Reference electrode signal correction method, device, equipment, medium and program product

Abstract

The application relates to a reference electrode signal correction method, device, equipment, medium and program product. The method comprises the following steps: acquiring a reference electrode signal of a target battery in a cycle process; in the case that the reference electrode signal is detected to drift, acquiring platform potential characteristic values in multiple complete cycles before the drift occurs; based on the platform potential characteristic values, performing correction processing on the reference electrode signal collected in an abnormal cycle where the drift occurs, to obtain a corrected reference electrode signal. The method can improve the accuracy of battery potential measurement.

Description

Technical Field

[0001] This application relates to the field of battery technology, and in particular to a method, apparatus, device, medium, and program product for correcting reference electrode signals. Background Technology

[0002] Lithium-ion batteries, with their high energy density, long cycle life, and excellent rate performance, have been widely used in electric vehicles, energy storage systems, and many other fields. The output voltage information of a battery originates from the potential difference between its positive and negative electrodes. This potential difference not only determines the battery's energy output capability but also directly reflects the battery's operating state.

[0003] Currently, a reference electrode is typically introduced inside the battery to achieve decoupled measurement of positive and negative electrode potentials. However, during long-term cyclic use, the reference electrode is prone to signal drift, causing its measured value to deviate from the true negative electrode potential. This drift not only weakens the accuracy of potential measurement but also limits the stable application of the reference electrode throughout the battery's entire lifespan. Summary of the Invention

[0004] Therefore, it is necessary to provide a reference electrode signal correction method, apparatus, device, medium, and program product that can improve the accuracy of battery potential measurement in response to the above-mentioned technical problems.

[0005] In a first aspect, this application provides a method for correcting a reference electrode signal, comprising:

[0006] Acquire the reference electrode signal of the target battery during cycling;

[0007] When a drift in the reference electrode signal is detected, the plateau potential characteristic values ​​in multiple complete cycles before the drift occurs are obtained;

[0008] Based on the platform potential characteristic value, the reference electrode signal collected in the abnormal cycle where drift occurs is corrected to obtain the corrected reference electrode signal.

[0009] Secondly, this application also provides a reference electrode signal correction device, comprising:

[0010] The signal acquisition module is used to acquire the reference electrode signal of the target battery during cycling.

[0011] The feature value acquisition module is used to acquire the plateau potential feature values ​​in multiple complete cycles before the drift occurs when a drift is detected in the reference electrode signal.

[0012] The correction module is used to correct the reference electrode signal collected in the abnormal cycle where drift occurs based on the platform potential characteristic value, so as to obtain the corrected reference electrode signal.

[0013] 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:

[0014] Acquire the reference electrode signal of the target battery during cycling;

[0015] When a drift in the reference electrode signal is detected, the plateau potential characteristic values ​​in multiple complete cycles before the drift occurs are obtained;

[0016] Based on the platform potential characteristic value, the reference electrode signal collected in the abnormal cycle where drift occurs is corrected to obtain the corrected reference electrode signal.

[0017] 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:

[0018] Acquire the reference electrode signal of the target battery during cycling;

[0019] When a drift in the reference electrode signal is detected, the plateau potential characteristic values ​​in multiple complete cycles before the drift occurs are obtained;

[0020] Based on the platform potential characteristic value, the reference electrode signal collected in the abnormal cycle where drift occurs is corrected to obtain the corrected reference electrode signal.

[0021] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0022] Acquire the reference electrode signal of the target battery during cycling;

[0023] When a drift in the reference electrode signal is detected, the plateau potential characteristic values ​​in multiple complete cycles before the drift occurs are obtained;

[0024] Based on the platform potential characteristic value, the reference electrode signal collected in the abnormal cycle where drift occurs is corrected to obtain the corrected reference electrode signal.

[0025] The aforementioned reference electrode signal correction method, apparatus, device, medium, and program products acquire the reference electrode signal of the target battery during cycling, providing fundamental data support for subsequent potential change trend analysis and anomaly detection. Secondly, when a drift in the reference electrode signal is detected, the reference electrode signal acquired during the abnormal cycle in which the drift occurred is corrected based on the platform potential characteristic value, resulting in a corrected reference electrode signal. This method can effectively correct reference electrode signal drift caused by long-term operation or changes in the electrochemical environment, thereby extending the effective monitoring period of the reference electrode and improving the accuracy of battery potential measurement. Attached Figure Description

[0026] 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.

[0027] Figure 1 This is an internal structural diagram of a computer device in one embodiment;

[0028] Figure 2 This is a flowchart illustrating a reference electrode signal correction method in one embodiment;

[0029] Figure 3 This is a flowchart illustrating the reference electrode signal correction method in another embodiment;

[0030] Figure 4 This is a flowchart illustrating the reference electrode signal correction method in another embodiment;

[0031] Figure 5 This is a flowchart illustrating the reference electrode signal correction method in another embodiment;

[0032] Figure 6 This is a flowchart illustrating the reference electrode signal correction method in another embodiment;

[0033] Figure 7 This is a schematic diagram of the reference electrode signal before correction in one embodiment;

[0034] Figure 8 This is a schematic diagram of the modified reference electrode signal in one embodiment;

[0035] Figure 9 This is a schematic diagram of the reference electrode measured potential at 100% SOC in each cycle after modification in one embodiment;

[0036] Figure 10This is a structural block diagram of a reference electrode signal device in one embodiment. Detailed Implementation

[0037] 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.

