Method and apparatus for correcting state of charge, storage medium and electronic device

Abstract

The application discloses a state of charge correction method and device, a storage medium and an electronic device. The method comprises the following steps: obtaining first battery data of a target battery at the time of power-off and second battery data of the target battery after power-on again after power-off, wherein the first battery data at least comprises the power-off time of the target battery, the power-off voltage at the power-off time, and the first state of charge value at the power-off time; the second battery data at least comprises the power-on time of the target battery and the power-on voltage at the power-on time; determining the static duration of the target battery and the working condition type corresponding to the target battery according to the first battery data and the second battery data; comparing the size of the static duration and the reference duration corresponding to the working condition type; and determining the state of charge correction strategy to be executed by the target battery based on the comparison result, the working condition type, the first battery data and the second battery data. The application solves the problems of high calculation amount and low state of charge correction precision of the current battery correction method.

Description

Technical Field

[0001] This application relates to the field of new energy vehicle batteries, and more specifically, to a method and apparatus for correcting the state of charge, a storage medium, and an electronic device. Background Technology

[0002] Currently, new energy vehicles are widely used, and their battery systems are also developing towards increasing cycle life, reducing weight, and improving integration. The stability and accuracy of battery management systems also need to be further improved.

[0003] In current BMS (Battery Management System), battery SOC (State of Charge) estimation is typically calculated using ampere-hour integration to determine the AHSOC value for a single cycle. Lithium iron phosphate (LFP) cells have a wide plateau region and a relatively small non-plateau region, meaning the probability of a user's vehicle operating within the non-plateau region is low. However, SOC estimation based on battery models and filtering algorithms is computationally intensive and requires consideration of applicable operating conditions and stability, thus having certain limitations.

[0004] Currently, there is no effective solution to the problem that the existing battery correction methods have high computational complexity and low accuracy in correcting the state of charge.

[0005] Therefore, it is necessary to improve the relevant technology to overcome the aforementioned defects. Summary of the Invention

[0006] This application provides a method and apparatus for correcting the state of charge, a storage medium, and an electronic device, which at least solves the problems of high computational complexity and low accuracy of current battery correction methods.

[0007] According to one aspect of the embodiments of this application, a method for correcting the state of charge (SOC) is provided, comprising: acquiring first battery data of a target battery when it is powered off, and second battery data of the target battery after it is powered off and then powered on again, wherein the first battery data includes at least: the power-off time of the target battery, the power-off voltage at the power-off time, and the first SOC value at the power-off time; the second battery data includes at least: the power-on time of the target battery and the power-on voltage at the power-on time; determining the resting time of the target battery and the corresponding operating condition type of the target battery based on the first battery data and the second battery data, wherein the operating condition type includes at least one of the following: normal discharge condition, normal charging condition, post-charging pulse discharge condition, and post-discharge pulse charging condition; comparing the resting time with the reference time corresponding to the operating condition type; and determining the SOC correction strategy to be executed for the target battery based on the comparison result, the operating condition type, the first battery data, and the second battery data.

[0008] In an exemplary embodiment, before determining the state-of-charge correction strategy to be executed for the target battery based on the comparison results, operating condition type, first battery data, and second battery data, the method further includes: determining that the voltage resting trend of the target battery is a monotonically increasing curve when the comparison results indicate that the resting time is greater than or equal to the reference time and the operating condition type is a normal discharge condition; determining that the voltage resting trend of the target battery is a non-monotonic curve that first increases and then decreases when the comparison results indicate that the resting time is greater than or equal to the reference time and the operating condition type is a post-charge pulse discharge condition; determining that the voltage resting trend of the target battery is a monotonically decreasing curve when the comparison results indicate that the resting time is greater than or equal to the reference time and the operating condition type is a normal charging condition; and determining that the voltage resting trend of the target battery is a non-monotonic curve that first decreases and then increases when the comparison results indicate that the resting time is greater than or equal to the reference time and the operating condition type is a post-discharge pulse charging condition.

[0009] In an exemplary embodiment, determining the state of charge (SOC) correction strategy for the target battery based on comparison results, the operating condition type, the first battery data, and the second battery data includes: determining a target curve of the voltage resting trend of the target battery between the power-off time and the power-on time based on the comparison results and the operating condition type, and determining a standard SOC value corresponding to each voltage value in the target curve based on a preset database; wherein the preset database stores multiple sets of open-circuit voltage and SOC correspondences, the open-circuit voltage under charging conditions is greater than the power-on voltage, and the open-circuit voltage under discharging conditions is less than the power-on voltage; estimating the SOC at the power-on time based on the target curve to obtain a second SOC value; determining the magnitude relationship between the second SOC value and the first SOC value, and determining the SOC correction strategy to be executed for the target battery based on the magnitude relationship.

[0010] In an exemplary embodiment, determining the state of charge (SOC) correction strategy to be executed for the target battery based on the magnitude relationship includes: when the target curve is a monotonically increasing curve or a non-monotonic curve that first decreases and then increases, and the magnitude relationship is that the second SOC value is greater than the first SOC value, determining to execute a first SOC correction strategy that increases the real-time value corresponding to the real-time charge state of the target battery at the time of power-on to the second SOC value; when the target curve is a monotonically decreasing curve or a non-monotonic curve that first increases and then decreases, and the magnitude relationship is that the second SOC value is less than the first SOC value, determining to execute a second SOC correction strategy that decreases the real-time value corresponding to the real-time charge state of the target battery at the time of power-on to the second SOC value.

[0011] In an exemplary embodiment, before acquiring first battery data when the target battery is powered off and second battery data after the target battery is powered off and powered on again, the method further includes: determining the battery type of the target battery and the operating condition type used by the target battery; establishing multiple test tasks for the target battery based on the battery type and the operating condition type; establishing a fitting curve of open circuit voltage and state of charge based on the test results of the multiple test tasks, and storing the corresponding values ​​of multiple sets of open circuit voltage and state of charge in the fitting curve in a target database to obtain a preset database for determining the state of charge of the battery at different voltage values.

[0012] In an exemplary embodiment, before determining the state of charge correction strategy to be executed for the target battery based on the comparison result, the operating condition type, the first battery data, and the second battery data, the method further includes: if it is determined that the current operating condition of the target battery does not have a matching type in the operating condition type, determining that the real-time state of charge of the target battery at the time of power-on is not changed; and issuing a prompt message to the target vehicle using the target battery indicating that the state of charge has not been corrected.

[0013] In an exemplary embodiment, after determining the state of charge correction strategy to be executed for the target battery based on the comparison results, the operating condition type, the first battery data, and the second battery data, the method further includes: obtaining the target state of charge value of the target battery after correction by the state of charge correction strategy to be executed; determining the difference between the target state of charge value and the first state of charge value; and marking the recorded data error of the target battery in the battery management system based on the difference.

