A battery SOH prediction method, storage medium and system

Abstract

The present invention provides a battery SOH prediction method, storage medium and system, which at least include: setting a first temperature and a first rate, performing a cyclic decay operation on a reference battery, causing the reference battery to decay to a reference capacity, and obtaining charging data of the reference battery in each decay operation; obtaining a charging curve of the reference battery from the charging data based on the voltage change rate, and obtaining the inflection point position of the charging curve; calculating the current capacity of the reference battery from the inflection point position to the charging cut-off position in each decay operation, and obtaining battery balance parameters based on the current capacity; obtaining a corresponding SOH value based on the battery balance parameters, and establishing a characteristic relationship diagram between the battery balance parameters and the SOH value; obtaining the SOH value of the test battery to complete the SOH prediction. During the battery charging process, the hysteresis effect of the battery is effectively eliminated, the inflection point position obtained is accurate, and the characteristic relationship diagram established is highly accurate. It has obvious characteristics, small calculation amount, and a wide range of application scenarios.

Description

Technical Field

[0001] The present invention relates to the technical field of battery management, and in particular to a battery SOH prediction method, storage medium, and system. Background Art

[0002] Amidst global initiatives promoting energy conservation and low-carbon emissions reduction, electric vehicles are showing promising growth trends. To ensure the reliable operation of electric vehicles, battery state of health (SOH) estimation has become both a key and challenging issue in the industry, and a current research hotspot. SOH (battery health) is expressed as a percentage of the battery's current capacity compared to its factory capacity. Currently, battery aging is primarily measured by an increase in internal resistance or capacity reduction. SOH typically affects the battery's internal resistance, as does ambient temperature, especially at low frequencies where electrochemical kinetics are diffusion-controlled. Large-capacity batteries typically have very low internal resistance, resulting in minimal fluctuations, requiring high-precision testing methods to measure SOH. For lithium iron phosphate batteries, internal resistance does not change significantly with aging, making internal resistance ineffective for measuring battery aging.

[0003] Numerous methods exist for studying SOH, primarily direct measurement, filter estimation based on battery models, and data-driven approaches. With the advent of the connected car and big data era, data-driven approaches are becoming the mainstream for battery SOH estimation. Extracting effective battery features to estimate SOH has become a major research topic within the industry. Summary of the Invention

[0004] In view of the shortcomings of the prior art described above, the purpose of the present invention is to provide a battery SOH prediction method, storage medium and system, which are used to solve the problems in the prior art that the battery cannot calculate the SOH by full-capacity discharge, the hysteresis effect of the battery affects the acquisition of SOH, the amount of calculation in the SOH acquisition process is large, and the application scenarios are relatively narrow.

[0005] To achieve the above-mentioned and other related objectives, the present invention provides a battery SOH prediction method, which at least includes:

[0006] 1) setting a first temperature and a first rate, performing a cyclic decay operation on a reference battery, causing the reference battery to decay to a reference capacity, and obtaining charging data of the reference battery in each decay operation;

[0007] 2) obtaining a charging curve of the reference battery from the charging data based on the voltage change rate, and obtaining a position of an inflection point of the charging curve;

[0008] 3) calculating the current capacity of the reference battery from the inflection point to the charging cut-off position in each decay operation, and obtaining a battery balance parameter based on the current capacity, wherein the battery balance parameter is equal to the ratio of the negative electrode capacity to the positive electrode capacity;

[0009] 4) obtaining a corresponding SOH value based on the battery balancing parameters, and establishing a characteristic relationship diagram between the battery balancing parameters and the SOH value, wherein the characteristic relationship diagram is a horizontal and vertical coordinate diagram established based on the battery balancing parameters and the SOH value;

[0010] 5) Setting a second temperature and a second rate, performing a cycle attenuation operation on the test battery, calculating the current capacity of the test battery from the inflection point to the charge cut-off position, querying the characteristic relationship diagram in step 4) based on the current capacity, obtaining the SOH value of the test battery, and completing the SOH prediction, wherein the second rate is equal to the first rate.

[0011] Optionally, the first temperature range is [30 degrees Celsius, 50 degrees Celsius].