[0038] Lithium-ion batteries, as a type of high-performance rechargeable battery, have been widely used in electric vehicles, energy storage systems, and other fields due to their advantages such as high energy density, long cycle life, and excellent rate performance. A lithium-ion battery typically consists of a positive electrode, a negative electrode, an electrolyte, and a separator. The potential difference between the positive and negative electrodes constitutes the battery's terminal voltage, which is the primary driving force for the battery to provide energy and output power.

[0039] In practical applications and research, the potentials of the positive and negative electrodes reflect the electrochemical behavior of the two electrodes of a battery and are intrinsic signals of the battery. Decoupling and measuring these two potentials separately allows for in-depth analysis of key characteristics such as battery performance, aging status, and abnormal reactions. Therefore, achieving independent monitoring of the positive and negative electrode potentials is of great significance for improving battery operating status diagnostic capabilities, extending service life, and optimizing battery system design.

[0040] Reference electrodes are a key technology for achieving decoupled measurement of positive and negative electrode potentials. By introducing a reference electrode into the battery system, a stable reference can be provided for potential measurement, thereby obtaining the potentials of the positive and negative electrodes relative to the reference point. In existing technologies, reference electrodes have been successfully used for current calibration during fast charging, lithium plating risk identification, monitoring of positive and negative electrode electrochemical processes, overcharge / over-discharge diagnosis, and assessment of electrode aging, demonstrating significant application value.

[0041] Currently, advanced reference electrodes can achieve dynamic electrochemical process monitoring for approximately 3000 hours and 300 cycles without relying on post-processing (such as material surface modification or signal fitting correction), while maintaining high signal stability. However, existing reference electrodes generally suffer from signal drift during long-term cyclic use, causing the measured electrode potential to no longer accurately reflect the actual negative electrode potential, thus affecting their reliability and effectiveness in long-term monitoring.

[0042] Due to the aforementioned issues, existing reference electrodes still struggle to meet the requirements for continuous and stable monitoring of positive and negative electrode potentials throughout the entire lifespan of lithium-ion batteries (e.g., more than 1000 cycles). Especially in applications requiring long-term, precise monitoring, such as battery aging studies, lifespan assessments, and safety control, signal drift severely restricts the practical application effectiveness of reference electrodes.

[0043] In summary, there is currently a lack of an effective method to correct the measurement signal of the reference electrode after signal drift occurs. Based on the above problems, this application proposes a reference electrode signal correction method to solve the measurement inaccuracy problem caused by signal drift and improve the practicality and stability of the reference electrode in battery life cycle monitoring.

[0044] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 1 As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores relevant data during the reference electrode signal correction process. The I / O interfaces are used for information exchange between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a reference electrode signal correction method.

[0045] Those skilled in the art will understand that Figure 1 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.

[0046] In one exemplary embodiment, such as Figure 2 As shown, a method for correcting a reference electrode signal is provided, which can be applied to... Figure 1 The following steps, 201 to 203, are used as an example of computer equipment.

[0047] Step 201: Obtain the reference electrode signal of the target battery during the cycling process.

[0048] The target battery refers to the lithium-ion battery to be measured and analyzed, which is connected to a reference electrode during use, and whose relevant electrochemical signals are collected during cyclic charging and discharging. The target battery can be a single cell or a unit in an integrated battery module.

[0049] A cycle refers to a complete charge and discharge cycle that a battery undergoes, including the entire process from charging to a set voltage or capacity from the initial state of charge, and then discharging to the termination voltage or capacity.

[0050] The reference electrode signal refers to the voltage value of the target electrode relative to the reference potential, measured by a reference electrode placed inside or outside the target cell. The reference electrode signal is used to characterize the electrochemical behavior of the target electrode and is the basis for judging its reaction characteristics, aging state, and abnormal behavior.

[0051] In this embodiment, a computer device acquires a reference electrode signal of the target battery during charge-discharge cycles. The reference electrode signal is collected by an embedded or external reference electrode and reflects the potential change of the battery's negative electrode relative to a reference point.

[0052] In one specific embodiment, during the normal charge-discharge cycle of the target battery, a device capable of acquiring and storing reference electrode signals can be used, such as a voltage sensor, voltage data acquisition instrument, battery charger / discharger, or voltage sampling auxiliary channel of battery testing equipment, to acquire the reference electrode signal of the battery negative electrode and send the acquired reference electrode signal to a computer device.

[0053] Step 202: If a drift in the reference electrode signal is detected, obtain the plateau potential characteristic values ​​in multiple complete cycles before the drift occurs.

