Lithium iron phosphate battery soc correction method, device, equipment, storage medium and computer program product

Abstract

The application relates to the technical field of battery application, in particular to a lithium iron phosphate battery SOC correction method and device, equipment, a storage medium and a computer program product. The method determines a SOC change amount according to voltage data and current data of a to-be-processed battery cell; determines an SOC estimation value according to the SOC change amount and an initial SOC value; if the to-be-processed battery cell is in a platform period, interpolation calculation is performed through a preset open-circuit voltage mapping table set and a preset dynamic internal resistance mapping table set to obtain a first correction value and a second correction value; and a target SOC value is determined according to the SOC estimation value, the first correction value and the second correction value. The method determines the SOC change amount according to the voltage data and the current data, and calculates the SOC estimation value in combination with the initial SOC value, finally determines the target SOC value by comprehensively combining the SOC estimation value and the two correction values, and the accuracy of SOC estimation is improved.

Description

Technical Field

[0001] This application relates to the field of battery application technology, and in particular to a method, apparatus, device, storage medium, and computer program product for correcting the SOC of a lithium iron phosphate battery. Background Technology

[0002] With the rapid development of electric vehicles, energy storage systems, and other fields, the demand for lithium iron phosphate (LiFePO4, LFP) batteries is increasing. LFP batteries, with their high safety, long cycle life, and stable operating characteristics, have become a core component widely used in the new energy industry. However, battery performance and lifespan are closely related to the accuracy of its management system, among which accurate estimation of the state of charge (SOC) is particularly crucial. SOC reflects the battery's remaining capacity and plays a vital role in charge-discharge control, safety protection, and lifespan management. Currently, SOC estimation mainly relies on methods such as the ampere-hour integration method and the open-circuit voltage (OCV) method. The ampere-hour integration method calculates the change in charge by multiplying the accumulated current by time, but this method is susceptible to the effects of current sensor drift and accumulated errors. The OCV method estimates SOC based on the relationship between open-circuit voltage and SOC, but the relationship between OCV and SOC is not obvious during the plateau period of LFP batteries (i.e., the SOC range where voltage changes are gradual), making it difficult for the OCV method to accurately estimate SOC during this stage. Therefore, improving the accuracy of SOC estimation for lithium iron phosphate batteries has become an urgent technical problem to be solved. Summary of the Invention

[0003] The main objective of this application is to provide a method, apparatus, device, storage medium, and product for correcting the state of charge (SOC) of lithium iron phosphate batteries, aiming to solve the technical problem of how to improve the accuracy of SOC estimation for lithium iron phosphate batteries.

[0004] To achieve the above objectives, this application provides a method for correcting the state of charge (SOC) of a lithium iron phosphate battery, the method comprising:

[0005] Determine the SOC change based on the voltage and current data of the battery cell to be processed;

[0006] Based on the change in SOC and the initial SOC value, determine the estimated SOC value;

[0007] If the cell to be processed is in a plateau period, interpolation calculation is performed using a preset open-circuit voltage mapping table and a preset dynamic internal resistance mapping table to obtain a first correction value and a second correction value.

[0008] The target SOC value is determined based on the estimated SOC value, the first correction value, and the second correction value.

[0009] In one embodiment, before the step of obtaining a first correction value and a second correction value by interpolation calculation using a preset open-circuit voltage mapping table and a preset dynamic internal resistance mapping table if the cell to be processed is in a plateau period, the method further includes:

[0010] Based on the voltage data and the current data, determine the voltage and current changes of the battery cell to be processed;

[0011] Acquire the temperature data of the battery cell to be processed, and determine the temperature change of the battery cell to be processed based on the temperature data;

[0012] Based on the voltage changes, current changes, and temperature changes, it is determined whether the battery cell to be processed is in the plateau period.

[0013] In one embodiment, the step of obtaining a first correction value and a second correction value by interpolation calculation using a preset open-circuit voltage mapping table and a preset dynamic internal resistance mapping table if the cell to be processed is in a plateau period includes:

[0014] Based on the current temperature of the cell to be processed, the open-circuit voltage mapping table corresponding to the preset open-circuit voltage mapping table set is selected as the first correction table;

[0015] Based on the first correction table, the SOC estimate is interpolated to obtain the first correction value;

[0016] Based on the current temperature and current charge / discharge rate of the cell to be processed, the dynamic internal resistance mapping table corresponding to the preset dynamic internal resistance mapping table set is selected as the second correction table.

[0017] Based on the second correction table, the estimated SOC value is interpolated to obtain the second correction value.

[0018] In one embodiment, the step of determining the target SOC value based on the estimated SOC value, the first correction value, and the second correction value includes:

[0019] Determine whether the difference between the estimated SOC value, the first corrected value, and the second corrected value exceeds a preset difference threshold.

[0020] If not, based on the first preset weighting rule, the estimated SOC value, the first corrected value, and the second corrected value are weighted and summed to obtain the target SOC value.

[0021] In one embodiment, before the step of determining the target SOC value based on the SOC estimate, the first correction value, and the second correction value, the method further includes:

[0022] If the cell to be processed is not in a plateau period, the target SOC value is obtained by weighted summation of the estimated SOC value, the first correction value, and the second correction value based on the second preset weighting rule; wherein, the weight corresponding to the estimated SOC value in the second preset weighting rule is greater than the weight corresponding to the estimated SOC value in the first preset weighting rule.

[0023] In one embodiment, after the step of determining the target SOC value based on the SOC estimate, the first correction value, and the second correction value, the method further includes:

[0024] The target SOC value is verified based on a preset SOC range standard.

[0025] If the verification is successful, the current SOC state of the cell to be processed is updated based on the target SOC value.

[0026] Furthermore, to achieve the above objectives, this application also proposes a lithium iron phosphate battery SOC correction device, the lithium iron phosphate battery SOC correction device comprising:

[0027] The preliminary module is used to determine the SOC change based on the voltage and current data of the battery cell to be processed;

[0028] The estimation module is used to determine the estimated SOC value based on the SOC change and the initial SOC value.