[0012] Optionally, the absolute value of the difference between the second temperature and the first temperature is k, where k is a natural number greater than or equal to 0 and less than or equal to 5.

[0013] Optionally, the first rate and the second rate are both 0.1C or 0.15C or 0.2C or 0.25C or 0.3C or 0.33C, wherein 1C represents the current intensity when the battery is fully discharged in one hour.

[0014] Optionally, the number of cyclic attenuation operations is 100 times, 200 times, 300 times, or 500 times.

[0015] Optionally, the reference capacity is n%, where n is a natural number greater than 0 and less than or equal to m, and m is equal to 80, 85 or 90.

[0016] Optionally, the process of acquiring the inflection point position includes: when the charging curve of the reference battery changes from a first state to a second state, a turning point where the slope of the charging curve changes from increasing to decreasing is obtained, and the turning point is the inflection point position.

[0017] The present invention provides a storage medium, which includes one or more programs, and the one or more programs include instructions for executing the battery SOH prediction method.

[0018] The present invention provides a battery SOH prediction system for implementing the battery SOH prediction method. The battery SOH prediction system includes:

[0019] Module 1: setting a first temperature and a first rate, performing a cyclic decay operation on a reference battery, causing the reference battery to decay to a reference capacity, and obtaining charging data of the reference battery in each decay operation;

[0020] Module 2: Obtaining a charging curve of the reference battery from the charging data based on the voltage change rate, and obtaining an inflection point position of the charging curve;

[0021] Module 3: Calculating the current capacity of the reference battery from the inflection point to the charging cut-off position in each decay operation, and obtaining the battery balancing parameters according to the current capacity;

[0022] Module 4: Obtain the corresponding SOH value based on the battery balancing parameters and establish a characteristic relationship diagram between the battery balancing parameters and the SOH value;

[0023] Module 5: Set the second temperature and the second rate, perform a cycle attenuation operation on the test battery, calculate the current capacity of the test battery from the inflection point position to the charge cut-off position, query the characteristic relationship diagram in the module 4 based on the current capacity, obtain the SOH value of the test battery, and complete the SOH prediction.

[0024] Optionally, the module 1 includes a data storage unit and a data processing unit, wherein: the data storage unit is used to store the charging data, wherein the charging data includes: voltage, current and sampling time; the data processing unit is used to extract, clean and fit the charging data.

[0025] As described above, the battery SOH prediction method, storage medium, and system of the present invention have the following beneficial effects:

[0026] 1) In the battery SOH prediction method, storage medium, and system of the present invention, during the battery charging process, the current and temperature are controlled by the battery management system and the environment, effectively eliminating the hysteresis effect of the battery, accurately obtaining the inflection point position, and establishing a characteristic relationship diagram with high precision.

[0027] 2) The battery SOH prediction method, storage medium, and system of the present invention have obvious characteristics, small computational complexity, and wide application scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It shows a functional flow chart of the battery SOH prediction method of the present invention.

[0029] Figure 2 Shown is a characteristic schematic diagram of obtaining the inflection point position of the battery SOH prediction method of the present invention.

[0030] Figure 3Shown is a schematic diagram of the functional modules of the battery SOH prediction system of the present invention.

[0031] Component number description

[0032] Steps S1 to S5 DETAILED DESCRIPTION

[0033] The following describes the embodiments of the present invention through specific examples. Those skilled in the art will readily understand the other advantages and benefits of the present invention from the disclosure herein. The present invention may also be implemented or applied through various other specific embodiments, and the details in this specification may be modified or altered based on different viewpoints and applications without departing from the spirit of the present invention.

[0034] See also Figures 1 to 2 It should be noted that the diagrams provided in this embodiment are merely schematic illustrations of the basic concept of the present invention. The diagrams only show components relevant to the present invention and are not drawn according to the number, shape, and size of components in actual implementation. In actual implementation, the type, quantity, and proportion of each component may be changed arbitrarily, and the component layout may also be more complex.