[0054] Drift refers to the systematic shift in the potential signal output by the reference electrode relative to the true electrode potential under long-term battery cycling or complex operating conditions. Drift can be caused by factors such as degradation of the reference electrode material, changes in the electrolyte environment, and changes in contact impedance.

[0055] The plateau potential characteristic value refers to the stable potential range of the reference electrode signal within a specific State of Charge (SOC) range under normal cycling conditions. The plateau potential characteristic values ​​across multiple cycles can serve as a benchmark for determining whether the signal has drifted and for making corrections.

[0056] In this embodiment, the computer device dynamically analyzes the acquired reference electrode signal to determine whether drift exists. In one specific embodiment, the computer device acquires the reference electrode potential within a specific state of charge (SOC) range in each cycle and compares it with the potential in the same SOC range from multiple normal cycles in the previous stage. When the potential of the current cycle deviates from the historical average level by more than a set threshold and exhibits continuous variation, the computer device can determine that the reference electrode signal has drifted.

[0057] In one specific embodiment, when determining whether the reference electrode signal has drifted during lithium-ion battery cycling, the computer device records and compares the reference electrode signal of the battery under a specific SOC (optionally set to 100%) condition. When it is found that the absolute value of the difference between the reference electrode potential under the current cycle SOC and the corresponding potential of the previous cycle is greater than or equal to 50mV, the computer device determines that reference electrode signal drift has occurred and initiates the subsequent correction process.

[0058] After a drift is detected, the computer device traces back several complete cycles before the drift occurred and obtains the platform potential characteristic values ​​of these cycles.

[0059] Step 203: Based on the platform potential characteristic value, the reference electrode signal collected in the abnormal cycle where drift occurs is corrected to obtain the corrected reference electrode signal.

[0060] Abnormal cycles refer to cycles in which the reference electrode signal exhibits significant drift.

[0061] In this embodiment, the computer device corrects the reference electrode signal in an abnormal cycle where drift occurs. First, it extracts the reference electrode voltage characteristic values ​​of the constant voltage range from multiple complete charge-discharge cycles before the drift occurs, and constructs a standard reference voltage curve based on these values ​​as a benchmark for subsequent correction. Then, in the abnormal cycle where the reference electrode signal drift is detected, time segments corresponding to obvious constant voltage characteristics during charging or discharging are identified, and the voltage curves of these segments are compared with the reference voltage curve. Based on the comparison results, the overall drift offset of the segment is estimated using a least-squares fitting or sliding window algorithm. Subsequently, the voltage value of the constant voltage range signal in the abnormal cycle is corrected according to the estimated drift offset. To avoid abrupt changes in the corrected signal at the boundaries, interpolation smoothing is applied to the transition region between the corrected and uncorrected segments. Finally, residual analysis is performed on the corrected reference electrode signal to confirm whether the correction effect meets the preset error range. If it does, the corrected reference electrode signal is output and stored for subsequent battery state analysis and modeling.

[0062] In the aforementioned reference electrode signal correction method, the reference electrode signal of the target battery during cycling is acquired to provide basic data support for subsequent potential change trend analysis and anomaly detection. Secondly, when a drift in the reference electrode signal is detected, the reference electrode signal collected during the abnormal cycle in which the drift occurred is corrected based on the platform potential characteristic value, resulting in a corrected reference electrode signal. This method can effectively correct reference electrode signal drift caused by long-term operation or changes in the electrochemical environment, thereby extending the effective monitoring period of the reference electrode and improving the accuracy of battery potential measurement.

[0063] In an exemplary embodiment, the reference electrode signal includes the discharge reference electrode voltage and the battery capacity, based on which, such as Figure 3 As shown, the above-mentioned "correcting the reference electrode signal collected in the abnormal cycle of drift based on the platform potential characteristic value to obtain the corrected reference electrode signal" includes steps 301 to 304. Wherein:

[0064] Step 301: For the discharge process in abnormal cycle, based on the first relationship curve between the discharge reference electrode voltage and the battery capacity, determine the first differential curve between the discharge reference electrode voltage and the battery capacity.

[0065] Step 302: Determine the first discharge voltage based on the peak value of the first differential curve.

[0066] The discharge process refers to the process of releasing battery energy, that is, the battery outputs current from a high voltage state to a low voltage state, accompanied by a gradual release of capacity.

[0067] The primary relationship curve between discharge reference electrode voltage and battery capacity refers to the functional relationship between the terminal voltage measured during the battery discharge phase in abnormal cycling and the cumulative discharge capacity. This curve, with voltage on the vertical axis and capacity on the horizontal axis, typically exhibits multiple plateaus or slope ranges, reflecting the characteristics of different battery material compositions and reaction mechanisms. This curve can be used to analyze the dynamic behavior of the battery's negative electrode reaction process.

[0068] The first differential curve refers to the curve obtained by taking the first derivative of the aforementioned "first relationship curve between discharge reference electrode voltage and battery capacity". This curve represents the rate of voltage change corresponding to a unit capacity change and reflects the trend of the curve's slope with capacity change.

