Battery cell fault early warning method and system based on dynamic impedance fitting

Abstract

The invention provides a cell fault early warning method and system based on dynamic impedance fitting, and the method comprises the steps: carrying out the impedance test of a target battery, obtaining an impedance value at an initial moment, and charging the target battery; performing impedance recording on the target battery at each time point through the excitation current with the preset frequency to obtain a real-time impedance observation value; constructing an exponential decay model and performing impedance fitting prediction on the real-time impedance observation value at each time point to obtain a real-time impedance prediction value; and carrying out residual error fitting and deviation analysis on the real-time impedance observation value and the real-time impedance prediction value to obtain battery abnormal change monitoring data, and sending out early warning when the target battery cell has a fault. The problem that in the prior art, in the battery charging and discharging process, the battery impedance change cannot be detected in real time, and the battery fault cannot be early warned in time, so that the safety of the battery cell is poor is solved. According to the invention, the impedance abnormal change time can be fed back in time and early warning can be made, so that the safety of the battery cell is improved.

Description

Technical Field

[0001] The present invention relates to the field of battery cell safety detection, and in particular to a battery cell fault early warning method and system based on dynamic impedance fitting. Background Art

[0002] Lithium batteries are currently widely used in various fields. Failures caused by battery overcharging, overheating and battery consistency differences seriously affect the safety and stability of energy storage systems. Therefore, timely feedback and early warning of abnormal battery status are required.

[0003] At present, the existing technology mainly adopts static impedance measurement, which is aimed at measuring the impedance characteristics of the battery under static (i.e. non-changing or DC) conditions. Usually, the changes in voltage and temperature lag behind the internal faults. When obvious changes in external parameters are detected, the problem may have already occurred seriously. Therefore, the existing methods have the problem of insufficient real-time performance during the charging and discharging process, and it is difficult to quickly respond to changes in the internal state of the battery, and it is impossible to warn of battery failure in time, resulting in poor safety of battery cells. Summary of the invention

[0004] In order to solve the above problems, the present invention proposes a battery cell fault warning method and system based on dynamic impedance fitting, which can realize real-time dynamic detection of battery cell impedance changes during charging, timely feedback of abnormal impedance change time and issue warnings, thereby improving the safety of battery cells.

[0005] To achieve the above object, an embodiment of the present invention provides a cell fault early warning method based on dynamic impedance fitting, comprising:

[0006] Performing an impedance test on a target battery to obtain an impedance value at an initial moment and charging the target battery;

[0007] The impedance of the target battery is recorded at each time point by an excitation current of a preset frequency to obtain a real-time impedance observation value;

[0008] Constructing an exponential decay model and performing impedance fitting prediction on the real-time impedance observation value at each time point to obtain a real-time impedance prediction value;

[0009] Performing residual fitting and deviation analysis on the real-time impedance observation value and the real-time impedance prediction value to obtain battery abnormal change monitoring data;

[0010] Based on the abnormal battery change monitoring data, an early warning is issued when a target battery cell fails.

[0011] Further, the impedance test is performed on the target battery to obtain the impedance value at the initial moment and the target battery is charged, including:

[0012] Fully discharge the battery to be tested to obtain a target battery;

[0013] Testing the impedance value between the positive and negative electrodes of the target battery to obtain the impedance value at the initial moment;

[0014] Based on a preset constant current, the target battery is charged with a constant current.

[0015] Furthermore, the impedance of the target battery is recorded at each time point by the excitation current of the preset frequency to obtain a real-time impedance observation value, including:

[0016] During the charging process, based on a preset time interval, the impedance of the target battery is recorded by the excitation current of the preset frequency to obtain a first real-time impedance change curve;

[0017] Based on the first real-time impedance change curve, a real-time impedance observation value is obtained.

[0018] Furthermore, the exponential decay model is constructed and impedance fitting prediction is performed on the real-time impedance observation value at each time point to obtain the real-time impedance prediction value, including:

[0019] Based on the impedance value at the initial moment and the preset decay constant, an exponential decay model is constructed;

[0020] During the charging process, the real-time impedance observation value at each time point is fitted by the exponential decay model to obtain a second real-time impedance change curve;

[0021] Based on the second real-time impedance change curve, a real-time impedance prediction value is obtained.