[0035] Example 1

[0036] like Figure 1 and Figure 2 As shown, this embodiment provides a battery SOH prediction method, which includes:

[0037] S1: If Figure 1 As shown, a first temperature and a first rate are set, and a cyclic decay operation is performed on a reference battery to make the reference battery reach a reference capacity, and charging data of the reference battery in each decay operation is obtained.

[0038] Specifically, as an example, Figure 1 As shown, the range of the first temperature is [30 degrees Celsius, 50 degrees Celsius]. It should be noted that, for the reference battery, especially for lithium iron phosphate batteries, a cycle attenuation operation is performed to allow the electrolyte in the reference battery to be fully infiltrated, and certain active components in the positive and negative active materials are inactivated through certain reactions, so that the overall performance of the reference battery is more stable. It is usually necessary to set the temperature appropriately to produce more deterioration effects on the active materials. If the control is good, the active components are fully reacted, and the reference battery characteristics are stable. If the control is not good, the reaction is excessive, the electrical performance is reduced, the IR is increased (including DCIR, i.e., DC resistance, DC resistance under a specific load and discharge current; ACIR, i.e., AC resistance, measured using a 1KHz AC power supply and a four-wire method, including resistance and reverse capacitance values. Generally speaking, the AC resistance of the reference battery is smaller than the DC resistance), and even leakage may occur.

[0039] The reference battery's performance is more stable after high-temperature cycling. After cycling, potential adverse reactions in the reference battery are exposed, such as changes in voltage, thickness, and internal resistance. These are comprehensive indicators that directly test the safety and electrochemical performance of the reference battery. High temperatures shorten the battery's lifecycle. High temperatures accelerate the internal chemical reactions of the reference battery, allowing the positive and negative electrodes, separator, and electrolyte to fully react and reach equilibrium. Only then does the reference battery's performance truly reflect its performance. Because the reference battery cannot be fully charged or discharged during actual operation, and to minimize the adverse effects of hysteresis, the first temperature range is set to [30°C, 50°C]. This takes into account the Earth's climatic conditions and the high temperature range encountered by humans in production activities. It also accounts for the ambient temperature fluctuations caused by the heat released by the internal electrochemical reactions during the reference battery's operation (including charging and discharging). It should be further explained that the range of the first temperature includes but is not limited to [30 degrees Celsius, 50 degrees Celsius]. Under normal circumstances, the operating temperature range of the battery is [-50 degrees Celsius, 85 degrees Celsius]. The operating temperature range of batteries used in extreme environments such as military-grade and aerospace-grade batteries is wider, and the upper limit temperature can reach above 100 degrees Celsius. Therefore, the range setting of the first temperature should take into account the properties of the battery and the application field of the battery, and is not limited to this embodiment.

[0040] Specifically, as an example, Figure 1 As shown, the first rate and the second rate are both 0.1C or 0.15C or 0.2C or 0.25C or 0.3C or 0.33C, wherein 1C represents the current intensity when the battery is fully discharged in one hour. It should be noted that the rate refers to the current value required for the battery to discharge its rated capacity within a specified time. In terms of value, it is equal to the multiple of the rated capacity of the battery, usually represented by the letter C. For lithium iron phosphate batteries, the battery energy density is large, the uniform output voltage is high, the self-discharge is small, and there is no memory effect. Figure 2 As shown, when the first temperature range is [30 degrees Celsius, 50 degrees Celsius], the first rate is set to, for example, 0.33C, and the inflection point position of the resulting charging curve is easier to identify and separate. Therefore, the setting of the first rate should take into account the first temperature, the electrochemical properties of the battery, and the properties of the inflection point position of the charging curve, and is not limited to this embodiment.

[0041] Specifically, as an example, Figure 1As shown, the number of cyclic attenuation operations is 100 times or 200 times or 300 times or 500 times. It should be noted that when the first temperature range is [30 degrees Celsius, 50 degrees Celsius] and the first rate is set to, for example, 0.33C, 300 cyclic attenuation operations are usually required, and the reference battery decays to a reference capacity to perform a separation operation of the inflection point of the charging curve. It should be further noted that the number of cyclic attenuation operations includes but is not limited to 100 times or 200 times or 300 times or 500 times, and can also be 1000 times or 1500 times or 2000 times. Any number of cyclic attenuation operations that can perform the separation operation of the inflection point of the charging curve is applicable, and they are not described here one by one.

