Calibration method and device for state of charge of lithium battery, computer device and program product

Abstract

The application relates to a lithium battery state of charge calibration method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: obtaining a state of charge value of a lithium battery system; in the case that the state of charge value is less than a preset threshold value, performing a charging process on the lithium battery system until the lithium battery system reaches a full charging state; based on an external load of the lithium battery system, performing a discharging process on the lithium battery system until the state of charge value of the lithium battery system returns to the preset threshold value; in the charging and discharging process of the lithium battery system, real-time acquisition of voltage data, current data and time data of the lithium battery system; based on the voltage data, the current data and the time data, determining actual capacity parameters and internal resistance parameters of the lithium battery system. The method can improve the accuracy of lithium battery state of charge calibration.

Description

Technical Field

[0001] This application relates to the field of state of charge calibration technology, and in particular to a method, apparatus, computer equipment, computer-readable storage medium, and computer program product for calibrating the state of charge of a lithium battery. Background Technology

[0002] Hydrogen fuel cell power generation technology is an important direction for achieving efficient use of clean energy, especially in off-grid scenarios (such as in the wild or isolated areas) with broad application prospects. In such systems, lithium-ion batteries undertake key functions such as high voltage establishment, power replenishment, and energy recovery, and are an important component to ensure the stable operation of the power generation system.

[0003] However, after prolonged charging and discharging, the cell voltage consistency of lithium batteries decreases, causing the state of charge (SOC) estimated by the battery management system (BMS) to gradually deviate from the actual value, resulting in the "false SOC" problem. If the SOC estimation is inaccurate, the BMS may misjudge the battery status and trigger protection, causing the power generation system to fail to start or to shut down.

[0004] In related technologies, calibrating the SOC of lithium batteries in off-grid mode usually relies on external mains power to fully charge them. However, this is difficult to achieve in scenarios without mains power, such as isolated islands or remote areas. Existing technologies lack effective online automatic calibration methods, which limits the reliability and application scope of hydrogen fuel cell power generation equipment. Summary of the Invention

[0005] Therefore, it is necessary to provide a method, apparatus, computer equipment, computer-readable storage medium, and computer program product for calibrating the state of charge (SOC) of lithium batteries, which can improve the reliability of SOC calibration, in order to address the above-mentioned technical problems.

[0006] Firstly, this application provides a method for calibrating the state of charge of a lithium battery, comprising:

[0007] Obtain the state of charge (SOC) value of the lithium battery system;

[0008] If the state of charge value is less than a preset threshold, the lithium battery system is charged until the lithium battery system reaches a fully charged state.

[0009] Based on the external load of the lithium battery system, the lithium battery system is discharged until the state of charge value of the lithium battery system returns to the preset threshold.

[0010] During the charging and discharging process of the lithium battery system, the voltage data, current data and time data of the lithium battery system are collected in real time.

[0011] Based on the voltage data, the current data, and the time data, the actual capacity parameters and internal resistance parameters of the lithium battery system are determined.

[0012] In one embodiment, discharging the lithium battery system based on an external load includes:

[0013] Determine the output power of the lithium battery system corresponding to the hydrogen fuel cell power generation system and the requested power of the external load; the hydrogen fuel cell power generation system includes a lithium battery system and a hydrogen fuel cell system;

[0014] Before the output power reaches the requested power of the external load, the external load is discharged based on the lithium battery system;

[0015] When the output power matches the requested power of the external load, the control state of the lithium battery system is switched to float charging state, and the external load is discharged based on the lithium battery load and the hydrogen fuel power generation system.

[0016] In one embodiment, determining the internal resistance parameter based on the voltage data, the current data, and the time data includes:

[0017] Based on the voltage data and the current data, the voltage and current signals of the lithium battery system under different states of charge are determined;

[0018] For each state of charge of the lithium battery system, the voltage change and current change within a preset time window are extracted;

[0019] The ratio between the voltage change and the current change is used as the DC internal resistance value of the lithium battery system under the corresponding state of charge.

