Methods, apparatus, electronic devices and storage media for fitting open-circuit voltages

Abstract

This application relates to the field of battery testing technology, and more particularly to a method, apparatus, electronic device, and storage medium for fitting open-circuit voltage. The method includes: acquiring test data obtained by performing a pulse charge-discharge test on a battery; assigning values ​​to a first model parameter in a target fitting model based on the test data, wherein the battery terminal voltage in the target fitting model is equal to the superposition of ohmic voltage drop, charge transfer polarization voltage drop, diffusion polarization voltage drop, and open-circuit voltage, and the first model parameter includes ohmic impedance in the ohmic voltage drop, reaction impedance in the charge transfer polarization voltage drop, and diffusion impedance in the diffusion polarization voltage drop; and obtaining the open-circuit voltage of the battery under different states of charge based on the target fitting model, wherein different states of charge correspond to different battery terminal voltages. Therefore, by employing pulse charge-discharge testing and model fitting, the estimation speed and prediction accuracy of the open-circuit voltage are improved.

Description

Technical Field

[0001] This application relates to the field of battery testing technology, and in particular to a method, apparatus, electronic device, and storage medium for fitting open-circuit voltage. Background Technology

[0002] Open circuit voltage (OCV) is an important parameter for studying the thermodynamic state of lithium-ion batteries and is of great significance for cell design and battery management system (BMS). Therefore, accurate estimation of OCV is essential.

[0003] Currently, the most commonly used method for OCV estimation is experimental measurement. This method involves adjusting the cell's SOC to a specified level, then maintaining the cell in an open-circuit state for an extended period until the open-circuit voltage stabilizes. This stable value is then used as the OCV data for the corresponding state of charge (SOC). However, this method is time-consuming and difficult to meet the needs of practical engineering and online applications. Summary of the Invention

[0004] This application provides a method, apparatus, electronic device, and storage medium for fitting open-circuit voltage, which can quickly and accurately obtain the open-circuit voltage of a battery under different states of charge.

[0005] To achieve the above objectives, this application adopts the following technical solution:

[0006] Firstly, a method for fitting open-circuit voltage is provided, including:

[0007] Obtain test data from pulse charge-discharge tests on the battery;

[0008] Based on the test data, assign values ​​to the first model parameters in the target fitting model.

[0009] In the target fitting model, the battery terminal voltage is equal to the superposition of ohmic voltage drop, charge transfer polarization voltage drop, diffusion polarization voltage drop and open circuit voltage. The first model parameters include the ohmic impedance in the ohmic voltage drop, the reaction impedance in the charge transfer polarization voltage drop and the diffusion impedance in the diffusion polarization voltage drop.

[0010] Based on the target fitting model, the open-circuit voltage of the battery under different states of charge is obtained, wherein different states of charge correspond to different battery terminal voltages.

[0011] In the technical solution of this application embodiment, pulse charge-discharge testing and model fitting are used to improve the estimation speed of open circuit voltage. The ohmic impedance in the ohmic voltage drop, the reaction impedance in the charge transfer polarization voltage drop, and the diffusion impedance in the diffusion polarization voltage drop are used as the first model parameters in the target fitting model, so that the fitting model can more accurately reflect the internal characteristics of the battery, thereby improving the prediction accuracy of open circuit voltage.

[0012] In some embodiments, assigning values ​​to the first model parameters in the target fitting model based on the test data includes:

[0013] Based on the test data, the ohmic impedance values ​​of the battery under different states of charge are obtained;

[0014] Extract the data to be processed from the test data, and perform impedance decomposition on the data to be processed to obtain the values ​​of the reaction impedance and the diffusion impedance.

[0015] The first model parameter in the target fitting model is assigned a value based on the obtained values ​​of the ohmic impedance, the reaction impedance, and the diffusion impedance.

[0016] In the technical solution of this application embodiment, the values ​​of reaction impedance and diffusion impedance are accurately calculated through impedance decomposition.

[0017] In some embodiments, obtaining the ohmic impedance values ​​of the battery under different states of charge based on the test data includes:

[0018] Based on the test data, determine the state of charge corresponding to each discharge period and relaxation period;

[0019] Based on the state of charge corresponding to each discharge period and relaxation period, and the test data, ohmic impedance curves corresponding to different states of charge are generated, wherein the ohmic impedance curves are used to reflect the ohmic impedance values ​​of the battery under different states of charge.

[0020] In the technical solution of this application embodiment, accurate and reliable ohmic impedance curves for different states of charge can be obtained.

[0021] In some embodiments, determining the state of charge corresponding to each discharge period and relaxation period based on the test data includes:

[0022] Based on the test data, obtain the cumulative charge and discharge capacity of the battery;

[0023] Based on the cumulative charge-discharge capacity, the initial state of charge of the battery, and the rated capacity of the battery, calculate the state of charge of the battery at different times;

[0024] Based on the state of charge of the battery at different times, and the times corresponding to each discharge period and relaxation period, the state of charge corresponding to each discharge period and relaxation period is determined.

[0025] In the technical solution of this application embodiment, a precise correspondence between ohmic impedance and SOC is achieved.

[0026] In some embodiments, generating ohmic impedance curves corresponding to different states of charge based on the states of charge corresponding to each discharge period and relaxation period, and the test data, includes:

[0027] Based on the time-voltage sequence data in the test data, determine the first voltage sample value and the second voltage sample value corresponding to multiple voltage transient periods, wherein the first voltage sample value represents the voltage value collected at the moment before the voltage transient, and the second voltage sample value represents the voltage value collected at the moment after the voltage transient.

[0028] Based on the first voltage sample value and the second voltage sample value corresponding to multiple voltage transient periods, the ohmic impedance value corresponding to each voltage transient period is calculated;

[0029] Based on the state of charge corresponding to each discharge period and relaxation period, and the time corresponding to each discharge period and relaxation period, the state of charge corresponding to each voltage transient period is determined.

[0030] Based on the ohmic impedance value and state of charge corresponding to each voltage transient period, an ohmic impedance curve corresponding to the continuous state of charge is generated.

[0031] In the technical solution of this application embodiment, the ohmic impedance is calculated by using the sampled values ​​before and after the voltage transient, which can obtain an accurate and reliable ohmic impedance curve when there is data acquisition at a high frequency of time points during the test.

[0032] In some embodiments, generating an ohmic impedance curve corresponding to a continuous state of charge based on the state of charge corresponding to each discharge period and relaxation period, and the test data, includes:

[0033] Based on the test data, determine the end voltage value of the relaxation period and the initial voltage value of the discharge period;

[0034] The value of the ohmic impedance corresponding to each initial current application period is determined based on the initial voltage value of each discharge period, the final voltage value of each relaxation period, and the current value of the discharge current applied at the beginning of the discharge period.

[0035] Based on the state of charge corresponding to each discharge period and relaxation period, determine the state of charge corresponding to each initial current application period;

[0036] Based on the ohmic impedance value and state of charge corresponding to each initial current application period, an ohmic impedance curve corresponding to the continuous state of charge is generated.

[0037] In the technical solution of this application embodiment, an accurate and reliable ohmic impedance curve can be obtained while maintaining high sampling time accuracy.

[0038] In some embodiments, the test data includes response voltages at different times, the response voltages being acquired based on data collected while a constant current is applied to the battery.

[0039] The step of generating an ohmic impedance curve corresponding to a continuous state of charge based on the state of charge corresponding to each discharge period and relaxation period, and the test data, includes:

[0040] The preset RC current fitting equation is invoked, and nonlinear fitting is performed based on the response voltage to obtain the ohmic impedance value of the battery at different times;

[0041] Based on the state of charge corresponding to the discharge period and relaxation period, and the time information corresponding to the discharge period and relaxation period, the time corresponding to each state of charge is determined.

[0042] Based on the ohmic impedance values ​​corresponding to the different times and the times corresponding to each state of charge, the ohmic impedance curves corresponding to the continuous states of charge are obtained.

[0043] In the technical solution of this application embodiment, the RC current fitting equation is used to perform nonlinear fitting of the response voltage under constant current to obtain the ohmic impedance, which can effectively make up for the problem of insufficient sampling accuracy and improve the accuracy of ohmic impedance calculation at different times.

[0044] In some embodiments, before invoking a preset RC current fitting equation and performing nonlinear fitting based on the response voltage to obtain the ohmic impedance values ​​of the battery at different times, the method further includes:

[0045] Determine the initial response voltage, the first product term of the constant current and the ohmic impedance, and the second product term of the constant current and the polarization impedance;

[0046] The second product term is corrected by exponential decay to obtain the third product term;

[0047] Based on the initial response voltage, the first product term, the third product term, and the response voltage, the RC current fitting equation is constructed.

[0048] The response voltage is equal to the sum of the initial response voltage, the first product term, and the third product term.

[0049] In the technical solution of this application embodiment, an RC current fitting equation including exponential decay correction is constructed, which better fits the voltage response characteristics of battery polarization impedance, thereby improving the reliability of ohmic impedance fitting results.

