Charge state estimation method and device, electronic equipment and medium

Abstract

The invention provides a state of charge estimation method and device, electronic equipment and a medium, and the method comprises the steps: determining the discharge capacity of a test battery pack at each collection point according to the total capacity of the test battery pack; the pulse current amplitude, the pulse current direction and the pulse duration of the initial pulse period are determined to form a pulse sequence for each collection point, each pulse sequence comprises a plurality of sub-pulse periods, and the pulse current amplitude absolute value of each sub-pulse period is half of the pulse current amplitude absolute value of the previous sub-pulse period; the pulse duration of each sub-pulse period is half of the pulse duration of the previous sub-pulse period, and the pulse current direction of each sub-pulse period is opposite to the pulse current direction of the previous sub-pulse period; applying a pulse sequence under the acquisition point to the tested battery pack, and measuring an open-circuit voltage value corresponding to the acquisition point; and obtaining an open-circuit voltage-state-of-charge curve of the tested battery pack according to all the open-circuit voltage values.

Description

Technical Field

[0001] The present application relates to the technical field of vehicle battery packs, and more specifically, to a method, device, electronic device, and medium for estimating a state of charge. Background Art

[0002] Lithium-ion batteries are widely used in electric vehicles, energy storage systems, and other fields due to their high energy density and long life. The state of charge (SOC) is a key indicator for measuring battery performance, and its accurate estimation is crucial for optimizing battery management systems and extending battery life. However, traditional SOC estimation methods, such as open-circuit voltage, ampere-hour measurement, electrochemical impedance spectroscopy, and entropy function methods, all have limitations. They all require the battery to rest for a long time before and after testing to eliminate polarization effects. The entire testing process can take days to weeks to complete, severely restricting battery R&D efficiency and the speed of updating battery management system (BMS) parameters. Summary of the Invention

[0003] In view of this, the purpose of this application is to provide a state of charge estimation method, device, electronic device and medium, aiming to overcome at least one of the above-mentioned defects.

[0004] In a first aspect, the present application provides a state of charge estimation method, comprising: determining the discharge capacity of the test battery pack at each acquisition point based on the total capacity of the test battery pack; determining the pulse current amplitude, pulse current direction, and pulse duration of the initial pulse cycle based on the cut-off voltage of the test battery pack and the discharge capacity at each acquisition point, so as to form a pulse sequence for each acquisition point, each pulse sequence comprising multiple sub-pulse cycles, wherein the absolute value of the pulse current amplitude of each sub-pulse cycle is half of the absolute value of the pulse current amplitude of the previous sub-pulse cycle, the pulse duration of each sub-pulse cycle is half of the pulse duration of the previous sub-pulse cycle, and the pulse current direction of each sub-pulse cycle is opposite to the pulse current direction of the previous sub-pulse cycle; for each acquisition point, applying the pulse sequence at the acquisition point to the test battery pack, and measuring the open circuit voltage value corresponding to the acquisition point; obtaining the open circuit voltage-state of charge curve of the test battery pack based on the open circuit voltage values ​​measured at all acquisition points, so as to estimate the state of charge of the test battery pack based on the open circuit voltage-state of charge curve.

[0005] In one possible embodiment, the state of charge of the test battery pack is estimated in the following manner: the open circuit voltage-state of charge curve is input into a battery state estimation algorithm to obtain a query relationship between open circuit voltage and charge estimation; an initial open circuit voltage measured value of the battery pack is obtained, and an initial state of charge estimated value corresponding to the initial open circuit voltage measured value is determined based on the query relationship; and an iterative estimation is performed based on the initial state of charge estimated value to obtain the state of charge estimated value at the current moment.

[0006] In a possible embodiment, the state of charge estimate at the current moment is obtained in the following manner: obtaining the actual terminal voltage value, the actual current value and the polarization voltage value of the test battery pack at the current moment; obtaining the state of charge prediction value at the current moment based on the initial state of charge estimate value, so as to determine the open circuit voltage prediction value corresponding to the state of charge prediction value through the query relationship; obtaining the terminal voltage prediction value based on the open circuit voltage prediction value, the polarization voltage value, the actual current value and the ohmic internal resistance value of the test battery pack; determining the prediction deviation between the terminal voltage prediction value and the terminal voltage actual value; and correcting the state of charge prediction value based on the prediction deviation to obtain the state of charge estimate at the current moment.