[0069] In this embodiment, after detecting a drift in the reference electrode signal of the target battery, the computer device acquires the discharge process data in the abnormal cycle, specifically including the voltage (denoted as V) measured at the reference electrode and the capacity (denoted as Q) at the corresponding time. Subsequently, the computer device constructs the first relationship curve of the abnormal cycle, namely the dQ / dV-V curve, with the reference electrode voltage as the abscissa and the derivative of Q with respect to V, dQ / dV, as the ordinate.

[0070] The dQ / dV-V curve reflects the rate of capacity change released by the battery under a unit voltage change and can be used to reveal sensitive regions of electrochemical reactions. Peaks on the curve typically correspond to major reaction plateaus or phase transition behaviors in the electrode material, and are important features for diagnosing the negative electrode state. Therefore, computer equipment further analyzes the curve, identifies its peak positions, and extracts the corresponding voltage values ​​as the first discharge voltage of the current abnormal cycle.

[0071] Step 303: Based on the relationship curve between voltage and state of charge, determine the first charging voltage corresponding to the first discharge voltage in the abnormal cycle.

[0072] The voltage-state-of-charge (SOC) curve refers to the mapping relationship between the terminal voltage (or negative electrode potential) and the SOC established during battery testing. This relationship can be obtained through static open-circuit voltage curves, constant current charging tests, or empirical fitting methods, and is used to infer the SOC level of the battery at a certain voltage.

[0073] The first charging voltage refers to the charging stage voltage value corresponding to the first discharging voltage, which is derived from the "voltage-state-of-charge curve". Since the charging and discharging voltages corresponding to the same state of charge (SOC) should be close under normal conditions, this value can be used to construct a drift correction reference coordinate system.

[0074] In this embodiment, the computer device uses a pre-established mapping curve between voltage and state of charge (SOC) and takes a first discharge voltage as input to determine its corresponding SOC value. Based on this, the computer device searches for the voltage response of this SOC value during normal charging, thereby determining the corresponding first charging voltage.

[0075] Step 304: Correct the reference electrode signal collected during the abnormal cycle in which drift occurs based on the first discharge voltage, the first charging voltage, and the characteristic value of the plateau potential to obtain the corrected reference electrode signal.

[0076] In this embodiment, the computer device combines the first discharge voltage, the first charging voltage, and the plateau potential characteristic value extracted from multiple complete normal cycles before drift occurs to correct the reference electrode signal collected during the abnormal cycle. The plateau potential characteristic value is a historical reference value of the stable potential behavior of the negative electrode within a specific SOC range, and has high repeatability and reliability.

[0077] During the correction process, the computer equipment can employ various methods to calibrate the signal, such as linear translation based on voltage mapping deviation, constructing an interpolation correction function using fitted dQ / dV feature points, or dynamic compensation based on the deviation between the first discharge voltage point and the reference plateau point. Finally, the computer equipment outputs the corrected reference electrode signal, and performs data annotation and recording to distinguish between the original and corrected signals, supporting subsequent battery state assessment or anomaly analysis tasks.

[0078] In an exemplary embodiment, the voltage-state-of-charge relationship curves mentioned above include a relationship curve corresponding to the first discharge voltage and a relationship curve corresponding to the first charging voltage. Based on this, such as... Figure 4As shown, the above-mentioned "determining the first charging voltage corresponding to the first discharge voltage in the target cycle based on the relationship curve between voltage and state of charge" includes steps 401 to 402. Wherein:

[0079] Step 401: Obtain the first state of charge corresponding to the first discharge voltage from the relationship curve corresponding to the first discharge voltage.

[0080] In this embodiment of the application, the computer device first obtains the first state of charge corresponding to the voltage from the discharge voltage state of charge relationship curve corresponding to the previously determined first discharge voltage.

[0081] Step 402: Obtain the first charging voltage corresponding to the first state of charge from the relationship curve corresponding to the first charging voltage.

[0082] In this embodiment of the application, the computer device obtains the voltage value corresponding to the first state of charge from the pre-established charging voltage state of charge relationship curve, and determines it as the first charging voltage under the first state of charge.

[0083] Through the above mapping process of discharge voltage, state of charge, and charging voltage, the computer equipment establishes a dynamic correlation from abnormal discharge behavior to normal charging state, thereby forming a more accurate correction reference point and providing multi-dimensional support for subsequent numerical offset compensation of reference electrode signals and platform alignment.

[0084] In one exemplary embodiment, such as Figure 5 As shown, the above-mentioned "correcting the reference electrode signal collected during the abnormal cycle in which drift occurs based on the first discharge voltage, the first charging voltage, and the plateau potential characteristic value to obtain the corrected reference electrode signal" includes steps 501 to 503. Wherein:

[0085] Step 501: Average the first charging voltage and the first discharging voltage to obtain the average reference voltage of the abnormal cycle.