[0022] Further, residual fitting and deviation analysis are performed on the real-time impedance observation value and the real-time impedance prediction value to obtain battery abnormal change monitoring data, including:

[0023] Obtaining an impedance residual by subtracting the real-time impedance observation value from the real-time impedance prediction value;

[0024] Fitting the impedance residual by minimizing the residual square sum to obtain a fitting residual;

[0025] The residual distribution and residual size of the fitting residual are analyzed to obtain battery abnormal change monitoring data.

[0026] Furthermore, the method of issuing an early warning when a target battery cell fails based on the battery abnormal change monitoring data includes:

[0027] Based on the battery abnormal change monitoring data, calculating the absolute value of the impedance residual at each time point to obtain the absolute value of the impedance residual;

[0028] If the absolute value of the impedance residual is greater than the fitting residual, it is determined that the target battery cell has failed and an early warning is issued;

[0029] If the distribution of the impedance residual does not meet the fitting residual distribution requirement, it is determined that the target battery cell has failed and an early warning is issued.

[0030] The embodiment of the present invention also provides a battery cell fault early warning system based on dynamic impedance fitting, including: an initial impedance test module, an impedance observation module, an impedance prediction module, an abnormal change analysis module and an early warning module;

[0031] The initial impedance test module is used to perform an impedance test on the target battery, obtain an impedance value at the initial moment and charge the target battery;

[0032] The impedance observation module is used to record the impedance of the target battery at various time points through an excitation current of a preset frequency to obtain a real-time impedance observation value;

[0033] The impedance prediction module is used to construct an exponential decay model and perform impedance fitting prediction on the real-time impedance observation value at each time point to obtain a real-time impedance prediction value;

[0034] The abnormal change analysis module is used to perform residual fitting and deviation analysis on the real-time impedance observation value and the real-time impedance prediction value to obtain battery abnormal change monitoring data;

[0035] The early warning module is used to issue an early warning when a target battery cell fails based on the battery abnormal change monitoring data.

[0036] Furthermore, the impedance prediction module is used to construct an exponential decay model and perform impedance fitting prediction on the real-time impedance observation value at each time point to obtain a real-time impedance prediction value, including:

[0037] A model building unit, an impedance prediction unit and an impedance value acquisition unit;

[0038] The model building unit is used to build an exponential decay model based on the impedance value at the initial moment and a preset decay constant;

[0039] The impedance prediction unit is used to obtain a second real-time impedance change curve by fitting the real-time impedance observation value at each time point through the exponential decay model during the charging process;

[0040] The impedance value acquisition unit is used to acquire a real-time impedance prediction value based on the second real-time impedance change curve.

[0041] Furthermore, the abnormal change analysis module is used to perform residual fitting and deviation analysis on the real-time impedance observation value and the real-time impedance prediction value to obtain battery abnormal change monitoring data, including:

[0042] Residual calculation unit, residual fitting unit and abnormality analysis unit;

[0043] The residual calculation unit is used to obtain an impedance residual by subtracting the real-time impedance observation value from the real-time impedance prediction value;

[0044] The residual fitting unit is used to fit the impedance residual by minimizing the residual square sum to obtain a fitting residual;

[0045] The abnormality analysis unit is used to analyze the residual distribution and residual size of the fitting residual to obtain battery abnormal change monitoring data.

[0046] Furthermore, the early warning module is used to issue an early warning when a target battery cell fails based on the battery abnormal change monitoring data, including:

[0047] A residual absolute value calculation unit, a first warning unit and a second warning unit;

[0048] The residual absolute value calculation unit is used to calculate the absolute value of the impedance residual at each time point based on the battery abnormal change monitoring data to obtain the impedance residual absolute value;

[0049] The first warning unit is used to determine that the target battery cell has failed and issue a warning if the absolute value of the impedance residual is greater than the fitting residual;

[0050] The second warning unit is used to determine that a target battery cell fails and issue a warning if the distribution of the impedance residual does not meet the fitting residual distribution requirement.