[0020] Data fitting was performed on the state of charge values ​​and DC internal resistance values ​​under all states of charge to determine the internal resistance parameters of the lithium battery system.

[0021] In one embodiment, determining the actual capacity parameters based on the voltage data, the current data, and the time data further includes:

[0022] The current data is converted into a discrete current sampling sequence, and based on the time data, a corresponding timestamp is marked for each current sampling value in the current sampling sequence.

[0023] The total charge is obtained by integrating the current sampling sequence during the charging process of the lithium battery system.

[0024] The total discharge charge is obtained by integrating the current sampling sequence during the discharge process of the lithium battery system.

[0025] Calculate the first ratio between the total charging charge and the sample capacity, and the second ratio between the total discharging charge and the sample capacity;

[0026] If both the first ratio and the second ratio are within a preset error range, the average value of the total charging charge and the total discharging charge is taken as the actual capacity parameter of the lithium battery system.

[0027] In one embodiment, the method further includes:

[0028] Obtain the internal cell temperature of the lithium battery system;

[0029] A fault warning will be issued if at least one of the internal cell temperature, voltage data, or current data exceeds a preset safety range.

[0030] In one embodiment, the method further includes:

[0031] The system receives a result display instruction sent by the user and visualizes the actual capacity parameter and the internal resistance parameter based on the result display instruction.

[0032] Secondly, this application also provides a calibration device for the state of charge of a lithium battery, comprising:

[0033] The acquisition module is used to acquire the state of charge (SOC) value of the lithium battery system.

[0034] The charging module is used to charge the lithium battery system when the state of charge value is less than a preset threshold until the lithium battery system reaches a fully charged state.

[0035] The discharge module is used to discharge the lithium battery system based on the external load of the lithium battery system until the state of charge value of the lithium battery system returns to a preset threshold.

[0036] The data acquisition module is used to acquire voltage data, current data and time data of the lithium battery system in real time during the charging and discharging process of the lithium battery system.

[0037] The determination module is used to determine the actual capacity parameters and internal resistance parameters of the lithium battery system based on the voltage data, the current data, and the time data.

[0038] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0039] Obtain the state of charge (SOC) value of the lithium battery system;

[0040] If the state of charge value is less than a preset threshold, the lithium battery system is charged until the lithium battery system reaches a fully charged state.

[0041] Based on the external load of the lithium battery system, the lithium battery system is discharged until the state of charge value of the lithium battery system returns to the preset threshold.

[0042] During the charging and discharging process of the lithium battery system, the voltage data, current data and time data of the lithium battery system are collected in real time.

[0043] Based on the voltage data, the current data, and the time data, the actual capacity parameters and internal resistance parameters of the lithium battery system are determined.

[0044] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0045] Obtain the state of charge (SOC) value of the lithium battery system;

[0046] If the state of charge value is less than a preset threshold, the lithium battery system is charged until the lithium battery system reaches a fully charged state.

[0047] Based on the external load of the lithium battery system, the lithium battery system is discharged until the state of charge value of the lithium battery system returns to the preset threshold.

[0048] During the charging and discharging process of the lithium battery system, the voltage data, current data and time data of the lithium battery system are collected in real time.

[0049] Based on the voltage data, the current data, and the time data, the actual capacity parameters and internal resistance parameters of the lithium battery system are determined.

[0050] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0051] Obtain the state of charge (SOC) value of the lithium battery system;

[0052] If the state of charge value is less than a preset threshold, the lithium battery system is charged until the lithium battery system reaches a fully charged state.

[0053] Based on the external load of the lithium battery system, the lithium battery system is discharged until the state of charge value of the lithium battery system returns to the preset threshold.

[0054] During the charging and discharging process of the lithium battery system, the voltage data, current data and time data of the lithium battery system are collected in real time.

[0055] Based on the voltage data, the current data, and the time data, the actual capacity parameters and internal resistance parameters of the lithium battery system are determined.