[0014] According to another aspect of the embodiments of this application, a state of charge correction device is also provided, comprising: an acquisition module, configured to acquire first battery data of a target battery when it is powered off, and second battery data of the target battery after it is powered off and then powered on again, wherein the first battery data includes at least: the power-off time of the target battery, the power-off voltage at the power-off time, and the first state of charge value at the power-off time; the second battery data includes at least: the power-on time of the target battery and the power-on voltage at the power-on time; a first determination module, configured to determine the resting time of the target battery and the corresponding operating condition type of the target battery based on the first battery data and the second battery data, wherein the operating condition type includes at least one of the following: normal discharge operating condition, normal charging operating condition, post-charging pulse discharge operating condition, and post-discharge pulse charging operating condition; a comparison module, configured to compare the resting time with the reference time corresponding to the operating condition type; and a second determination module, configured to determine the state of charge correction strategy to be executed for the target battery based on the comparison result, the operating condition type, the first battery data, and the second battery data.

[0015] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, wherein a computer program is stored in the computer program, and the computer program is configured to execute the above-described method for correcting the state of charge when it is run.

[0016] According to another aspect of the embodiments of this application, an electronic device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the above-mentioned state of charge correction method through the computer program.

[0017] According to another aspect of the embodiments of this application, a computer program product is also provided, including a computer program and the above-mentioned method for correcting the state of charge when the computer program is executed by a processor.

[0018] This application obtains first battery data when the target battery is powered off and second battery data after power-on; determines the resting time and corresponding operating condition type of the target battery based on the first and second battery data; compares the resting time with the reference time corresponding to the operating condition type; and determines the state of charge (SOC) correction strategy for the target battery based on the comparison results, operating condition type, first battery data, and second battery data. This solves the problems of high computational complexity and low SOC correction accuracy in current battery correction methods. Consequently, it effectively improves the accuracy of battery SOC, avoids SOC estimation deviations caused by battery resting, and enhances the efficiency and safety of the battery management system. In practical applications, it significantly reduces SOC errors in battery management systems, extends battery life, and improves the performance and user experience of electric vehicles and other devices. Attached Figure Description

[0019] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0020] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a hardware structure block diagram of a mobile terminal for a method of correcting the state of charge according to an embodiment of this application.

[0022] Figure 2 This is a flowchart of a method for correcting the state of charge according to an embodiment of this application;

[0023] Figure 3This is a schematic diagram illustrating the voltage change trend after conventional discharge in an optional embodiment of this application.

[0024] Figure 4 This is a schematic diagram illustrating the variation trend of conventional charging resting voltage in an optional embodiment of this application;

[0025] Figure 5 This is a schematic diagram illustrating the trend of pulse discharge voltage change after charging under special operating conditions in an optional embodiment of this application.

[0026] Figure 6 This is a schematic diagram illustrating the trend of pulse charging voltage change after discharge under special operating conditions in an optional embodiment of this application;

[0027] Figure 7 This is a structural block diagram of a state of charge correction device according to an embodiment of this application. Detailed Implementation

[0028] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0029] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0030] The methods and embodiments provided in this application can be executed on a mobile terminal, computer terminal, or similar computing device. Taking running on a mobile terminal as an example, Figure 1 This is a hardware structure block diagram of a mobile terminal for a method of correcting the state of charge according to an embodiment of this application. Figure 1 As shown, a mobile terminal may include one or more ( Figure 1Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor (MCU) or a field-programmable gate array (FPGA)) and a memory 104 for storing data are also shown. The mobile terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the mobile terminal described above. For example, the mobile terminal may also include components that are more... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0031] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the state of charge correction method in this embodiment. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thereby implementing the above-described method. The memory 104 may include high-speed random access memory and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the mobile terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0032] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the mobile terminal's communication provider. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0033] This embodiment provides a method for correcting the state of charge. Figure 2 This is a flowchart of a method for correcting the state of charge according to an embodiment of this application, as shown below. Figure 2 As shown, the process includes the following steps S202-S208:

[0034] Step S202: Obtain first battery data when the target battery is powered off, and second battery data after the target battery is powered off and then powered on again. The first battery data includes at least: the power-off time of the target battery, the power-off voltage at the power-off time, and the first state of charge value at the power-off time. The second battery data includes at least: the power-on time of the target battery and the power-on voltage at the power-on time.

[0035] Optionally, when the vehicle stops and the power is disconnected (i.e., the battery is de-energized), the Battery Management System (BMS) records a series of data, including: Power-off time: the moment the vehicle stops and the power is disconnected; Power-off voltage: the battery voltage at the moment of power-off; First State of Charge (SOC): the estimated battery SOC calculated based on the BMS algorithm at the moment of power-off. When the vehicle restarts (i.e., the battery is re-energized), the BMS records: Power-on time: the moment the vehicle restarts; Power-on voltage: the battery voltage at the moment of power-on.

[0036] Step S204: Determine the resting time of the target battery and the corresponding operating condition type of the target battery based on the first battery data and the second battery data, wherein the operating condition type includes at least one of the following: normal discharge condition, normal charging condition, post-charging pulse discharge condition, and post-discharge pulse charging condition.

[0037] Optionally, the battery remains in a resting state between the vehicle's stop and restart. The BMS calculates the length of this period: Resting time: equal to the time difference between power-on and power-off. Then, the BMS determines the battery's operating condition during this period based on the trend of the voltage change from power-off to power-on. Specifically, this includes: Normal discharge condition: If the power-on voltage is higher than the power-off voltage and the resting time is relatively long, it may mean the battery was discharging before the vehicle stopped. Normal charging condition: If the power-on voltage is lower than the power-off voltage and the resting time is relatively long, it may mean the battery was charging before the vehicle stopped. Post-charging pulse discharge condition: If the power-on voltage is lower than the power-off voltage but the resting time is relatively short, it may mean a brief discharge occurred after charging. Post-discharge pulse charging condition: If the power-on voltage is higher than the power-off voltage but the resting time is relatively short, it may mean a brief charging occurred after discharging.

[0038] Step S206: Compare the resting time with the reference time corresponding to the working condition type;

[0039] Understandably, the BMS compares the resting time with a predefined "reference time," which is preset based on different operating conditions and battery characteristics to determine whether a SOC correction strategy can be applied. If the resting time exceeds the corresponding reference time, it indicates that the battery has been rested long enough for SOC correction to be performed.

[0040] Step S208: Based on the comparison results, the operating condition type, the first battery data, and the second battery data, determine the state of charge correction strategy to be executed for the target battery.

