Method and system for optimizing high-rate discharge characteristic of power battery

Abstract

The invention relates to the technical field of power type batteries, and discloses a high-rate discharge characteristic optimization method and system for a power type battery, and the method comprises the steps: analyzing a material crystal structure corresponding to an electrode material, measuring and calculating a material ion migration rate corresponding to the electrode material, and designing a microstructure optimization blueprint corresponding to the electrode material; calculating the discharge energy dissipation degree of the power type battery; calculating a material breakage coefficient corresponding to the electrode material, calculating a stability confidence coefficient corresponding to the electrode material, and calculating a material health quotient corresponding to the electrode material; and determining a discharge optimization parameter of the power type battery, planning a discharge control strategy of the power type battery, and executing optimization management of high-rate discharge of the power type battery to obtain a discharge optimization result. The invention mainly aims to solve the problem that the optimization effect of the high-rate discharge characteristic of a power battery is poor.

Description

Technical Field

[0001] The invention relates to a method and system for optimizing 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 science and technology, power batteries are increasingly used in many fields, especially in electric vehicles, power tools and energy storage systems. The market performance requirements for power batteries are also rising. Among them, high-rate discharge characteristics are the key indicators to measure the ability of power batteries to quickly release a large amount of electrical energy in a short period of time. Its optimization has become a research hotspot and a key task in the industry.

[0003] At present, in the optimization of high-rate discharge characteristics of power batteries, the traditional method based on a combination of empirical formulas and limited experimental data is mainly used. First, based on the existing electrochemical theory and the engineering experience accumulated in the past, a series of factors that may affect the high-rate discharge characteristics are determined. By 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 adjust and optimize the battery design and manufacturing process.

[0004] However, this traditional method has many limitations. Due to the limited number of experiments, the sample size of data obtained is often small, which makes it difficult to fully and accurately reflect the complex nonlinear relationship between various factors and high-rate discharge characteristics. Moreover, this optimization method based on experience and limited data lacks dynamic adaptability and is difficult to cope with fluctuations in raw material properties and slight changes in production processes during battery production, resulting in poor optimization of 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, the main purpose of which is to solve the problem that the optimization effect of the high-rate discharge characteristics of the power battery is not good.

[0006] To achieve the above object, the present invention provides a method for optimizing high-rate discharge characteristics of a power battery, comprising: 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 variation 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 by combining the internal resistance variation and the polarization potential difference; 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.

[0007] Optionally, analyzing the crystal structure of the material 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.

[0008] Optionally, 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.

[0009] Optionally, the calculating the discharge energy dissipation of the power battery by combining the internal resistance variation and the polarization potential difference 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: 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; In combination with the equivalent average internal resistance, the discharge current, the average polarization power and the full discharge cycle, the discharge energy dissipation of the power battery can be calculated 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, and A represents the discharge current.

[0010] Optionally, 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 of the power battery, 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.

[0011] Optionally, calculating the material loss coefficient corresponding to the electrode material based on the current parameter set 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 motor 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 motor 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.

[0012] Optionally, the 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.

[0013] Optionally, 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.

[0014] Optionally, the combining 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.

[0015] A high-rate discharge characteristic optimization system for a power battery, 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; An 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 by combining the internal resistance variation and the polarization potential difference; 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.

[0016] Compared with the problems described in the background technology, the present invention analyzes the material crystal structure corresponding to the electrode material and measures the material ion migration rate corresponding to the electrode material. According to the material crystal structure and the material ion migration rate, a more reasonable microstructure optimization blueprint can be assisted in designing, effectively reducing energy loss and improving the overall discharge efficiency and stability of the battery. The present invention calculates the discharge energy dissipation of the power battery by combining the internal resistance amplitude and the polarization potential difference, and can accurately quantify the degree of energy loss during discharge of the power battery, which is helpful for subsequent optimization of discharge parameters, improving the overall energy utilization efficiency of the power battery and enhancing its high-rate discharge performance. The present invention calculates the electrode material corresponding to the current parameter set based on the current parameter set. The material loss coefficient can accurately quantify the degree of loss 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. The present invention determines the discharge optimization parameters of the power battery by combining the material ion migration rate and the discharge energy dissipation. The discharge optimization parameters can avoid excessive internal loss of the battery caused by unreasonable discharge, slow down the aging of components such as electrodes, and plan the discharge control strategy of the power battery according to the material health quotient and the discharge optimization parameters, maximize the performance of the power battery and ensure operational stability, so as to improve the optimization effect of the high-rate discharge characteristics of the power battery. Therefore, the high-rate discharge characteristics optimization method and system of the power battery proposed in the present invention can improve the optimization effect of the high-rate discharge characteristics of the power battery. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A schematic flow chart of a method for optimizing high-rate discharge characteristics of a power battery provided in one embodiment of the present invention; Figure 2 A functional module diagram of a system for optimizing the high-rate discharge characteristics of a power battery provided in one embodiment of the present invention.