[0042] Specifically, as an example, Figure 1 As shown, the reference capacity is n%, where n is a natural number greater than 0 and less than or equal to m, and m is equal to 80, 85, or 90. It should be noted that the capacity of the battery in this embodiment refers to the capacity of the reference battery, which is used to measure the amount of stored electricity and represents the amount of electricity discharged by the reference battery under certain conditions (discharge rate, temperature, cut-off voltage, etc.). It is usually measured in ampere-hours and is divided into actual capacity, theoretical capacity, and rated capacity. As the reference battery undergoes cyclic decay operation, the capacity of the reference battery, such as a lithium iron phosphate battery, decreases. Generally, when the capacity of the reference battery decays to 80% of the rated capacity, the service life of the reference battery will also be reached, and it is relatively easy to obtain the inflection point position of the charging curve. It should be further noted that the setting of the reference capacity includes but is not limited to 80%, 85%, or 90%. Any method that can make the inflection point position of the charging curve easy to obtain is applicable, and they are not described here one by one.

[0043] Specifically, as an example, Figure 1 As shown, the process of obtaining the charging data of the reference battery in each decay operation includes: extracting the charging data, cleaning the data, and fitting the data. More specifically, the charging data includes: voltage, current, and sampling time. It should be noted that the charging data obtained in each decay operation of the reference battery has a huge amount of data and contains invalid data. Therefore, it is necessary to extract, clean, and fit the charging data. Cleaning includes re-examining and verifying the charging data, deleting duplicate information, correcting existing errors, processing invalid data and missing data, and ultimately maintaining consistency in the charging data, facilitating the establishment of a characteristic relationship diagram, improving processing speed, and the value of the charging data.

[0044] S2: If Figure 1 As shown, the charging curve of the reference battery is obtained from the charging data based on the voltage change rate, and the inflection point position of the charging curve is obtained.

[0045] Specifically, as an example, Figure 1 As shown, the process of obtaining the inflection point location includes: when the charging curve of the reference battery changes from a first state to a second state, the slope of the charging curve changes from increasing to decreasing, and the inflection point is the inflection point location. More specifically, the first state is represented by the reference battery's SOC equal to 50%, and the second state is represented by the reference battery's SOC equal to 70%. An SOC equal to 1 indicates that the battery is fully charged. It should be noted that SOC (State of Charge), the state of charge of a battery (in this embodiment, the reference battery and the test battery), reflects the battery's remaining capacity. Its numerical value is defined as the ratio of the remaining capacity to the battery capacity, and is usually expressed as a percentage. Its value range is 0 to 1. When SOC = 0, the battery is fully discharged, and when SOC = 1, the battery is fully charged. SOC also affects the battery's internal resistance. Batteries (including the reference battery and the test battery in this embodiment) have a rapid rise period and a rapid fall period at the beginning and end of charging / discharging. When the battery is charging, ions are deintercalated from the positive electrode, migrate to the negative electrode, and then intercalate. When the number of positive electrode ions reaches a certain level, the John-Teller effect makes it increasingly difficult to deintercalate and remove them, requiring more energy. This manifests externally as an increase in polarization resistance and a sharp rise in voltage. During discharge, ions deintercalate from the negative electrode, migrate to the positive electrode, and become embedded in the positive electrode's crystal lattice. When the number of ions at the negative electrode drops to a certain level, the electrode surface reaction rate decreases, the internal resistance increases sharply, and the battery voltage drops sharply. Typically, after the inflection point occurs, the remaining battery capacity is less than 10% of the total capacity (if charging, this is the remaining capacity at the end of charging; if discharging, this is the remaining capacity at the end of discharging). Therefore, the "inflection point" phenomenon in batteries is inevitable. Once the inflection point is reached, continuing to charge or discharge can easily lead to catastrophic consequences such as overcharge or overdischarge and overcurrent, which are particularly devastating for the battery. In other words, the inflection point is a weak point in the battery. By analyzing the location of the inflection point on the charging curve, it can reflect the relative balance parameters of the battery.