[0086] In this embodiment, after acquiring the first discharge voltage and the first charging voltage during an abnormal cycle, the computer device first averages the first discharge voltage and the first charging voltage to obtain the average reference voltage of the abnormal cycle. This average value integrates the voltage characteristics of the discharge and charging phases, which helps to reduce the impact of voltage fluctuations under a single operating condition on the correction and improves the stability and accuracy of the correction.

[0087] Step 502: Perform a difference calculation on the average reference voltage and the characteristic value of the plateau potential during the abnormal cycle to obtain a correction value.

[0088] In this embodiment, the computer device performs a difference calculation between the average reference voltage and the plateau potential characteristic values ​​extracted from multiple normal cycles before the drift occurs, and calculates a correction value. This correction value reflects the degree to which the reference electrode signal deviates from the historical stable plateau potential during the abnormal cycle, and is a quantitative value for signal correction.

[0089] Step 503: Based on the correction value, the reference electrode signal collected in the abnormal cycle is corrected to obtain the corrected reference electrode signal.

[0090] In this embodiment of the application, the computer device performs overall correction processing on the reference electrode signal acquired during the abnormal cycle based on the correction value.

[0091] In one specific embodiment, the computer device corrects the drifted reference electrode signal based on the consistency of the platform signal characteristic values. For each drifted single loop (denoted as the i-th loop), ) Loop through the data and perform signal correction.

[0092] Differentiate the reference electrode signal curve during battery discharge. Take the voltage (denoted as V) - capacity (denoted as Q) curve measured by the reference electrode during the discharge process of this cycle, differentiate the capacity with respect to the voltage, and obtain the curve of this differential value dQ / dV as a function of the reference electrode voltage V (denoted as the dQdV-V curve);

[0093] Find the maximum value of the dQdV-V curve. Record its x-coordinate (denoted as ). ).

[0094] turn up The corresponding SOC. Find the original V-SOC curve during the discharge process. The corresponding SOC is denoted as .

[0095] During the charging process of this cycle, find The corresponding reference electrode measurement voltage. Find the reference electrode measurement value curve within the same charging cycle. The corresponding reference electrode measurement voltage is denoted as .

[0096] Calculate the average value of the reference electrode measurement voltage after drift, denoted as .

[0097]

[0098] Calculate the characteristic value of the reference electrode measurement voltage plateau signal, denoted as .

[0099]

[0100] The reference electrode signal is corrected based on the consistency of the platform signal characteristic values ​​after drift. For the i-th cycle, the original reference electrode measured voltage (denoted as V) is shifted to obtain the corrected reference electrode measured voltage (denoted as V). ).

[0101]

[0102] Through the above steps, the computer equipment effectively calibrates the abnormal cycle reference electrode signal, effectively extending the service life of the reference electrode and meeting the demand for high-precision electrode potential measurement throughout the entire life cycle of lithium-ion batteries.

[0103] In one exemplary embodiment, such as Figure 6 As shown, the process of determining the "platform potential characteristic value" includes steps 601 to 606. Wherein:

[0104] Step 601: For the discharge process in each normal cycle before drift occurs, determine the second differential curve between the discharge reference electrode voltage and the battery capacity based on the second relationship curve between the discharge reference electrode voltage and the battery capacity.

[0105] In this embodiment, for each normal cycle before drift occurs, the computer device first acquires voltage and capacity data during the discharge process of that normal cycle. Based on this data, the computer device constructs a second relationship curve between the discharge reference electrode voltage and the battery capacity, i.e., a curve with voltage as the abscissa and the derivative of capacity with respect to voltage, dQ / dV, as the ordinate. Subsequently, the computer device performs a first-order differential operation on this second relationship curve to obtain a second differential curve, reflecting the trend of voltage change rate.

[0106] Step 602: Determine the second discharge voltage based on the peak value of the second differential curve.

[0107] Step 603: Obtain the second state of charge corresponding to the second discharge voltage from the pre-obtained relationship curve corresponding to the second discharge voltage.

[0108] Step 604: Obtain the second charging voltage corresponding to the second state of charge from the pre-obtained relationship curve corresponding to the second charging voltage.

[0109] Step 605: Average the second charging voltage and the second discharging voltage to obtain the average reference voltage for normal cycling.

[0110] Step 606: Average the reference voltage values ​​of multiple normal cycles to obtain the plateau potential characteristic value.

[0111] In this embodiment, the computer device further identifies the peak value on the second differential curve and extracts the voltage corresponding to the peak value, determining it as the second discharge voltage of the normal cycle. The second discharge voltage reflects the important electrochemical reaction points of the electrode material during the discharge process.

[0112] Subsequently, the computer device uses the pre-acquired voltage-state-of-charge (SOC) curve corresponding to the second discharge voltage to find the second SOC value. Based on this SOC value, the computer device further obtains the corresponding second charging voltage from the established second charging voltage-state-of-charge curve.