[0051] Beneficial effects:

[0052] By using the exponential decay model to predict the battery impedance during the charging process, a data basis is provided for the dynamic change fitting of the battery impedance data. The real-time impedance of the battery is recorded by the excitation current of a preset frequency, which can effectively reduce high-frequency noise interference. The exponential decay model can also more accurately capture the change trend of impedance over time, ensuring the real-time and accuracy of the measurement data. Further, the abnormal change monitoring data of impedance is obtained through dynamic fitting and deviation analysis, which helps to discover the abnormal change trend of impedance in real time, monitor the battery health status in real time, and finally provide timely warning of abnormal changes, provide early warning of potential risks, and improve the safety of battery cells. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 A schematic diagram of the steps of a method for early warning of a cell failure based on dynamic impedance fitting provided by an embodiment of the present invention;

[0054] Figure 2 A schematic diagram of a first real-time impedance change curve of a cell fault early warning method based on dynamic impedance fitting provided by an embodiment of the present invention;

[0055] Figure 3 A schematic diagram of a fitting residual variation curve of a cell fault early warning method based on dynamic impedance fitting provided by an embodiment of the present invention;

[0056] Figure 4 A schematic diagram of the module structure of a battery cell fault warning system based on dynamic impedance fitting provided by an embodiment of the present invention;

[0057] Figure 5 A schematic diagram of the structure of an impedance prediction module of a battery cell fault warning system based on dynamic impedance fitting provided by an embodiment of the present invention;

[0058] Figure 6 A schematic diagram of the structure of an abnormal change analysis module of a battery cell fault early warning system based on dynamic impedance fitting provided by an embodiment of the present invention;

[0059] Figure 7 A schematic diagram of the structure of an early warning module of a battery cell failure early warning system based on dynamic impedance fitting is provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0060] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0061] Example 1

[0062] See also Figure 1 , Figure 1 A schematic diagram of the steps of a cell fault warning method based on dynamic impedance fitting is provided in an embodiment of the present invention. Figure 1 As shown, the embodiment of the present invention proposes a cell fault early warning method based on dynamic impedance fitting, including steps 101 to 105, each of which is specifically as follows:

[0063] Step 101, performing an impedance test on a target battery, obtaining an impedance value at an initial moment and charging the target battery;

[0064] As an example of this embodiment, the battery to be tested is fully discharged to obtain a target battery; the impedance value between the positive and negative electrodes of the target battery is tested to obtain the impedance value at the initial moment; based on a preset constant current, the target battery is charged with a constant current. A specific implementation method is to fully discharge the battery to be tested and let it stand for 4 hours to eliminate the interference of residual power on subsequent tests. The collection contacts of the impedance measurement device can be connected to the positive and negative electrodes of the target battery respectively to detect the impedance value of the target battery. The impedance value obtained by detecting the target battery is the impedance value Z0 at the initial moment; then a constant current of 1C (equivalent to the preset constant current) is set to charge the target battery.

[0065] Step 102, recording the impedance of the target battery at various time points by means of an excitation current of a preset frequency to obtain a real-time impedance observation value;

[0066] As an example of this embodiment, during the charging process, based on a preset time interval, the impedance of the target battery is recorded by the excitation current of the preset frequency to obtain a first real-time impedance change curve; based on the first real-time impedance change curve, a real-time impedance observation value is obtained.

[0067] In a specific implementation method, during the charging process, the impedance of the battery under the 150Hz frequency excitation current (equivalent to the preset frequency excitation current) is recorded in real time at fixed intervals (equivalent to the preset time interval), and the impedance change curve of the battery (equivalent to the first real-time impedance change curve) is obtained in real time to obtain the real-time impedance observation value Z i ,join Figure 2 , Figure 2 A schematic diagram of a first real-time impedance change curve of a cell fault early warning method based on dynamic impedance fitting provided by an embodiment of the present invention; Figure 2 As shown, at the beginning of charging, the battery impedance is 0.09519Ω, and the impedance changes from 0.09324Ω to 0.09117Ω between SOC 0.1 and 0.7, showing a slow downward trend. When the SOC reaches 0.8, the battery is about to be overcharged. After the SOC reaches 0.9, the battery impedance changes from 0.08793Ω to 0.08205Ω, showing an obvious rapid decay trend. In this embodiment, the model fitting effect can be optimized by adjusting the impedance data acquisition frequency. Specifically, 150Hz is selected as the data acquisition frequency to ensure that accurate and continuous impedance change data is obtained during the battery charging process.