[0050] In some embodiments, the data to be processed includes the following:

[0051] The voltage value at the end of the relaxation period;

[0052] The first voltage value corresponding to the application of a constant current for a first duration during the discharge period;

[0053] The second voltage value corresponding to the application of a constant current for a second duration during the discharge period, wherein the first duration is shorter than the second duration; and

[0054] The value of the constant current applied during the discharge period.

[0055] Correspondingly, the impedance decomposition process performed on the data to be processed to obtain the values ​​of both the reaction impedance and the diffusion impedance includes:

[0056] The first DC internal resistance value is determined based on the first voltage value, the terminal voltage value, and the constant current value.

[0057] The second DC internal resistance value is determined based on the second voltage value, the terminal voltage value, and the constant current value.

[0058] The value of the diffusion impedance is determined based on the difference between the second DC internal resistance value and the first DC internal resistance value;

[0059] The value of the reactive impedance is determined based on the difference between the first DC internal resistance value and the ohmic impedance value.

[0060] In the technical solution of this application embodiment, impedance decomposition is achieved based on the difference of DC internal resistance for different durations. The difference between long-term DCR and short-term DCR corresponds to diffusion impedance, and the difference between short-term DCR and ohmic impedance corresponds to reaction impedance.

[0061] In some embodiments, after assigning values ​​to the first model parameters in the target fitting model based on the test data, the method further includes:

[0062] Based on the values ​​of the first model parameters, assign values ​​to the second model parameters in the target fitting model.

[0063] The second model parameters include the reaction impedance time constant in the charge transfer polarization voltage drop, the diffusion impedance time constant in the diffusion polarization voltage drop, the initial open-circuit voltage, and the overpotential.

[0064] In the technical solution of this application embodiment, the values ​​of the first model parameters are obtained first, and the remaining second model parameters are derived last, which ensures the accuracy of parameter calculation, provides accurate initial values ​​for fitting the target fitting model to obtain OCV, reduces the number of optimization attempts, and improves the stability of the algorithm.

[0065] In some embodiments, assigning values ​​to the second model parameters in the target fitting model based on the values ​​of the first model parameters includes:

[0066] Based on the values ​​of the ohmic impedance, the reaction impedance, and the diffusion impedance, the reaction impedance time constant and the diffusion impedance time constant are obtained by segmenting the voltage response according to the time sequence.

[0067] The ohmic impedance, the corresponding state of charge, the value of the reaction impedance, the value of the diffusion impedance, and the charge / discharge rate are input into a pre-trained machine learning model to obtain the overpotential.

[0068] The sum of the voltage value at the end of the relaxation period and the overpotential is taken as the initial open-circuit voltage.

[0069] In the technical solution of this application embodiment, the correlation between SOC, diffusion impedance, and overpotential can be accurately fitted through a machine learning model, which has the advantages of strong interpretability, few parameters, and strong robustness. The time constant is obtained by time-series segmented calculation, which aligns with the characteristic that reactive impedance dominates first and diffusion impedance dominates later in the voltage response, ensuring the accuracy of the time constant calculation.

[0070] In some embodiments, the step of calculating the reaction impedance time constant and the diffusion impedance time constant in segments according to the time sequence of the voltage response based on the values ​​of the ohmic impedance, the reaction impedance, and the diffusion impedance includes:

[0071] Determine the first equation corresponding to the first interval after the current is applied during the discharge period, wherein the first interval represents the time interval in which the reaction impedance dominates the voltage response;

[0072] Substitute the first battery terminal voltage value, the ohmic impedance value, and the reaction impedance value corresponding to the first interval into the first equation, and perform a first-order Taylor expansion on the first equation to obtain the reaction impedance time constant.

[0073] Determine the second equation corresponding to the second interval after the current is applied during the discharge period, wherein the second interval represents the time interval in which the diffusion impedance dominates the voltage response;

[0074] Substitute the second battery terminal voltage value, the first battery terminal voltage value, and the diffusion impedance value corresponding to the second interval into the second equation, and perform a first-order Taylor expansion on the second equation to obtain the diffusion impedance time constant.

[0075] In the technical solution of this application embodiment, equations are established for different time intervals dominated by reaction impedance and diffusion impedance, which accurately matches the timing characteristics of battery voltage response.

[0076] In some embodiments, after obtaining the open-circuit voltage of the battery under different states of charge based on the target fitting model, the method further includes:

[0077] Determine the battery terminal voltage value corresponding to the target time and the current value applied to the battery, wherein the target time represents the time when the diffusion impedance is stable;

[0078] Determine the corresponding target open-circuit voltage based on the state of charge at the target time;

[0079] The DC internal resistance of the battery at the target time is calculated based on the battery terminal voltage, the current value, and the target open-circuit voltage.

[0080] In the technical solution of this application embodiment, the DC internal resistance value of the battery when the diffusion impedance is relatively stable can be calculated.

[0081] In some embodiments, acquiring test data for pulse charge-discharge testing of the battery includes:

[0082] Acquire initial data, which includes test data from pulse charge-discharge tests performed on the battery;

[0083] Identify the target data segment in the initial data, wherein the target data segment refers to the data reflecting the battery from the discharge period to the relaxation period;

[0084] If the number of consecutive occurrences of the target data segment in the initial data is greater than the target number of segments, the consecutively occurring target data segments will be used as the test data.

[0085] The test data is extracted from the initial data.

[0086] In the technical solution of this application embodiment, the target data segment reflecting the discharge-relaxation process is selected from the initial data as test data, which effectively eliminates aliased data and ensures the validity of the test data.

[0087] Secondly, an open-circuit voltage fitting device is provided, comprising:

[0088] The first acquisition module is used to acquire test data obtained from pulse charge-discharge tests on the battery;

[0089] The assignment module is used to assign values ​​to the first model parameters in the target fitting model based on the test data.

[0090] In the target fitting model, the battery terminal voltage is equal to the superposition of ohmic voltage drop, charge transfer polarization voltage drop, diffusion polarization voltage drop and open circuit voltage. The first model parameters include the ohmic impedance in the ohmic voltage drop, the reaction impedance in the charge transfer polarization voltage drop and the diffusion impedance in the diffusion polarization voltage drop.

[0091] The second acquisition module is used to acquire the open-circuit voltage of the battery under different states of charge based on the target fitting model, wherein different states of charge correspond to different battery terminal voltages.

[0092] Thirdly, embodiments of this application provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the open-circuit voltage fitting method as described in any of the first aspects above.

[0093] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method for fitting open-circuit voltage as described in any of the first aspects above.

[0094] Fifthly, embodiments of this application provide a computer program product that, when run on an electronic device, causes the electronic device to execute the open-circuit voltage fitting method described in any of the first aspects above.

[0095] It is understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here.

[0096] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0097] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiments below. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0098] Figure 1 This is a flowchart illustrating the method for fitting open-circuit voltage provided in an embodiment of this application;

[0099] Figure 2 This is the voltage-time curve obtained from the battery pulse charge-discharge test provided in the embodiments of this application;

[0100] Figure 3 This is a schematic diagram of the fitting circuit for ohmic impedance provided in an embodiment of this application;

[0101] Figure 4 A schematic diagram of the battery equivalent circuit for the fitting model provided in the embodiments of this application;

[0102] Figure 5 This is a schematic diagram of pulse OCV based on dynamic initial value fitting provided in an embodiment of this application;

[0103] Figure 6 This is a structural block diagram of the open-circuit voltage fitting device provided in the embodiments of this application;

[0104] Figure 7 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0105] The embodiments of the technical solutions of this application will now be described in detail with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of this application, and are therefore merely examples and should not be used to limit the scope of protection of this application. When the following description relates to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. Various changes, modifications, and equivalents of the methods, apparatus, and / or systems described herein will become apparent upon understanding this disclosure. For example, the order of operations described herein is merely illustrative and is not limited to those orders set forth herein, but can be changed as will become apparent upon understanding this disclosure, except for operations that must be performed in a specific order. Furthermore, for clarity and conciseness, descriptions of features known in the art may be omitted.

[0106] The embodiments described in the following examples of this disclosure are not representative of all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0107] It should be noted that lithium battery OCV requires low current or long periods of rest to depolarize, therefore the testing time is often very long. For example, a low-current test of 0.04C would require over 25 hours to complete. To measure the true OCV for each state of charge (SOC), the battery needs to be left to rest at that SOC for 2 to 5 hours. Measuring the OCV at all points across the entire SOC range would take several days, making the process extremely lengthy.

[0108] Currently, some methods utilize equivalent circuit models to obtain the OCV (Optical Characteristic Value). However, the initial values ​​of the equivalent circuit model have a significant impact on the estimated OCV. Due to limitations in project timelines and testing resources, it is often difficult to obtain a large number of samples to fully calibrate the initial values, resulting in inaccurate OCV fitting results.

[0109] Some methods involve fitting OCV using fixed initial values. However, fixing these initial values ​​is affected by the diffusion coefficient, leading to unstable and inaccurate fitting results. For example, battery materials typically exhibit significant differences in diffusion coefficients between high and low SOC ranges, resulting in unstable fitting performance at both SOC levels. Furthermore, the large differences in diffusion coefficients during the relaxation periods of different battery systems also affect the final fitting results.

[0110] To address at least one of the aforementioned problems, embodiments of this application propose a method, apparatus, electronic device, and storage medium for fitting open-circuit voltage.