[0029] The correction module is used to perform interpolation calculations using a preset open-circuit voltage mapping table and a preset dynamic internal resistance mapping table if the cell to be processed is in a plateau period, to obtain a first correction value and a second correction value.

[0030] The target module is used to determine a target SOC value based on the estimated SOC value, the first correction value, and the second correction value.

[0031] Furthermore, to achieve the above objectives, this application also proposes a lithium iron phosphate battery SOC correction device, the device comprising: a memory, a processor, and a lithium iron phosphate battery SOC correction program stored in the memory and executable on the processor, the lithium iron phosphate battery SOC correction program being configured to implement the steps of the lithium iron phosphate battery SOC correction method as described above.

[0032] In addition, to achieve the above objectives, this application also proposes a storage medium storing a lithium iron phosphate battery SOC correction program, which, when executed by a processor, implements the steps of the lithium iron phosphate battery SOC correction method as described above.

[0033] In addition, to achieve the above objectives, this application also proposes a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the lithium iron phosphate battery SOC correction method described above.

[0034] This application determines the SOC change based on the voltage and current data of the cell to be processed; it then determines an estimated SOC value based on the SOC change and the initial SOC value; if the cell to be processed is in a plateau period, it performs interpolation calculations using a preset open-circuit voltage mapping table and a preset dynamic internal resistance mapping table to obtain a first correction value and a second correction value; finally, it determines the target SOC value based on the estimated SOC value, the first correction value, and the second correction value. This application determines the SOC change based on voltage and current data, calculates the estimated SOC value in conjunction with the initial SOC value, performs interpolation calculations using the open-circuit voltage mapping table and the dynamic internal resistance mapping table during the plateau period to obtain the first and second correction values, and finally determines the target SOC value by combining the estimated SOC value and the two correction values. Through multiple data fusion and correction, it effectively compensates for the error caused by voltage stability during the plateau period, improving the accuracy and stability of SOC estimation. Attached Figure Description

[0035] Figure 1 This is a flowchart illustrating the first embodiment of the lithium iron phosphate battery SOC correction method of this application;

[0036] Figure 2 This is a schematic diagram of a sub-process in the second embodiment of the lithium iron phosphate battery SOC correction method of this application;

[0037] Figure 3 This is a schematic diagram of a sub-process in the third embodiment of the lithium iron phosphate battery SOC correction method of this application;

[0038] Figure 4 This is a schematic diagram of the module structure of the lithium iron phosphate battery SOC correction device according to an embodiment of this application;

[0039] Figure 5 This is a schematic diagram of the hardware operating environment involved in the lithium iron phosphate battery SOC correction method in the embodiments of this application.

[0040] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0041] It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of this application.

[0042] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0043] It should be noted that with the rapid development of electric vehicles, energy storage systems, and other fields, the demand for lithium iron phosphate (LiFePO4, LFP) batteries is increasing. LFP batteries, with their high safety, long cycle life, and stable operating characteristics, have become a core component widely used in the new energy industry. However, battery performance and lifespan are closely related to the accuracy of its management system, among which accurate estimation of the state of charge (SOC) is particularly crucial. SOC reflects the remaining capacity of the battery and plays an important role in battery charge-discharge control, safety protection, and lifespan management. Currently, SOC estimation mainly relies on methods such as the ampere-hour integration method and the open-circuit voltage (OCV) method. The ampere-hour integration method calculates the change in charge by multiplying the accumulated current by time, but this method is easily affected by current sensor drift and accumulated errors. The OCV method estimates SOC based on the relationship between open-circuit voltage and SOC, but in the plateau period of LFP batteries (i.e., the SOC range where voltage changes are gradual), the relationship between OCV and SOC is not obvious, making it difficult for the OCV method to accurately estimate SOC during this stage. Therefore, how to improve the accuracy of SOC estimation for lithium iron phosphate batteries has become an urgent technical problem to be solved.

[0044] The main solution of this application is as follows: determine the SOC change based on the voltage and current data of the cell to be processed; determine the estimated SOC value based on the SOC change and the initial SOC value; if the cell to be processed is in a plateau period, perform interpolation calculations using a preset open-circuit voltage mapping table and a preset dynamic internal resistance mapping table to obtain a first correction value and a second correction value; determine the target SOC value based on the estimated SOC value, the first correction value, and the second correction value.

[0045] This application determines the SOC change based on voltage and current data, and calculates the estimated SOC value by combining the initial SOC value. During the plateau period, interpolation calculations are performed using open-circuit voltage mapping tables and dynamic internal resistance mapping tables to obtain first and second correction values. Finally, the target SOC value is determined by combining the estimated SOC value with the two correction values. Through multiple data fusion and correction, the error caused by voltage stability during the plateau period is effectively compensated, and the accuracy and stability of SOC estimation are improved.

[0046] It should be noted that the execution subject of the method in this embodiment can be a computing service device with data processing, network communication, and program execution functions, or it can be the aforementioned lithium iron phosphate battery SOC correction device with the same or similar functions. This embodiment and the following embodiments will be described using a lithium iron phosphate battery SOC correction device as an example.

[0047] Based on this, a first embodiment of the lithium iron phosphate battery SOC correction method of this application is proposed. Please refer to [link / reference]. Figure 1 , Figure 1This is a flowchart illustrating the first embodiment of the lithium iron phosphate battery SOC correction method of this application.