[0068] Step 103, constructing an exponential decay model and performing impedance fitting prediction on the real-time impedance observation value at each time point to obtain a real-time impedance prediction value;

[0069] As an example of this embodiment, an exponential decay model is constructed based on the impedance value at the initial moment and a preset decay constant; during the charging process, the real-time impedance observation value at each time point is fitted by the exponential decay model to obtain a second real-time impedance change curve; based on the second real-time impedance change curve, a real-time impedance prediction value is obtained.

[0070] A specific implementation method is to construct an exponential decay model by determining the impedance value Z0 and the decay constant λ at the initial moment. The specific calculation formula is as follows:

[0071] Z(t)=Z0·e -λt

[0072] Where Z(t) represents the impedance value at time t, Z0 represents the impedance value at the initial moment, and λ represents the attenuation constant, which controls the decay rate of impedance over time.

[0073] After constructing the exponential decay model, for the data at each observation time point (t i ,Z i ) (equivalent to the real-time impedance observation value at each time point), the impedance value calculation formula predicted by exponential decay model fitting is:

[0074]

[0075] In the formula It is the real-time impedance prediction value.

[0076] After fitting and predicting the data at each observation time point through the exponential decay model, a battery impedance change prediction curve (equivalent to the second real-time impedance change curve) is constructed, and the real-time impedance prediction value can be reflected in the battery impedance change prediction curve The exponential decay model can more accurately reflect the real-time change trend of impedance, thereby achieving more accurate fault prediction.

[0077] Step 104, performing residual fitting and deviation analysis on the real-time impedance observation value and the real-time impedance prediction value to obtain battery abnormal change monitoring data;

[0078] As an example of this embodiment, the impedance residual is obtained by subtracting the real-time impedance observation value and the real-time impedance prediction value; the impedance residual is fitted by minimizing the residual sum of squares to obtain the fitting residual; the residual distribution and residual size of the fitting residual are analyzed to obtain the battery abnormal change monitoring data.

[0079] A specific implementation method is to fit the impedance curve residual at 150Hz from the beginning of charging to the current moment in real time during the charging process, that is, the real-time impedance observation value Z i Real-time impedance prediction The specific calculation formula is as follows:

[0080]

[0081] In this embodiment, the residual ε i It is defined as the difference between the observed impedance value and the model predicted impedance value, where the real-time impedance observation value can be obtained from the battery impedance change curve (equivalent to the first real-time impedance change curve), and the real-time impedance prediction value can be obtained from the battery impedance change prediction curve (equivalent to the second real-time impedance change curve); the size of the residual reflects the accuracy of the model prediction.

[0082] The real-time impedance observation value Z is calculated i Real-time impedance prediction After the residuals are obtained, the model parameters are estimated by minimizing the residual sum of squares. The specific calculation formula is as follows:

[0083]

[0084] Where n is the total number of observed data points. Under normal circumstances, the residuals should be randomly distributed around zero and have a small variance.

[0085] The abnormal detection mechanism based on the above residual analysis helps to find the rapid decrease trend of impedance before overcharging in real time. Then, by minimizing the residual sum of squares, the impedance abnormality can be effectively found. For a specific explanation, see Figure 3 , Figure 3 A schematic diagram of a fitting residual variation curve of a cell fault early warning method based on dynamic impedance fitting provided by an embodiment of the present invention; Figure 3 As shown in the figure, at the beginning of charging, the impedance is 3.963Ω, and the change is gentle. At this time, the fitting residual is 0, which is at a small change level. As time changes, when the charging is close to half (1500s), the impedance is 3.687Ω, and the fitting residual is 0.043Ω. When the time reaches 2500s, the battery is about to be overcharged, and the impedance is 3.568Ω. At this time, the fitting residual is 0.061Ω. Within the next 300s, the fitting residual increases rapidly from 0.062Ω to 0.113Ω. The impedance data recorded in real time is analyzed by the above-mentioned dynamic impedance index fitting residual, and whether the impedance curve of the battery shows a rapid attenuation trend in real time is judged in real time, thereby obtaining the battery abnormal change monitoring data, which can record the rapid change of the impedance value or the fitting residual value.

[0086] Step 105 , based on the battery abnormal change monitoring data, issuing a warning when a target battery cell fails.

[0087] As an example of this embodiment, based on the battery abnormal change monitoring data, the absolute value of the impedance residual at each time point is calculated to obtain the absolute value of the impedance residual; if the absolute value of the impedance residual is greater than the fitting residual, it is determined that the target battery cell has failed and an early warning is issued; if the distribution of the impedance residual does not meet the requirements of the fitting residual distribution, it is determined that the target battery cell has failed and an early warning is issued.