[0111] It should be noted that the execution subject of the open-circuit voltage fitting method in this embodiment can be an open-circuit voltage fitting device, hereinafter referred to as "device". This device can be configured in any type of electronic device, such as a server, a laptop, a super mobile personal computer, or other electronic devices that can implement the open-circuit voltage fitting method. This application embodiment does not limit this.

[0112] See Figure 1 This is a flowchart illustrating the open-circuit voltage fitting method provided in an embodiment of this application. Figure 1 As shown, the method for fitting the open-circuit voltage may include the following steps:

[0113] Step 100: Obtain test data from pulse charge-discharge tests on the battery.

[0114] Pulse charge-discharge testing, also known as pulse OCV testing, is a method for quickly obtaining the open-circuit voltage of a battery under various states of charge. In pulse charge-discharge testing, short-duration constant charge / discharge pulses are applied to the battery multiple times. It should be noted that pulse charge-discharge testing significantly reduces testing time compared to traditional static OCV testing.

[0115] Open-circuit voltage refers to the voltage across the battery terminals when there is no load (i.e., the circuit is open). Open-circuit voltage depends primarily on the battery's chemical composition and the current temperature.

[0116] As an example, in the pulse charge-discharge test of this application, the battery can be charged once and then discharged more than 30 times, without limitation.

[0117] The test data can refer to the data collected during the electrical pulse charge and discharge test, such as the voltage, current, and cumulative charge and discharge capacity at different times, etc., without limitation.

[0118] One possible approach is to first acquire initial data, then identify target data segments within the initial data. If the number of consecutive occurrences of the target data segment in the initial data is greater than the target number of segments, the consecutively occurring target data segments are used as test data, and test data is extracted from the initial data.

[0119] The initial data may include test data from pulse charge-discharge tests on the battery.

[0120] In some scenarios, the initial data can be a mixture of multiple types of data. For example, in addition to test data for pulse charge and discharge testing of the battery, the initial data can also include data from other types of tests (such as rate test data), etc. There are no restrictions here.

[0121] For example, the initial data might be raw lifetime test data, which contains overlapping data from rate testing and pulse charge-discharge testing. Therefore, it's necessary to extract the data from the initial data based on the characteristics of pulse charge-discharge testing.

[0122] The target number of segments can be set by the testers based on their actual experience, such as 10 segments, 15 segments, etc., and is not limited here.

[0123] The target data segment refers to the data that reflects the battery's transition from the discharge phase to the relaxation phase.

[0124] The discharge period can refer to the test data period during which a constant current is applied to the battery in a pulse charge-discharge test.

[0125] The relaxation period can be the test data period during pulse charge-discharge testing when the current applied to the battery is stopped and the battery is left to rest. During the relaxation period, the battery polarization gradually decreases and the battery voltage recovers to the equilibrium potential.

[0126] Figure 2 The voltage-time curve obtained from the battery pulse charge-discharge test reflects the voltage changes during the pulse charge-discharge test.

[0127] like Figure 2 As shown, Figure 2 It contains multiple cycles of "sudden drop in discharge voltage → slight rebound in resting voltage", each voltage rebound ( Figure 2 The sawtooth wave pattern in the image corresponds to one pulse cycle of "discharge-relaxation". The target data segment reflects the data of this "discharge-relaxation" pulse cycle. With the accumulation of multiple discharge pulses, the battery gradually decreases from a high SOC to a low SOC, and the voltage slowly drops from approximately 4.3V to approximately 2.5V. After each discharge, the battery enters a relaxation phase, during which the voltage briefly rises, reflecting the gradual decay of battery polarization and recovery towards equilibrium OCV.

[0128] Step 200: Assign values ​​to the first model parameters in the target fitting model based on the test data.

[0129] The first model parameters include the ohmic impedance in the ohmic voltage drop, the reaction impedance in the charge transfer polarization voltage drop, and the diffusion impedance in the diffusion polarization voltage drop.

[0130] In the target fitting model, the battery terminal voltage is equal to the superposition of the ohmic voltage drop, the charge transfer polarization voltage drop, the diffusion polarization voltage drop, and the open circuit voltage.

[0131] Optionally, the target fitting model can be an RC circuit model, which is not limited here. As one implementation, the fitting model in this embodiment can be a second-order RC circuit fitting equation.

[0132] Specifically, based on the test data, the ohmic impedance values ​​of the battery under different states of charge can be obtained. Then, the data to be processed in the test data can be extracted and impedance decomposition can be performed on the data to be processed to obtain the values ​​of reaction impedance and diffusion impedance. After that, based on the obtained values ​​of ohmic impedance, reaction impedance and diffusion impedance, the first model parameter in the target fitting model can be assigned.

[0133] In one embodiment, the terminal voltage ΔV and discharge current I corresponding to different discharge durations (such as 5s, 10s, 30s, 60s) can be extracted from the test data, and then the DC internal resistance for each discharge duration can be calculated according to the formula DCR=ΔV / I.

[0134] Among them, the Direct Current Resistance (DCR) is a parameter that measures the resistance generated inside the battery when a direct current passes through it.

[0135] Furthermore, a series of time-voltage curves are generated based on SOC, and then nonlinear fitting is performed on the time-voltage curves to obtain the ohmic impedance reference value (intercept of the fitted curve), the reaction impedance fitted value (the rapidly rising segment of the curve), and the diffusion impedance fitted value (the flat segment of the curve), thereby obtaining the ohmic impedance, reaction impedance, and diffusion impedance.

[0136] In some embodiments, the step of "obtaining the ohmic impedance value of the battery under different states of charge based on test data" may further include the following sub-steps (steps 211 and 212):

[0137] Step 211: Based on the test data, determine the state of charge corresponding to each discharge period and relaxation period.

[0138] One possible approach is to first obtain the battery's cumulative charge-discharge capacity based on test data. Then, based on the cumulative charge-discharge capacity, the battery's initial state of charge (SOC), and the battery's rated capacity, calculate the battery's SOC at different times. Finally, based on the battery's SOC at different times, and the times corresponding to each discharge and relaxation period, determine the SOC for each discharge and relaxation period.

[0139] The cumulative charge-discharge capacity refers to the total amount of electricity that the battery has accumulated from the start of the test to the current time t, measured in ampere-hours (Ah). If the test data does not include the cumulative charge-discharge capacity, it can be calculated using the ampere-hour integration method.

[0140] The initial state of charge (OSC) refers to the percentage of the battery's usable charge relative to its rated capacity at the start of the test (t=0). The OSC can be determined by the initial static loading time (OCV) or preset operating conditions before the test.

[0141] Rated capacity refers to the maximum nominal amount of electricity a battery can discharge under specified charge and discharge conditions, measured in ampere-hours (Ah). Rated capacity is used to normalize the cumulative charge and discharge capacity to a percentage of state of charge.

[0142] The formula for calculating the battery's state of charge at different times, based on the cumulative charge-discharge capacity, the battery's initial state of charge, and the battery's rated capacity, can be as follows:

[0143]

[0144] in, It is the state of charge of the battery at time t. This represents the initial state of charge of the battery. The cumulative charge and discharge capacity of the battery. This refers to the battery's rated capacity.

[0145] It should be noted that in some cases, the cumulative charge and discharge capacity of the battery is not directly included in the test data. In such cases, the cumulative charge and discharge capacity of the battery can be obtained by integrating the ampere-hours. At this point, the formula for calculating the state of charge can be as follows:

[0146]

[0147] in, This represents the sampling time interval.

[0148] In determining the state of charge (SOC) for each discharge and relaxation period based on the battery's SOC at different times and the times corresponding to each discharge and relaxation period, the time boundaries of each discharge and relaxation period can be obtained first. The midpoint of the time boundary can be selected, and the SOC corresponding to the midpoint can be used as the SOC for that discharge or relaxation period. Alternatively, the start and end times of the time boundary can be selected, and the SOC corresponding to the start and end times can be used as the SOC for that discharge or relaxation period.

[0149] Step 212: Based on the state of charge corresponding to each discharge period and relaxation period, and the test data, generate ohmic impedance curves corresponding to different states of charge.

[0150] The ohmic impedance curve is used to reflect the ohmic impedance of the battery under different states of charge.

[0151] As one implementation method, if there is data acquisition with a high time frequency during the test, the first voltage sample value and the second voltage sample value corresponding to multiple voltage transient periods can be determined firstly based on the time voltage sequence data in the test data. Then, based on the first voltage sample value and the second voltage sample value corresponding to multiple voltage transient periods, the ohmic impedance value corresponding to each voltage transient period can be calculated. According to the state of charge corresponding to each discharge period and relaxation period, and the time corresponding to each discharge period and relaxation period, the state of charge corresponding to each voltage transient period can be determined. Based on the ohmic impedance value and state of charge corresponding to each voltage transient period, the ohmic impedance curve corresponding to the continuous state of charge can be generated.

[0152] Among them, the time-voltage sequence data can be "time-battery terminal voltage" paired data collected by the test equipment at fixed time intervals, such as (t1,V1), (t2,V2), (t3,V3)...(tn,Vn).

