining the material ion migration rate and the discharge energy dissipation degree, plan the discharge control strategy of the power battery according to the material health quotient and the discharge optimization parameters, and perform optimization management on the high-rate discharge of the power battery based on the discharge control strategy and the microstructure optimization blueprint to obtain a discharge optimization result.

[0160] Specifically, each module in the high-rate discharge characteristic optimization system 100 of a power battery described in the embodiment of the present application is used in the same way as the aboveFigure 1 The technical means are the same as those described in the method for optimizing the high-rate discharge characteristics of a power-type battery, and the same technical effects can be achieved, which will not be elaborated here.

[0161] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above-described exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic characteristics of the present invention.

[0162] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for optimizing high-rate discharge characteristics of a power battery, characterized in that: The method comprises: Obtaining the electrode material of the power battery, analyzing the material crystal structure corresponding to the electrode material, calculating the material ion migration rate corresponding to the electrode material, and designing a microstructure optimization blueprint corresponding to the electrode material according to the material crystal structure and the material ion migration rate; Measuring the internal resistance amplitude corresponding to the power battery, and measuring the polarization potential difference of the power battery during high-rate discharge, and calculating the discharge energy dissipation of the power battery in combination with the internal resistance amplitude and the polarization potential difference, including: combining the equivalent average internal resistance, discharge current, average polarization power and full discharge cycle, and calculating the discharge energy dissipation of the power battery by the following formula: Where D represents the discharge energy dissipation of the power battery, T represents the full discharge cycle, and I represents the discharge current. represents the equivalent average internal resistance, A represents the average polarization power; The discharge energy dissipation refers to the degree of energy dissipation of the power battery during the discharge process, and is used to measure the battery discharge efficiency and energy loss; Respectively record the current parameter set and the temperature parameter set of the power battery during the discharge process, calculate the material loss coefficient corresponding to the electrode material based on the current parameter set, calculate the stability confidence corresponding to the electrode material based on the temperature parameter set, and calculate the material health quotient corresponding to the electrode material by combining the material loss coefficient and the stability confidence; In combination with the material ion migration rate and the discharge energy dissipation, the discharge optimization parameters of the power battery are determined; according to the material health quotient and the discharge optimization parameters, the discharge control strategy of the power battery is planned; based on the discharge control strategy and the microstructure optimization blueprint, the high-rate discharge of the power battery is optimized and management is performed to obtain a discharge optimization result.

2. The method for optimizing high-rate discharge characteristics of a power battery according to claim 1, characterized in that: The analyzing the material crystal structure corresponding to the electrode material includes: Sampling the electrode material to obtain an electrode material sample; Using a preset ray diffractometer to perform radiation treatment on the electrode material sample to obtain a ray diffraction spectrum of the material; Performing peak position identification on the material ray diffraction spectrum to obtain the material diffraction peak position; Extracting peak position spectrum information corresponding to the diffraction peak position of the material from the ray diffraction spectrum of the material; The material crystal structure corresponding to the electrode material is analyzed based on the material diffraction peak position and the peak position spectrum information.

3. The method for optimizing high-rate discharge characteristics of a power battery according to claim 1, characterized in that: The method of designing a microstructure optimization blueprint corresponding to the electrode material according to the crystal structure of the material and the ion migration rate of the material includes: Performing characteristic analysis on the crystal structure of the material to obtain crystal structure characteristics; Analyzing the ion migration characteristics in the crystal structure of the material based on the ion migration rate of the material; Combining the crystal structure characteristics and the ion migration characteristics, constructing a material simulation model corresponding to the electrode material; Iteratively optimizing the material simulation model to obtain an optimized material simulation model; Based on the optimized material simulation model, a microstructure optimization blueprint corresponding to the electrode material is designed.

4. The method for optimizing high-rate discharge characteristics of a power battery according to claim 1, characterized in that: The step of calculating the discharge energy dissipation of the power battery by combining the internal resistance variation and the polarization potential difference further includes: Counting the full discharge cycles corresponding to the power battery, and measuring the discharge current corresponding to the polarization potential difference; Sorting the internal resistance amplitudes to obtain a sequence internal resistance amplitude; Calculate the equivalent average internal resistance of the power battery by combining the internal resistance variation of the sequence and the full discharge cycle; In combination with the polarization potential difference, the discharge current and the full discharge cycle, the average polarization power of the power battery is calculated by the following formula: Among them, A represents the average polarization power of the power battery, T represents the full discharge cycle, I represents the discharge current, and U represents the polarization potential difference.

5. The method for optimizing high-rate discharge characteristics of a power battery according to claim 4, characterized in that: The calculating the equivalent average internal resistance of the power battery by combining the sequence internal resistance variation and the full discharge cycle includes: Identify the amplitude change timestamp corresponding to the amplitude change of the sequence internal resistance, and calculate the amplitude change duration period corresponding to the amplitude change of the sequence internal resistance based on the amplitude change timestamp; Calculate the amplitude variation weight corresponding to the amplitude variation of the sequence internal resistance in combination with the amplitude variation duration period and the discharge full period; In combination with the sequence internal resistance variation and the variation weight, the equivalent average internal resistance of the power battery is calculated by the following formula: in, represents the equivalent average internal resistance, It represents the amplitude variation weight corresponding to the ath internal resistance amplitude variation in the sequence internal resistance amplitude variation, It represents the ath internal resistance variation in the sequence internal resistance variation, a represents the sequence number corresponding to the sequence internal resistance variation, and q represents the number corresponding to the sequence internal resistance variation.