[0056] The aforementioned method, apparatus, computer equipment, computer-readable storage medium, and computer program product for calibrating the state of charge (SOC) of lithium batteries first acquire the SOC value of the lithium battery system; if the SOC value is less than a preset threshold, the lithium battery system is charged until it reaches full charge; based on an external load, the lithium battery system is discharged until the SOC value returns to the preset threshold; during the charging and discharging process, voltage, current, and time data of the lithium battery system are collected in real time; based on the voltage, current, and time data, the actual capacity and internal resistance parameters of the lithium battery system are determined. Thus, by acquiring the SOC value of the lithium battery system and triggering a full charge-discharge cycle when it falls below a preset threshold, and by collecting voltage, current, and time data in real time throughout the charging and discharging process to determine the actual capacity and internal resistance parameters, online automatic calibration of the SOC of a lithium battery system in off-grid mode is achieved. Attached Figure Description

[0057] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0058] Figure 1 This is an application environment diagram of a lithium battery state of charge calibration method in one embodiment;

[0059] Figure 2 This is a flowchart illustrating a method for calibrating the state of charge of a lithium battery in one embodiment.

[0060] Figure 3 This is a schematic diagram of the structure of a hydrogen fuel power generation system in one embodiment;

[0061] Figure 4 This is a structural block diagram of a lithium battery state of charge calibration device in one embodiment;

[0062] Figure 5 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0063] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0064] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0065] The lithium battery state-of-charge calibration method provided in this application embodiment can be applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104 or located in the cloud or on other network servers. Terminal 102 can be, but is not limited to, various IoT devices and portable wearable devices. IoT devices can be smart vehicle devices, etc. Portable wearable devices can be head-mounted devices, etc. Head-mounted devices can be virtual reality (VR) devices, augmented reality (AR) devices, smart glasses, etc. Server 104 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0066] In one exemplary embodiment, such as Figure 2 As shown, a method for calibrating the state of charge of a lithium battery is provided, which can be applied to... Figure 1 Taking terminal 102 as an example, the explanation includes the following steps 202 to 210. Wherein:

[0067] Step 202: Obtain the state of charge (SOC) value of the lithium battery system.

[0068] The hydrogen fuel cell power generation system in the terminal includes a lithium battery system and a hydrogen fuel cell system, as shown in the schematic diagram below. Figure 3As shown, the hydrogen fuel cell power generation system and the lithium battery system are connected in parallel to the external load via a DC bus.

[0069] For example, the state of charge (SOC) value of the lithium battery system is collected through the FCU (Fuel Cell Control Unit) in the hydrogen fuel cell system.

[0070] Step 204: If the state of charge value is less than a preset threshold, charge the lithium battery system until the lithium battery system reaches a fully charged state.

[0071] Among them, the fully charged state refers to the state of charge of the lithium battery system reaching 100% under specific charging conditions.

[0072] Optionally, if the state of charge of the lithium battery system is less than a preset threshold (e.g., 20%), the lithium battery system is charged until it reaches full charge.

[0073] Step 206: Based on the external load of the lithium battery system, discharge the lithium battery system until the state of charge of the lithium battery system returns to the preset threshold.

[0074] External loads are electrical equipment or units that are connected to the hydrogen fuel cell system and lithium battery system and consume output electrical energy.

[0075] For example, the lithium battery system is discharged by an external load until the state of charge of the lithium battery system returns to a preset threshold.

[0076] Step 208: During the charging and discharging process of the lithium battery system, collect the voltage data, current data, and time data of the lithium battery system in real time.

[0077] Optionally, a full charge and discharge cycle of the lithium battery is considered as one complete cycle. During a single cycle, the voltage, current, and time data of the lithium battery system are collected in real time.

[0078] Step 210: Based on voltage data, current data, and time data, determine the actual capacity parameters and internal resistance parameters of the lithium battery system.

[0079] For example, based on voltage data, current data, and time data, the actual capacity parameters and internal resistance parameters of the lithium battery system are determined, and the state of charge of the lithium battery is calibrated.