[0088] A specific implementation method is to identify data points that do not conform to the exponential decay trend by analyzing the distribution and size of the residuals. For example, if the absolute value of a residual (equivalent to the absolute value of the impedance residual to eliminate the influence of negative values) is significantly larger than other residuals, or the distribution of the residuals shows a systematic deviation (equivalent to not meeting the requirements of the fitted residual distribution), this may indicate that the impedance has changed abnormally at that point in time. By combining dynamic impedance measurement with the residual analysis method, an early warning mechanism can be provided, thereby effectively avoiding thermal runaway caused by overcharging. By cutting off charging in time, the operating safety of the battery can be further improved.

[0089] An embodiment of the present invention proposes a battery cell fault warning method based on dynamic impedance fitting. The battery impedance is predicted by using an exponential decay model during the charging process, so as to provide a data basis for the dynamic change fitting of the battery impedance data. The real-time impedance of the battery is recorded by an excitation current of a preset frequency, which can effectively reduce high-frequency noise interference. The exponential decay model can also more accurately capture the change trend of impedance over time, thereby ensuring the real-time and accuracy of the measurement data. The abnormal change monitoring data of impedance is further obtained through dynamic fitting and deviation analysis, which is helpful to discover the abnormal change trend of impedance in real time, monitor the battery health status in real time, and finally warn of abnormal changes in time, provide early warning of potential risks, and improve the safety of battery cells.

[0090] Example 2

[0091] See also Figure 4 , Figure 4 A schematic diagram of the module structure of a battery cell fault warning system based on dynamic impedance fitting is provided in an embodiment of the present invention; Figure 4 As shown, the embodiment of the present invention proposes a battery cell fault early warning system based on dynamic impedance fitting, including: an initial impedance test module 401, an impedance observation module 402, an impedance prediction module 403, an abnormal change analysis module 404 and an early warning module 405;

[0092] The initial impedance test module 401 is used to perform an impedance test on a target battery, obtain an impedance value at an initial moment, and charge the target battery;

[0093] The impedance observation module 402 is used to record the impedance of the target battery at each time point through an excitation current of a preset frequency to obtain a real-time impedance observation value;

[0094] The impedance prediction module 403 is used to construct an exponential decay model and perform impedance fitting prediction on the real-time impedance observation value at each time point to obtain a real-time impedance prediction value;

[0095] As an example of this embodiment, see Figure 5 , Figure 5 A schematic diagram of the structure of an impedance prediction module of a cell fault warning system based on dynamic impedance fitting is provided in an embodiment of the present invention; Figure 5 As shown, the impedance prediction module 403 is used to construct an exponential decay model and perform impedance prediction on the target battery at each time point to obtain a real-time impedance prediction value, including:

[0096] Model building unit 501, impedance prediction unit 502 and impedance value acquisition unit 503;

[0097] The model building unit 501 is used to build an exponential decay model based on the impedance value at the initial moment and a preset decay constant;

[0098] The impedance prediction unit 502 is used to predict the impedance value of the target battery at each time point through the exponential decay model during the charging process to obtain a second real-time impedance change curve;

[0099] The impedance value acquisition unit 503 is used to acquire a real-time impedance prediction value based on the second real-time impedance change curve.

[0100] The abnormal change analysis module 404 is used to perform residual fitting and deviation analysis on the real-time impedance observation value and the real-time impedance prediction value to obtain battery abnormal change monitoring data;

[0101] As an example of this embodiment, see Figure 6 , Figure 6 A schematic diagram of the structure of an abnormal change analysis module of a battery cell fault early warning system based on dynamic impedance fitting is provided in an embodiment of the present invention; Figure 6 As shown, the abnormal change analysis 404 module is used to perform residual fitting and deviation analysis on the real-time impedance observation value and the real-time impedance prediction value to obtain battery abnormal change monitoring data, including:

[0102] A residual calculation unit 601, a residual fitting unit 602 and an abnormality analysis unit 603;

[0103] The residual calculation unit 601 is used to obtain an impedance residual by subtracting the real-time impedance observation value from the real-time impedance prediction value;

[0104] The residual fitting unit 602 is used to fit the impedance residual by minimizing the residual square sum to obtain a fitting residual;

[0105] The abnormality analysis unit 603 is used to analyze the residual distribution and residual size of the fitting residual to obtain battery abnormal change monitoring data.