[0041] Based on the comparison results and the determined operating condition type in step S206, the BMS will perform the following operations:

[0042] You can choose your preferred method. If the operating condition is determined to be either a normal discharge condition or a post-charge pulse discharge condition, and the resting time is longer than the reference time, the BMS will check if the initial SOC is higher than the subsequent SOC. If so, it indicates that the estimated SOC is too low and can be corrected upwards. If the operating condition is determined to be either a normal charging condition or a post-discharge pulse charging condition, and the resting time is longer than the reference time, the BMS will check if the initial SOC is lower than the subsequent SOC. If so, it indicates that the estimated SOC is too high and can be corrected downwards. Through these correction strategies, the BMS can more accurately correct the SOC during vehicle resting periods by utilizing voltage trends, improving the accuracy of SOC estimation and thus optimizing battery management and usage.

[0043] Through the above steps, the system acquires first battery data when the target battery is powered off and second battery data after power-on. Based on the first and second battery data, it determines the target battery's resting time and corresponding operating condition type. The resting time is compared with a reference time corresponding to the operating condition type. Based on the comparison results, operating condition type, and the first and second battery data, a state-of-charge (SOC) correction strategy for the target battery is determined. This solves the problems of high computational complexity and low SOC correction accuracy in current battery correction methods. Consequently, it effectively improves the accuracy of battery SOC, avoids SOC estimation deviations caused by battery resting, and enhances the efficiency and safety of the battery management system. In practical applications, it significantly reduces SOC errors in battery management systems, extends battery life, and improves the performance and user experience of electric vehicles and other devices.

[0044] In an exemplary embodiment, before determining the state-of-charge correction strategy to be executed for the target battery based on the comparison results, operating condition type, first battery data, and second battery data, the method further includes: determining that the voltage resting trend of the target battery is a monotonically increasing curve when the comparison results indicate that the resting time is greater than or equal to the reference time and the operating condition type is a normal discharge condition; determining that the voltage resting trend of the target battery is a non-monotonic curve that first increases and then decreases when the comparison results indicate that the resting time is greater than or equal to the reference time and the operating condition type is a post-charge pulse discharge condition; determining that the voltage resting trend of the target battery is a monotonically decreasing curve when the comparison results indicate that the resting time is greater than or equal to the reference time and the operating condition type is a normal charging condition; and determining that the voltage resting trend of the target battery is a non-monotonic curve that first decreases and then increases when the comparison results indicate that the resting time is greater than or equal to the reference time and the operating condition type is a post-discharge pulse charging condition.

[0045] Understandably, before implementing the SOC correction strategy, the above method also includes a step of analyzing the voltage resting trend of the target battery, as follows:

[0046] Determine a monotonically increasing curve (normal discharge condition): If the comparison results indicate that the resting time is equal to or exceeds a preset reference time (e.g., T2), and the operating condition is identified as a normal discharge condition (discharging before the vehicle is powered off), then the battery's resting voltage is typically expected to gradually increase over time, forming a monotonically increasing curve.

[0047] Identify the non-monotonic curve that increases first and then decreases (special charging condition): If the comparison results indicate that the resting time is equal to or exceeds the preset reference time, and the operating condition is identified as a special charging condition (charging before the vehicle is powered off, followed by a possible brief pulse discharge), then under this condition, the battery's resting voltage may first rise (charging effect) and then fall (pulse discharge effect) in a short period of time, forming a non-monotonic curve that increases first and then decreases.

[0048] Determine a monotonically decreasing curve (normal charging condition): If the comparison results indicate that the resting time is equal to or exceeds the preset reference time, and the operating condition is identified as a normal charging condition (charging was underway before the vehicle was powered off), then the battery's resting voltage is typically expected to gradually decrease over time, forming a monotonically decreasing curve.

[0049] Identify the non-monotonic curve that decreases first and then increases (special discharge condition): If the comparison results indicate that the resting time is equal to or exceeds the preset reference time, and the condition type is identified as a special discharge condition (discharging before the vehicle is powered off, followed by a brief pulse charge), then under this condition, the battery's resting voltage may decrease first (discharge effect) and then increase (pulse charge effect) in a short period of time, forming a non-monotonic curve that decreases first and then increases.

[0050] In summary, through the above embodiments, by carefully analyzing the voltage change trend of the battery during rest, and combining the operating condition type and rest duration, the SOC can be effectively corrected, thereby improving the accuracy of the battery management system.

[0051] In an exemplary embodiment, determining the state of charge (SOC) correction strategy for the target battery based on comparison results, the operating condition type, the first battery data, and the second battery data includes: determining a target curve of the voltage resting trend of the target battery between the power-off time and the power-on time based on the comparison results and the operating condition type, and determining a standard SOC value corresponding to each voltage value in the target curve based on a preset database; wherein the preset database stores multiple sets of open-circuit voltage and SOC correspondences, the open-circuit voltage under charging conditions is greater than the power-on voltage, and the open-circuit voltage under discharging conditions is less than the power-on voltage; estimating the SOC at the power-on time based on the target curve to obtain a second SOC value; determining the magnitude relationship between the second SOC value and the first SOC value, and determining the SOC correction strategy to be executed for the target battery based on the magnitude relationship.

[0052] Understandably, when implementing the SOC correction strategy, the target curve of the target battery's voltage resting trend between the power-off moment and the power-on moment is first determined through the following steps:

[0053] Step S32: Determine the target curve: Based on whether the voltage change is monotonic and whether it exceeds a preset reference duration, determine the shape of the voltage change curve over time. If the voltage change is monotonic, the target curve will be monotonically increasing or monotonically decreasing; if the voltage change is non-monotonic, the target curve will contain one or more inflection points, forming a curve that first increases and then decreases or first decreases and then increases.

[0054] Step S34: Find the standard state of charge (SOC) value: Using a preset database, for each voltage value on the target curve, look up the corresponding open-circuit voltage (OCV) and state of charge (SOC) to obtain the standard SOC value corresponding to these voltage values. The preset database stores open-circuit voltage values ​​under different SOC states, which are obtained through laboratory testing and data analysis and are used for accurate SOC estimation.

[0055] Step S36: Estimate the SOC at the power-on moment: Based on the target curve, find the voltage value corresponding to the power-on moment, and query the standard state of charge value corresponding to the voltage value through the preset database to obtain the second state of charge value (power-on SOC).

[0056] Step S38: Compare SOC values ​​and determine correction strategy: Compare the second state of charge (SOC) value with the first state of charge (SOC after power-off). If the second SOC value is greater than the first SOC value, and the operating condition is a discharge condition (or a special discharge condition), it indicates that the estimated battery SOC value is too low, and an upward correction strategy should be implemented; if the second SOC value is less than the first SOC value, and the operating condition is a charging condition (or a special charging condition), it indicates that the estimated battery SOC value is too high, and a downward correction strategy should be implemented.