[0018] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments. DETAILED DESCRIPTION

[0019] 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.

[0020] The embodiment of the present application provides a method for optimizing the high-rate discharge characteristics of a power battery. The execution subject of the method for optimizing the high-rate discharge characteristics of a power battery includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided in the embodiment of the present application. In other words, the method for optimizing the high-rate discharge characteristics of a power battery can be executed by software or hardware installed in 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.

[0021] Embodiment 1: Reference Figure 1 FIG. 1 is a flow chart of a method for optimizing high-rate discharge characteristics of a power battery provided by an embodiment of the present invention. In this embodiment, the method for optimizing high-rate discharge characteristics of a power battery includes: S1. 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.

[0022] The present invention analyzes the material crystal structure corresponding to the electrode material and calculates the material ion migration rate corresponding to the electrode material. According to the material crystal structure and the material ion migration rate, a more reasonable microstructure optimization blueprint can be assisted in designing, thereby effectively reducing energy loss and improving the overall discharge efficiency and stability of the battery. It should be explained that the power battery is an energy storage device that provides a power source for various electric devices and needs to have high energy conversion and fast charging and discharging capabilities. The electrode material is a key material component in the power battery that participates in electrochemical reactions to achieve mutual conversion between electrical energy and chemical energy. The material crystal structure is a specific structural form formed by the periodic arrangement of atoms corresponding to the electrode material in three-dimensional space. The material ion migration rate is the speed at which ions corresponding to the electrode material move inside the crystal or at the interface under the action of an electric field. Furthermore, the calculation of the material ion migration rate corresponding to the electrode material can be achieved by a potential step method.

[0023] In detail, 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.

[0024] It should be explained that the electrode material sample is a physical sample of the electrode material used for detection and analysis, the X-ray diffractometer is an instrument for irradiating the electrode material sample with rays to obtain information related to its internal crystal structure, the material X-ray diffraction spectrum is a spectrum reflecting the crystal structure characteristics after the X-ray diffractometer irradiates the electrode material sample, the material diffraction peak position is the location of the peak-like feature in the material X-ray diffraction spectrum that characterizes the specific crystal structure information, and the peak position spectrum information is the detailed data content of the material diffraction peak position reflected in the material X-ray diffraction spectrum, such as the peak intensity, shape, position relationship, etc., which can be used to analyze the crystal structure of the electrode material.

[0025] Furthermore, the electrode material can be sampled and processed by professional electrode material sampling equipment to obtain electrode material samples, such as a handheld sampler; the material X-ray diffraction spectrum can be peak identified by high-precision image analysis software combined with a diffraction peak recognition algorithm to obtain material diffraction peaks, such as Image-Pro Plus software; the peak spectrum information corresponding to the material diffraction peak can be extracted from the material X-ray diffraction spectrum by a data extraction tool, and the data extraction tool is compiled by a script language, such as JS script language; based on the material diffraction peak and the peak spectrum information, the material crystal structure corresponding to the electrode material is analyzed, the position, number and relative intensity of the material diffraction peak reflect the arrangement spacing and periodicity of atoms in the crystal, and the peak shape and other characteristics in the peak spectrum information imply the crystallinity, grain size and orientation distribution of the crystal, and through the comprehensive interpretation of the material diffraction peak and the peak spectrum information, the crystallographic theory and analysis method can be used to accurately infer the type, symmetry, defect situation and other material crystal structures of the material corresponding to the electrode material.