[0007] In one possible embodiment, the polarization voltage value at the current moment is calculated in the following manner: the polarization voltage value at the previous moment is obtained; and the polarization voltage value at the current moment is obtained through an equivalent circuit model based on the actual current measured value at the current moment and the polarization voltage value at the previous moment.

[0008] In a possible embodiment, the terminal voltage prediction value is obtained by subtracting the polarization voltage value from the open circuit voltage prediction value, and then subtracting the product of the current measured value and the ohmic internal resistance value to obtain the terminal voltage prediction value.

[0009] In a possible embodiment, the step of correcting the state of charge prediction value based on the prediction deviation to obtain the state of charge estimation value at the current moment includes: multiplying the prediction deviation by the Kalman gain coefficient in the extended Kalman filter algorithm to obtain a product result; and superimposing the product result on the state of charge prediction value to obtain the state of charge estimation value at the current moment.

[0010] In the second aspect, the present application provides a state of charge estimation device, comprising: a first determination module, for determining the discharge capacity of the test battery pack at each acquisition point according to the total capacity of the test battery pack; a second determination module, for determining the pulse current amplitude, pulse current direction, and pulse duration of the initial pulse cycle according to the cut-off voltage of the test battery pack and the discharge capacity at each acquisition point, so as to form a pulse sequence for each acquisition point, each pulse sequence comprising a plurality of sub-pulse cycles, wherein the absolute value of the pulse current amplitude of each sub-pulse cycle is half the absolute value of the pulse current amplitude of the previous sub-pulse cycle, and each sub-pulse cycle The pulse duration is half of the pulse duration of the previous sub-pulse period, and the direction of the pulse current in each sub-pulse period is opposite to the direction of the pulse current in the previous sub-pulse period; a measurement module is used to apply the pulse sequence at each collection point to the test battery pack, so that the test battery pack releases the corresponding discharge capacity at the collection point and measures the open circuit voltage value corresponding to the collection point; an estimation module is used to obtain the open circuit voltage-state of charge curve of the test battery pack according to the open circuit voltage values ​​measured at all collection points, so as to estimate the state of charge of the test battery pack according to the open circuit voltage-state of charge curve.

[0011] In a possible embodiment, the estimation module is further used to: input the open circuit voltage-state of charge curve into a battery state estimation algorithm to obtain a query relationship between open circuit voltage and charge estimation; obtain an initial open circuit voltage measured value of the battery pack, and determine an initial state of charge estimated value corresponding to the initial open circuit voltage measured value based on the query relationship; and perform iterative estimation based on the initial state of charge estimated value to obtain an estimated state of charge value at the current moment.

[0012] In a third aspect, the present application also provides an electronic device comprising: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor and the memory communicate through the bus, and when the machine-readable instructions are executed by the processor, the steps of the above method are performed.

[0013] In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above method are executed.

[0014] The beneficial effects of the state of charge estimation solution of this application are as follows: This application stimulates the battery pack by using an oscillating current of specific frequency and amplitude, accelerating the ion migration and charge transfer process inside the battery, allowing the battery to quickly return to a thermodynamic equilibrium state, significantly shortening the relaxation time that originally required several hours, and significantly improving test efficiency.

[0015] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 A flow chart of a method for estimating state of charge provided in an embodiment of the present application; Figure 2 A schematic diagram of a pulse sequence provided in an embodiment of the present application; Figure 3 A schematic diagram of a voltage-time curve collected according to an embodiment of the present application; Figure 4 A schematic diagram comparing the OCV-SOC curve collected by the present application and the OCV-SOC curve collected by the common discharge method provided in the embodiment of the present application; Figure 5 A schematic diagram comparing the EIS curve collected by the present application and the EIS curve collected by the conventional discharge method provided in the embodiments of the present application; Figure 6 A flow chart of estimating the state of charge of a test battery pack provided in an embodiment of the present application; Figure 7 A flowchart for obtaining an estimated state of charge at the current moment provided in an embodiment of the present application; Figure 8 A schematic diagram of the structure of a state of charge estimation device provided in an embodiment of the present application; Figure 9 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application for which protection is claimed, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, each other embodiment obtained by those skilled in the art without making creative work falls within the scope of protection of the present application.