[0057] In an exemplary embodiment, determining the state of charge (SOC) correction strategy to be executed for the target battery based on the magnitude relationship includes: when the target curve is a monotonically increasing curve or a non-monotonic curve that first decreases and then increases, and the magnitude relationship is that the second SOC value is greater than the first SOC value, determining to execute a first SOC correction strategy that increases the real-time value corresponding to the real-time charge state of the target battery at the time of power-on to the second SOC value; when the target curve is a monotonically decreasing curve or a non-monotonic curve that first increases and then decreases, and the magnitude relationship is that the second SOC value is less than the first SOC value, determining to execute a second SOC correction strategy that decreases the real-time value corresponding to the real-time charge state of the target battery at the time of power-on to the second SOC value.

[0058] It should be noted that when the target curve is identified as a monotonically increasing curve or a non-monotonic curve that first decreases and then increases, and the second state of charge (SOC) value is greater than the first SOC value, this indicates that the voltage change trend of the battery during resting is consistent with the natural recovery law of SOC. That is, the battery voltage rises when resting after discharge, and the SOC should also recover to some extent. In this case, the first SOC correction strategy should be implemented to adjust the real-time SOC value of the target battery at the moment of power-on to the second SOC value to more accurately reflect the true SOC value.

[0059] Conversely, when the target curve is identified as a monotonically decreasing curve or a non-monotonic curve that first increases and then decreases, and the second state of charge (SOC) value is less than the first SOC value, this indicates that the voltage change trend of the battery during resting is consistent with the natural decay law of SOC. That is, when the battery voltage decreases after being charged and then resting, the SOC should also decay. In this case, a second SOC correction strategy should be implemented to lower the real-time SOC value of the target battery at the moment of power-on to the second SOC value, so as to more accurately reflect the true value of SOC.

[0060] By analyzing the voltage change trend during the resting period and comparing the SOC estimates at power-on and power-off times using the above embodiments, the direction of SOC estimation deviation can be accurately determined, and the state of charge value can be adjusted accordingly, thereby improving the accuracy of the battery management system. This method is particularly suitable for SOC estimation correction under complex operating conditions such as LFP batteries, ensuring the battery's performance and safety in different usage scenarios.

[0061] In an exemplary embodiment, before acquiring first battery data when the target battery is powered off and second battery data after the target battery is powered off and powered on again, the method further includes: determining the battery type of the target battery and the operating condition type used by the target battery; establishing multiple test tasks for the target battery based on the battery type and the operating condition type; establishing a fitting curve of open circuit voltage and state of charge based on the test results of the multiple test tasks, and storing the corresponding values ​​of multiple sets of open circuit voltage and state of charge in the fitting curve in a target database to obtain a preset database for determining the state of charge of the battery at different voltage values.

[0062] As an optional implementation method, before acquiring the power-on and power-off data of the target battery, it is first necessary to determine the battery type and operating condition type, and then establish multiple test tasks based on this information. The specific steps are as follows:

[0063] Step 1: Determine the battery type and operating conditions: Different battery types (e.g., LFP, NMC, NCA, etc.) exhibit different voltage change patterns during discharge and charging. Furthermore, the battery's operating conditions (e.g., normal driving conditions, high-speed driving conditions, idling conditions, mixed conditions, etc.) also affect its voltage and SOC performance. Therefore, it is essential to first identify the type of the target battery and the typical operating conditions it operates under.

[0064] Step 2: Establish multiple test tasks: Design a series of laboratory test tasks for specific battery types and operating conditions to simulate the charging and discharging process of the target battery under different states of charge and operating conditions, and record the voltage changes during its resting period.

[0065] Step 3: Test Result Analysis and Fitting: After performing the test, collect and analyze the test data. Based on the measured values ​​of voltage and SOC, use mathematical methods (such as linear regression, polynomial fitting, etc.) to establish fitting curves between open-circuit voltage and state of charge. These curves reflect the intrinsic relationship between voltage changes and estimated SOC values ​​during battery resting periods.

[0066] Step 4: Store Corresponding Value Relationships: Store the estimated SOC values ​​corresponding to each voltage value in the fitted curve as data points in the target database, forming a preset database. This database will serve as the basis for the BMS to determine the battery SOC value during actual use.

[0067] Example 1: Database Establishment for LFP Batteries under Normal Discharge Conditions. Battery type: LFP (Lithium Iron Phosphate) battery. Operating condition type: Discharge under normal driving conditions, such as low-speed urban driving. Test task establishment: Design test tasks to simulate the voltage change trend of LFP batteries under different states of charge (e.g., 20%, 40%, 60%, 80%) and normal driving discharge conditions. Testing and analysis: Perform the above test tasks in the laboratory, record the voltage change data of the battery during resting periods, and then use a nonlinear fitting method to establish the correspondence curve between voltage and SOC. Storing corresponding values: Store the voltage values ​​and corresponding SOC values ​​of different states of charge in the target database, forming a preset database of LFP batteries under normal driving discharge conditions.

[0068] Example 2: Database Establishment for NMC Batteries under Mixed Operating Conditions. Battery type: NMC (Nickel-Manganese-Cobalt) battery. Operating condition type: Mixed operating conditions, including fast charging / discharging, idling, and normal driving. Test tasks: Design test tasks covering different states of charge (SOC) of NMC batteries under mixed operating conditions (e.g., 10%, 30%, 50%, 70%, 90%). Testing and analysis: Simulate mixed operating conditions in a laboratory environment, record the voltage changes of the NMC battery, and then use polynomial fitting or other suitable data analysis methods to establish the correspondence curve between open-circuit voltage and SOC. Storing corresponding values: Store the estimated SOC values ​​corresponding to different voltage values ​​of the NMC battery under mixed operating conditions in a database, forming a pre-set database to provide data support for subsequent SOC correction strategies.

[0069] The above examples demonstrate that establishing a pre-defined database is a meticulous process requiring a deep understanding of battery types and operating conditions. Through laboratory testing and data analysis, accurate OCV-SOC correspondence curves can be constructed, providing a solid foundation for battery state-of-charge estimation and correction, and ensuring the performance and safety of the battery management system.

[0070] In an exemplary embodiment, before determining the state of charge correction strategy to be executed for the target battery based on the comparison result, the operating condition type, the first battery data, and the second battery data, the method further includes: if it is determined that the current operating condition of the target battery does not have a matching type in the operating condition type, determining that the real-time state of charge of the target battery at the time of power-on is not changed; and issuing a prompt message to the target vehicle using the target battery indicating that the state of charge has not been corrected.

[0071] Optionally, let's assume it's an LFP battery of a certain model. Current operating condition: The vehicle experienced complex driving and charging modes throughout the day, including high-speed driving, idling, charging, and rapid discharging, causing the BMS to be unable to clearly categorize this condition into a preset operating condition type. During the period from power-off to power-on, the BMS attempts to analyze the voltage change trend, but due to the complexity of the current operating condition, it cannot determine whether the target curve type matches any preset operating condition type. The BMS decides not to change the real-time SOC value at power-on and sends a prompt message to the vehicle, informing it that the SOC has not been corrected, possibly because the operating condition type did not match a preset type.