[0048] In this embodiment, the method includes the following steps:

[0049] S1: Determine the SOC change based on the voltage and current data of the battery cell to be processed;

[0050] It's important to note that a battery cell is the basic unit inside a battery, containing components such as the positive electrode, negative electrode, and electrolyte. The battery cell is the core component of a battery, and multiple cells can form a complete battery pack. Voltage data refers to the voltage value monitored in real time during the charging and discharging process of the battery cell, reflecting its state of charge (SOC) and operating status. Current data refers to the current value passing through the battery cell during charging and discharging; positive current indicates charging, and negative current indicates discharging. Current and voltage data together determine the battery's charging and discharging behavior. SOC change refers to the change in the cell's SOC (state of charge) over a specific period of time. SOC represents the percentage of the cell's remaining capacity relative to its maximum capacity, and the change in SOC can be calculated by accumulating current over time.

[0051] Specifically, sensors monitor the voltage and current data of the battery cells in real time. This data is collected periodically to ensure accurate tracking of the cell's charging and discharging process. The monitored current data is used to determine whether the cell is currently charging or discharging, and changes are recorded based on different current directions. The system then inputs this data into the battery management system (BMS) as the basis for SOC estimation.

[0052] Furthermore, the change in SOC is calculated using the ampere-hour integration method. Specifically, within a time interval, the system multiplies the collected current value by the time length to obtain the change in charge within that time interval. Then, this change in charge is compared with the total battery capacity to calculate the change in SOC. The change in SOC at each time interval is added to or subtracted from the SOC at the previous moment to obtain an updated SOC estimate.

[0053] By monitoring voltage and current data in real time and calculating SOC changes, the system can accurately capture the charge and discharge state of the battery cell at every moment, avoiding estimation errors that may arise from relying on a single data point (such as voltage). Compared to simple voltage monitoring, this method can provide more accurate SOC estimates during voltage plateau periods, effectively avoiding estimation deviations caused by voltage stability. Furthermore, this step, through the accumulation of current and time, can reflect the true state of the battery under different operating conditions (such as different charge and discharge rates). This calculation method ensures the real-time nature and reliability of SOC estimation, providing accurate basic data for subsequent corrections and optimizations, and contributing to improved battery management system safety and battery lifespan.

[0054] S2: Determine the estimated SOC value based on the SOC change and the initial SOC value;

[0055] It's important to note that the initial SOC value refers to the battery's SOC at the start of the calculation, representing the percentage of remaining charge in the cell relative to its total capacity at that moment. The initial SOC value serves as the fundamental reference point for subsequent SOC estimation and dynamic adjustments. The estimated SOC value is the current SOC value calculated based on the initial SOC value and the SOC change; it represents an estimate of the cell's remaining charge state at a specific time and is used to guide charging / discharging strategies and battery management.

[0056] Specifically, at the start of the calculation, an initial SOC value is recorded, which is the percentage of remaining charge in the cell relative to the total capacity at that moment. This initial SOC value may be derived from records taken when the battery is fully charged, or from previous SOC estimates as a reference starting point. Subsequently, the system calculates the change in SOC over a certain period using real-time acquired current data and the ampere-hour integration method, and then adds or subtracts it from the initial SOC value.

[0057] Furthermore, the calculation method is adjusted according to the charging and discharging state of the battery cell: During charging, the change in SOC is added to the initial SOC value to calculate the current estimated SOC value of the battery cell; during discharging, the change in SOC is subtracted from the initial SOC value to estimate the current SOC. This process is cumulative hourly, meaning that the estimated SOC value in each time period is used as the initial SOC value for the next stage, ensuring the continuity and real-time nature of the SOC estimation results.

[0058] By combining the change in SOC with the initial SOC value, this step ensures the accuracy and continuity of SOC estimation. This cumulative or subtractive approach not only tracks the battery's state of charge in real time but also avoids the impact of single estimation errors on the overall result. Furthermore, this method provides fundamental data for addressing cell state changes under different operating conditions (such as high-rate charging / discharging or plateau periods). This hourly SOC update method enhances the robustness of the battery management system, allowing for real-time adjustments to SOC estimation during charging and discharging, avoiding misjudgments caused by sensor drift or calculation errors, and providing a reliable basis for corrections during subsequent plateau periods. Simultaneously, this process ensures battery safety in various application scenarios, preventing overcharging or over-discharging, and improving battery life and system stability.

[0059] S3: If the cell to be processed is in a plateau period, interpolation calculation is performed using a preset open-circuit voltage mapping table and a preset dynamic internal resistance mapping table to obtain a first correction value and a second correction value.

[0060] It's important to note that the plateau period refers to a specific State of Charge (SOC) range during the charging and discharging process of a lithium iron phosphate battery. Within this range, voltage fluctuations are relatively small; even if the SOC changes significantly, the voltage change is very limited. This makes it difficult to accurately estimate the SOC solely based on voltage data. The Open Circuit Voltage Map (OCV-map) is a pre-measured table recording the correspondence between the cell's open circuit voltage and SOC under different temperature and SOC conditions. These tables are used to supplement the non-linear relationship between voltage and SOC during the plateau period. The Dynamic Internal Resistance Map (DCR-map) is a pre-established mapping table recording the changes in the cell's internal resistance under different temperature, SOC levels, and charge / discharge rates, reflecting the battery's characteristics under dynamic operating conditions. The first correction value is the SOC correction value calculated by interpolation using the open circuit voltage map, compensating for estimation errors caused by the insignificant voltage changes during the plateau period. The second correction value is the SOC correction value calculated by interpolation using the dynamic internal resistance map, reflecting the impact of internal resistance changes on SOC estimation.

[0061] Specifically, determine and select the corresponding open-circuit voltage mapping table (OCV-map) and dynamic internal resistance mapping table (DCR-map).

[0062] The system first selects the OCV (Open Circuit Voltage) table from the open circuit voltage mapping table set that best matches the current temperature of the battery cell. Simultaneously, it selects the corresponding DCR (Dynamic Internal Resistance) table from the dynamic internal resistance mapping table set based on the cell's temperature and charge / discharge rate. This step ensures that the selected mapping table accurately reflects the current operating conditions.