[0026] The present invention designs 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. According to the crystal structure characteristics and the ion migration rate, an adaptive microstructure can be accurately constructed to reduce the obstacles to ion transmission and greatly improve the battery charging and discharging efficiency. It should be explained that the microstructure optimization blueprint is a planned and guiding plan corresponding to the electrode material, which is formulated based on the analysis of its material crystal structure, internal pore distribution, atomic arrangement and other microscopic characteristics, aiming to improve electrode performance, battery discharge efficiency and stability, etc.

[0027] In detail, the microstructure optimization blueprint corresponding to the electrode material is designed according to the crystal structure of the material and the ion migration rate of the material, including: 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.

[0028] It should be explained that the crystal structure characteristics are the relevant characteristics of the crystal structure of the material, such as lattice type, unit cell parameters, atomic arrangement, symmetry and the presence of defects, which reflect its inherent microscopic structural characteristics. The ion migration characteristics are the characteristics that affect ion transmission, such as the diffusion channel, 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 its crystal structure characteristics, ion migration characteristics and other factors, and is used to digitally present the physical and chemical behavior 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 the material simulation model is optimized by adjusting parameters, improving structure and other optimization methods, and is used to guide the improvement of electrode performance and the optimization of battery-related performance.

[0029] Furthermore, 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; in combination with the crystal structure characteristics and the ion migration characteristics, a material simulation model corresponding to the electrode material can be constructed by computational materials 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 microstructure optimization blueprint corresponding to the electrode material can be designed by performing multi-objective optimization analysis on microstructure parameters and combining electrode performance requirements.

[0030] S2. 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 by combining the internal resistance variation and the polarization potential difference.

[0031] The present invention calculates the discharge energy dissipation of the power battery by combining the internal resistance variation and the polarization potential difference, and can accurately quantify the degree of energy loss of the power battery during discharge, which is helpful for subsequent optimization of discharge parameters, improving the overall energy utilization efficiency of the power battery and enhancing its high-rate discharge performance. It should be explained that the internal resistance variation is the amplitude of the internal resistance change of the power battery under different working conditions (such as charging and discharging process, temperature change, 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 caused by the electrode polarization phenomenon of the power battery during high-rate discharge, reflecting the degree of deviation of the electrode reaction of the battery during high-load discharge; the discharge energy dissipation is the degree to which the energy of the power battery is dissipated in the form of heat during the discharge process, which is used to measure the discharge efficiency and energy loss of the battery. Further, the measurement of the internal resistance variation corresponding to the power battery can be achieved by the electrochemical impedance spectroscopy (EIS) technology, and the measurement of the polarization potential difference of the power battery during high-rate discharge can be achieved by linear sweep voltammetry.

[0032] Specifically, the step of calculating the discharge energy dissipation of the power battery by combining the internal resistance variation and the polarization potential difference 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: 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; In combination with the equivalent average internal resistance, the discharge current, the average polarization power and the full discharge cycle, the discharge energy dissipation of the power battery can be calculated 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, and A represents the discharge current.

[0033] It should be explained that the full discharge cycle is the time from the start of discharge to the end of discharge corresponding to the power battery, the discharge current is the physical quantity of charge flow formed by the potential difference caused by polarization during the battery discharge process corresponding to the polarization potential difference, the serial internal resistance amplitude is the internal resistance amplitude of the internal resistance amplitude arranged in sequence according to time or discharge stage, the equivalent average internal resistance is the equivalent average value of the internal resistance of the power battery during the entire discharge process, and the average polarization power is the average power loss of the power battery due to polarization during the discharge process, which is used to measure the degree of influence of polarization on battery performance.

[0034] Furthermore, the timing module in the power battery can be used to count the full discharge cycle corresponding to the power battery; the measurement of the discharge current corresponding to the polarization potential difference can be achieved by a direct measurement method of an ammeter; and the time series corresponding to the internal resistance amplitude can be sorted to obtain a sequence internal resistance amplitude.

[0035] Further, as an optional embodiment of the present invention, the equivalent average internal resistance of the power battery is calculated by combining the sequence internal resistance variation and the full discharge cycle, including: 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 sequence internal resistance amplitude variation by combining 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 of the power battery, 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.