[0113] To comprehensively reflect the electrode potential characteristics of this normal cycle, the computer equipment averages the second discharge voltage and the second charge voltage to calculate the average reference voltage for this normal cycle. This average value effectively balances the voltage differences during the charging and discharging process, enhancing the stability of the characteristic values.

[0114] Finally, the computer equipment performs multiple averaging processes on the reference voltage average value of multiple normal cycles before the drift occurs, and obtains the plateau potential characteristic value of the stable performance of multiple cycles.

[0115] In one specific embodiment, the plateau signal characteristic value of the reference electrode measurement potential under normal conditions before drift is obtained.

[0116] Before the reference electrode signal drift, the total number of complete charge-discharge cycle data collected is denoted as n cycles (optionally: ).

[0117] For the complete charge-discharge cycle data from cycle 1 to cycle n, the following operations are performed on each cycle's data (the subscript k in the parameters listed below represents cycle k). ):

[0118] Differentiate the reference electrode signal curve during battery discharge. Take the voltage (denoted as V) - capacity (denoted as Q) curve measured by the reference electrode during the discharge process of the kth cycle, differentiate the capacity with respect to the voltage, and obtain the curve of this differential value dQ / dV as a function of the reference electrode voltage V (denoted as the dQdV-V curve);

[0119] Find the maximum value of the dQdV-V curve. Record its x-coordinate (denoted as ). ).

[0120] turn up The corresponding SOC. Find the original V-SOC curve during the discharge process. The corresponding SOC is denoted as .

[0121] During the charging process of the kth cycle, find The corresponding reference electrode measurement voltage. Find the reference electrode measurement value curve during the same charging cycle (cycle k). The corresponding reference electrode measurement voltage is denoted as .

[0122] Calculate the average value of the reference electrode measured in the kth cycle, denoted as . .

[0123]

[0124] Obtain the plateau signal characteristic value of the reference electrode measurement potential under normal conditions before drift, denoted as .

[0125]

[0126] In one specific embodiment Figure 7 This is a schematic diagram of the reference electrode signal before correction in one embodiment; specifically, Figure 7 There were two signal drifts, the first upward and the second downward. Figure 8 This is a corrected reference electrode signal in one embodiment, reflecting the effect of correcting the reference electrode signal drift. It is compared to the large voltage jumps (upward and downward drifts) before correction. Figure 8 The reference electrode voltage fluctuated around a stable range (e.g., 1.2-1.6V) for most of the cycle. The extreme voltage values ​​(e.g., below 0.5V, above 1.8V) caused by the drift were corrected, indicating that the signal returned to a reasonable electrochemical range.

[0127] In one specific embodiment, a lithium-ion battery using graphite as the negative electrode is taken as an example. Figure 9 This is a schematic diagram illustrating the reference electrode measurement potential at 100% SOC for each cycle, after correction, in one embodiment. Figure 9 In this case, with 1.46mV as the reference, the range of the reference electrode signal value is between 1.41mV and 1.51mV. It can be seen that the correction method of this application embodiment can control the fluctuation of the measured voltage value of the reference electrode over 1000 cycles to within 50mV.

[0128] In one exemplary embodiment, the method further includes:

[0129] If the discharge reference electrode voltage corresponding to the current cycle and the discharge reference electrode voltage corresponding to the previous cycle meet the preset conditions, it is determined that the reference electrode signal has drifted.

[0130] In this embodiment, the computer device acquires the discharge reference electrode voltage corresponding to the reference electrode signal in the current cycle and the previous cycle. The computer device determines whether the discharge reference electrode voltages of the current cycle and the previous cycle meet a preset comparison condition, such as the difference between the two discharge reference electrode voltages being less than a preset threshold, or both being within the same discharge reference electrode voltage range. Only when this condition is met is subsequent drift determination performed.

[0131] Subsequently, when the potential difference of the discharge reference electrode voltage exceeds the preset drift threshold, the computer equipment determines that the reference electrode signal has drifted.

[0132] The computer equipment also performs trend analysis on the reference electrode signals from multiple cycles, using statistical methods such as moving averages or linear regression to determine whether there is a continuous shift trend in the signal. When the trend determination criteria are met, the system confirms the existence of drift.

[0133] To avoid abnormal data interfering with drift determination, computer equipment can also preprocess the collected signals to remove abrupt changes and noise data, ensuring that drift determination is based on a valid and continuous signal range.

[0134] In addition, the computer equipment combines auxiliary parameters such as temperature and current to perform multi-parameter joint judgment. By analyzing the changes in these parameters, it helps to identify the drift of the reference electrode signal.

[0135] In one exemplary embodiment, the method further includes:

[0136] Step 1: Obtain the reference electrode signal of the target battery during cycling.

[0137] Step 2: If the discharge reference electrode voltage corresponding to the current cycle and the discharge reference electrode voltage corresponding to the previous cycle meet the preset conditions, it is determined that the reference electrode signal has drifted.