[0153] The first voltage sample value represents the voltage value collected before the voltage transient, which is the stable voltage before the current is applied. The second voltage sample value represents the voltage value collected after the voltage transient, which is the sudden voltage change immediately after the current is applied.

[0154] Among them, the voltage transient period refers to the extremely short time period during which the current suddenly increases from zero. During the voltage transient period, the battery voltage will jump instantly.

[0155] The formula for calculating the ohmic impedance corresponding to the voltage transient period based on the first and second voltage sample values ​​can be as follows:

[0156]

[0157] in, This is the second voltage sample value. This is the first voltage sample value. I is the value of the ohmic impedance, and I is the applied current value.

[0158] Furthermore, after obtaining the ohmic impedance value corresponding to each voltage transient period, the state of charge corresponding to each discharge period and relaxation period calculated in step 211, as well as the calibrated time intervals of each discharge period and relaxation period, is used to first determine the state of charge corresponding to each voltage transient period. Next, the ohmic impedance value corresponding to each voltage transient period is correlated with the state of charge of the voltage transient period to form multiple sets of state of charge-ohmic impedance numerical pairs. Finally, nonlinear fitting processing is performed on these numerical pairs to generate an ohmic impedance curve corresponding to a continuous state of charge with the state of charge as the abscissa and the ohmic impedance value as the ordinate.

[0159] As another implementation method, when the sampling time accuracy is high, the end voltage value of the relaxation period and the initial voltage value of the discharge period can be determined based on the test data. Then, based on the initial voltage value of each discharge period, the end voltage value of each relaxation period, and the current value of the discharge current applied at the beginning of the discharge period, the ohmic impedance value corresponding to each current initial application period can be determined. Based on the state of charge corresponding to each discharge period and relaxation period, the state of charge corresponding to each current initial application period can be determined. Finally, based on the ohmic impedance value and state of charge corresponding to each current initial application period, the ohmic impedance curve corresponding to the continuous state of charge can be generated.

[0160] The voltage value at the end of the relaxation period refers to the last stable voltage sample value of the battery before it enters the discharge phase after the previous relaxation period ends.

[0161] The initial voltage value during the discharge period refers to the first voltage sample value when the battery relaxation period ends and the current is applied at the beginning of the discharge period. It is the first response voltage after the initial application of current.

[0162] The initial current application period is a very short time from the end of the relaxation phase and the start of the discharge current application to the acquisition of the first voltage sample value of the discharge phase.

[0163] The formula for determining the ohmic impedance corresponding to the initial current application period, based on the initial voltage value of the discharge period, the final voltage value of the relaxation period, and the current value of the discharge current applied at the beginning of the discharge period, can be as follows:

[0164]

[0165] in, For ohmic impedance, This represents the initial voltage value during the discharge period. I is the voltage value at the end of the relaxation period, and I is the current value of the discharge current applied at the beginning of the charging and discharging period.

[0166] Furthermore, after obtaining the ohmic impedance value corresponding to each initial current application period, the state of charge corresponding to each discharge period and relaxation period calculated in step 211, as well as the calibrated time intervals of each discharge period and relaxation period, is used to first determine the state of charge corresponding to each initial current application period. Next, the ohmic impedance value corresponding to each initial current application period is correlated with the state of charge during the initial current application period to form multiple sets of state of charge-ohmic impedance numerical pairs. Finally, these numerical pairs are subjected to nonlinear fitting processing to generate an ohmic impedance curve corresponding to a continuous state of charge, with the state of charge as the abscissa and the ohmic impedance value as the ordinate.

[0167] As another implementation method, when the sampling accuracy is insufficient, a preset RC current fitting equation can be called first to perform nonlinear fitting based on the response voltage to obtain the ohmic impedance value of the battery at different times. Then, based on the state of charge corresponding to the discharge period and relaxation period, as well as the time information corresponding to the discharge period and relaxation period, the time corresponding to each state of charge is determined. After that, based on the ohmic impedance value corresponding to different times and the time corresponding to each state of charge, the ohmic impedance curve corresponding to the continuous state of charge is obtained.

[0168] The test data includes response voltages at different times, which can be obtained by applying a constant current to the battery.

[0169] The preset RC current fitting equation can be as follows:

[0170]

[0171] Where V(t) is the response voltage at time t, in units of V. The impedance is in ohms, expressed in Ω. This is the polarization resistance, measured in Ω. is a time constant, related to the electrochemical response rate, and is measured in seconds (s).

[0172] Optionally, before calling the preset RC current fitting equation and performing nonlinear fitting based on the response voltage to obtain the ohmic impedance value of the battery at different times, the first product term of the initial response voltage, constant current and ohmic impedance, and the second product term of constant current and polarization impedance are first determined. Then, the second product term is corrected by exponential decay to obtain the third product term. After that, the RC current fitting equation is constructed based on the initial response voltage, the first product term, the third product term and the response voltage.

[0173] The initial response voltage is the stable voltage during the relaxation period before the current is applied, and it is the fitted voltage reference value.

[0174] The response voltage is equal to the sum of the initial response voltage, the first product term, and the third product term.

[0175] Among them, polarization impedance is the sum of reaction impedance and diffusion impedance, representing the total impedance corresponding to the electrochemical polarization of the battery.

[0176] The first product term is the product of the constant current and the ohmic impedance. , representing the instantaneous ohmic voltage drop.

[0177] The second product term is the product of the constant current and the polarization impedance. , representing polarization voltage drop.

[0178] The third product term is This indicates an exponentially decaying correction to the polarization voltage drop.

[0179] Combining the initial response voltage, the first product term, the third product term, and the response voltage, the RC current fitting equation is constructed as follows: .

[0180] It should be noted that, firstly, a preset RC current fitting equation is invoked, and the time-response voltage sequence data from the test data is substituted into the RC current fitting equation for nonlinear fitting to obtain the ohmic impedance values ​​of the battery at different times. Subsequently, based on the determined states of charge (SOCs) for each discharge and relaxation period, and the corresponding time information, a mapping relationship between time and SOC is established, thereby determining the specific time corresponding to each SOC. Finally, based on the ohmic impedance values ​​at different times, combined with the SOCs at each time, multiple sets of SOC and ohmic impedance data are fitted to generate an ohmic impedance curve that continuously covers the entire SOC range.

[0181] Figure 3 A schematic diagram of the fitting circuit for ohmic impedance, as shown below. Figure 3 As shown, the circuit consists of an open-circuit voltage source U oc The circuit consists of an ohmic resistor R2, a parallel polarizing resistor R1, and a polarizing capacitor C1 connected in series. The two ends of the circuit are the positive and negative output terminals of the battery terminal voltage UL. When a constant current I is applied, the change of the battery terminal voltage UL with time t satisfies: UL(t) = U oc +IR2+IR1( ), τ=R1C1.

[0182] The data to be processed is a set of test data used for impedance decomposition, specifically including the following items:

[0183] The voltage value at the end of the relaxation period;

[0184] The first voltage value corresponding to the application of a constant current for a first duration during the discharge period;

[0185] The second voltage value corresponding to the application of a constant current for a second duration during the discharge period;

[0186] The value of the constant current applied during the discharge period.

[0187] The voltage value at the end of the relaxation period refers to the last voltage sample value when the battery is placed in a stable state after the previous discharge stage ends and before the current discharge stage begins.

[0188] The first voltage value refers to the battery terminal voltage value collected after applying a constant current for a first duration (e.g., 1 second) during the discharge period. When a constant current for the first duration is applied during the discharge period, the battery polarization is dominated by ohmic impedance and reaction impedance, while diffusion impedance has not yet been fully established.

[0189] The first duration is shorter than the second duration. As a typical example, the first duration is 1 second and the second duration is 60 seconds.

[0190] The second voltage value refers to the battery terminal voltage value collected after applying a constant current for a second duration (e.g., 60s) during the discharge period. At this time, the battery's ohmic impedance, reaction impedance, and diffusion impedance have been fully established, forming a stable polarization state.

[0191] The constant current refers to the magnitude of the constant discharge current applied during the discharge period.

[0192] It should be noted that diffusion impedance refers to the impedance generated during the charging and discharging process of a battery when lithium ions diffuse within the active material of the electrode, forming concentration polarization, reflecting the ease or difficulty of concentration polarization. Reaction impedance refers to the impedance generated when lithium ions and electrons undergo a charge transfer reaction at the electrode / electrolyte interface, reflecting the ease or difficulty of the charge transfer reaction.

[0193] Among these steps, impedance decomposition of the data to be processed, yielding the values ​​of both reaction impedance and diffusion impedance, may include:

[0194] The first DC internal resistance value is determined based on the first voltage value, the terminal voltage value, and the constant current value.

[0195] The second DC internal resistance value is determined based on the second voltage value, the terminal voltage value, and the constant current value.

[0196] The value of the diffusion impedance is determined based on the difference between the second DC internal resistance value and the first DC internal resistance value.

[0197] The value of the reactive impedance is determined based on the difference between the first DC internal resistance value and the ohmic impedance value.

[0198] The first DC internal resistance value can refer to the DC internal resistance calculated based on the first voltage value, the voltage value at the end of the relaxation period, and the constant current value. The first DC internal resistance value can represent the battery internal resistance under the first duration, which is mainly composed of ohmic impedance and reactive impedance.