[0046] For this embodiment, the inflection point phenomenon at the end indicates that the battery (reference battery or test battery) has reached the end of its capacity. Figure 2As shown, the specific position of the inflection point is obtained by using the rate of change of the voltage, where the rate of change of the voltage is the ratio of the rate of change of the voltage to the time taken to complete the change. It should be noted that the setting of the first state includes but is not limited to the SOC of the reference battery mentioned in this embodiment being equal to 50%, and the setting of the second state includes but is not limited to the SOC of the reference battery mentioned in this embodiment being equal to 70%. As long as the accurate inflection point position of the charging curve can be analyzed and the relatively true battery balance parameters can be reflected, thereby completing accurate battery SOH prediction, any first state, second state, and method for obtaining any inflection point position are applicable, and are not limited to this embodiment.

[0047] S3: If Figure 1 As shown, the current capacity of the reference battery from the inflection point position to the charging cut-off position in each decay operation is calculated, and the battery balancing parameter is obtained according to the current capacity.

[0048] Specifically, as an example, Figure 1 As shown, the battery balance parameter is equal to the ratio of the negative electrode capacity to the positive electrode capacity. It should be noted that the ratio of the negative electrode capacity to the positive electrode capacity, that is, the Negative / Positive ratio, is a reference battery such as a lithium iron phosphate battery. The capacity decay is mainly manifested as the decay of the negative electrode capacity. Therefore, when the reference battery undergoes a cycle decay operation to reach the reference capacity, the battery balance parameter will also change with the cycle decay operation, showing a positive correlation.

[0049] S4: As Figure 1 As shown, the corresponding SOH value is obtained based on the battery balancing parameters, and a characteristic relationship diagram between the battery balancing parameters and the SOH value is established, wherein the characteristic relationship diagram is a horizontal and vertical coordinate diagram established based on the battery balancing parameters and the SOH value.

[0050] It should be noted that the characteristic relationship diagram is a distribution diagram of battery balancing parameters and SOH values. The characteristic relationship diagram is established based on the correspondence between the battery balancing parameters and SOH values ​​of the reference battery, which is convenient for big data analysis. When a battery of the same type as the reference battery is subjected to cycle attenuation operations, the SOH value is further obtained by obtaining the battery balancing parameters, which has a direct prediction effect and facilitates the classification and clustering operations of the battery. It has broad guiding significance for battery calibration, especially shipment.

[0051] S5: If Figure 1 As shown, a second temperature and a second rate are set, a cycle attenuation operation is performed on the test battery, the current capacity of the test battery from the inflection point position to the charging cut-off position is calculated, and the SOH value of the test battery is obtained based on the characteristic relationship diagram in the current capacity query step S4 to complete the SOH prediction, wherein the second rate is equal to the first rate.

[0052] Specifically, as an example, Figure 1 As shown, the absolute value of the difference between the second temperature and the first temperature is k, where k is a natural number greater than or equal to 0 and less than or equal to 5. The second rate is equal to the first rate. It should be noted that the test battery and the reference battery are batteries of the same type. When predicting the SOH of the test battery, in order to maintain the accuracy of the prediction, the difference between the second temperature and the first temperature is controlled within ±5 degrees Celsius, and the second rate must be consistent with the first rate. This is because during the charging process of the battery, the internal electrochemical reaction releases heat, causing the temperature of the surrounding environment to change. It is difficult to make the first temperature and the second temperature completely equal, but it is difficult to keep the second rate consistent with the first rate. After testing the current capacity of the battery, the SOH value is obtained from the characteristic relationship diagram to ensure the accuracy of the SOH prediction. It should be further explained that, as Figure 2 As shown, the two curves represent the charging curves when the SOH is n% and the SOH is 100%, respectively. The two charging curves are obtained from the charging data based on the voltage change rate. The inflection point positions of the two charging curves are obtained by analysis, wherein the voltage value range at the inflection point position is obtained according to the first temperature, the first rate and the properties of the reference battery. Through this embodiment, the prediction of SOH is completed.