[0080] The aforementioned method for calibrating the state of charge (SOC) of a lithium battery involves: acquiring the SOC value of the lithium battery system; charging the lithium battery system until it reaches full charge when the SOC value is below a preset threshold; discharging the lithium battery system based on an external load until the SOC value returns to the preset threshold; collecting voltage, current, and time data in real time during the charging and discharging processes; and determining the actual capacity and internal resistance parameters of the lithium battery system based on the voltage, current, and time data. Thus, by acquiring the SOC value of the lithium battery system and triggering a full charge-discharge cycle when it falls below a preset threshold, and collecting voltage, current, and time data in real time throughout the charging and discharging process to determine the actual capacity and internal resistance parameters, online automatic calibration of the SOC of a lithium battery system in off-grid mode is achieved.

[0081] In an exemplary embodiment, discharging the lithium battery system based on an external load includes: determining the output power of the lithium battery system corresponding to a hydrogen fuel cell power generation system and the requested power of the external load; the hydrogen fuel cell power generation system includes a lithium battery system and a hydrogen fuel cell system; discharging the external load based on the lithium battery system before the output power reaches the requested power of the external load; and switching the control state of the lithium battery system to a float charge state when the output power matches the requested power of the external load, and discharging the external load based on the lithium battery load and the hydrogen fuel cell power generation system.

[0082] In practical implementation, the output power of the lithium battery system corresponding to the hydrogen fuel cell power generation system and the requested power of the external load are determined; the hydrogen fuel cell power generation system includes a lithium battery system and a hydrogen fuel cell system; before the output power reaches the requested power of the external load, the external load is discharged based on the lithium battery system; when the output power matches the requested power of the external load, the control state of the lithium battery system is switched to float charging state, and the external load is discharged based on the lithium battery load and the hydrogen fuel cell power generation system.

[0083] In the above embodiments, by monitoring and comparing the real-time output power of the hydrogen fuel cell system with the requested power of the external load, the lithium battery system is controlled to discharge for the external load first before the output power of the hydrogen fuel cell system reaches the requested power. This compensates for the technical defects of slow start-up and lag in dynamic response of the hydrogen fuel cell system, achieving millisecond-level response to load power demand and avoiding the risk of load power loss or system shutdown due to power gap. At the same time, after the output power of the hydrogen fuel cell system fully matches the requested power, the lithium battery system is immediately switched to float charging state, and the hydrogen fuel cell system alone undertakes the entire load power. This allows the lithium battery system to exit the deep discharge state and return to full charge standby in a timely manner after completing the discharge calibration task. This avoids unnecessary continuous deep discharge of the lithium battery and ensures that the lithium battery system always maintains sufficient reserve capacity to cope with power supplementation or energy recovery needs under conditions such as load changes and fuel cell load reduction.

[0084] In an exemplary embodiment, determining the internal resistance parameter based on voltage data, current data, and time data includes: determining the voltage and current signals of the lithium battery system under different states of charge based on the voltage and current data; extracting the voltage and current changes within a preset time window for each state of charge of the lithium battery system; using the ratio between the voltage and current changes as the DC internal resistance value of the lithium battery system under the corresponding state of charge; performing data fitting on the state of charge values ​​and DC internal resistance values ​​under all states of charge, and determining the internal resistance parameter of the lithium battery system.

[0085] In practical implementation, based on voltage and current data, the voltage and current signals of the lithium battery system under different states of charge are determined. For each state of charge of the lithium battery system, the voltage and current changes within a preset time window are extracted. The ratio between the voltage and current changes is used as the DC internal resistance value of the lithium battery system under the corresponding state of charge, as shown in the following formula:

[0086] R=△U / △I

[0087] Where R is the DC internal resistance, ΔU is the voltage change, and ΔI is the current change.

[0088] Data fitting was performed on the state of charge (SOC) values ​​and DC internal resistance values ​​under all states of charge to determine the internal resistance parameters of the lithium battery system.