[0199] The formula for determining the first DC internal resistance value based on the first voltage value, the terminal voltage value, and the constant current value can be as follows:

[0200]

[0201] in, This represents the first DC internal resistance value with a duration of 1 second. The first voltage value, Here, I represents the terminal voltage, and I represents the constant current. It should be noted that the first DC internal resistance is approximately equal to the sum of the ohmic impedance and the reactive impedance, that is... .in, For ohmic impedance, This represents the reaction impedance.

[0202] The second DC internal resistance value can refer to the DC internal resistance calculated based on the second voltage value, the voltage value at the end of the relaxation period, and the constant current value. The second DC internal resistance value can represent the battery internal resistance under the second duration, which is composed of ohmic impedance, reaction impedance, and diffusion impedance.

[0203] The formula for determining the second DC internal resistance value based on the second voltage value, the terminal voltage value, and the constant current value can be as follows:

[0204]

[0205] in, This represents the second DC internal resistance value with a duration of 60 seconds. This is the second voltage value. Here, I represents the terminal voltage, and I represents the constant current. It should be noted that the second DC internal resistance is equal to the sum of the ohmic impedance, the reactive impedance, and the diffusion impedance, that is... .in, It represents the diffusion impedance.

[0206] The formula for determining the diffusion impedance based on the difference between the second DC internal resistance and the first DC internal resistance can be: .

[0207] The formula for determining the reaction impedance based on the difference between the first DC internal resistance and the ohmic impedance is as follows: .

[0208] Furthermore, the values ​​of the first model parameters can be used to assign values ​​to the second model parameters in the target fitting model.

[0209] The second model parameters include the reaction impedance time constant in the charge transfer polarization voltage drop, the diffusion impedance time constant in the diffusion polarization voltage drop, the initial open-circuit voltage, and the overpotential.

[0210] The reaction impedance time constant can be a parameter characterizing the rate of battery reaction polarization decay. It is obtained by multiplying the reaction impedance and the reaction capacitance. The smaller the reaction impedance time constant, the faster the reaction polarization decay.

[0211] The diffusion impedance time constant can be a parameter characterizing the concentration polarization decay rate of the battery. It is obtained by multiplying the diffusion impedance and the diffusion capacitance. The smaller the diffusion impedance time constant, the faster the concentration polarization decays.

[0212] The initial open-circuit voltage can be the initial reference value of the open-circuit voltage, which is different from the actual open-circuit voltage obtained by battery fitting. It can be calculated from the end voltage of the battery relaxation period combined with the overpotential.

[0213] Among them, overpotential can be the difference between the actual working potential of the battery electrode and the reversible equilibrium potential, reflecting the degree of voltage deviation caused by polarization during the battery charging and discharging process.

[0214] In some embodiments, the step "Assigning second model parameters to the target fitted model based on the values ​​of the first model parameters" may include the following sub-steps (steps 221, 222, and 223):

[0215] Step 221: Based on the values ​​of ohmic impedance, reaction impedance, and diffusion impedance, perform segmented calculations according to the time sequence of the voltage response to obtain the reaction impedance time constant and the diffusion impedance time constant.

[0216] Among them, the timing of voltage response refers to the order in which the battery terminal voltage changes over time after the battery discharge current is applied, that is, ohmic impedance → reaction impedance → diffusion impedance.

[0217] As one possible approach, firstly, the first equation corresponding to the first interval after the current is applied during the discharge period is determined. Then, the first battery terminal voltage value, ohmic impedance value, and reaction impedance value corresponding to the first interval are substituted into the first equation, and a first-order Taylor expansion is performed on the first equation to obtain the reaction impedance time constant.

[0218] The first interval represents the time interval during which the voltage response is dominated by the reaction impedance after the current is applied during the discharge period. During this stage, the diffusion impedance is not fully established, and the voltage response is mainly determined by the ohmic impedance and the reaction impedance.

[0219] The first battery terminal voltage value can be the measured value of the battery terminal voltage collected at a certain moment within the first interval, such as the battery terminal voltage value collected at the end of the first interval.

[0220] It should be noted that ohmic impedance is an instantaneous response, reactive impedance has a slower response speed, and diffuse impedance stabilizes even slower. In this embodiment, the equation corresponding to the instantaneous response stage of the ohmic impedance is first established, which can be: .

[0221] The first equation is a mathematical equation describing the relationship between the battery terminal voltage and the ohmic impedance, reaction impedance, and reaction impedance time constant within the first interval.

[0222] The reaction impedance time constant can be a parameter characterizing the rate of battery reaction polarization decay. It is obtained by multiplying the reaction impedance and the reaction capacitance. The smaller the reaction impedance time constant, the faster the reaction polarization decay.

[0223] It should be noted that in the first region dominated by reaction impedance, since the diffusion impedance time constant is generally an order of magnitude larger than the reaction impedance time constant, the diffusion impedance term can be neglected, and the first equation can be constructed as follows:

[0224]

[0225] in, This is the voltage value at the first battery terminal. The value of the ohmic impedance. The value of the reaction impedance. This is the open-circuit voltage of the battery at the corresponding SOC equilibrium state.

[0226] Performing a first-order Taylor expansion on the first equation above, we can obtain:

[0227]

[0228] It should be noted that the calculation is based on the value of the ohmic impedance. In this case, the voltage value of the first battery terminal can be... The value of reaction impedance Substituting into the above equation, the reaction impedance time constant can be calculated. .

[0229] Furthermore, the second equation corresponding to the second interval after the current is applied during the discharge period is determined. Then, the values ​​of the second battery terminal voltage, the first battery terminal voltage, and the diffusion impedance corresponding to the second interval are substituted into the second equation, and a first-order Taylor expansion is performed on the second equation to obtain the diffusion impedance time constant.

[0230] The second interval represents the time interval in which the diffusion impedance dominates the voltage response, that is, the time interval in which the diffusion impedance dominates after the current is applied during the discharge period. During this stage, the reaction polarization has tended to stabilize, and the change in voltage response is mainly determined by the diffusion impedance.

[0231] The second battery terminal voltage value can be the measured value of the battery terminal voltage collected at a certain moment within the second interval, such as the battery terminal voltage value collected at the end of the second interval.

[0232] The second equation is a mathematical equation that describes the relationship between the battery terminal voltage and the diffusion impedance and the diffusion impedance time constant within the second interval.

[0233] The diffusion impedance time constant can be a parameter characterizing the concentration polarization decay rate of the battery. It is obtained by multiplying the diffusion impedance and the diffusion capacitance. The smaller the diffusion impedance time constant, the faster the concentration polarization decays.

[0234] The second equation can be constructed as follows: .

[0235] Performing a first-order Taylor expansion on the second equation above, we can obtain:

[0236]

[0237] in, This is the voltage value at the first battery terminal. The value of the diffusion impedance. This is the voltage value at the second battery terminal.

[0238] It should be noted that after calculating In this case, the voltage value of the first battery terminal can be... The second battery terminal voltage value reflects the impedance. and the value of diffusion impedance Substituting into the above equation, the diffusion impedance time constant can be calculated. .

[0239] Figure 4 This is a schematic diagram of the battery equivalent circuit of the fitting model provided in this embodiment. The circuit includes an open-circuit voltage Uoc and an internal resistance of ohms R. ohm And RC networks, where the ohmic internal resistance R ohm Connected in series with an RC network, the RC network consists of multiple R i With C i The parallel branches are connected in series in sequence, and the output voltage of the circuit model is U. L .

[0240] It should be noted that, as an example, the fitting model in this application can be a second-order RC equivalent circuit model, and the corresponding equation can be:

[0241]

[0242] in, The reaction impedance time constant, , unit s. The diffusion impedance time constant is , unit s. For ohmic voltage drop, This is the charge transfer polarization voltage drop. For diffusion polarization voltage drop

[0243] Step 222: Input the ohmic impedance and the corresponding state of charge, reaction impedance, diffusion impedance and charge / discharge rate into the pre-trained machine learning model to obtain the overpotential.

[0244] Wherein, overpotential refers to the difference between the actual working potential of the electrode (actual electrode potential) and the reversible equilibrium potential of the electrode (reversible electrode potential), and the formula is:

[0245]

[0246] in, It is overpotential. It is the actual working potential of the electrode. It is the equilibrium potential of the electrode reversibility.

[0247] It is understandable that steady-state diffusion follows Fick's law, the formula for which is: Where J is the diffusion flux, representing the amount of matter passing through a unit area per unit time. D is the diffusion coefficient, which is related to the properties of the diffusing substance and the medium. Under pulse charge-discharge conditions, the pulse time is short, and the electrolyte concentration is approximately constant.

[0248] This application's embodiments establish the relationship between diffusion impedance and voltage drop using a machine learning model. The machine learning model can accurately fit the correlation between SOC, diffusion impedance, and overpotential, and has the advantages of strong interpretability, few parameters, and strong robustness.

[0249] It should be noted that in the short-term performance verification phase of battery cells, conventional OCV testing is generally used to obtain basic data. In long-term cycle life testing scenarios, pulsed OCV testing is generally used to effectively compress the overall testing cycle and improve testing efficiency. Therefore, the model training dataset of the machine learning model in this application embodiment can include conventional OCV test data and pulsed OCV test data of the same batch of battery cells.