[0036] It should be explained that the amplitude variation timestamp is an identifier of the time point at which each internal resistance amplitude variation occurs corresponding to the sequence internal resistance amplitude variation; the amplitude variation duration period is the time period from the beginning of the internal resistance change to the end of the change corresponding to the sequence internal resistance amplitude variation, reflecting the time span of the internal resistance change; the amplitude variation weight represents a quantitative indicator corresponding to the sequence internal resistance amplitude variation, which is determined according to factors such as the size of the internal resistance amplitude variation and the duration, and is used to measure the overall impact of each internal resistance amplitude variation on the battery performance. Furthermore, the amplitude variation timestamp corresponding to the sequence internal resistance amplitude variation can be identified by a timestamp identification tool, and the timestamp identification tool is compiled by a programming language; the amplitude variation duration period corresponding to the sequence internal resistance amplitude variation can be obtained by subtracting the start time point from the end time point in the amplitude variation timestamp; the cycle ratio of the amplitude variation duration period to the full discharge cycle is calculated, and the cycle ratio is used as the amplitude variation weight corresponding to the sequence internal resistance amplitude variation.

[0037] S3. Record the current parameter set and temperature parameter set of the power battery during the discharge process respectively, calculate the material deterioration coefficient corresponding to the electrode material based on the current parameter set, calculate the stability 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 deterioration coefficient and the stability confidence level.

[0038] The present invention calculates the material depreciation coefficient corresponding to the electrode material based on the current parameter set, thereby accurately quantifying the degree of loss 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. It should be explained that the current parameter set and the temperature parameter set are respectively a series of related data sets reflecting the current size and temperature conditions recorded over time during the discharge process of the power battery, and the material depreciation coefficient represents the quantified value of the degree of loss corresponding to the electrode material. Furthermore, the recording of the current parameter set and the temperature parameter set of the power battery during the discharge process can be achieved by a current sensor and a temperature sensor, respectively.

[0039] In detail, the calculating of the material loss coefficient corresponding to the electrode material based on the current parameter set 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 motor 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 motor 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.

[0040] It should be explained that the target current parameter set is a set of current parameters obtained after the invalid data in the current parameter set is removed; the material molar mass is the mass of the electrode material per unit substance amount corresponding to each material in the electrode material, reflecting its basic stoichiometric characteristics; the reaction molar mass is the mass of the electrode material corresponding to the unit substance amount of the substance involved in the electrode reaction process 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 electrode initial mass is the mass of the electrode material itself before the start of the relevant electrochemical process (such as discharge, charging and other operations) corresponding to the electrode material.

[0041] Furthermore, the current parameter set can be cleaned by a 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 in a human-computer interactive manner; based on the material molar mass, the reaction molar mass corresponding to the motor material is determined. First, the chemical equation of the electrode reaction is clarified to find the stoichiometric coefficient of the electrode material-related substances in the reaction. For example, in a certain battery electrode reaction, the stoichiometric coefficient of a certain electrode material substance x is s, and then, the material molar mass of the known substance x is p, then the reaction molar mass corresponding to the 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 the 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 direct weighing; the material loss coefficient corresponding to the electrode material can be obtained by calculating (the electrode reaction mass-the electrode initial mass) / the electrode initial mass.

[0042] Further, as an optional embodiment of the present invention, 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.

[0043] Among them, the electrode reaction formula is the chemical equation corresponding to the electrode material, which represents the oxidation or reduction reaction of the electrode material in the electrochemical process (such as battery charging and discharging), which clearly shows the reactants and products and the direction of the reaction; the electron transfer number is the number of electrons transferred from one substance to another substance in the electrode material during the reaction process, which is used to measure the degree of redox in the electrode reaction process. The Faraday constant is a basic physical constant with a value of approximately 96485C / mol, which represents the amount of charge carried by each mole of electrons. Furthermore, the electrode reaction formula corresponding to the electrode material can be queried through the electrochemical database, and based on the electrode reaction formula, the electron transfer number of the electrode material in the reaction process can be determined. For example, in a zinc-copper primary battery, an oxidation reaction occurs at the zinc electrode: , the reduction reaction of the copper electrode is: In the oxidation reaction of the zinc electrode, each zinc atom loses 2 electrons, so the electron transfer number is 2; in the reduction reaction of the copper electrode, each copper ion gains 2 electrons, and the electron transfer number is also 2.

[0044] The present invention calculates the stability confidence corresponding to the electrode material based on the temperature parameter set, so as to understand the stability of the performance of the electrode material under different temperature environments, provide a basis for optimizing the discharge characteristics of the power battery, and ensure the stable operation of the power battery. It should be explained that the stability confidence indicates the stability of the performance of the electrode material under different temperature environments.