[0063] Furthermore, linear interpolation is performed between adjacent data points in the OCV table based on the current SOC estimate. If the SOC estimate does not precisely fall on a data point in the OCV table, the corresponding open-circuit voltage is estimated using interpolation, and the first correction value is derived from this. In the DCR table, using the current charge / discharge rate and temperature, the internal resistance data point corresponding to the SOC range is found, and the dynamic internal resistance correction value under the current SOC state is calculated through interpolation. This internal resistance value reflects the impact of battery dynamic behavior on SOC.

[0064] By combining OCV and DCR mapping tables for interpolation calculations during the plateau period, this method effectively compensates for SOC estimation errors during voltage stabilization. The open-circuit voltage mapping table provides supplementary information on the nonlinear voltage-SOC relationship, making SOC estimation no longer dependent on a single voltage signal. The introduction of a dynamic internal resistance mapping table fully considers the impact of temperature and rate changes on SOC, resulting in more accurate estimation results. This multi-table interpolation correction strategy improves the robustness and accuracy of SOC estimation, avoiding the biases caused by single-voltage estimation methods during the plateau period. By introducing dynamic internal resistance correction, the actual state of the battery under complex operating conditions can also be reflected, thereby improving the reliability of the battery management system (BMS), extending battery life, and ensuring the safe operation of the system.

[0065] S4: Determine the target SOC value based on the estimated SOC value, the first correction value, and the second correction value;

[0066] It should be noted that the target SOC value is the final SOC value obtained by combining the estimated SOC value, the first correction value, and the second correction value, and serves as the basis for the battery management system (BMS) to manage the battery status in real time.

[0067] Specifically, the SOC estimate, the first correction value, and the second correction value are first compared to check if the difference between them is within a preset threshold range. If the difference between the three values ​​exceeds the threshold, there may be an anomaly, such as sensor drift or data acquisition error. The system will then trigger an alarm and enter the anomaly handling process.

[0068] Furthermore, if the differences among the three key values ​​are within a reasonable range, the system will perform a weighted sum of the SOC estimate, the first correction value, and the second correction value based on the first preset weighting rule. During the plateau period, the weights of the first and second correction values ​​will be appropriately increased to compensate for the error in the SOC estimate; during the non-plateau period, the weight of the SOC estimate will be higher because the voltage change is more consistent with the SOC change at this time.

[0069] By comprehensively calculating the estimated SOC value, the first correction value, and the second correction value, this step ensures the accuracy of the final target SOC value. Especially during plateau periods, relying solely on voltage signal estimation yields significant errors, while OCV and DCR corrections effectively improve the accuracy of SOC estimation. Furthermore, by flexibly adjusting weighting rules based on different operating conditions, the system can adapt to different charge and discharge states, achieving more precise battery management. This multi-factor fusion calculation strategy enables the battery management system to accurately grasp the cell status even in complex environments, avoiding the risks of overcharging or over-discharging, and ensuring battery safety and lifespan. Simultaneously, determining the target SOC value provides a reliable management basis for the system, helping to optimize battery charge and discharge efficiency.

[0070] This embodiment determines the SOC change based on the voltage and current data of the cell to be processed; it then determines an estimated SOC value based on the SOC change and the initial SOC value; if the cell to be processed is in a plateau period, it performs interpolation calculations using a preset open-circuit voltage mapping table and a preset dynamic internal resistance mapping table to obtain a first correction value and a second correction value; finally, it determines the target SOC value based on the estimated SOC value, the first correction value, and the second correction value. This embodiment determines the SOC change based on voltage and current data, calculates the estimated SOC value using the initial SOC value, performs interpolation calculations using the open-circuit voltage mapping table and the dynamic internal resistance mapping table during the plateau period to obtain the first and second correction values, and finally determines the target SOC value by combining the estimated SOC value and the two correction values. Through multiple data fusion and correction, it effectively compensates for the error caused by voltage stability during the plateau period, improving the accuracy and stability of SOC estimation.

[0071] Based on the first embodiment described above, a second embodiment of the SOC correction method for lithium iron phosphate batteries in this application is proposed. Please refer to... Figure 2 , Figure 2 This is a schematic diagram of a sub-process in the second embodiment of the lithium iron phosphate battery SOC correction method of this application.

[0072] like Figure 2 As shown, in this embodiment, before step S3, the following steps are also included:

[0073] S3a: Based on the voltage data and the current data, determine the voltage and current changes of the battery cell to be processed;

[0074] S3b: Obtain the temperature data of the battery cell to be processed, and determine the temperature change of the battery cell to be processed based on the temperature data;

[0075] S3c: Based on the voltage change, the current change, and the temperature change, determine whether the cell to be processed is in the plateau period.

[0076] It should be noted that voltage variation refers to the trend of cell voltage changes over a period of time, including voltage increases, decreases, or stabilization. This is used to determine the cell's charge / discharge state and whether it is in a voltage plateau. Current variation refers to the current fluctuations during the cell's charge / discharge process, including the magnitude, direction (charging or discharging), and changes over time. Temperature data refers to the real-time temperature value of the cell during operation. Temperature variation describes the trend of cell temperature changes over time, used to analyze whether the temperature is stable and whether it may affect the battery's state.

[0077] Specifically, sensors collect real-time data on the cell's voltage, current, and temperature, continuously recording this data at set time intervals. The system then processes the collected data, calculating the rate of change of voltage, current, and temperature over a given period. If the voltage variation is small across multiple time points, the cell voltage is considered stable. Current fluctuations are analyzed to determine if the cell is in a stable charging / discharging state. If the cell temperature fluctuates little over a period, it indicates temperature stability and no significant impact on voltage and internal resistance.

[0078] Furthermore, if the voltage remains stable within a certain period, i.e., the change is below a preset threshold, the cell may be in a plateau phase. When the current remains stable without significant fluctuations, it indicates that the cell is currently in a constant charge / discharge state. Temperature stability verifies the authenticity of voltage changes. If temperature fluctuations are small and voltage changes are not significant, it further supports the judgment that the cell is in a plateau phase. If the changes in the above three parameters all meet the stability condition, the system will determine that the cell is in a plateau phase; otherwise, it is considered that the cell has not entered a plateau phase, and the conventional SOC estimation method needs to be used for calculation.