[0089] In the above embodiments, by continuously acquiring voltage and current signals at different states of charge (SOC) during the full charge and discharge cycle of the lithium battery system, and extracting the voltage and current changes within a preset time window for each SOC, the ratio of the two is used as the DC internal resistance value under that SOC. This achieves complete acquisition of the internal resistance distribution characteristics of the lithium battery system across the entire SOC range (from 100% to a preset threshold). Based on this, data fitting is performed on the DC internal resistance values ​​corresponding to all SOC nodes, which can identify the ohmic internal resistance component and the dynamic polarization internal resistance component of the lithium battery system in different SOC ranges at once. Compared with traditional technologies that only estimate the internal resistance at a single SOC point (such as 50% SOC) or rely solely on factory-fixed parameters, this invention effectively avoids the technical defect that single-point measurement is difficult to characterize the internal resistance characteristics of the battery under all operating conditions.

[0090] In an exemplary embodiment, determining the actual capacity parameter based on voltage data, current data, and time data further includes: converting the current data into a discrete current sampling sequence, and labeling each current sampling value in the current sampling sequence with a corresponding timestamp based on the time data; integrating the current sampling sequence during the charging process of the lithium battery system to obtain the total charging charge; integrating the current sampling sequence during the discharging process of the lithium battery system to obtain the total discharging charge; calculating a first ratio between the total charging charge and the sample capacity, and a second ratio between the total discharging charge and the sample capacity; and, if both the first ratio and the second ratio are within a preset error range, using the average of the total charging charge and the total discharging charge as the actual capacity parameter of the lithium battery system.

[0091] In practical implementation, the current data is converted into a discrete current sampling sequence, and based on the time data, a corresponding timestamp is marked for each current sampling value in the current sampling sequence; the current sampling sequence during the charging process of the lithium battery system is integrated to obtain the total charging charge; the current sampling sequence during the discharging process of the lithium battery system is integrated to obtain the total discharging charge.

[0092] The formula for calculating the total charge is as follows:

[0093]

[0094] Where C is the total charge, which can be either the total discharge charge or the total charge during charging.

[0095] Calculate the first ratio between the total charge and the sample capacity, and the second ratio between the total discharge and the sample capacity; if both the first and second ratios are within the preset error range, use the average of the total charge and the total discharge as the actual capacity parameter of the lithium battery system.

[0096] In the above embodiments, the current signal of the lithium battery system throughout the charging and discharging process is discretized and timestamped for each sample value. The current sampling sequences of the charging and discharging processes are independently integrated to obtain the total charging charge and the total discharging charge. The average of the total charging charge and the total discharging charge is used as the actual capacity parameter only when the ratios of both to the nominal capacity are within a preset error range. This scheme effectively eliminates the systematic deviations introduced by unidirectional measurement due to current sensor zero-point drift, integration start-point error, or insufficient charging and discharging in bidirectional measurement through bidirectional independent measurement and cross-verification. It ensures that calibration data is adopted only when the measurement results of the charging side and the discharging side corroborate each other. At the same time, the bidirectional result averaging reduces the impact of random measurement noise on capacity estimation, avoiding the risk of further deterioration of SOC estimation due to updating capacity parameters based on erroneous data. This enables the battery management system to obtain accurate and reliable actual effective capacity values. After replacing the original capacity benchmark value in the SOC estimation model, it significantly improves the long-term estimation accuracy of SOC in off-grid mode, ensuring the long-term stable operation of the hydrogen fuel cell power generation system in isolated, field, and other grid-free scenarios.

[0097] In one exemplary embodiment, the method further includes: acquiring the internal cell temperature of the lithium battery system; and issuing a fault warning when at least one of the internal cell temperature, voltage data, or current data exceeds a preset safety range.

[0098] In practical implementation, the internal cell temperature of the lithium battery system is obtained; if at least one of the internal cell temperature, voltage data, or current data exceeds the preset safety range, a fault warning is issued.