[0019] First, the application scenarios to which this application is applicable are introduced. This application can be applied to vehicle battery packs.

[0020] Research has found that lithium-ion batteries, thanks to their high energy density, long cycle life, and lack of memory effect, have been widely used in portable electronic devices, electric vehicles, and energy storage systems. With the continuous expansion of lithium-ion battery applications and increasing safety requirements, accurate monitoring and estimation of battery status have become crucial. State of Charge (SOC) is a key indicator of battery performance and is crucial for optimizing the operation of the Battery Management System (BMS) and extending battery life.

[0021] At present, the estimation methods of lithium-ion battery SOC mainly include open circuit voltage method (OCV-SOC relationship method), ampere-hour measurement method, electrochemical impedance spectroscopy (EIS) analysis method and entropy function method.

[0022] The open circuit voltage method (OCV-SOC relationship method) estimates the battery SOC based on the corresponding relationship between SOC and OCV. However, the traditional OCV-SOC curve measurement requires a "step discharge-rest" method. After each discharge, the battery needs to rest for 4-10 hours to eliminate the influence of polarization. The entire test process usually takes 1-2 days, which greatly prolongs the test cycle.

[0023] The ampere-hour measurement method is based on the principle of current integration. This method is easily affected by factors such as initial SOC estimation error, current measurement deviation and capacity attenuation. As the number of battery cycles increases, the cumulative error will gradually amplify.

[0024] The EIS analysis method can effectively reflect the changes in the internal state of the battery, but the traditional EIS test requires multiple measurements at different SOC points, and a long period of static rest before each measurement is required to eliminate the polarization effect. The entire testing process is time-consuming and lengthy.

[0025] The entropy function of the entropy function method has a good correspondence with SOC, but traditional entropy function measurement requires the battery to be stabilized at multiple SOC points before undergoing temperature cycling testing. Each test point takes 2-3 hours, and the entire test process may take several days.

[0026] The main drawbacks of current technology are that traditional battery state estimation methods, particularly OCV-SOC curve measurement, EIS analysis, and entropy function measurement, require the battery to rest for extended periods before and after testing to eliminate polarization effects. The entire testing process can take days to weeks to complete, severely limiting battery R&D efficiency and the speed of BMS parameter updates. Batteries experience concentration polarization and activation polarization after charging and discharging. Traditional methods passively wait for this polarization to dissipate by allowing the battery to rest for extended periods, resulting in inefficiency and uncontrollability. Rapid, coordinated testing of multiple SOC parameters is difficult. For example, obtaining a battery's OCV-SOC curve, incremental capacity curve, and EIS data typically requires separate testing, which is time-consuming and difficult to ensure consistent test conditions. High-precision data-driven algorithms require a large amount of high-quality training data, but traditional testing methods are extremely inefficient in acquiring such data. Existing technologies struggle to support rapid battery state assessment and diagnosis, failing to meet the real-time battery state monitoring requirements for applications such as electric vehicles and smart grids.

[0027] Based on this, embodiments of the present application provide a method, device, electronic device, and medium for estimating a state of charge.

[0028] See also Figure 1 , Figure 1 This is a flow chart of a method for estimating the state of charge provided in an embodiment of the present application. Figure 1 As shown in , the state of charge estimation method provided by the embodiment of the present application includes: S101 : Determine the discharge capacity of the test battery pack at each collection point based on the total capacity of the test battery pack.

[0029] S102 : Determine the pulse current amplitude, pulse current direction, and pulse duration of the initial pulse cycle according to the cut-off voltage of the test battery pack and the discharge capacity at each collection point, so as to form a pulse sequence for each collection point.