[0079] By monitoring changes in voltage, current, and temperature, the system can accurately determine whether a battery cell is in a plateau phase. This multi-parameter judgment method overcomes the limitations of relying solely on voltage monitoring, effectively improving the accuracy of SOC estimation during the plateau phase. Furthermore, by incorporating temperature data, the system can identify the impact of the environment on the cell's state, ensuring the reliability of the judgment results. This comprehensive judgment lays the foundation for SOC correction during the plateau phase, enabling the system to flexibly switch between different estimation strategies. During the plateau phase, interpolation correction can be performed using a mapping table, while during non-plateau phases, estimation relies on the ampere-hour integration method, thereby improving the overall accuracy of SOC estimation and the safety of battery management.

[0080] Based on the first embodiment described above, in this embodiment, step S3 includes:

[0081] S31: Based on the current temperature of the cell to be processed, select the open circuit voltage mapping table corresponding to the preset open circuit voltage mapping table set as the first correction table;

[0082] S32: Based on the first correction table, interpolate the estimated SOC value to obtain the first correction value;

[0083] S33: Based on the current temperature and current charge / discharge rate of the cell to be processed, select the dynamic internal resistance mapping table corresponding to the preset dynamic internal resistance mapping table set as the second correction table;

[0084] S34: Based on the second correction table, interpolate the estimated SOC value to obtain the second correction value.

[0085] It should be noted that the Open Circuit Voltage Mapping Set (OCV-map) contains multiple mapping tables showing the relationship between battery SOC (State of Charge) and open circuit voltage under different temperature conditions. Each table corresponds to a specific temperature environment, reflecting the battery's voltage variation characteristics at different temperatures. The first correction table is selected from the OCV mapping set and corresponds to the current cell temperature. It is used to interpolate and correct the estimated SOC value, compensating for errors caused by insignificant voltage changes during plateau periods. The Dynamic Internal Resistance Mapping Set (DCR-map) records the relationship between the cell's internal resistance at different temperatures, SOC levels, and charge / discharge rates. It reflects the cell's resistance characteristics under dynamic operating conditions. The second correction table is selected from the DCR mapping set based on the cell's current temperature and charge / discharge rate, used to further correct the estimated SOC value. The charge / discharge rate represents the ratio between the current charging or discharging current of the cell and its rated capacity, such as 1C, 0.5C, etc. This parameter affects the battery's internal resistance performance and operating state.

[0086] Specifically, based on the current temperature of the battery cell, the system searches for the open-circuit voltage mapping table corresponding to that temperature in the OCV mapping table set and uses it as the first correction table. Based on the position of the estimated SOC value in this mapping table, the system determines that it lies between two adjacent data points. A linear interpolation method is then used to calculate the voltage corresponding to the estimated SOC value between these two data points. This interpolation result serves as the first correction value, used to compensate for errors caused by the unclear relationship between voltage and SOC during the plateau period.

[0087] Furthermore, based on the cell's current temperature and charge / discharge rate, a corresponding dynamic internal resistance mapping table is selected from the DCR mapping table set and used as the second correction table. The position of the estimated SOC value in this internal resistance mapping table is used to determine if it lies between two adjacent SOC data points. Through linear interpolation, the system estimates the corresponding internal resistance correction value between these two data points and uses it as the second correction value. This correction value reflects the impact of temperature and rate changes on the internal resistance.

[0088] By combining the OCV mapping table and the DCR mapping table, the accuracy of SOC estimation is effectively improved. First, the introduction of the OCV mapping table compensates for the error in SOC estimation when the battery voltage change is not significant during the plateau period, making the estimation results more accurate. Second, the DCR mapping table reflects the impact of temperature and charge / discharge rate on the cell's internal resistance, further correcting the SOC estimation value and ensuring its applicability under different operating conditions. This dual correction mechanism not only improves the accuracy and robustness of SOC estimation but also allows for flexible adjustment of the estimation strategy according to different operating conditions, ensuring that the Battery Management System (BMS) can reliably control the battery state, thereby avoiding overcharging or over-discharging, extending battery life, and improving system safety and stability.

[0089] This embodiment determines the SOC change based on the voltage and current data of the cell to be processed; it then determines an estimated SOC value based on the SOC change and the initial SOC value; if the cell to be processed is in a plateau period, it performs interpolation calculations using a preset open-circuit voltage mapping table and a preset dynamic internal resistance mapping table to obtain a first correction value and a second correction value; finally, it determines the target SOC value based on the estimated SOC value, the first correction value, and the second correction value. This embodiment determines the SOC change based on voltage and current data, calculates the estimated SOC value using the initial SOC value, performs interpolation calculations using the open-circuit voltage mapping table and the dynamic internal resistance mapping table during the plateau period to obtain the first and second correction values, and finally determines the target SOC value by combining the estimated SOC value and the two correction values. Through multiple data fusion and correction, it effectively compensates for the error caused by voltage stability during the plateau period, improving the accuracy and stability of SOC estimation.

[0090] Based on the second embodiment described above, a third embodiment of the SOC correction method for lithium iron phosphate batteries in this application is proposed. Please refer to... Figure 3 , Figure 3 This is a schematic diagram of a sub-process in the third embodiment of the lithium iron phosphate battery SOC correction method of this application.

[0091] In this embodiment, step S4 includes:

[0092] S41: Determine whether the difference between the estimated SOC value, the first corrected value, and the second corrected value exceeds a preset difference threshold;

[0093] S42: If not, based on the first preset weighting rule, the estimated SOC value, the first correction value, and the second correction value are weighted and summed to obtain the target SOC value.