[0053] If the above method is implemented in the form of a software functional unit and sold or applied as an independent product, it can be stored in a computer-readable storage medium, or it can be multiple computers, servers or network devices, etc. As long as the storage medium can be read, any device is applicable, not limited to this embodiment. The storage medium includes one or more programs, and the one or more programs are used to execute the instructions of the battery SOH prediction method provided in this embodiment, and the instructions include all or part of the steps of executing the battery SOH prediction method. The storage medium includes: U disk, mobile hard disk, private cloud, public cloud, read-only memory (ROM, Read Only Memory), random access memory (RAM, Random Access Memory) and other media that can store program code.

[0054] Example 2

[0055] This embodiment provides a battery SOH prediction system for implementing the battery SOH prediction method in the first embodiment. The battery SOH prediction system includes:

[0056] Module 1: Setting a first temperature and a first rate, performing a cyclic decay operation on a reference battery, causing the reference battery to decay to a reference capacity, and obtaining charging data of the reference battery in each decay operation.

[0057] Specifically, as an example, the module 1 includes a data storage unit and a data processing unit, wherein: the data storage unit is used to store the charging data, wherein the charging data includes: voltage, current and sampling time; the data processing unit is used to extract, clean and fit the charging data. It should be noted that the data storage unit provides the function of a database, classifies and stores the charging data, and has the basic database functions of adding, deleting, modifying and querying. The data processing unit extracts, cleans and fits the charging data, wherein cleaning includes re-examining and verifying the charging data, deleting duplicate information, correcting existing errors, processing invalid data and missing data, and ultimately maintaining consistency in the charging data, facilitating the establishment of a characteristic relationship diagram, improving processing speed, and the value of the charging data.

[0058] Module 2: Obtaining a charging curve of the reference battery from the charging data based on the voltage change rate, and obtaining the inflection point position of the charging curve.

[0059] Module 3: Calculate the current capacity of the reference battery from the inflection point to the charging cut-off position in each decay operation, and obtain the battery balancing parameters according to the current capacity.

[0060] Module 4: Obtain the corresponding SOH value based on the battery balancing parameters and establish a characteristic relationship diagram between the battery balancing parameters and the SOH value.

[0061] Module 5: Set the second temperature and the second rate, perform a cycle attenuation operation on the test battery, calculate the current capacity of the test battery from the inflection point position to the charge cut-off position, query the characteristic relationship diagram in the module 4 based on the current capacity, obtain the SOH value of the test battery, and complete the SOH prediction. In summary, a battery SOH prediction method, storage medium and system of the present invention at least include: setting a first temperature and a first rate, performing a cyclic decay operation on a reference battery, causing the reference battery to decay to a reference capacity, and obtaining charging data of the reference battery in each decay operation; obtaining a charging curve of the reference battery from the charging data based on the voltage change rate, and obtaining the inflection point position of the charging curve; calculating the current capacity of the reference battery from the inflection point position to the charging cut-off position in each decay operation, and obtaining battery balancing parameters through the current capacity; obtaining a corresponding SOH value based on the battery balancing parameters, and establishing a characteristic relationship diagram between the battery balancing parameters and the SOH value, wherein the characteristic relationship diagram is a horizontal and vertical coordinate diagram established based on the battery balancing parameters and the SOH value; setting a second temperature and a second rate, performing a cyclic decay operation on the test battery, calculating the current capacity of the test battery from the inflection point position to the charging cut-off position, obtaining the SOH value of the test battery based on the characteristic relationship diagram queried by the current capacity, and completing SOH prediction, wherein the second rate is equal to the first rate. The battery SOH prediction method, storage medium, and system of the present invention effectively eliminate the battery's hysteresis effect during the battery charging process, controlling the current and temperature by the battery management system and the environment. The obtained inflection point position is accurate, and the established characteristic relationship diagram is highly accurate. The battery SOH prediction method, storage medium, and system of the present invention have distinct characteristics, low computational complexity, and a wide range of application scenarios. Therefore, the present invention effectively overcomes the various shortcomings of the prior art and has high industrial application value.