[0250] Because the training datasets for machine learning models have strong physical properties and require a small number of samples, supervised learning methods can be used to build machine learning models in some embodiments. Specifically, supervised learning methods such as artificial neural networks and one-dimensional convolutional neural networks can be employed, without limitation here.

[0251] The number of training samples for the machine learning model can vary depending on the different cell material systems. For example, 58 sets of data can be used for ternary material cell samples, while 63 sets of data can be used for lithium iron phosphate cell samples.

[0252] Step 223: The sum of the voltage at the end of the relaxation period and the overpotential is used as the initial open-circuit voltage.

[0253] Specifically, you can calculate it using the following formula:

[0254]

[0255] in, For the initial open circuit voltage, The end voltage value of the relaxation period, This is the overpotential.

[0256] Step 300: Based on the target fitting model, obtain the open-circuit voltage of the battery under different states of charge, where different states of charge correspond to different battery terminal voltages.

[0257] Specifically, we can iterate through each SOC point in the SOC interval to obtain a set of first model parameters corresponding to each SOC. Then, we input the first model parameters corresponding to each SOC and perform fitting to obtain the open-circuit voltage corresponding to that SOC. Thus, we can obtain the OCV-SOC curve for the entire interval (0~100% SOC range).

[0258] When only the first model parameters are used for fitting, the second model parameters can be fixed values ​​that can be set by the user, and there are no restrictions on this.

[0259] Optionally, numerical fitting tools (such as the curve_fit function in Python's scipy) can be used to perform curve fitting on the voltage data during the relaxation period and output the fitted open-circuit voltage value.

[0260] Specifically, we can iterate through each SOC point in the SOC interval to obtain a set of first model parameters and second model parameters corresponding to each SOC. Then, we input the first model parameters and second model parameters corresponding to each SOC and perform fitting to obtain the open-circuit voltage corresponding to that SOC. Thus, we can obtain the OCV-SOC curve for the entire interval (0~100% SOC range).

[0261] Figure 5 The diagram shows the pulse OCV fitted based on dynamic initial values, illustrating the lithium battery discharge voltage-time curve (the legend uses measured data, and the legend uses fitted data).

[0262] In some embodiments, the battery terminal voltage value and the current value applied to the battery at the target time are first determined. Then, the target open-circuit voltage is determined according to the state of charge at the target time. After that, the DC internal resistance value of the battery at the target time is calculated based on the battery terminal voltage, current value and target open-circuit voltage at the target time.

[0263] Here, the target time represents the moment when the diffusion impedance is stable, and the target open-circuit voltage is the open-circuit voltage corresponding to the target time.

[0264] It should be noted that the DCR value varies at different times. The diffusion impedance corresponding to the DCR over a longer period (e.g., ≥30s) is relatively stable.

[0265] Among them, the target time corresponds to The calculation formula can be:

[0266]

[0267] in, The battery terminal voltage value at the target time. The target open-circuit voltage.

[0268] In the technical solution of this application embodiment, test data obtained from pulse charge-discharge testing of the battery is first acquired. Then, based on the test data, values ​​are assigned to the first model parameters in the target fitting model. In the target fitting model, the battery terminal voltage is equal to the superposition of the ohmic voltage drop, charge transfer polarization voltage drop, diffusion polarization voltage drop, and open-circuit voltage. The first model parameters include the ohmic impedance in the ohmic voltage drop, the reaction impedance in the charge transfer polarization voltage drop, and the diffusion impedance in the diffusion polarization voltage drop. Then, based on the target fitting model, the open-circuit voltage of the battery under different states of charge is obtained, where different states of charge correspond to different battery terminal voltages. Therefore, by using pulse charge-discharge testing and model fitting, the estimation speed of the open-circuit voltage is improved. By using the ohmic impedance in the ohmic voltage drop, the reaction impedance in the charge transfer polarization voltage drop, and the diffusion impedance in the diffusion polarization voltage drop as the first model parameters in the target fitting model, the fitting model more accurately reflects the internal characteristics of the battery, thereby improving the prediction accuracy of the open-circuit voltage.

[0269] Corresponding to the open-circuit voltage fitting method described in the above embodiments, Figure 6 This is a structural block diagram of the open-circuit voltage fitting device provided in the embodiments of this application.

[0270] Reference Figure 6 The open-circuit voltage fitting device 10 includes:

[0271] The first acquisition module 11 is used to acquire test data obtained by performing pulse charge and discharge tests on the battery;

[0272] Assignment module 12 is used to assign values ​​to the first model parameters in the target fitting model based on the test data.

[0273] In the target fitting model, the battery terminal voltage is equal to the superposition of ohmic voltage drop, charge transfer polarization voltage drop, diffusion polarization voltage drop and open circuit voltage. The first model parameters include the ohmic impedance in the ohmic voltage drop, the reaction impedance in the charge transfer polarization voltage drop and the diffusion impedance in the diffusion polarization voltage drop.

[0274] The second acquisition module 13 is used to acquire the open-circuit voltage of the battery under different states of charge based on the target fitting model, wherein different states of charge correspond to different battery terminal voltages.

[0275] Optionally, the assignment module includes:

[0276] The first acquisition unit is used to acquire the ohmic impedance values ​​of the battery under different states of charge based on the test data.

[0277] An extraction unit is used to extract the data to be processed from the test data and to perform impedance decomposition processing on the data to be processed to obtain the values ​​of the reaction impedance and the diffusion impedance.

[0278] The assignment unit is used to assign values ​​to the first model parameters in the target fitting model based on the obtained values ​​of the ohmic impedance, the reaction impedance, and the diffusion impedance.

[0279] Optionally, the first acquisition unit includes:

[0280] The sub-unit is determined based on the test data to determine the state of charge corresponding to each discharge period and relaxation period.

[0281] The generation sub-unit is used to generate ohmic impedance curves corresponding to different states of charge based on the state of charge corresponding to each discharge period and relaxation period, as well as the test data. The ohmic impedance curves are used to reflect the ohmic impedance values ​​of the battery under different states of charge.

[0282] Optionally, define sub-units, specifically for:

[0283] Based on the test data, obtain the cumulative charge and discharge capacity of the battery;

[0284] Based on the cumulative charge and discharge capacity, the initial state of charge of the battery, and the rated capacity of the battery, the state of charge of the battery at different times is calculated.

[0285] Based on the battery's state of charge at different times, and the times corresponding to each discharge period and relaxation period, the state of charge corresponding to each discharge period and relaxation period is determined.

[0286] Optionally, generate sub-units, specifically for:

[0287] Based on the time-voltage sequence data in the test data, the first voltage sample value and the second voltage sample value corresponding to multiple voltage transient periods are determined. The first voltage sample value represents the voltage value collected at the moment before the voltage transient, and the second voltage sample value represents the voltage value collected at the moment after the voltage transient.

[0288] Based on the first voltage sample value and the second voltage sample value corresponding to multiple voltage transient periods, the ohmic impedance value corresponding to each voltage transient period is calculated;

[0289] Based on the state of charge corresponding to each discharge period and relaxation period, and the time corresponding to each discharge period and relaxation period, determine the state of charge corresponding to each voltage transient period.

[0290] Based on the ohmic impedance value and state of charge corresponding to each voltage transient period, an ohmic impedance curve corresponding to the continuous state of charge is generated.

[0291] Optionally, generate sub-units, specifically for:

[0292] Based on the test data, determine the end voltage value of the relaxation period and the initial voltage value of the discharge period;

[0293] Based on the initial voltage value of each discharge period, the final voltage value of each relaxation period, and the current value of the discharge current applied at the beginning of the discharge period, determine the value of the ohmic impedance corresponding to the initial current application period.

[0294] Based on the state of charge corresponding to each discharge period and relaxation period, determine the state of charge corresponding to each initial current application period;

[0295] Based on the ohmic impedance value and state of charge corresponding to each initial current application period, an ohmic impedance curve corresponding to the continuous state of charge is generated.

[0296] Optionally, the test data includes the response voltage at different times, which is obtained based on the constant current applied to the battery, generating sub-cells, including:

[0297] The fitting submodule is used to call the preset RC current fitting equation and perform nonlinear fitting based on the response voltage to obtain the ohmic impedance value of the battery at different times.

[0298] The determination submodule is used to determine the time corresponding to each state of charge based on the state of charge corresponding to the discharge period and the relaxation period, as well as the time information corresponding to the discharge period and the relaxation period.

[0299] The acquisition submodule is used to obtain the ohmic impedance curve corresponding to the continuous charging state based on the ohmic impedance value at different times and the time corresponding to each charging state.

[0300] Optionally, the fitting submodule is also used for:

[0301] Determine the first product term of the initial response voltage, constant current, and ohmic impedance, and the second product term of the constant current and polarization impedance;

[0302] The second product term is corrected by exponential decay to obtain the third product term;

[0303] Based on the initial response voltage, the first product term, the third product term, and the response voltage, an RC current fitting equation is constructed.

[0304] The response voltage is equal to the sum of the initial response voltage, the first product term, and the third product term.