[0072] Optionally, let's assume a high-performance NMC battery. The vehicle operates under extreme conditions, such as high-speed driving in extreme temperatures, followed immediately by charging. This operating condition may exceed the range of preset operating conditions. BMS Operation: During the period from power-down to power-up, the voltage change trend and time duration recorded by the BMS are difficult to correlate with normal or special operating conditions, possibly because the battery exhibits unconventional behavior under extreme conditions. The BMS decides not to change the real-time SOC value at the time of power-up and simultaneously issues a notification to the vehicle user or management system, explaining that due to the uncertainty of the operating condition, the SOC has not been corrected.

[0073] In summary, when the battery operating condition type cannot match the preset type, maintaining the current estimated value of SOC and promptly notifying relevant parties can effectively avoid unnecessary risks, ensure the stability and safety of the battery management system under complex or unknown operating conditions, and help improve the overall driving experience and vehicle performance.

[0074] In an exemplary embodiment, after determining the state of charge correction strategy to be executed for the target battery based on the comparison results, the operating condition type, the first battery data, and the second battery data, the method further includes: obtaining the target state of charge value of the target battery after correction by the state of charge correction strategy to be executed; determining the difference between the target state of charge value and the first state of charge value; and marking the recorded data error of the target battery in the battery management system based on the difference.

[0075] Understandably, after implementing the SOC correction strategy, the BMS immediately obtains the corrected SOC value, i.e., the target SOC value, and compares it with the initial SOC value before correction, calculating the difference between the two. This difference reflects the magnitude of the SOC correction and is a key indicator for evaluating the effectiveness and accuracy of the correction strategy. Subsequently, the BMS records this error value in its system for: real-time monitoring of SOC estimation accuracy: By continuously recording the error value of each correction, the BMS can monitor the accuracy and stability of SOC estimation in real time, promptly identifying and handling any anomalies or deviations. Optimizing the correction strategy: Long-term accumulated error data can provide the BMS with feedback on the effectiveness of the correction strategy, helping the system learn and optimize the correction algorithm, improving the accuracy of SOC estimation. Battery health status monitoring: Analysis of error data can also help the BMS monitor the battery's health status. For example, if the error value continues to increase, it may indicate a decline in battery performance, requiring further inspection or maintenance.

[0076] Through the above embodiments, the difference between SOC and SOC correction is accurately recorded, assisting the system in real-time monitoring and adjustment of SOC estimates, providing valuable data for long-term battery maintenance and performance optimization. Furthermore, by continuously monitoring and recording SOC estimation errors, the BMS can continuously learn and improve its correction strategy, enhancing its adaptability to complex operating conditions and the intelligence level of battery management.

[0077] Obviously, the embodiments described above are only some embodiments of this application, and not all embodiments. To better understand the above method, the following description, in conjunction with embodiments, illustrates the process, but is not intended to limit the technical solutions of the embodiments of this application. Specifically:

[0078] As an optional implementation, this application provides a voltage-based SOC correction method, mainly applied in battery packs. The method includes: acquiring voltage change trends under different operating conditions through laboratory testing. Specifically, the voltage change trends of LFP cells are relatively obvious under different operating conditions. After continuous discharge, the voltage change trend shows an upward trend; after continuous charging, the voltage change trend shows a downward trend. However, for a certain special operating condition, after continuous discharge followed by pulse charging, the voltage change trend shows a decline followed by an increase; after continuous charging followed by pulse discharge, the voltage change trend shows an increase followed by a decline. Given these operating condition changes, and combining the SOC-OCV curve, a reference SOC value is determined after repeated power-on. Based on this reference SOC value, the real-time SOC value of the battery during rest is corrected. That is, during battery charging and discharging, the SOC is estimated using the external characteristic trend of voltage change, given the relatively obvious and predictable voltage change trend. This increases the SOC correction opportunities for LFP cells without increasing the algorithm load, thus improving SOC accuracy.

[0079] Optionally, the trend classification of the static voltage after working conditions is divided into four working conditions.

[0080] The first is the normal discharge condition. Figure 3 This is a schematic diagram of the change trend of the static voltage after normal discharge in an optional embodiment of the present application. If the static state is maintained after the discharge condition, the initial static voltage is VOLTA, and the calculated SOC value corresponding to the start of the static state is NVMSOCA. After the static state lasts for a certain period of time, the voltage is VOLTB, and it shows a monotonically increasing trend, VOLTB > VOLTA. Through testing, the duration T1 can be obtained, and T1 is much less than the full static time. Based on VOLTB, look up the SOC-OCV curve to obtain the SOC value VOLTBSOC corresponding to VOLTB. From the monotonicity, it can be known that after full static, the OCV value VOLTOCV > VOLTB, and the corresponding true SOC value > VOLTBSOC. Compare the difference between VOLTBSOC and NVMSOCA. If VOLTBSOC > NVMSOCA, and the current true SOC value > VOLTBSOC > NVMSOCA, it can be determined that the current calculated SOC value is low, and it can be partially corrected upward to VOLTBSOC to achieve the correction purpose.

[0081] The second is the normal charging condition. Figure 4 This is a schematic diagram of the change trend of the static voltage after normal charging in an optional embodiment of the present application. If the static state is maintained after the charging condition, the initial static voltage is VOLTA, and the calculated SOC value corresponding to the start of the static state is NVMSOCA. After the static state lasts for a certain period of time, the voltage is VOLTB, and it shows a monotonically decreasing trend, VOLTB < VOLTA. Through testing, the duration T1 can be obtained, and T1 is much less than the full static time. Based on VOLTB, look up the SOC-OCV curve to obtain the SOC value VOLTBSOC corresponding to VOLTB. From the monotonicity, it can be known that after full static, the OCV value VOLTOCV < VOLTB, and the corresponding true SOC value < VOLTBSOC. Compare the difference between VOLTBSOC and NVMSOCA. If VOLTBSOC < NVMSOCA, and the current true SOC value < VOLTBSOC < NVMSOCA, it can be determined that the current calculated SOC value is high, and it can be partially corrected downward to VOLTBSOC to achieve the correction purpose.