[0138] Step 3: When a drift in the reference electrode signal is detected, for the discharge process in each normal cycle before the drift occurs, a second differential curve between the discharge reference electrode voltage and the battery capacity is determined based on the second relationship curve between the discharge reference electrode voltage and the battery capacity.

[0139] Step 4: Determine the second discharge voltage based on the peak value of the second differential curve.

[0140] Step 5: Obtain the second state of charge corresponding to the second discharge voltage from the pre-obtained relationship curve corresponding to the second discharge voltage.

[0141] Step 6: Obtain the second charging voltage corresponding to the second state of charge from the pre-obtained relationship curve corresponding to the second charging voltage.

[0142] Step 7: Average the second charging voltage and the second discharging voltage to obtain the average reference voltage for normal cycling.

[0143] Step 8: Average the reference voltage values ​​from multiple normal cycles to obtain the plateau potential characteristic value.

[0144] Step 9: For the discharge process in abnormal cycles, based on the first relationship curve between the discharge reference electrode voltage and the battery capacity, determine the first differential curve between the discharge reference electrode voltage and the battery capacity.

[0145] Step 10: Determine the first discharge voltage based on the peak value of the first differential curve.

[0146] Step 11: Obtain the first state of charge corresponding to the first discharge voltage from the relationship curve corresponding to the first discharge voltage.

[0147] Step 12: Obtain the first charging voltage corresponding to the first state of charge from the relationship curve corresponding to the first charging voltage.

[0148] Step 13: Average the first charging voltage and the first discharging voltage to obtain the average reference voltage of the abnormal cycle.

[0149] Step 14: Perform a difference calculation on the average reference voltage and the characteristic value of the plateau potential during the abnormal cycle to obtain the correction value.

[0150] Step 15: Based on the correction value, the reference electrode signal collected in the abnormal cycle is corrected to obtain the corrected reference electrode signal.

[0151] It should be understood that although the steps in the flowcharts of the above embodiments 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 above embodiments 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 of other steps.

[0152] Based on the same inventive concept, this application also provides a reference electrode signal correction device for implementing the reference electrode signal correction method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more embodiments of the reference electrode signal correction device provided below can be found in the limitations of the reference electrode signal correction method described above, and will not be repeated here.

[0153] In one exemplary embodiment, such as Figure 10 As shown, a reference electrode signal correction device is provided, comprising: a signal acquisition module 701, a feature value acquisition module 702, and a correction module 703, wherein:

[0154] The signal acquisition module 701 is used to acquire the reference electrode signal of the target battery during the cycling process;

[0155] The feature value acquisition module 702 is used to acquire the plateau potential feature values ​​in multiple complete cycles before the drift occurs when a drift is detected in the reference electrode signal.

[0156] The correction module 703 is used to correct the reference electrode signal collected in the abnormal cycle where drift occurs based on the platform potential characteristic value, so as to obtain the corrected reference electrode signal.

[0157] In an exemplary embodiment, the correction module 703 is specifically used to determine a first differential curve between the discharge reference electrode voltage and the battery capacity based on a first relationship curve between the discharge reference electrode voltage and the battery capacity for the discharge process in an abnormal cycle.

[0158] The first discharge voltage is determined based on the peak value of the first differential curve;

[0159] Based on the relationship curve between voltage and state of charge, the first charging voltage corresponding to the first discharge voltage in the abnormal cycle is determined.

[0160] The reference electrode signal acquired during the abnormal cycle in which drift occurs is corrected based on the first discharge voltage, the first charging voltage, and the characteristic value of the plateau potential, to obtain the corrected reference electrode signal.

[0161] In an exemplary embodiment, the correction module 703 is specifically used to obtain the first state of charge corresponding to the first discharge voltage from the relationship curve corresponding to the first discharge voltage.

[0162] From the relationship curve corresponding to the first charging voltage, obtain the first charging voltage corresponding to the first state of charge.

[0163] In an exemplary embodiment, the correction module 703 is specifically used to average the first charging voltage and the first discharging voltage to obtain the average reference voltage of the abnormal cycle.

[0164] The difference between the average reference voltage and the characteristic value of the plateau potential in the abnormal cycle is calculated to obtain the correction value;

[0165] Based on the correction value, the reference electrode signal collected in the abnormal cycle is corrected to obtain the corrected reference electrode signal.

[0166] In an exemplary embodiment, the reference electrode signal correction device described above is further configured to determine a second differential curve between the discharge reference electrode voltage and the battery capacity based on a second relationship curve between the discharge reference electrode voltage and the battery capacity for the discharge process in each normal cycle before drift occurs.

[0167] The second discharge voltage is determined based on the peak value of the second differential curve;

[0168] From the pre-obtained relationship curve corresponding to the second discharge voltage, obtain the second state of charge corresponding to the second discharge voltage;

[0169] From the pre-obtained relationship curve corresponding to the second charging voltage, obtain the second charging voltage corresponding to the second state of charge;

[0170] The second charging voltage and the second discharging voltage are averaged to obtain the average reference voltage during normal cycling.