[0305] Optionally, the data to be processed includes the following items:

[0306] The voltage value at the end of the relaxation period;

[0307] The first voltage value corresponding to the application of a constant current for a first duration during the discharge period;

[0308] The second voltage value corresponding to the application of a constant current for a second duration during the discharge period, wherein the first duration is shorter than the second duration; and

[0309] The value of the constant current applied during the discharge period.

[0310] Correspondingly, the extraction unit is specifically used for:

[0311] The first DC internal resistance value is determined based on the first voltage value, the terminal voltage value, and the constant current value.

[0312] The second DC internal resistance value is determined based on the second voltage value, the terminal voltage value, and the constant current value.

[0313] The value of the diffusion impedance is determined based on the difference between the second DC internal resistance value and the first DC internal resistance value.

[0314] The value of the reactive impedance is determined based on the difference between the first DC internal resistance value and the ohmic impedance value.

[0315] Optionally, the device may also include:

[0316] The second model parameter assignment module is specifically used to: assign values ​​to the second model parameters in the target fitting model based on the values ​​of the first model parameters.

[0317] The second model parameters include the reaction impedance time constant in the charge transfer polarization voltage drop, the diffusion impedance time constant in the diffusion polarization voltage drop, the initial open-circuit voltage, and the overpotential.

[0318] Optional, the second model parameter assignment module includes:

[0319] The calculation subunit is used to perform segmented calculations based on the values ​​of the ohmic impedance, the reaction impedance, and the diffusion impedance, according to the time sequence of the voltage response, to obtain the reaction impedance time constant and the diffusion impedance time constant.

[0320] The input subunit is used to input the ohmic impedance and the corresponding state of charge, the value of the reaction impedance, the value of the diffusion impedance, and the charge / discharge rate into a pre-trained machine learning model to obtain the overpotential.

[0321] The summation subunit is used to sum the end voltage value of the relaxation period with the overpotential as the initial open-circuit voltage.

[0322] Optional, compute sub-units, specifically used for:

[0323] Determine the first equation corresponding to the first interval after the current is applied during the discharge period, where the first interval represents the time interval in which the reaction impedance dominates the voltage response;

[0324] Substitute the first battery terminal voltage value, ohmic impedance value, and reaction impedance value corresponding to the first interval into the first equation, and perform a first-order Taylor expansion on the first equation to obtain the reaction impedance time constant.

[0325] Determine the second equation corresponding to the second interval after the current is applied during the discharge period, where the second interval represents the time interval dominated by the diffusion impedance in the voltage response;

[0326] Substitute the second battery terminal voltage value, the first battery terminal voltage value, and the diffusion impedance value corresponding to the second interval into the second equation, and perform a first-order Taylor expansion on the second equation to obtain the diffusion impedance time constant.

[0327] Optionally, the second acquisition module is also used for:

[0328] Determine the battery terminal voltage value corresponding to the target time and the current value applied to the battery, where the target time represents the moment when the diffusion impedance is stable;

[0329] Determine the corresponding target open-circuit voltage based on the state of charge at the target time.

[0330] Calculate the DC internal resistance of the battery at the target time based on the battery terminal voltage, current, and target open-circuit voltage at the target time.

[0331] Optional, the first acquisition module is specifically used for:

[0332] Acquire initial data, which includes test data from pulse charge-discharge tests performed on the battery;

[0333] Identify the target data segment in the initial data, wherein the target data segment refers to the data reflecting the battery from the discharge period to the relaxation period;

[0334] If the number of consecutive occurrences of the target data segment in the initial data is greater than the target number of segments, the consecutively occurring target data segments will be used as the test data.

[0335] The test data is extracted from the initial data.

[0336] In the technical solution of this application embodiment, test data obtained from pulse charge-discharge testing of the battery is first acquired. Then, based on the test data, values ​​are assigned to the first model parameters in the target fitting model. In the target fitting model, the battery terminal voltage is equal to the superposition of the ohmic voltage drop, charge transfer polarization voltage drop, diffusion polarization voltage drop, and open-circuit voltage. The first model parameters include the ohmic impedance in the ohmic voltage drop, the reaction impedance in the charge transfer polarization voltage drop, and the diffusion impedance in the diffusion polarization voltage drop. Then, based on the target fitting model, the open-circuit voltage of the battery under different states of charge is obtained, where different states of charge correspond to different battery terminal voltages. Therefore, by using pulse charge-discharge testing and model fitting, the estimation speed of the open-circuit voltage is improved. By using the ohmic impedance in the ohmic voltage drop, the reaction impedance in the charge transfer polarization voltage drop, and the diffusion impedance in the diffusion polarization voltage drop as the first model parameters in the target fitting model, the fitting model more accurately reflects the internal characteristics of the battery, thereby improving the prediction accuracy of the open-circuit voltage.

[0337] in addition, Figure 6 The open-circuit voltage fitting device shown can be a software unit, a hardware unit, or a combination of software and hardware built into existing electronic devices. It can also be integrated into the electronic device as a separate component, or exist as a standalone electronic device.

[0338] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0339] Figure 7 This is a schematic diagram of the structure of the electronic device provided in an embodiment of this application. For example... Figure 7 As shown, the electronic device 5 of this embodiment includes: at least one processor 50 ( Figure 7 (Only one is shown in the diagram) a processor, a memory 51, and a computer program 52 stored in the memory 51 and executable on the at least one processor 50, wherein the processor 50 executes the computer program 52 to implement the steps in any of the above-described open-circuit voltage fitting method embodiments.

[0340] The electronic device may be a desktop computer, laptop, handheld computer, or cloud server, etc. This electronic device may include, but is not limited to, a processor and memory. Those skilled in the art will understand that... Figure 7 This is merely an example of electronic device 5 and does not constitute a limitation on electronic device 5. It may include more or fewer components than shown in the figure, or combine certain components, or different components. For example, it may also include input / output devices, network access devices, etc.

[0341] The processor 50 may be a central processing unit, or it may be other general-purpose processors, digital signal processors, application-specific integrated circuits, off-the-shelf programmable gate arrays or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0342] In some embodiments, the memory 51 may be an internal storage unit of the electronic device 5, such as a hard disk or memory of the electronic device 5. In other embodiments, the memory 51 may be an external storage device of the electronic device 5, such as a plug-in hard disk, smart memory card, secure digital card, flash memory card, etc., equipped on the electronic device 5. Further, the memory 51 may include both internal storage units and external storage devices of the electronic device 5. The memory 51 is used to store operating systems, applications, boot loaders, data, and other programs, such as the program code of the computer program. The memory 51 can also be used to temporarily store data that has been output or will be output.

[0343] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the steps in the above-described method embodiments.

[0344] This application provides a computer program product that, when run on an electronic device, enables the electronic device to implement the steps described in the various method embodiments above.

[0345] If the integrated unit is implemented as a software functional unit and used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to a device / electronic device, a recording medium, a computer memory, a read-only memory, a random access memory, an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0346] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0347] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0348] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0349] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0350] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for fitting open-circuit voltage, characterized in that, include: Obtain test data from pulse charge-discharge tests on the battery; Based on the test data, assign values ​​to the first model parameters in the target fitting model. In the target fitting model, the battery terminal voltage is equal to the superposition of ohmic voltage drop, charge transfer polarization voltage drop, diffusion polarization voltage drop and open circuit voltage. The first model parameters include the ohmic impedance in the ohmic voltage drop, the reaction impedance in the charge transfer polarization voltage drop and the diffusion impedance in the diffusion polarization voltage drop. Based on the values ​​of the first model parameters, assign values ​​to the second model parameters in the target fitting model. The second model parameters include the reaction impedance time constant in the charge transfer polarization voltage drop, the diffusion impedance time constant in the diffusion polarization voltage drop, the initial open-circuit voltage, and the overpotential. Assigning values ​​to the second model parameters in the target fitting model based on the values ​​of the first model parameters includes: Based on the values ​​of the ohmic impedance, the reaction impedance, and the diffusion impedance, the reaction impedance time constant and the diffusion impedance time constant are obtained by segmenting the voltage response according to the time sequence. The ohmic impedance, the corresponding state of charge, the value of the reaction impedance, the value of the diffusion impedance, and the charge / discharge rate are input into a pre-trained machine learning model to obtain the overpotential. The sum of the voltage at the end of the relaxation period and the overpotential is taken as the initial open-circuit voltage. The time constants of the reaction impedance and the diffusion impedance are obtained by segmenting the voltage response according to the time sequence, based on the values ​​of the ohmic impedance, the reaction impedance, and the diffusion impedance, including: Determine the first equation corresponding to the first interval after the current is applied during the discharge period, where the first interval represents the time interval dominated by the reaction impedance in the voltage response; Substitute the first battery terminal voltage value, the ohmic impedance value, and the reaction impedance value corresponding to the first interval into the first equation, and perform a first-order Taylor expansion on the first equation to obtain the reaction impedance time constant. Determine the second equation corresponding to the second interval after the current is applied during the discharge period, wherein the second interval represents the time interval in which the diffusion impedance dominates the voltage response; Substitute the second battery terminal voltage value, the first battery terminal voltage value, and the diffusion impedance value corresponding to the second interval into the second equation, and perform a first-order Taylor expansion on the second equation to obtain the diffusion impedance time constant. Based on the target fitting model, the open-circuit voltage of the battery under different states of charge is obtained, wherein different states of charge correspond to different battery terminal voltages.