[0082] The third is the pulse discharge condition after charging. Figure 5It is a schematic diagram of the change trend of the pulse discharge voltage after charging under special working conditions in an optional embodiment of this application; if it is static after pulse discharge under the charging working condition, the starting voltage of the static state is VOLTA, and the calculated value of SOC corresponding to the starting of the static state is NVMSOCA. After the static state lasts for a certain time T2, the voltage reaches the maximum value of VOLTC. Continuing to be static until T1, the voltage drops to VOLTB, and the whole process shows non-monotonicity. However, it shows monotonic increase during the period from T2 to T1, indicating that it shows monotonic increase during the period from T1 to full static state, and VOLTC > VOLTB > VOLTA. The durations T2 and T1 can be obtained through testing, and T2 < T1 < full static state time. Based on VOLTB, look up the SOC-OCV curve to obtain the SOC value VOLTBSOC corresponding to VOLTB. From the monotonicity, it can be known that the OCV value VOLTOCV > VOLTB after full static state, and the corresponding true value of SOC > VOLTBSOC. Compare the difference between VOLTBSOC and NVMSOCA. If VOLTBSOC > NVMSOCA, and the current true value of SOC > VOLTBSOC > NVMSOCA, and at the same time confirm that the static state time > T2, then it can be determined that the current calculated value of SOC is on the low side, and it can be partially corrected upward to VOLTBSOC to achieve the correction purpose.

[0083] The fourth type is the pulse charging working condition after discharge; Figure 6 It is a schematic diagram of the change trend of the pulse charging voltage after discharge under special working conditions in an optional embodiment of this application; if it is static after pulse charging under the discharge working condition, the starting voltage of the static state is VOLTA, and the calculated value of SOC corresponding to the starting of the static state is NVMSOCA. After the static state lasts for a certain time T2, the voltage reaches the maximum value of VOLTC. Continuing to be static until T1, the voltage rises back to VOLTB, and the whole process shows non-monotonicity. However, it shows monotonic increase during the period from T2 to T1, indicating that it shows monotonic increase during the period from T1 to full static state, and VOLTC < VOLTB < VOLTA. The durations T, and T1 can be obtained through testing, and T2 < T1 < full static state time. Based on VOLTB, look up the SOC-OCV curve to obtain the SOC value VOLTBSOC corresponding to VOLTB. From the monotonicity, it can be known that the OCV value VOLTOCV < VOLTB after full static state, and the corresponding true value of SOC < VOLTBSOC. Compare the difference between VOLTBSOC and NVMSOCA. If VOLTBSOC < NVMSOCA, and the current true value of SOC < VOLTBSOC < NVMSOCA, and at the same time confirm that the static state time > T2, then it can be determined that the current calculated value of SOC is on the high side, and it can be partially corrected downward to VOLTBSOC to achieve the correction purpose.

[0084] In summary, by applying the above four trends of the static voltage external characteristics, the correction opportunity of the battery SOC during the static period can be increased, and the SOC accuracy can be improved. It should be noted that it has been verified that the single correction opportunity can be increased by more than 10%.

[0085] In practical applications, the specific execution process of SOC correction is as follows:

[0086] In the first step, before the vehicle is powered off after driving and parking, mark the moment as STARTTIME (the start time of static), the BMS records the voltage VOLTSTART (the voltage at power-off) at the moment of power-off, and the NVM-SOC-START (equivalent to the above first state of charge value) at the moment of power-off.

[0087] In the second step, record the time during the BMS sleep period when the vehicle stops.

[0088] In the third step, when the vehicle is powered on again, mark the moment as ENDTIME (the end time of static), the BMS records the voltage VOLTEND (the voltage at power-on), and calculate detTimA = ENDTIME - STARTTIME, which represents the static time detTimA of the vehicle. If the power-on voltage VOLTEND > the power-off voltage VOLTSTART and the static time detTimA > T2, it means that the voltage change trend shows Figure 3 and Figure 5 . According to the voltage static change trend, after sufficient static, the OCV value VOLTOCV (open circuit voltage) > the power-on voltage VOLTEND, and the corresponding true SOC value > VOLTENDSOC. Compare the difference between VOLTENDSOC and NVMSOCSTART. If VOLTENDSOC > NVMSOCSTART and the current true SOC value > VOLTENDSOC > NVMSOCSTART, it can be determined that the current SOC calculated value is low, and it can be corrected upward to VOLTENDSOC to achieve the correction purpose.

[0089] In the fourth step, following the third step, if the vehicle is powered on again and VOLTEND < VOLTSTART, and the static time detTimA > T2, it means that the voltage change trend shows Figure 4 and Figure 6Based on the voltage static change trend, after sufficient static, if the OCV value VOLTOCV < VOLTEND, the corresponding true SOC value < VOLTENDSOC. By comparing the difference between VOLTENDSOC and NVMSOCSTART, if VOLTENDSOC < NVMSOCSTART and the current true SOC value < VOLTENDSOC < NVMSOCSTART, it can be determined that the current SOC calculated value is on the high side, and it can be corrected downward to VOLTENDSOC to achieve the correction purpose.

[0090] In summary, in the above embodiments, by obtaining the data when the target battery is powered off and on, analyzing the static duration and operating condition type of the battery, and then estimating the change of the state of charge of the battery, the correction strategy of the state of charge is determined according to the change trend and size relationship. This method can effectively improve the accuracy of the state of charge of the battery, avoid the estimation deviation of the state of charge caused by the battery static, improve the working efficiency and safety of the battery management system, and solve the problems of high calculation amount and low correction accuracy of the current battery correction method. Subsequently, it can effectively improve the accuracy of the state of charge of the battery, avoid the estimation deviation of the state of charge caused by the battery static, and improve the working efficiency and safety of the battery management system. In practical applications, it significantly reduces the state of charge error in the battery management system, prolongs the battery life, and improves the performance and user experience of electric vehicles and other devices.

[0091] Through the description of the above embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by means of software plus a necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases, the former is a better implementation method. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disc), and includes several instructions for causing a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of the present application.

[0092] In this embodiment, a correction device for the state of charge is also provided. The device is used to implement the above embodiments and preferred implementation manners, and those that have been described will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that can achieve a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware is also possible and contemplated.

[0093] Figure 7 It is a structural block diagram of a correction device for the state of charge according to an embodiment of the present application. The device includes:

[0094] The acquisition module 72 is used to acquire first battery data when the target battery is powered off, and second battery data after the target battery is powered off and then powered on again. The first battery data includes at least: the power-off time of the target battery, the power-off voltage at the power-off time, and the first state of charge value at the power-off time; the second battery data includes at least: the power-on time of the target battery and the power-on voltage at the power-on time.

[0095] The first determining module 74 is used to determine the resting time of the target battery and the operating condition type corresponding to the target battery based on the first battery data and the second battery data, wherein the operating condition type includes at least one of the following: normal discharge condition, normal charging condition, post-charging pulse discharge condition, and post-discharge pulse charging condition.

[0096] Comparison module 76 is used to compare the resting time with the reference time corresponding to the working condition type;

[0097] The second determining module 78 is used to determine the state of charge correction strategy to be executed for the target battery based on the comparison result, the operating condition type, the first battery data, and the second battery data.