[0030] Specifically, each pulse sequence includes multiple sub-pulse periods, such as Figure 2As shown, the absolute value of the pulse current amplitude of each sub-pulse period is half of the absolute value of the pulse current amplitude of the previous sub-pulse period, the pulse duration of each sub-pulse period is half of the pulse duration of the previous sub-pulse period, and the direction of the pulse current of each sub-pulse period is opposite to that of the previous sub-pulse period.

[0031] Here, the pulse current amplitude of the initial pulse cycle is determined according to the voltage fluctuation of the test battery pack per unit time. When the voltage fluctuation is less than the test threshold, the corresponding current amplitude is determined to be the pulse current amplitude of the initial pulse cycle.

[0032] S103 : For each collection point, apply a pulse sequence at the collection point to the test battery pack, and measure the open circuit voltage value corresponding to the collection point.

[0033] S104 : Obtain an open circuit voltage-state of charge curve of the test battery pack according to the open circuit voltage values ​​measured at all acquisition points, so as to estimate the state of charge of the test battery pack according to the open circuit voltage-state of charge curve.

[0034] In one example, to obtain a battery OCV-SOC curve as an initial input parameter for estimating the battery SOC based on an equivalent circuit model, the following oscillating discharge method is used for rapid parameter acquisition.

[0035] Specifically, determine that there are 100 collection points, and each discharge is 1% of the capacity. Take the 2500mAh 18650 cylindrical battery as an example, the discharge capacity is 25mAh each time. After calculation, set the charge and discharge rate to 1C, determine that the pulse current amplitude of the initial pulse period is 37.6mAh, and the pulse current direction is forward, that is, constant current discharge 37.6mAh. According to the initial pulse period, it can be obtained that the sub-pulses are constant current discharge-18.8mAh, constant current discharge 9.4mAh, and constant current discharge-4.7mAh for each charging and discharging step. After that, the discharge capacity is halved and the direction is changed until the current output interval is less than 1s, until each sub-pulse in the pulse sequence is applied, and then stand for two minutes to collect the voltage-time curve as shown below. Figure 3 As shown, the final data of each rest time is taken as the OCV value at this moment. The OCV-SOC curve collected by this method is the same as the OCV-SOC curve collected by the ordinary discharge method. Figure 4 As shown, Figure 4 This is a schematic diagram comparing the OCV-SOC curve collected by this application and the OCV-SOC curve collected by the conventional discharge method. This technology reduces the test time by 71% and the resulting curve is closer to the equilibrium curve.

[0036] Another example is to obtain the EIS curves of the battery at different SOC points as input parameters for estimating the battery SOH based on the semi-empirical equation and data-driven method. The following oscillation discharge method can also be used to quickly obtain parameters: Specifically, taking a 2500mAh 18650 cylindrical battery as an example, first charge the battery to a full charge state and test the initial EIS curve after standing; then set the voltage fluctuation amplitude standard to ΔV≤3mV / h, determine the discharge target to 50% SOC (corresponding to releasing 1250mAh capacity), set the charge and discharge rate to 1C, and use the corresponding pulse sequence for discharge. The subsequent pulse capacity is halved and the current direction is changed until the current output interval is less than 1s, and the pulse sequence is repeated until the cumulative discharge is 1250mAh; after the discharge is completed, stand for 0.5 to 1 hour, and test the EIS curve of the battery at 50% SOC; after comparison and verification, the traditional 1C constant current discharge to 50% SOC requires standing for 5.5 hours, while this technology only requires standing for 1 hour after oscillation discharge. The EIS curves measured by the two methods are as follows Figure 5 As shown, Figure 5 This is a schematic diagram comparing the EIS curve collected by the present application and the EIS curve collected by the common discharge method provided in the embodiment of the present application. The impedance data obtained by this technology is close to the real impedance.

[0037] The battery state estimation method based on EIS testing, entropy function testing, multi-point HPPC, multi-point EIS, and battery PRT testing requirements and the parameters obtained through these tests can greatly improve the estimation efficiency through the oscillation discharge method of this application.

[0038] Below through Figure 6 This section describes the specific process of estimating the state of charge (SOC) of a test battery pack.