2. The method according to claim 1, characterized in that, Assigning values ​​to the first model parameters in the target fitting model based on the test data includes: Based on the test data, the ohmic impedance values ​​of the battery under different states of charge are obtained; Extract the data to be processed from the test data, and perform impedance decomposition on the data to be processed to obtain the values ​​of the reaction impedance and the diffusion impedance. The first model parameter in the target fitting model is assigned a value based on the obtained values ​​of the ohmic impedance, the reaction impedance, and the diffusion impedance.

3. The method according to claim 2, characterized in that, The step of obtaining the ohmic impedance values ​​of the battery under different states of charge based on the test data includes: Based on the test data, determine the state of charge corresponding to each discharge period and relaxation period; Based on the state of charge corresponding to each discharge period and relaxation period, and the test data, ohmic impedance curves corresponding to different states of charge are generated, wherein the ohmic impedance curves are used to reflect the ohmic impedance values ​​of the battery under different states of charge.

4. The method according to claim 3, characterized in that, The step of determining the state of charge corresponding to each discharge period and relaxation period based on the test data includes: Based on the test data, obtain the cumulative charge and discharge capacity of the battery; Based on the cumulative charge-discharge capacity, the initial state of charge of the battery, and the rated capacity of the battery, calculate the state of charge of the battery at different times; Based on the state of charge of the battery at different times, and the times corresponding to each discharge period and relaxation period, the state of charge corresponding to each discharge period and relaxation period is determined.

5. The method according to claim 3, characterized in that, The step of generating ohmic impedance curves corresponding to different states of charge based on the states of charge corresponding to each discharge period and relaxation period, and the test data, includes: Based on the time-voltage sequence data in the test data, determine the first voltage sample value and the second voltage sample value corresponding to multiple voltage transient periods, wherein the first voltage sample value represents the voltage value collected at the moment before the voltage transient, and the second voltage sample value represents the voltage value collected at the moment after the voltage transient. Based on the first voltage sample value and the second voltage sample value corresponding to multiple voltage transient periods, the ohmic impedance value corresponding to each voltage transient period is calculated; Based on the state of charge corresponding to each discharge period and relaxation period, and the time corresponding to each discharge period and relaxation period, the state of charge corresponding to each voltage transient period is determined. Based on the ohmic impedance value and state of charge corresponding to each voltage transient period, an ohmic impedance curve corresponding to the continuous state of charge is generated.

6. The method according to claim 3, characterized in that, The step of generating an ohmic impedance curve corresponding to a continuous state of charge based on the state of charge corresponding to each discharge period and relaxation period, and the test data, includes: Based on the test data, determine the end voltage value of the relaxation period and the initial voltage value of the discharge period; The value of the ohmic impedance corresponding to each initial current application period is determined based on the initial voltage value of each discharge period, the final voltage value of each relaxation period, and the current value of the discharge current applied at the beginning of the discharge period. Based on the state of charge corresponding to each discharge period and relaxation period, determine the state of charge corresponding to each initial current application period; Based on the ohmic impedance value and state of charge corresponding to each initial current application period, an ohmic impedance curve corresponding to the continuous state of charge is generated.

7. The method according to claim 3, characterized in that, The test data includes response voltages at different times, which are obtained based on data collected while a constant current is applied to the battery. The step of generating an ohmic impedance curve corresponding to a continuous state of charge based on the state of charge corresponding to each discharge period and relaxation period, and the test data, includes: The preset RC current fitting equation is invoked, and nonlinear fitting is performed based on the response voltage to obtain the ohmic impedance value of the battery at different times; Based on the state of charge corresponding to the discharge period and relaxation period, and the time information corresponding to the discharge period and relaxation period, the time corresponding to each state of charge is determined. Based on the ohmic impedance values ​​corresponding to the different times and the times corresponding to each state of charge, the ohmic impedance curves corresponding to the continuous states of charge are obtained.

8. The method according to claim 7, characterized in that, Before invoking the preset RC current fitting equation and performing nonlinear fitting based on the response voltage to obtain the ohmic impedance values ​​of the battery at different times, the method further includes: Determine the initial response voltage, the first product term of the constant current and the ohmic impedance, and the second product term of the constant current and the polarization impedance; The second product term is corrected by exponential decay to obtain the third product term; Based on the initial response voltage, the first product term, the third product term, and the response voltage, the RC current fitting equation is constructed. The response voltage is equal to the sum of the initial response voltage, the first product term, and the third product term.

9. The method according to any one of claims 2 to 8, characterized in that, The data to be processed includes the following items: The voltage value at the end of the relaxation period; The first voltage value corresponding to the application of a constant current for a first duration during the discharge period; The second voltage value corresponding to the application of a constant current for a second duration during the discharge period, wherein the first duration is less than the second duration; as well as The value of the constant current applied during the discharge period. Correspondingly, the impedance decomposition process performed on the data to be processed to obtain the values ​​of both the reaction impedance and the diffusion impedance includes: The first DC internal resistance value is determined based on the first voltage value, the terminal voltage value, and the constant current value. The second DC internal resistance value is determined based on the second voltage value, the terminal voltage value, and the constant current value. The value of the diffusion impedance is determined based on the difference between the second DC internal resistance value and the first DC internal resistance value; The value of the reactive impedance is determined based on the difference between the first DC internal resistance value and the ohmic impedance value.

10. The method according to claim 1, characterized in that, After obtaining the open-circuit voltage of the battery under different states of charge based on the target fitting model, the method further includes: Determine the battery terminal voltage value corresponding to the target time and the current value applied to the battery, wherein the target time represents the time when the diffusion impedance is stable; Determine the corresponding target open-circuit voltage based on the state of charge at the target time; The DC internal resistance of the battery at the target time is calculated based on the battery terminal voltage, the current value, and the target open-circuit voltage.

11. The method according to claim 1, characterized in that, The acquisition of test data for pulse charge-discharge testing of the battery includes: Acquire initial data, which includes test data from pulse charge-discharge tests performed on the battery; Identify the target data segment in the initial data, wherein the target data segment refers to the data reflecting the battery from the discharge period to the relaxation period; If the number of consecutive occurrences of the target data segment in the initial data is greater than the target number of segments, the consecutively occurring target data segments will be used as the test data. The test data is extracted from the initial data.

12. A fitting device for open-circuit voltage, characterized in that, include: The first acquisition module is used to acquire test data obtained from pulse charge-discharge tests on the battery; The assignment module is used to assign values ​​to the first model parameters in the target fitting model based on the test data. In the target fitting model, the battery terminal voltage is equal to the superposition of ohmic voltage drop, charge transfer polarization voltage drop, diffusion polarization voltage drop and open circuit voltage. The first model parameters include the ohmic impedance in the ohmic voltage drop, the reaction impedance in the charge transfer polarization voltage drop and the diffusion impedance in the diffusion polarization voltage drop. Based on the values ​​of the first model parameters, assign values ​​to the second model parameters in the target fitting model. The second model parameters include the reaction impedance time constant in the charge transfer polarization voltage drop, the diffusion impedance time constant in the diffusion polarization voltage drop, the initial open-circuit voltage, and the overpotential. Assigning values ​​to the second model parameters in the target fitting model based on the values ​​of the first model parameters includes: Based on the values ​​of the ohmic impedance, the reaction impedance, and the diffusion impedance, the reaction impedance time constant and the diffusion impedance time constant are obtained by segmenting the voltage response according to the time sequence. The ohmic impedance, the corresponding state of charge, the value of the reaction impedance, the value of the diffusion impedance, and the charge / discharge rate are input into a pre-trained machine learning model to obtain the overpotential. The sum of the voltage at the end of the relaxation period and the overpotential is taken as the initial open-circuit voltage. The time constants of the reaction impedance and the diffusion impedance are obtained by segmenting the voltage response according to the time sequence, based on the values ​​of the ohmic impedance, the reaction impedance, and the diffusion impedance, including: Determine the first equation corresponding to the first interval after the current is applied during the discharge period, where the first interval represents the time interval dominated by the reaction impedance in the voltage response; Substitute the first battery terminal voltage value, the ohmic impedance value, and the reaction impedance value corresponding to the first interval into the first equation, and perform a first-order Taylor expansion on the first equation to obtain the reaction impedance time constant. Determine the second equation corresponding to the second interval after the current is applied during the discharge period, wherein the second interval represents the time interval in which the diffusion impedance dominates the voltage response; Substitute the second battery terminal voltage value, the first battery terminal voltage value, and the diffusion impedance value corresponding to the second interval into the second equation, and perform a first-order Taylor expansion on the second equation to obtain the diffusion impedance time constant. The second acquisition module is used to acquire the open-circuit voltage of the battery under different states of charge based on the target fitting model, wherein different states of charge correspond to different battery terminal voltages.

13. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the steps of the method as claimed in any one of claims 1 to 11.

14. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store a computer program, which is loaded by a processor to perform the steps of the method according to any one of claims 1 to 11.

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