[0098] The aforementioned device acquires first battery data when the target battery is powered off and second battery data after power-on; determines the resting time and corresponding operating condition type of the target battery based on the first and second battery data; compares the resting time with a reference time corresponding to the operating condition type; and determines the state of charge (SOC) correction strategy for the target battery based on the comparison result, operating condition type, first battery data, and second battery data. This solves the problems of high computational complexity and low SOC correction accuracy in current battery correction methods. Consequently, it effectively improves the accuracy of battery SOC, avoids SOC estimation deviations caused by battery resting, and enhances the efficiency and safety of the battery management system. In practical applications, it significantly reduces SOC errors in battery management systems, extends battery life, and improves the performance and user experience of electric vehicles and other devices.

[0099] In an exemplary embodiment, the above-described apparatus further includes: a third determining module, configured to, before determining the state-of-charge correction strategy to be executed for the target battery based on the comparison result, operating condition type, first battery data, and second battery data, determine that the voltage resting change trend of the target battery is a monotonically increasing curve when the comparison result indicates that the resting time is greater than or equal to the reference time and the operating condition type is a normal discharge condition; determine that the voltage resting change trend of the target battery is a non-monotonic curve that first increases and then decreases when the comparison result indicates that the resting time is greater than or equal to the reference time and the operating condition type is a normal charging condition; and determine that the voltage resting change trend of the target battery is a monotonically decreasing curve when the comparison result indicates that the resting time is greater than or equal to the reference time and the operating condition type is a discharge pulse charging condition; and determine that the voltage resting change trend of the target battery is a non-monotonic curve that first decreases and then increases when the comparison result indicates that the resting time is greater than or equal to the reference time and the operating condition type is a discharge pulse charging condition.

[0100] In an exemplary embodiment, the second determining module is further configured to determine a target curve of the voltage resting change trend of the target battery between the power-off time and the power-on time based on the comparison result and the operating condition type, and to determine the standard state of charge value corresponding to each voltage value in the target curve based on a preset database; wherein, the preset database stores multiple sets of open-circuit voltage and state of charge correspondence values, the open-circuit voltage under charging condition is greater than the power-on voltage, and the open-circuit voltage under discharging condition is less than the power-on voltage; to estimate the state of charge at the power-on time based on the target curve to obtain a second state of charge value; to determine the magnitude relationship between the second state of charge value and the first state of charge value, and to determine the state of charge correction strategy to be executed for the target battery according to the magnitude relationship.

[0101] In an exemplary embodiment, the second determining module is further configured to, when the target curve is a monotonically increasing curve or a non-monotonic curve that first decreases and then increases, and the magnitude relationship is that the second state of charge value is greater than the first state of charge value, determine to execute a first state of charge correction strategy that increases the real-time value corresponding to the real-time charge state of the target battery at the time of power-on to the second state of charge value; and when the target curve is a monotonically decreasing curve or a non-monotonic curve that first increases and then decreases, and the magnitude relationship is that the second state of charge value is less than the first state of charge value, determine to execute a second state of charge correction strategy that decreases the real-time value corresponding to the real-time charge state of the target battery at the time of power-on to the second state of charge value.

[0102] In an exemplary embodiment, the above-described apparatus further includes: a setup module, used to acquire first battery data when the target battery is powered off, and second battery data after the target battery is powered off and then powered on again. Before acquiring these data, the method further includes: determining the battery type of the target battery and the operating condition type used by the target battery; establishing multiple test tasks for the target battery based on the battery type and the operating condition type; establishing a fitting curve of open-circuit voltage versus state of charge based on the test results of the multiple test tasks; and storing the corresponding values ​​of multiple sets of open-circuit voltage and state of charge in the fitting curve in a target database to obtain a preset database for determining the state of charge of the battery at different voltage values.

[0103] In an exemplary embodiment, the above-described apparatus further includes: a prompting module, configured to, before determining the state of charge correction strategy to be executed for the target battery based on the comparison result, the operating condition type, the first battery data, and the second battery data, determine that the real-time state of charge of the target battery at the time of power-on should not be changed if it is determined that the current operating condition of the target battery does not have a matching type in the operating condition type; and issue a prompt message to the target vehicle using the target battery indicating that the state of charge has not been corrected.

[0104] In an exemplary embodiment, the above-described apparatus further includes: an error module, configured to: after determining the state of charge correction strategy to be executed for the target battery based on the comparison result, the operating condition type, the first battery data, and the second battery data; obtain the target state of charge value of the target battery after correction by the state of charge correction strategy to be executed; determine the difference between the target state of charge value and the first state of charge value; and mark the recorded data error of the target battery in the battery management system based on the difference.

[0105] Embodiments of this application also provide a computer-readable storage medium storing a computer program, wherein the computer program is configured to execute the steps in any of the above method embodiments when run.

[0106] Optionally, in this embodiment, the storage medium may be configured to store a computer program for performing the following steps:

[0107] S1, acquire first battery data when the target battery is powered off, and second battery data after the target battery is powered off and then powered on again, wherein the first battery data includes at least: the power-off time of the target battery, the power-off voltage at the power-off time, and the first state of charge value at the power-off time; the second battery data includes at least: the power-on time of the target battery and the power-on voltage at the power-on time.

[0108] S2, determine the resting time of the target battery and the operating condition type corresponding to the target battery based on the first battery data and the second battery data, wherein the operating condition type includes at least one of the following: normal discharge condition, normal charging condition, post-charging pulse discharge condition, and post-discharge pulse charging condition;

[0109] S3, compare the resting time with the reference time corresponding to the working condition type;

[0110] S4. Based on the comparison results, the operating condition type, the first battery data, and the second battery data, determine the state of charge correction strategy to be executed for the target battery.

[0111] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard disk, magnetic disk, or optical disk.

[0112] Specific examples in this embodiment can be found in the examples described in the above embodiments and exemplary implementations, and will not be repeated here.

[0113] Embodiments of this application also provide a computer program product, including a computer program, wherein the computer program, when executed by a processor, performs the steps in any of the above method embodiments.

[0114] Embodiments of this application also provide an electronic device including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in any of the above method embodiments.

[0115] Optionally, in this embodiment, the processor can be configured to perform the following steps via a computer program:

[0116] S1, acquire first battery data when the target battery is powered off, and second battery data after the target battery is powered off and then powered on again, wherein the first battery data includes at least: the power-off time of the target battery, the power-off voltage at the power-off time, and the first state of charge value at the power-off time; the second battery data includes at least: the power-on time of the target battery and the power-on voltage at the power-on time.