[0062] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the present invention. Anyone skilled in the art may modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by one of ordinary skill in the art without departing from the spirit and technical principles disclosed herein are intended to be covered by the claims of the present invention.

Claims

1. A battery SOH prediction method, characterized in that: The battery SOH prediction method at least includes: 1) setting a first temperature and a first rate, performing a cyclic decay operation on a reference battery, causing the reference battery to decay to a reference capacity, and obtaining charging data of the reference battery in each decay operation; 2) obtaining a charging curve of the reference battery from the charging data based on the voltage change rate, and obtaining a position of an inflection point of the charging curve; 3) calculating the current capacity of the reference battery from the inflection point to the charging cut-off position in each decay operation, and obtaining a battery balance parameter based on the current capacity, wherein the battery balance parameter is equal to the ratio of the negative electrode capacity to the positive electrode capacity; 4) obtaining a corresponding SOH value based on the battery balancing parameters, and establishing a characteristic relationship diagram between the battery balancing parameters and the SOH value, wherein the characteristic relationship diagram is a horizontal and vertical coordinate diagram established based on the battery balancing parameters and the SOH value; 5) Setting a second temperature and a second rate, performing a cycle attenuation operation on the test battery, calculating the current capacity of the test battery from the inflection point to the charge cut-off position, querying the characteristic relationship diagram in step 4) based on the current capacity, obtaining the SOH value of the test battery, and completing the SOH prediction, wherein the second rate is equal to the first rate.

2. The battery SOH prediction method according to claim 1, characterized in that: The first temperature range is [30 degrees Celsius, 50 degrees Celsius].

3. The battery SOH prediction method according to claim 2, characterized in that: The absolute value of the difference between the second temperature and the first temperature is k, where k is a natural number greater than or equal to 0 and less than or equal to 5.

4. The battery SOH prediction method according to claim 1, characterized in that: The first rate and the second rate are both 0.1C or 0.15C or 0.2C or 0.25C or 0.3C or 0.33C, wherein 1C represents the current intensity when the battery is fully discharged in one hour.

5. The battery SOH prediction method according to claim 1, characterized in that: The number of cyclic decay operations is 100 times, 200 times, 300 times, or 500 times.

6. The battery SOH prediction method according to claim 1, characterized in that: The reference capacity is n%, where n is a natural number greater than 0 and less than or equal to m, and m is equal to 80, 85, or 90.

7. The battery SOH prediction method according to claim 1, characterized in that: The process of obtaining the inflection point position includes: in the process of the charging curve of the reference battery changing from the first state to the second state, the inflection point at which the slope of the charging curve changes from increasing to decreasing is obtained, and the inflection point is the inflection point position.

8. A storage medium, characterized in that: The storage medium includes one or more programs, and the one or more programs include instructions for executing the battery SOH prediction method according to any one of claims 1 to 7.

9. A battery SOH prediction system, used to implement the battery SOH prediction method according to any one of claims 1 to 7, characterized in that: The battery SOH prediction system includes: Module 1: setting a first temperature and a first rate, performing a cyclic decay operation on a reference battery, causing the reference battery to decay to a reference capacity, and obtaining charging data of the reference battery in each decay operation; Module 2: Obtaining a charging curve of the reference battery from the charging data based on the voltage change rate, and obtaining an inflection point position of the charging curve; Module 3: Calculating the current capacity of the reference battery from the inflection point to the charging cut-off position in each decay operation, and obtaining the battery balancing parameters according to the current capacity; Module 4: Obtain the corresponding SOH value based on the battery balancing parameters and establish a characteristic relationship diagram between the battery balancing parameters and the SOH value; Module 5: Set the second temperature and the second rate, perform a cycle attenuation operation on the test battery, calculate the current capacity of the test battery from the inflection point position to the charge cut-off position, query the characteristic relationship diagram in the module 4 based on the current capacity, obtain the SOH value of the test battery, and complete the SOH prediction.

10. The battery SOH prediction system according to claim 9, characterized in that: The module 1 includes a data storage unit and a data processing unit, wherein: the data storage unit is used to store the charging data, wherein the charging data includes: voltage, current and sampling time; the data processing unit is used to extract, clean and fit the charging data.

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