[0099] In the above embodiments, by acquiring internal cell temperature, voltage, and current data in real time during the full charge-discharge cycle of the lithium battery system, and immediately issuing a fault warning when at least one of the internal cell temperature, voltage, or current data exceeds a preset safety range, real-time monitoring and proactive protection of the multi-dimensional safety status of the lithium battery system throughout the charging and discharging process are achieved. This solution, through cross-monitoring of the three physical parameters of temperature, voltage, and current, can promptly detect and warn of various fault precursors such as over-temperature, over-voltage, under-voltage, and over-current, effectively preventing the continued deterioration of the fault state from leading to serious consequences such as thermal runaway, cell damage, or system shutdown.

[0100] In an exemplary embodiment, the method further includes: receiving a result display instruction sent by a user, and visually displaying the actual capacity parameters and internal resistance parameters based on the result display instruction.

[0101] In actual implementation, the system receives result display instructions sent by users and visualizes the actual capacity parameters and internal resistance parameters based on these instructions.

[0102] In the above embodiments, by receiving the result display command sent by the user and visually displaying the actual capacity parameters and internal resistance parameters based on the command, the intuitive presentation and human-computer interaction of the health status information of the lithium battery system are realized. This solution enables maintenance personnel to directly view the internal resistance-state of charge characteristic curve, the historical trend chart of the actual capacity parameters, and the historical trend chart of the internal resistance parameters after the current full charge-discharge cycle update through the human-computer interaction interface. Different colors or line types are used to distinguish the updated data from historical data, which facilitates the rapid identification of the capacity decay trend and internal resistance aging degree of the lithium battery system. This overcomes the cumbersome operation in the prior art where maintenance personnel need to export data through dedicated host computer software and then draw charts separately.

[0103] To illustrate the calibration method for the state of charge of a lithium battery in this application in detail, an embodiment is described below. For example, this application describes a calibration method for the state of charge of a lithium battery in a specific scenario.

[0104] First, the state of charge (SOC) value of the lithium battery system is collected through the FCU (Fuel Cell Control Unit) in the hydrogen fuel cell system. If the SOC value of the lithium battery system is lower than a preset threshold (e.g., 20%), the lithium battery system is charged until it reaches a fully charged state.

[0105] The lithium battery system is discharged using an external load until its state of charge (SOC) returns to a preset threshold. One full charge-discharge cycle is considered complete. During each cycle, voltage, current, and time data of the lithium battery system are collected in real time.

[0106] Based on voltage, current, and time data, the actual capacity and internal resistance parameters of the lithium battery system are determined, and the state of charge of the lithium battery is calibrated.

[0107] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0108] Based on the same inventive concept, this application also provides a lithium battery state of charge calibration apparatus for implementing the above-described lithium battery state of charge calibration method. The solution provided by this apparatus is similar to the implementation described in the above method; therefore, the specific limitations of one or more lithium battery state of charge calibration apparatus embodiments provided below can be found in the limitations of the lithium battery state of charge calibration method described above, and will not be repeated here.

[0109] In one exemplary embodiment, such as Figure 4 As shown, a calibration device for the state of charge of a lithium battery is provided, comprising: an acquisition module 401, a charging module 402, a discharging module 403, a data acquisition module 404, and a determination module 405, wherein:

[0110] The acquisition module is used to acquire the state of charge (SOC) value of the lithium battery system.

[0111] The charging module is used to charge the lithium battery system when the state of charge value is less than a preset threshold until the lithium battery system reaches a fully charged state.

[0112] The discharge module is used to discharge the lithium battery system based on the external load of the lithium battery system until the state of charge value of the lithium battery system returns to a preset threshold.

[0113] The acquisition module is used to acquire voltage data, current data, and time data of the lithium battery system in real time during the charging and discharging process.

[0114] The determination module is used to determine the actual capacity parameters and internal resistance parameters of the lithium battery system based on the voltage data, the current data, and the time data.