[0117] S2, determine the resting time of the target battery and the operating condition type corresponding to the target battery based on the first battery data and the second battery data, wherein the operating condition type includes at least one of the following: normal discharge condition, normal charging condition, post-charging pulse discharge condition, and post-discharge pulse charging condition;

[0118] S3, compare the resting time with the reference time corresponding to the working condition type;

[0119] S4. Based on the comparison results, the operating condition type, the first battery data, and the second battery data, determine the state of charge correction strategy to be executed for the target battery.

[0120] In one exemplary embodiment, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor and the input / output device is connected to the processor.

[0121] Specific examples in this embodiment can be found in the examples described in the above embodiments and exemplary implementations, and will not be repeated here.

[0122] Obviously, those skilled in the art should understand that the modules or steps of this application described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. They can be implemented using computer-executable program code, and thus can be stored in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented here, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, this application is not limited to any particular combination of hardware and software.

[0123] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for correcting the state of charge, characterized in that, include: Acquire first battery data when the target battery is powered off, and second battery data after the target battery is powered off and then powered on again. The first battery data includes at least: the power-off time of the target battery, the power-off voltage at the power-off time, and the first state of charge value at the power-off time. The second battery data includes at least: the power-on time of the target battery and the power-on voltage at the power-on time. The resting time of the target battery and the corresponding operating condition type of the target battery are determined based on the first battery data and the second battery data, wherein the operating condition type includes at least one of the following: normal discharge condition, normal charging condition, post-charging pulse discharge condition, and post-discharge pulse charging condition; the resting time is compared with the reference time corresponding to the operating condition type. Based on the comparison results, the operating condition type, the first battery data, and the second battery data, the state of charge correction strategy to be executed for the target battery is determined.

2. The method for correcting the state of charge according to claim 1, characterized in that, Before determining the state-of-charge correction strategy to be executed for the target battery based on the comparison results, the operating condition type, the first battery data, and the second battery data, the method further includes: If the comparison result indicates that the resting time is greater than or equal to the reference time, and the operating condition is a normal discharge condition, the voltage change trend of the target battery during resting is determined to be a monotonically increasing curve. If the comparison result indicates that the resting time is greater than or equal to the reference time, and the operating condition is a post-charge pulse discharge condition, the voltage resting change trend of the target battery is determined to be a non-monotonic curve that first increases and then decreases. If the comparison result indicates that the resting time is greater than or equal to the reference time, and the operating condition is a normal charging condition, the voltage resting change trend of the target battery is determined to be a monotonically decreasing curve. If the comparison result indicates that the resting time is greater than or equal to the reference time, and the operating condition is a post-discharge pulse charging condition, the voltage resting change trend of the target battery is determined to be a non-monotonic curve that first decreases and then increases.

3. The method for correcting the state of charge according to claim 1, characterized in that, Based on the comparison results, the operating condition type, the first battery data, and the second battery data, a state-of-charge correction strategy to be executed for the target battery is determined, including: Based on the comparison results and the operating condition type, a target curve of the voltage static change trend of the target battery between the power-off time and the power-on time is determined, and a standard state of charge value corresponding to each voltage value in the target curve is determined based on a preset database; wherein, the preset database stores multiple sets of open circuit voltage and state of charge correspondence values, the open circuit voltage under the charging condition is greater than the power-on voltage, and the open circuit voltage under the discharging condition is less than the power-on voltage. Based on the target curve, the state of charge at the power-on moment is estimated to obtain a second state of charge value; the relationship between the second state of charge value and the first state of charge value is determined, and a state of charge correction strategy to be executed for the target battery is determined according to the relationship.

4. The method for correcting the state of charge according to claim 3, characterized in that, Based on the aforementioned size relationship, a state-of-charge correction strategy to be executed for the target battery is determined, including: If the target curve is a monotonically increasing curve or a non-monotonic curve that first decreases and then increases, and the magnitude relationship is that the second state of charge value is greater than the first state of charge value, then it is determined to execute a first state of charge correction strategy that adjusts the real-time value corresponding to the real-time charge state of the target battery at the time of power-on to the second state of charge value. If the target curve is a monotonically decreasing curve or a non-monotonic curve that first increases and then decreases, and the magnitude relationship is that the second state of charge value is less than the first state of charge value, then a second state of charge correction strategy is determined to be executed, which reduces the real-time value corresponding to the real-time charge state of the target battery at the time of power-on to the second state of charge value.

5. The method for correcting the state of charge according to any one of claims 1 to 4, characterized in that, Before acquiring the first battery data when the target battery is powered off, and the second battery data after the target battery is powered off and then powered on again, the method further includes: Determine the battery type of the target battery and the operating conditions under which the target battery is used; Multiple test tasks for the target battery are established based on the battery type and the operating condition type. Based on the test results of the multiple test tasks, a fitting curve of open circuit voltage and state of charge is established, and the corresponding values ​​of multiple sets of open circuit voltage and state of charge in the fitting curve are stored in the target database to obtain a preset database for determining the state of charge of the battery at different voltage values.

6. The method for determining the power supply mode according to claim 1, characterized in that, Before determining the state-of-charge correction strategy to be executed for the target battery based on the comparison results, the operating condition type, the first battery data, and the second battery data, the method further includes: If it is determined that the current operating condition of the target battery does not have a matching type in the operating condition type, it is determined that the real-time state of charge of the target battery at the time of power-on will not be changed. A notification message indicating that the state of charge has not been corrected is sent to the target vehicle using the target battery.

7. The method for determining the power supply mode according to claim 1, characterized in that, After determining the state-of-charge correction strategy to be executed for the target battery based on the comparison results, the operating condition type, the first battery data, and the second battery data, the method further includes: Obtain the target state of charge value of the target battery after correction by the state of charge correction strategy to be executed; The difference between the target state of charge value and the first state of charge value is determined, and the recorded data error of the target battery is marked in the battery management system based on the difference.

8. A state of charge correction device, characterized in that, include: The acquisition module is used to acquire first battery data when the target battery is powered off, and second battery data after the target battery is powered off and then powered on again. The first battery data includes at least: the power-off time of the target battery, the power-off voltage at the power-off time, and the first state of charge value at the power-off time; the second battery data includes at least: the power-on time of the target battery and the power-on voltage at the power-on time. The first determining module is used to determine the resting time of the target battery and the operating condition type corresponding to the target battery based on the first battery data and the second battery data, wherein the operating condition type includes at least one of the following: normal discharge condition, normal charging condition, post-charging pulse discharge condition, and post-discharge pulse charging condition. The comparison module is used to compare the resting time with the reference time corresponding to the working condition type; The second determining module is used to determine the state of charge correction strategy to be executed for the target battery based on the comparison results, the operating condition type, the first battery data, and the second battery data.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein the program, when executed, performs the method of any one of claims 1 to 7.

10. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to execute the method of any one of claims 1 to 7 through the computer program.

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