[0045] Specifically, 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.

[0046] It should be explained that the smoothed temperature parameter is a temperature-related parameter obtained after data smoothing processing is performed on the recorded temperature parameter; the temperature change is the temperature change value corresponding to the electrode material, reflecting the dynamic change of the ambient temperature of the electrode; the material thermal expansion coefficient is the proportional coefficient of the material volume expansion (or contraction) caused by the unit temperature change of the electrode material when the temperature changes; the material reference volume is the volume corresponding to the electrode material in a certain initial state, which serves as a reference for measuring the volume change; the volume change is the value of the material volume change corresponding to the electrode material due to temperature changes, physical and chemical processes and other factors.

[0047] Furthermore, the temperature parameter set can be smoothed by a moving average filtering algorithm to obtain smoothed temperature parameters; based on the smoothed temperature parameters, the temperature change corresponding to the electrode material can be calculated by calculating the difference between the smoothed temperature values ​​at different times; the thermal expansion coefficient of the material corresponding to the electrode material and the corresponding material reference volume can be measured respectively by a thermal expansion meter and a volume measuring instrument; the ratio between the volume change and the material reference volume is calculated to obtain the volume change rate, the average change rate corresponding to the volume change rate is calculated, and the volume change standard deviation is calculated by combining the volume change rate and the average change rate. The volume change standard deviation is the stability confidence corresponding to the electrode material.

[0048] The present invention calculates the material health quotient corresponding to the electrode material by combining the material depreciation coefficient and the stability confidence, so as to accurately understand the health status corresponding to the electrode material and improve 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 status corresponding to the electrode material.

[0049] In detail, the material health quotient corresponding to the electrode material is calculated by combining the material loss coefficient and the stability confidence, including: 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.

[0050] It should be explained that the battery application scenario refers to the specific environment and usage of the power battery in actual use, such as electric vehicles, energy storage power stations and other different application fields; the power load characteristics are related characteristics such as the power changes 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 the electrode performance of the power battery that will affect it, such as electrode material composition, structure, reaction environment, etc.; the first criticality coefficient and the second criticality coefficient are respectively the material depreciation coefficient and the stability confidence corresponding to the quantitative indicators used to measure their importance in evaluating the overall performance, stability, etc. of the battery or electrode.

[0051] 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 correlation factors of the power battery can be determined by correlating the electrode reaction mechanism, the electrode material characteristics and the mutual influence relationship of the power load; by constructing a hierarchical analysis model (AHP), the electrode performance correlation factors can be scored with the material depreciation coefficient and the stability confidence according to the importance of the impact on the battery performance, and the correlation degree of the material depreciation coefficient and the stability confidence in the electrode performance correlation factors can be determined according to the scoring values, and the criticality ratio corresponding to the material depreciation coefficient and the stability confidence can be allocated according to the correlation degree to obtain the first criticality coefficient and the second criticality coefficient; the first criticality coefficient and the second criticality coefficient are respectively multiplied by the material depreciation coefficient and the stability confidence and the summed up to obtain the material health quotient corresponding to the electrode material.

[0052] S4. 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.