[0039] Figure 6 This is a flow chart for estimating the state of charge of a test battery pack provided in an embodiment of the present application.

[0040] S201 : Inputting an open circuit voltage-state of charge curve into a battery state estimation algorithm to obtain a query relationship between open circuit voltage and state of charge estimation.

[0041] Here, you also need to set the parameters of the test battery pack, including rated capacity, battery capacity, high and low cutoff voltages, etc. The battery state estimation algorithm is preferably an extended Kalman filter algorithm. The initial parameter setting of the extended Kalman filter includes setting the initial internal resistance, polarization resistance, polarization capacitance, noise covariance, etc. based on experience or battery AC impedance testing.

[0042] S202 : Obtain an initial open circuit voltage measurement value of the battery pack, and determine an initial state of charge estimation value corresponding to the initial open circuit voltage measurement value according to a query relationship.

[0043] S203 : Perform iterative estimation based on the initial state of charge estimation value to obtain the state of charge estimation value at the current moment.

[0044] Below through Figure 7 This section describes the specific process of obtaining the estimated state of charge at the current moment.

[0045] Figure 7 This is a flow chart for obtaining the estimated state of charge value at the current moment provided in an embodiment of the present application.

[0046] S301. Obtain the actual terminal voltage value, the actual current value, and the polarization voltage value of the test battery pack at the current moment.

[0047] The polarization voltage value at the current moment is calculated in the following way: the polarization voltage value at the previous moment is obtained; based on the current measured value and the polarization voltage value at the previous moment, the polarization voltage value at the current moment is obtained through the equivalent circuit model. The specific formula is:

[0048] Specifically, is the polarization voltage value at the current moment, is the polarization voltage value at the previous moment, τ is the polarization time constant, Rp is the polarization resistance value, is the actual measured current value at the current moment.

[0049] S302 : Obtaining a state of charge prediction value at the current moment according to the initial state of charge estimation value, and determining an open circuit voltage prediction value corresponding to the state of charge prediction value through a query relationship.

[0050] Specifically, the state of charge prediction value at the current moment is calculated using the following formula:

[0051]

[0052]

[0053] here, is the predicted state of charge at the current moment, is the estimated state of charge at the previous moment, is the estimated initial state of charge, is the polarization voltage value at the current moment, is the measured current value at the current moment, is the interval between the current moment and the previous moment, To test the total capacity of the battery pack.

[0054] S303 , obtaining a terminal voltage prediction value according to the open circuit voltage prediction value, the polarization voltage value, the current measurement value, and the ohmic internal resistance value of the test battery pack.

[0055] The terminal voltage prediction value is obtained by subtracting the polarization voltage value from the open circuit voltage prediction value, and then subtracting the product of the current measurement value and the ohmic internal resistance value to obtain the terminal voltage prediction value.

[0056] Specifically, the terminal voltage prediction value is calculated by the following formula:

[0057] here, is the predicted value of terminal voltage, To test the terminal voltage of the battery pack under no-load condition, To test the ohmic internal resistance of the battery pack.

[0058] S304: Determine a prediction deviation between the terminal voltage prediction value and the terminal voltage actual measurement value.

[0059] Specifically, the calculation formula for prediction deviation is:

[0060] Here, y is the prediction deviation, is the measured value of the terminal voltage, is the predicted value of terminal voltage.

[0061] S305 : Correct the state of charge prediction value according to the prediction deviation to obtain the state of charge estimation value at the current moment.

[0062] Specifically, the prediction deviation is multiplied by the Kalman gain coefficient in the extended Kalman filter algorithm to obtain a product result; the product result is superimposed on the state of charge prediction value to obtain the state of charge estimate at the current moment. The specific calculation formula is:

[0063]

[0064] here, is the estimated state of charge at the current moment, is the predicted state of charge at the current moment, y is the prediction deviation, K is the Kalman gain coefficient, is the covariance matrix, which characterizes the uncertainty of state estimation, H is the observation matrix, which is used to describe the relationship between state and observation, and R is the observation noise covariance matrix, which characterizes the measurement uncertainty.