[0094] It should be noted that the difference value refers to the magnitude of the difference between the SOC estimate, the first correction value, and the second correction value, used to measure whether these estimation results are consistent. The preset difference threshold is a tolerance range pre-set by the system, used to determine whether the differences between multiple SOC estimation results are within a reasonable range. The first preset weighting rule assigns weight ratios to the SOC estimate, the first correction value, and the second correction value according to the importance of different parameters, and is used to calculate the target SOC value through weighted summation.

[0095] Specifically, the differences between the SOC estimate, the first correction value, and the second correction value are compared one by one, and the difference values ​​are calculated. If all these differences are within the preset difference threshold range set by the system, the consistency between the estimates is considered good, and a weighted summation calculation can be performed. If any difference value exceeds the threshold, the system may consider a certain estimation result to be abnormal, for example, due to sensor drift or data error. In this case, the system will trigger an alarm or enter an anomaly handling process, and will not directly use these data to calculate the target SOC value.

[0096] Furthermore, based on the system's operating conditions (e.g., during or outside a plateau period), weights are assigned to the estimated SOC, the first correction value, and the second correction value. For example, during a plateau period, the weights of the first and second correction values ​​may be increased. The estimated SOC, the first correction value, and the second correction value are then weighted and summed according to the set weight ratios to calculate the target SOC value. This target SOC value serves as the final output, guiding the operation of the battery management system.

[0097] By determining whether the difference value exceeds a preset threshold, the system can filter out estimation results that may contain errors or anomalies, ensuring the reliability and accuracy of the target SOC value. Simultaneously, weighted summation calculation based on a first preset weighting rule allows the system to flexibly adapt to SOC estimation needs under different operating conditions. The introduction of this weighted summation method avoids the error accumulation caused by a single estimation method, improving the robustness and adaptability of SOC estimation. The system can prioritize correction values ​​during plateau periods and rely more on SOC estimation values ​​during non-plateau periods, thus outputting accurate SOC estimation results under various conditions and ensuring the safety and stability of battery operation.

[0098] Based on the second embodiment described above, in this embodiment, before step S4, the following is further included:

[0099] S4A: If the cell to be processed is not in a plateau period, the target SOC value is obtained by weighted summation of the estimated SOC value, the first correction value, and the second correction value based on the second preset weighting rule; wherein, the weight corresponding to the estimated SOC value in the second preset weighting rule is greater than the weight corresponding to the estimated SOC value in the first preset weighting rule.

[0100] It should be noted that the second preset weighting rule refers to the weighting rule used when the battery cell is not in a plateau period, and the weight ratio of the SOC estimate is higher than that of the first preset weighting rule during the plateau period.

[0101] Specifically, the system first determines whether the battery cell is in a plateau phase based on changes in voltage, current, and temperature data. If the system detects a significant change in voltage with SOC, it determines that the battery cell is not in a plateau phase and proceeds to the normal SOC estimation process.

[0102] Furthermore, during the non-plateau period, since voltage changes more directly reflect the SOC state, the system relies on the estimated SOC value as the primary reference, thus giving it a larger weight. The first and second correction values ​​have smaller weights at this time. According to the second preset weighting rule, the estimated SOC value, the first correction value, and the second correction value are weighted and summed to obtain the final target SOC value. Because the cell is not in a plateau period at this time, the system primarily relies on the estimated SOC value to reflect the battery's real-time state.

[0103] By employing a second preset weighting rule, this step ensures that the system prioritizes the SOC estimate when the cell is not in a plateau phase, fully utilizing the accuracy and real-time performance of the ampere-hour integration method. This weighted strategy avoids errors that may arise from relying on OCV and DCR correction values ​​when voltage changes significantly, thereby improving the adaptability and accuracy of SOC estimation. Furthermore, by flexibly switching the weighting rule, the system can adapt to different operating conditions, prioritizing correction values ​​during plateau phases and relying on the SOC estimate during non-plateau phases. This strategy enhances the robustness of the battery management system, ensuring the battery outputs accurate SOC values ​​under various conditions, thereby optimizing the charge / discharge control strategy, extending battery life, and ensuring system safety and stability.

[0104] Based on the second embodiment described above, in this embodiment, after step S4, the following is further included:

[0105] S4a: Verify the target SOC value based on a preset SOC range standard;

[0106] S4b: If the verification is successful, update the current SOC state of the cell to be processed based on the target SOC value.

[0107] It should be noted that the SOC range standard is a pre-defined reasonable range or threshold for SOC, used to determine whether the target SOC value is within a safe and effective range. For example, SOC should generally be between 0% and 100%, but in some application scenarios there may be stricter range requirements (such as 20% to 80%). The current SOC state refers to the SOC value of the cell at the current point in time, representing the remaining capacity of the cell, and is key data for the Battery Management System (BMS) to perform charge and discharge control and safety protection.

[0108] Specifically, the calculated target SOC value is compared with a preset SOC range standard to check if the value is within a reasonable SOC range. For example, if the SOC value exceeds 100%, it indicates a possible error in the calculation, such as current accumulation error or sensor drift. If the SOC value is below 0% or other set minimum thresholds, it may indicate abnormal battery consumption or misjudgment of battery status. If the target SOC value fails verification, the system will trigger a corresponding alarm and take measures as appropriate, such as adjusting calculation parameters or recalculating the SOC value, to ensure the accuracy of the battery status.

[0109] Furthermore, if the target SOC value passes the range verification, the system will use this value as the current SOC state of the cell and record it in the Battery Management System (BMS) for subsequent charge and discharge management. The updated SOC state will be used as the initial SOC value for the next time period, and the battery's charge and discharge strategy will be adjusted accordingly. For example, when the SOC is close to the upper limit, the system will limit further charging to prevent overcharging; when the SOC is close to the lower limit, the system may stop discharging to prevent over-discharging.