[0171] The average value of the reference voltage from multiple normal cycles is averaged to obtain the plateau potential characteristic value.

[0172] In an exemplary embodiment, the reference electrode signal correction device is further configured to determine that the reference electrode signal has drifted when the discharge reference electrode voltage corresponding to the current cycle and the discharge reference electrode voltage corresponding to the previous cycle meet preset conditions.

[0173] Each module in the aforementioned reference electrode signal correction 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 operations corresponding to each module.

[0174] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0175] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above method embodiments.

[0176] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0177] 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.

[0178] 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.

[0179] 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 correcting a reference electrode signal, characterized in that, The method includes: Acquire the reference electrode signal of the target battery during cycling; If a drift is detected in the reference electrode signal, the plateau potential characteristic values ​​of multiple complete cycles before the drift occurs are obtained; The reference electrode signal includes the discharge reference electrode voltage and the battery capacity; For the discharge process in abnormal cycles, based on the first relationship curve between the discharge reference electrode voltage and the battery capacity, the first differential curve between the discharge reference electrode voltage and the battery capacity is determined; The first discharge voltage is determined based on the peak value of the first differential curve; Based on the relationship curve between voltage and state of charge, the first charging voltage corresponding to the first discharge voltage in the abnormal cycle is determined. The first charging voltage and the first discharging voltage are averaged to obtain the average reference voltage of the abnormal cycle. The difference between the average reference voltage of the abnormal cycle and the characteristic value of the platform potential is calculated to obtain the correction value; Based on the correction value, the reference electrode signal collected in the abnormal cycle is corrected to obtain the corrected reference electrode signal. The process of determining the platform potential characteristic value includes: For the discharge process in each normal cycle before drift occurs, based on the second relationship curve between the discharge reference electrode voltage and the battery capacity, the second differential curve between the discharge reference electrode voltage and the battery capacity is determined; The second discharge voltage is determined based on the peak value of the second differential curve; From the pre-obtained relationship curve corresponding to the second discharge voltage, obtain the second state of charge corresponding to the second discharge voltage; From the pre-obtained relationship curve corresponding to the second charging voltage, obtain the second charging voltage corresponding to the second state of charge; The second charging voltage and the second discharging voltage are averaged to obtain the average reference voltage of the normal cycle; The average value of the reference voltage for multiple normal cycles is averaged to obtain the plateau potential characteristic value.

2. The method according to claim 1, characterized in that, The voltage-state-of-charge relationship curve includes a relationship curve corresponding to the first discharge voltage and a relationship curve corresponding to the first charging voltage. Determining the first charging voltage corresponding to the first discharge voltage in the abnormal cycle based on the voltage-state-of-charge relationship curve includes: From the relationship curve corresponding to the first discharge voltage, obtain the first state of charge corresponding to the first discharge voltage; From the relationship curve corresponding to the first charging voltage, obtain the first charging voltage corresponding to the first state of charge.

3. The method according to any one of claims 1 to 2, characterized in that, The method further includes: If the discharge reference electrode voltage corresponding to the current cycle and the discharge reference electrode voltage corresponding to the previous cycle meet the preset conditions, it is determined that the reference electrode signal has drifted.

4. A reference electrode signal correction device, characterized in that, The device includes: The signal acquisition module is used to acquire the reference electrode signal of the target battery during cycling. The feature value acquisition module is used to acquire plateau potential feature values ​​in multiple complete cycles before the drift occurs when the reference electrode signal is detected to drift. The reference electrode signal includes the discharge reference electrode voltage and the battery capacity. For the discharge process in each normal cycle before the drift occurs, a second differential curve between the discharge reference electrode voltage and the battery capacity is determined based on a second relationship curve between the discharge reference electrode voltage and the battery capacity. A second discharge voltage is determined based on the peak value of the second differential curve. A second state of charge corresponding to the second discharge voltage is acquired from the relationship curve corresponding to the pre-acquired second discharge voltage. A second charging voltage corresponding to the second state of charge is acquired from the relationship curve corresponding to the pre-acquired second charging voltage. The second charging voltage and the second discharge voltage are averaged to obtain the average reference voltage of the normal cycle. The average reference voltage of multiple normal cycles is averaged to obtain the plateau potential feature value. The correction module is used to, for the discharge process in an abnormal cycle, determine a first differential curve between the discharge reference electrode voltage and the battery capacity based on a first relationship curve between the discharge reference electrode voltage and the battery capacity; determine a first discharge voltage based on the peak value of the first differential curve; determine a first charging voltage corresponding to the first discharge voltage in the abnormal cycle based on the relationship curve between voltage and state of charge; average the first charging voltage and the first discharge voltage to obtain an average reference voltage for the abnormal cycle; perform a difference calculation on the average reference voltage for the abnormal cycle and the plateau potential characteristic value to obtain a correction value; and perform correction processing on the reference electrode signal collected in the abnormal cycle based on the correction value to obtain a corrected reference electrode signal.

5. 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 3.

6. 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 3.

7. 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 3.

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