[0065] Based on the same inventive concept, an embodiment of the present application also provides a state of charge estimation device corresponding to the state of charge estimation method. Since the principle of solving the problem by the device in the embodiment of the present application is similar to the above-mentioned state of charge estimation method in the embodiment of the present application, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be repeated.

[0066] See also Figure 8 , Figure 8 A schematic diagram of the structure of a charge state estimation device provided in an embodiment of the present application is shown in FIG. Figure 8 As shown in FIG, the state of charge estimation device 400 includes: The first determining module 401 is configured to determine the discharge capacity of the test battery pack at each collection point according to the total capacity of the test battery pack.

[0067] The second determination module 402 is used to determine the pulse current amplitude, pulse current direction, and pulse duration of the initial pulse cycle based on the cut-off voltage of the test battery pack and the discharge capacity at each acquisition point, so as to form a pulse sequence for each acquisition point, wherein each pulse sequence includes multiple sub-pulse cycles, wherein the absolute value of the pulse current amplitude of each sub-pulse cycle is half of the absolute value of the pulse current amplitude of the previous sub-pulse cycle, the pulse duration of each sub-pulse cycle is half of the pulse duration of the previous sub-pulse cycle, and the pulse current direction of each sub-pulse cycle is opposite to the pulse current direction of the previous sub-pulse cycle.

[0068] The measurement module 403 is configured to apply a pulse sequence at each collection point to the test battery pack to enable the test battery pack to release the discharge capacity corresponding to the collection point and measure the open circuit voltage value corresponding to the collection point.

[0069] The estimation module 404 is configured to obtain an open circuit voltage-state of charge curve of the test battery pack according to the open circuit voltage values ​​measured at all acquisition points, so as to estimate the state of charge of the test battery pack according to the open circuit voltage-state of charge curve.

[0070] See also Figure 9 , Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 9 As shown in FIG, the electronic device 500 includes a processor 510, a memory 520 and a bus 530.

[0071] The memory 520 stores machine-readable instructions executable by the processor 510. When the electronic device 500 is running, the processor 510 communicates with the memory 520 through the bus 530. When the machine-readable instructions are executed by the processor 510, the steps of the charge state estimation method in the above-mentioned method embodiment can be executed. The specific implementation method can be found in the method embodiment and will not be repeated here.

[0072] An embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is run by a processor, the steps of the state of charge estimation method in the above-mentioned method embodiment can be executed. The specific implementation method can be found in the method embodiment and will not be repeated here.

[0073] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0074] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. There may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed may be through some communication interface, indirect coupling or communication connection of devices or units, which may be electrical, mechanical or other forms.

[0075] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0076] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0077] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0078] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The scope of protection of the present application is not limited thereto. Although the present application has been described in detail with reference to the above-mentioned embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily conceive of changes to the technical solutions described in the above-mentioned embodiments within the technical scope disclosed in the present application, or perform equivalent replacements for some of the technical features thereof. These modifications, changes, or replacements do not deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A method for estimating state of charge, characterized in that: include: Determining the discharge capacity of the test battery pack at each collection point based on the total capacity of the test battery pack; Determine the pulse current amplitude, pulse current direction, and pulse duration of the initial pulse cycle according to the cut-off voltage of the test battery pack and the discharge capacity at each collection point to form a pulse sequence for each collection point, wherein each pulse sequence includes multiple sub-pulse cycles, wherein the absolute value of the pulse current amplitude of each sub-pulse cycle is half the absolute value of the pulse current amplitude of the previous sub-pulse cycle, the pulse duration of each sub-pulse cycle is half the pulse duration of the previous sub-pulse cycle, and the pulse current direction of each sub-pulse cycle is opposite to the pulse current direction of the previous sub-pulse cycle; For each collection point, applying the pulse sequence at the collection point to the test battery pack, and measuring the open circuit voltage value corresponding to the collection point; An open circuit voltage-state of charge curve of the test battery pack is obtained according to the open circuit voltage values ​​measured at all the acquisition points, so as to estimate the state of charge of the test battery pack according to the open circuit voltage-state of charge curve.