[0110] By verifying the target SOC value based on a preset SOC range standard, this step ensures the accuracy and reliability of the SOC value, avoiding potential battery damage or performance degradation caused by incorrect SOC calculations. Upon successful verification, the current SOC state of the battery cell is updated promptly, providing reliable foundational data for the system's charge / discharge control and safety management. This process enhances the robustness of the battery management system, ensuring the continuity of SOC estimation and management. Simultaneously, through reasonable SOC updates and control strategies, risks such as overcharging and over-discharging can be avoided, extending battery life and ensuring the safe and stable operation of the system.

[0111] This embodiment determines the SOC change based on the voltage and current data of the cell to be processed; it then determines an estimated SOC value based on the SOC change and the initial SOC value; if the cell to be processed is in a plateau period, it performs interpolation calculations using a preset open-circuit voltage mapping table and a preset dynamic internal resistance mapping table to obtain a first correction value and a second correction value; finally, it determines the target SOC value based on the estimated SOC value, the first correction value, and the second correction value. This embodiment determines the SOC change based on voltage and current data, calculates the estimated SOC value using the initial SOC value, performs interpolation calculations using the open-circuit voltage mapping table and the dynamic internal resistance mapping table during the plateau period to obtain the first and second correction values, and finally determines the target SOC value by combining the estimated SOC value and the two correction values. Through multiple data fusion and correction, it effectively compensates for the error caused by voltage stability during the plateau period, improving the accuracy and stability of SOC estimation.

[0112] In one embodiment, a method for correcting the State of Charge (SOC) of a lithium iron phosphate battery during charging and discharging is provided, comprising the following stages: acquiring discharge DCR-maps (including three test durations of 2s, 5s, and 10s) and dynamic discharge OCV-maps when discharging from 100% SOC to 0% at 0.2C, 0.33C, 0.5C, 1C, 2C, and MaxC (maximum discharge rate) at (-30℃, -20℃, -10℃, 0℃, 10℃, 25℃, 45℃, and 55℃ respectively). Simultaneously, acquiring dynamic charging OCV-maps and charging DCR-maps (10s, 30s, and 60s) based on the charging map test. When the cell is charging / discharging during the discharge plateau period, based on the current temperature T, charging / discharging current I and duration t, and cell voltage V, comparing with the dynamic charging / discharging OCV-maps at different rates, and taking the linear difference, the SOC is obtained. V1 Simultaneously, based on the changes in charging / discharging current and cell voltage, the charging / discharging DCR can be obtained. By comparing this with the charging / discharging DCR-map at different rates and taking the linear difference, the SOC can be obtained. R1 Simultaneously, based on the time-based integration, the SOC can be obtained. Ah The formula for defining the true SOC is: SOC real =A*SOC V1 +B*SOC R1 +C*SOC Ah (Where A, B, and C are proportionality coefficients, A+B+C=1, and are corrected in real time based on the SOC correction results in the non-platform area). When the accuracy requirements of SOC are further increased, it can be extended to:

[0113] Where n is a constant, the value of n can be adjusted based on actual needs and test verification data to obtain the true SOC at the end of the plateau discharge period.

[0114] This application also provides a lithium iron phosphate battery SOC correction device. Please refer to... Figure 4 , Figure 4 This is a schematic diagram of the module structure of the lithium iron phosphate battery SOC correction device according to an embodiment of this application. The lithium iron phosphate battery SOC correction device includes:

[0115] The preliminary module 401 is used to determine the SOC change based on the voltage and current data of the battery cell to be processed.

[0116] The estimation module 402 is used to determine the estimated SOC value based on the SOC change and the initial SOC value.

[0117] The correction module 403 is used to perform interpolation calculations using a preset open-circuit voltage mapping table and a preset dynamic internal resistance mapping table if the cell to be processed is in a plateau period, to obtain a first correction value and a second correction value.

[0118] The target module 404 is used to determine a target SOC value based on the estimated SOC value, the first correction value, and the second correction value.

[0119] The lithium iron phosphate battery SOC correction device provided in this application, employing the lithium iron phosphate battery SOC correction method described in the above embodiments, can solve the technical problem of how to improve the accuracy of lithium iron phosphate battery SOC estimation. Compared with the prior art, the beneficial effects of the lithium iron phosphate battery SOC correction device provided in this application are the same as those of the lithium iron phosphate battery SOC correction method described in the above embodiments, and other technical features in the lithium iron phosphate battery SOC correction device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0120] This application provides a lithium iron phosphate battery SOC correction device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the lithium iron phosphate battery SOC correction method in the above embodiments.

[0121] The following is for reference. Figure 5This document illustrates a structural schematic diagram suitable for implementing the lithium iron phosphate battery SOC correction device in the embodiments of this application. The lithium iron phosphate battery SOC correction device in the embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 5 The lithium iron phosphate battery SOC correction device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0122] like Figure 5 As shown, the lithium iron phosphate battery SOC correction device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the lithium iron phosphate battery SOC correction device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the lithium iron phosphate battery SOC correction device to communicate wirelessly or wiredly with other devices to exchange data. Although lithium iron phosphate battery SOC correction devices with various systems are shown in the figures, it should be understood that it is not required to implement or possess all the systems shown. More or fewer systems can be implemented alternatively.

[0123] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0124] The lithium iron phosphate battery SOC correction device provided in this application, employing the lithium iron phosphate battery SOC correction method described in the above embodiments, can solve the technical problem of how to improve the accuracy of lithium iron phosphate battery SOC estimation. Compared with the prior art, the beneficial effects of the lithium iron phosphate battery SOC correction device provided in this application are the same as those of the lithium iron phosphate battery SOC correction method provided in the above embodiments, and other technical features in this lithium iron phosphate battery SOC correction device are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0125] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0126] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0127] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the lithium iron phosphate battery SOC correction method in the above embodiments.

[0128] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof. The aforementioned computer-readable storage medium may be included in the lithium iron phosphate battery SOC correction device; or it may exist independently and not assembled into the lithium iron phosphate battery SOC correction device.