[0115] In some exemplary embodiments, the discharge module described above is further used for:

[0116] Determine the output power of the lithium battery system corresponding to the hydrogen fuel cell power generation system and the requested power of the external load; the hydrogen fuel cell power generation system includes a lithium battery system and a hydrogen fuel cell system;

[0117] Before the output power reaches the requested power of the external load, the external load is discharged based on the lithium battery system;

[0118] When the output power matches the requested power of the external load, the control state of the lithium battery system is switched to float charging state, and the external load is discharged based on the lithium battery load and the hydrogen fuel power generation system.

[0119] In some exemplary embodiments, the determining module described above is further configured to:

[0120] Based on voltage and current data, the voltage and current signals of the lithium battery system under different states of charge are determined;

[0121] For each state of charge of the lithium battery system, extract the voltage and current changes within a preset time window;

[0122] The ratio between the voltage change and the current change is used as the DC internal resistance value of the lithium battery system under the corresponding state of charge.

[0123] Data fitting was performed on the state of charge (SOC) values ​​and DC internal resistance values ​​under all states of charge to determine the internal resistance parameters of the lithium battery system.

[0124] In some exemplary embodiments, the determining module described above is further configured to:

[0125] The current data is converted into a discrete current sampling sequence, and based on the time data, a timestamp is marked for each current sampling value in the current sampling sequence.

[0126] The total charge is obtained by integrating the current sampling sequence during the charging process of the lithium battery system.

[0127] The total discharge charge is obtained by integrating the current sampling sequence during the discharge process of the lithium battery system.

[0128] Calculate the first ratio between the total charge during charging and the sample size, and the second ratio between the total charge during discharging and the sample size;

[0129] If both the first ratio and the second ratio are within the preset error range, the average value of the total charging charge and the total discharging charge is taken as the actual capacity parameter of the lithium battery system.

[0130] In some exemplary embodiments, the above-described apparatus further includes a warning module for:

[0131] To obtain the internal cell temperature of a lithium battery system;

[0132] A fault warning will be issued if at least one of the internal cell temperature, voltage, or current data exceeds the preset safety range.

[0133] In some exemplary embodiments, the above-described apparatus further includes a display module for:

[0134] It receives the result display command sent by the user and visualizes the actual capacity parameters and internal resistance parameters based on the result display command.

[0135] Each module in the aforementioned lithium battery state of charge calibration device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0136] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 5 As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When executed by the processor, the computer program implements a method for calibrating the state of charge of a lithium battery.

[0137] The display unit of this computer device is used to form a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of this computer device can be a touch layer covering the display screen, or buttons, a trackball, or a touchpad set on the casing of the computer device, or an external keyboard, touchpad, or mouse, etc.

[0138] Those skilled in the art will understand that Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0139] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0140] Obtain the state of charge (SOC) value of the lithium battery system;

[0141] If the state of charge value is less than a preset threshold, the lithium battery system is charged until the lithium battery system reaches a fully charged state.

[0142] Based on the external load of the lithium battery system, the lithium battery system is discharged until the state of charge value of the lithium battery system returns to the preset threshold.

[0143] During the charging and discharging process of the lithium battery system, the voltage data, current data and time data of the lithium battery system are collected in real time.

[0144] Based on the voltage data, the current data, and the time data, the actual capacity parameters and internal resistance parameters of the lithium battery system are determined.

[0145] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0146] Obtain the state of charge (SOC) value of the lithium battery system;

[0147] If the state of charge value is less than a preset threshold, the lithium battery system is charged until the lithium battery system reaches a fully charged state.

[0148] Based on the external load of the lithium battery system, the lithium battery system is discharged until the state of charge value of the lithium battery system returns to the preset threshold.

[0149] During the charging and discharging process of the lithium battery system, the voltage data, current data and time data of the lithium battery system are collected in real time.

[0150] Based on the voltage data, the current data, and the time data, the actual capacity parameters and internal resistance parameters of the lithium battery system are determined.

[0151] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0152] Obtain the state of charge (SOC) value of the lithium battery system;

[0153] If the state of charge value is less than a preset threshold, the lithium battery system is charged until the lithium battery system reaches a fully charged state.