2. The method according to claim 1, characterized in that The state of charge of the test battery pack is estimated by: Inputting the open circuit voltage-state of charge curve into a battery state estimation algorithm to obtain a query relationship between open circuit voltage and state of charge estimation; Obtaining an initial open circuit voltage measurement value of the battery pack, and determining an initial state of charge estimation value corresponding to the initial open circuit voltage measurement value according to the query relationship; Iterative estimation is performed based on the initial state of charge estimation value to obtain the state of charge estimation value at the current moment.

3. The method according to claim 2, characterized in that The estimated state of charge at the current moment is obtained by: Obtaining a measured terminal voltage value, a measured current value, and a polarization voltage value of the test battery pack at a current moment; Obtaining a predicted state of charge value at a current moment according to the initial state of charge estimate, and determining a predicted open circuit voltage value corresponding to the predicted state of charge value through the query relationship; Obtaining a terminal voltage prediction value according to the open circuit voltage prediction value, the polarization voltage value, the current measurement value, and the ohmic internal resistance value of the test battery pack; Determining a prediction deviation between the terminal voltage prediction value and the terminal voltage actual measurement value; The state of charge prediction value is corrected according to the prediction deviation to obtain the state of charge estimation value at the current moment.

4. The method according to claim 3, characterized in that The polarization voltage value at the current moment is calculated as follows: Get the polarization voltage value at the previous moment; According to the measured current value at the current moment and the polarization voltage value at the previous moment, the polarization voltage value at the current moment is obtained through the equivalent circuit model.

5. The method according to claim 3, characterized in that The terminal voltage prediction value is obtained by the following method: The polarization voltage value is subtracted from the open circuit voltage prediction value, and then the product of the current measurement value and the ohmic internal resistance value is subtracted to obtain the terminal voltage prediction value.

6. The method according to claim 3, characterized in that The step of correcting the state of charge prediction value according to the prediction deviation to obtain the state of charge estimation value at the current moment includes: Multiplying the prediction deviation by a Kalman gain coefficient in an extended Kalman filter algorithm to obtain a product result; The product result is added to the state of charge prediction value to obtain the state of charge estimation value at the current moment.

7. A state of charge estimation device, characterized in that: include: A first determining module is configured to determine the discharge capacity of the test battery pack at each collection point according to the total capacity of the test battery pack; a second determination module, configured to determine the pulse current amplitude, pulse current direction, and pulse duration of an initial pulse cycle according to the cut-off voltage of the test battery pack and the discharge capacity at each acquisition point, so as to form a pulse sequence for each acquisition point, wherein each pulse sequence includes a plurality of sub-pulse cycles, wherein the absolute value of the pulse current amplitude of each sub-pulse cycle is half the absolute value of the pulse current amplitude of the previous sub-pulse cycle, the pulse duration of each sub-pulse cycle is half the pulse duration of the previous sub-pulse cycle, and the pulse current direction of each sub-pulse cycle is opposite to that of the pulse current of the previous sub-pulse cycle; a measurement module, configured to apply, for each collection point, the pulse sequence at the collection point to the test battery pack, so that the test battery pack releases the discharge capacity corresponding to the collection point, and measures the open circuit voltage value corresponding to the collection point; An estimation module is used to obtain an open circuit voltage-state of charge curve of the test battery pack according to the open circuit voltage values ​​measured at all acquisition points, so as to estimate the state of charge of the test battery pack according to the open circuit voltage-state of charge curve.

8. The device according to claim 7, characterized in that The estimation module is further configured to: Inputting the open circuit voltage-state of charge curve into a battery state estimation algorithm to obtain a query relationship between open circuit voltage and state of charge estimation; Obtaining an initial open circuit voltage measurement value of the battery pack, and determining an initial state of charge estimation value corresponding to the initial open circuit voltage measurement value according to the query relationship; Iterative estimation is performed based on the initial state of charge estimation value to obtain the state of charge estimation value at the current moment.

9. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate via the bus, and the processor executes the machine-readable instructions to perform the steps of any one of the methods described in claims 1 to 6.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are executed.

Images