6. The method for optimizing high-rate discharge characteristics of a power battery according to claim 1, characterized in that: The calculating, based on the current parameter set, a material loss coefficient corresponding to the electrode material includes: Performing parameter cleaning processing on the current parameter set to obtain a target current parameter set; Querying the material molar mass corresponding to the electrode material, and determining the reaction molar mass corresponding to the electrode material based on the material molar mass; Calculate the electrode reaction mass corresponding to the electrode material by combining the target current parameter set and the reaction molar mass; The initial mass of the electrode corresponding to the electrode material is determined, and the material loss coefficient corresponding to the electrode material is calculated by combining the electrode reaction mass and the initial mass of the electrode.

7. The method for optimizing high-rate discharge characteristics of a power battery according to claim 6, characterized in that: The step of combining the target current parameter set and the reaction molar mass to calculate the electrode reaction mass corresponding to the electrode material includes: Querying the electrode reaction formula corresponding to the electrode material, and determining the number of electron transfers of the electrode material during the reaction process based on the electrode reaction formula; Combining the electron transfer number, the target current parameter set and the reaction molar mass, the electrode reaction mass corresponding to the electrode material is calculated by the following formula: Among them, E represents the electrode reaction mass corresponding to the electrode material, F represents the reaction molar mass, represents the bth current value in the target current parameter set, represents the time period corresponding to the bth current value in the target current parameter set, n represents the number of electron transfers, G represents the Faraday constant, and b represents the current sequence number in the target current parameter set.

8. The method for optimizing high-rate discharge characteristics of a power battery according to claim 1, characterized in that: The calculating the stability confidence corresponding to the electrode material based on the temperature parameter set includes: Smoothing the temperature parameter set to obtain smoothed temperature parameters; Based on the smooth temperature parameter, calculating the temperature change corresponding to the electrode material; Respectively measure the thermal expansion coefficient and the corresponding material reference volume of the electrode material; Combining the temperature change, the thermal expansion coefficient of the material and the reference volume of the material, the volume change corresponding to the electrode material is calculated by the following formula: Among them, H represents the volume change corresponding to the electrode material, Represents the base volume of the material. Indicates the thermal expansion coefficient of the material. Indicates the temperature change; The stability confidence level corresponding to the electrode material is calculated by combining the volume change and the material reference volume.

9. The method for optimizing high-rate discharge characteristics of a power battery according to claim 1, characterized in that: The combining of the material loss coefficient and the stability confidence to calculate the material health quotient corresponding to the electrode material includes: Query the battery application scenario corresponding to the power battery, and analyze the power load characteristics in the battery application scenario; Determining electrode performance-related factors of the power battery based on the power load characteristics; According to the electrode performance-related factors, the criticality ratios corresponding to the material loss coefficient and the stability confidence are allocated to obtain a first criticality coefficient and a second criticality coefficient; The material health quotient corresponding to the electrode material is calculated by combining the first criticality coefficient, the second criticality coefficient, the material loss coefficient and the stability confidence.

10. A high rate discharge characteristic optimization system for power batteries, characterized in that: The system comprises: An optimization blueprint design module is used to obtain the electrode material of the power battery, analyze the material crystal structure corresponding to the electrode material, calculate the material ion migration rate corresponding to the electrode material, and design a microstructure optimization blueprint corresponding to the electrode material according to the material crystal structure and the material ion migration rate; The energy dissipation calculation module is used to measure the internal resistance variation corresponding to the power battery, and measure the polarization potential difference of the power battery during high-rate discharge, and calculate the discharge energy dissipation of the power battery in combination with the internal resistance variation and the polarization potential difference, including: combining the equivalent average internal resistance, discharge current, average polarization power and full discharge cycle, and calculating the discharge energy dissipation of the power battery by the following formula: Where D represents the discharge energy dissipation of the power battery, T represents the full discharge cycle, and I represents the discharge current. represents the equivalent average internal resistance, A represents the average polarization power; The discharge energy dissipation refers to the degree of energy dissipation of the power battery during the discharge process, and is used to measure the battery discharge efficiency and energy loss; A health quotient calculation module, used to respectively record the current parameter set and the temperature parameter set of the power battery during the discharge process, calculate the material loss coefficient corresponding to the electrode material based on the current parameter set, calculate the stability confidence corresponding to the electrode material based on the temperature parameter set, and calculate the material health quotient corresponding to the electrode material by combining the material loss coefficient and the stability confidence; The discharge optimization processing module is used to determine the discharge optimization parameters of the power battery in combination with the material ion migration rate and the discharge energy dissipation, plan the discharge control strategy of the power battery according to the material health quotient and the discharge optimization parameters, and perform optimization management of the high-rate discharge of the power battery based on the discharge control strategy and the microstructure optimization blueprint to obtain a discharge optimization result.

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