[0053] The present invention determines the discharge optimization parameters of the power battery by combining the material ion migration rate and the discharge energy dissipation. The discharge optimization parameters can avoid excessive internal battery loss caused by unreasonable discharge, slow down the aging of components such as electrodes, and plan the discharge control strategy of the power battery according to the material health quotient and the discharge optimization parameters to maximize the performance of the power battery and ensure operational stability, thereby improving the optimization effect of the high-rate discharge characteristics of the power battery. It should be explained that the discharge optimization parameters are key adjustment indicators for improving the discharge efficiency of the power battery determined based on the material ion migration rate and the discharge energy dissipation. The discharge control strategy is a specific discharge operation plan of the power battery planned based on the material health quotient and the discharge optimization parameters. Furthermore, the discharge optimization parameters of the power battery are determined in combination with the material ion migration rate and the discharge energy dissipation. By in-depth analysis of the material ion migration rate, it can be clearly Determine the speed of ion transmission inside the battery, which is closely related to the discharge efficiency. At the same time, study the discharge energy dissipation to understand the energy loss during the discharge process. Combining the two, we can determine the optimization parameters such as discharge current and discharge cut-off voltage to balance energy output and loss, achieve efficient and stable discharge process, and improve the comprehensive performance of the battery; plan the discharge control strategy of the power battery according to the material health quotient and the discharge optimization parameters. First, judge the health status and remaining life of the electrode material according to the material health quotient. If the health quotient is high, it means that the electrode is in good condition. Combined with 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, in order 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, the material health quotient and the actual discharge effect are continuously monitored during the discharge process, and the discharge control strategy is dynamically adjusted to ensure that the battery can be discharged safely, efficiently and stably under different working conditions;Based on the discharge control strategy and the microstructure optimization blueprint, the optimization management of the high-rate discharge of the power battery is performed to obtain the discharge optimization result. First, the current, voltage and other key parameters of the power battery during high-rate discharge are set according to the discharge control strategy to ensure that the discharge process is carried out within a safe and efficient range. For example, according to the material health quotient and the discharge optimization parameters, the discharge current is limited to a reasonable range to prevent battery overheating or electrode damage due to excessive current. Then, with reference 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 increase the reaction rate during high-rate discharge. During the discharge process, the battery performance indicators 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 the battery has a more stable energy output, a higher capacity retention rate, and effectively controlled heating under high-rate discharge, thereby improving the overall performance and service life of the power battery in high-power demand scenarios. ;

[0054] Compared with the problems described in the background technology, the present invention analyzes the material crystal structure corresponding to the electrode material and measures the material ion migration rate corresponding to the electrode material. According to the material crystal structure and the material ion migration rate, a more reasonable microstructure optimization blueprint can be assisted in designing, effectively reducing energy loss and improving the overall discharge efficiency and stability of the battery. The present invention calculates the discharge energy dissipation of the power battery by combining the internal resistance amplitude and the polarization potential difference, and can accurately quantify the degree of energy loss during discharge of the power battery, which is helpful for subsequent optimization of discharge parameters, improving the overall energy utilization efficiency of the power battery and enhancing its high-rate discharge performance. The present invention calculates the electrode material corresponding to the current parameter set based on the current parameter set. The material loss coefficient can accurately quantify the degree of loss 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. The present invention determines the discharge optimization parameters of the power battery by combining the material ion migration rate and the discharge energy dissipation. The discharge optimization parameters can avoid excessive internal loss of the battery caused by unreasonable discharge, slow down the aging of components such as electrodes, and plan the discharge control strategy of the power battery according to the material health quotient and the discharge optimization parameters, maximize the performance of the power battery and ensure operational stability, so as to improve the optimization effect of the high-rate discharge characteristics of the power battery. Therefore, the high-rate discharge characteristics optimization method of the power battery proposed in the present invention is used to improve the optimization effect of the high-rate discharge characteristics of the power battery.

[0055] Embodiment 2: like Figure 2 , which is a functional module diagram of a system for optimizing high-rate discharge characteristics of a power battery provided by an embodiment of the present invention.

[0056] The high-rate discharge characteristic optimization system 100 of a power battery of the present invention can be installed in an electronic device. According to the functions to be implemented, the high-rate discharge characteristic optimization system 100 of a power battery can include an optimization blueprint design module 101, an energy dissipation calculation module 102, a health quotient calculation module 103 and a discharge optimization processing module 104. The module of the present invention can also be referred to as a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0057] In this embodiment, the functions of each module / unit are as follows: 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, calculate the material ion migration rate corresponding to the electrode material, and design the 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 102 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 by combining the internal resistance variation and the polarization potential difference; The health quotient calculation module 103 is 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 104 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.

[0058] In detail, each module described 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 manner as described above. Figure 1 The same technical means are used as the method for optimizing the high-rate discharge characteristics of a power battery described in the specification and can produce the same technical effects, which will not be repeated here.

[0059] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0060] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution 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 variation 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 by combining the internal resistance variation and the polarization potential difference; 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 calculating the discharge energy dissipation of the power battery by combining the internal resistance variation and the polarization potential difference comprises: 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: 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; In combination with the equivalent average internal resistance, the discharge current, the average polarization power and the full discharge cycle, the discharge energy dissipation of the power battery can be calculated 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, and A represents the discharge current.

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 of the power battery, 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 motor 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 motor 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; An 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 by combining the internal resistance variation and the polarization potential difference; 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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