[0154] Based on the external load of the lithium battery system, the lithium battery system is discharged until the state of charge value of the lithium battery system returns to the preset threshold.

[0155] During the charging and discharging process of the lithium battery system, the voltage data, current data and time data of the lithium battery system are collected in real time.

[0156] Based on the voltage data, the current data, and the time data, the actual capacity parameters and internal resistance parameters of the lithium battery system are determined.

[0157] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0158] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0159] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0160] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for calibrating the state of charge of a lithium battery, characterized in that, The method includes: Obtain the state of charge (SOC) value of the lithium battery system; If the state of charge value is less than a preset threshold, the lithium battery system is charged until the lithium battery system reaches a fully charged state. Based on the external load of the lithium battery system, the lithium battery system is discharged until the state of charge of the lithium battery system returns to the preset threshold. During the charging and discharging process of the lithium battery system, the voltage data, current data and time data of the lithium battery system are collected in real time. Based on the voltage data, the current data, and the time data, the actual capacity parameters and internal resistance parameters of the lithium battery system are determined.

2. The method according to claim 1, characterized in that, The discharge process of the lithium battery system based on the external load of the lithium battery system includes: Determine the output power of the lithium battery system corresponding to the hydrogen fuel cell power generation system and the requested power of the external load; the hydrogen fuel cell power generation system includes a lithium battery system and a hydrogen fuel cell system; Before the output power reaches the requested power of the external load, the external load is discharged based on the lithium battery system; When the output power matches the requested power of the external load, the control state of the lithium battery system is switched to float charging state, and the external load is discharged based on the lithium battery load and the hydrogen fuel power generation system.

3. The method according to claim 1, characterized in that, Based on the voltage data, the current data, and the time data, the internal resistance parameter is determined, including: Based on the voltage data and the current data, the voltage and current signals of the lithium battery system under different states of charge are determined; For each state of charge of the lithium battery system, the voltage and current changes within a preset time window are extracted. The ratio between the voltage change and the current change is used as the DC internal resistance value of the lithium battery system under the corresponding state of charge. Data fitting was performed on the state of charge values ​​and DC internal resistance values ​​under all states of charge to determine the internal resistance parameters of the lithium battery system.

4. The method according to claim 1, characterized in that, Determining the actual capacity parameters based on the voltage data, the current data, and the time data further includes: The current data is converted into a discrete current sampling sequence, and based on the time data, a corresponding timestamp is marked for each current sampling value in the current sampling sequence. The total charge is obtained by integrating the current sampling sequence during the charging process of the lithium battery system. The total discharge charge is obtained by integrating the current sampling sequence during the discharge process of the lithium battery system. Calculate the first ratio between the total charging charge and the sample capacity, and the second ratio between the total discharging charge and the sample capacity; If both the first ratio and the second ratio are within a preset error range, the average value of the total charging charge and the total discharging charge is taken as the actual capacity parameter of the lithium battery system.

5. The method according to claim 1, characterized in that, The method further includes: Obtain the internal cell temperature of the lithium battery system; A fault warning will be issued if at least one of the internal cell temperature, voltage data, or current data exceeds a preset safety range.

6. The method according to claim 1, characterized in that, The method further includes: The system receives a result display instruction sent by the user and visualizes the actual capacity parameter and the internal resistance parameter based on the result display instruction.

7. A calibration device for the state of charge of a lithium battery, characterized in that, The device includes: The acquisition module is used to acquire the state of charge (SOC) value of the lithium battery system. The charging module is used to charge the lithium battery system when the state of charge value is less than a preset threshold until the lithium battery system reaches a fully charged state. The discharge module is used to discharge the lithium battery system based on the external load of the lithium battery system until the state of charge value of the lithium battery system returns to a preset threshold. The data acquisition module is used to acquire voltage data, current data and time data of the lithium battery system in real time during the charging and discharging process of the lithium battery system. The determination module is used to determine the actual capacity parameters and internal resistance parameters of the lithium battery system based on the voltage data, the current data, and the time data.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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