[0129] The aforementioned computer-readable storage medium carries one or more programs. When these programs are executed by the lithium iron phosphate battery SOC correction device, the lithium iron phosphate battery SOC correction device: determines the SOC change based on the voltage and current data of the cell to be processed; determines an estimated SOC value based on the SOC change and the initial SOC value; if the cell to be processed is in a plateau period, performs interpolation calculations using a preset open-circuit voltage mapping table and a preset dynamic internal resistance mapping table to obtain a first correction value and a second correction value; and determines a target SOC value based on the estimated SOC value, the first correction value, and the second correction value. Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof. These programming languages ​​include object-oriented programming languages—such as Java, Smalltalk, and C++—and conventional procedural programming languages—such as C or similar programming languages. The program code can be executed entirely on a user's computer, partially on a user's computer, as a standalone software package, partially on a user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer through any type of network—including a local area network (LAN) or a wide area network (WAN)—or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0130] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0131] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0132] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described lithium iron phosphate battery SOC correction method, thereby solving the technical problem of how to improve the accuracy of lithium iron phosphate battery SOC estimation. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the lithium iron phosphate battery SOC correction method provided in the above embodiments, and will not be repeated here.

[0133] This application provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the lithium iron phosphate battery SOC correction method described above.

[0134] The computer program product provided in this application can solve the technical problem of how to improve the SOC estimation accuracy of lithium iron phosphate batteries. Compared with the prior art, the beneficial effects of the computer program product provided in the embodiments of this application are the same as the beneficial effects of the lithium iron phosphate battery SOC correction method provided in the above embodiments, and will not be repeated here.

[0135] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent scope of this application.

Claims

1. A method for correcting the state of charge (SOC) of a lithium iron phosphate battery, characterized in that, The method includes: Determine the SOC change based on the voltage and current data of the battery cell to be processed; Based on the change in SOC and the initial SOC value, determine the estimated SOC value; Based on the voltage data and the current data, determine the voltage and current changes of the battery cell to be processed; Acquire the temperature data of the battery cell to be processed, and determine the temperature change of the battery cell to be processed based on the temperature data; Based on the voltage change, current change, and temperature change, determine whether the battery cell to be processed is in a plateau period; If the cell to be processed is in a plateau period, interpolation calculation is performed using a preset open-circuit voltage mapping table and a preset dynamic internal resistance mapping table to obtain a first correction value and a second correction value. Determine whether the difference between the estimated SOC value, the first corrected value, and the second corrected value exceeds a preset difference threshold. If not, based on the first preset weighting rule, the estimated SOC value, the first corrected value, and the second corrected value are weighted and summed to obtain the target SOC value; If the cell to be processed is not in a plateau period, the target SOC value is obtained by weighted summation of the estimated SOC value, the first correction value, and the second correction value based on the second preset weighting rule; wherein, the weight corresponding to the estimated SOC value in the second preset weighting rule is greater than the weight corresponding to the estimated SOC value in the first preset weighting rule.

2. The method as described in claim 1, characterized in that, The step of obtaining a first correction value and a second correction value by interpolation calculation using a preset open-circuit voltage mapping table and a preset dynamic internal resistance mapping table if the cell to be processed is in a plateau period includes: Based on the current temperature of the cell to be processed, the open-circuit voltage mapping table corresponding to the preset open-circuit voltage mapping table set is selected as the first correction table; Based on the first correction table, the SOC estimate is interpolated to obtain the first correction value; Based on the current temperature and current charge / discharge rate of the cell to be processed, the dynamic internal resistance mapping table corresponding to the preset dynamic internal resistance mapping table set is selected as the second correction table. Based on the second correction table, the estimated SOC value is interpolated to obtain the second correction value.

3. The method as described in claim 1, characterized in that, After the step of determining the target SOC value based on the SOC estimate, the first correction value, and the second correction value, the method further includes: The target SOC value is verified based on a preset SOC range standard. If the verification is successful, the current SOC state of the cell to be processed is updated based on the target SOC value.

4. A lithium iron phosphate battery SOC correction device, characterized in that, The device includes: The preliminary module is used to determine the SOC change based on the voltage and current data of the battery cell to be processed; The estimation module is used to determine the estimated SOC value based on the SOC change and the initial SOC value. The correction module is used to determine the voltage and current changes of the cell to be processed based on the voltage and current data, acquire the temperature data of the cell to be processed, determine the temperature changes of the cell to be processed based on the temperature data, and determine whether the cell to be processed is in a plateau period based on the voltage, current, and temperature changes. If the cell to be processed is in a plateau period, the module performs interpolation calculations using a preset open-circuit voltage mapping table and a preset dynamic internal resistance mapping table to obtain a first correction value and a second correction value. The target module is used to determine whether the difference between the estimated SOC value, the first corrected value, and the second corrected value exceeds a preset difference threshold; if not, based on a first preset weighting rule, the estimated SOC value, the first corrected value, and the second corrected value are weighted and summed to obtain a target SOC value; if the cell to be processed is not in a plateau period, based on a second preset weighting rule, the estimated SOC value, the first corrected value, and the second corrected value are weighted and summed to obtain the target SOC value; wherein, the weight corresponding to the estimated SOC value in the second preset weighting rule is greater than the weight corresponding to the estimated SOC value in the first preset weighting rule.

5. A computer device, characterized in that, The device includes: a memory, a processor, and a lithium iron phosphate battery SOC correction program stored in the memory and executable on the processor, the lithium iron phosphate battery SOC correction program being configured to implement the steps of the lithium iron phosphate battery SOC correction method as described in any one of claims 1 to 3.

6. A storage medium, characterized in that, The storage medium stores a lithium iron phosphate battery SOC correction program, which, when executed by a processor, implements the steps of the lithium iron phosphate battery SOC correction method as described in any one of claims 1 to 3.

7. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the steps of the lithium iron phosphate battery SOC correction method as described in any one of claims 1 to 3.

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