[0106] The warning module 405 is used to issue a warning when a target battery cell fails based on the battery abnormal change monitoring data.

[0107] As an example of this embodiment, see Figure 7 , Figure 7 A schematic diagram of the structure of an early warning module of a battery cell fault early warning system based on dynamic impedance fitting is provided in one embodiment of the present invention. Figure 7 As shown, the early warning module 405 is used to issue an early warning when a target battery cell fails based on the battery abnormal change monitoring data, including:

[0108] Residual absolute value calculation unit 701, first warning unit 702 and second warning unit 703;

[0109] The residual absolute value calculation unit 701 is used to calculate the absolute value of the impedance residual at each time point based on the battery abnormal change monitoring data to obtain the impedance residual absolute value;

[0110] The first warning unit 702 is used to determine that the target battery cell has failed and issue a warning if the absolute value of the impedance residual is greater than the fitting residual;

[0111] The second warning unit 703 is used to determine that a target battery cell fails and issue a warning if the distribution of the impedance residual does not meet the fitting residual distribution requirement.

[0112] An embodiment of the present invention proposes a battery cell fault warning system based on dynamic impedance fitting. The initial impedance test module and the impedance prediction module use an exponential decay model to predict the battery impedance during the charging process, providing a data basis for the dynamic change fitting of the battery impedance data. The impedance observation module uses an excitation current of a preset frequency to record the real-time impedance of the battery, which can effectively reduce high-frequency noise interference. The impedance prediction module uses an exponential decay model to more accurately capture the change trend of impedance over time, ensuring the real-time and accuracy of the measurement data. The abnormal change analysis module is further used to perform dynamic fitting and deviation analysis to obtain abnormal impedance change monitoring data, which is helpful to discover the abnormal impedance change trend in real time and monitor the battery health status in real time. Finally, the early warning module promptly warns of abnormal changes, provides early warning of potential risks, and improves the safety of battery cells.

[0113] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

[0114] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example" or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. Moreover, the described specific features, structures, materials or characteristics may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples, unless they are contradictory.

[0115] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

Claims

1. A cell fault early warning method based on dynamic impedance fitting, characterized in that: include: Performing an impedance test on a target battery to obtain an impedance value at an initial moment and charging the target battery; The impedance of the target battery is recorded at each time point by an excitation current of a preset frequency to obtain a real-time impedance observation value; Constructing an exponential decay model and performing impedance fitting prediction on the real-time impedance observation value at each time point to obtain a real-time impedance prediction value; Performing residual fitting and deviation analysis on the real-time impedance observation value and the real-time impedance prediction value to obtain battery abnormal change monitoring data; Based on the abnormal battery change monitoring data, an early warning is issued when a target battery cell fails.

2. A cell fault early warning method based on dynamic impedance fitting as claimed in claim 1, characterized in that: The step of performing an impedance test on a target battery, obtaining an impedance value at an initial moment, and charging the target battery comprises: Fully discharge the battery to be tested to obtain a target battery; Testing the impedance value between the positive and negative electrodes of the target battery to obtain the impedance value at the initial moment; Based on a preset constant current, the target battery is charged with a constant current.

3. A cell fault early warning method based on dynamic impedance fitting as claimed in claim 1, characterized in that: The impedance of the target battery is recorded at each time point by the excitation current of the preset frequency to obtain a real-time impedance observation value, including: During the charging process, based on a preset time interval, the impedance of the target battery is recorded by the excitation current of the preset frequency to obtain a first real-time impedance change curve; Based on the first real-time impedance change curve, a real-time impedance observation value is obtained.

4. A cell fault early warning method based on dynamic impedance fitting as claimed in claim 1, characterized in that: The exponential decay model is constructed and impedance fitting prediction is performed on the real-time impedance observation value at each time point to obtain the real-time impedance prediction value, including: Based on the impedance value at the initial moment and the preset decay constant, an exponential decay model is constructed; During the charging process, the real-time impedance observation value at each time point is fitted by the exponential decay model to obtain a second real-time impedance change curve; Based on the second real-time impedance change curve, a real-time impedance prediction value is obtained.

5. A cell fault early warning method based on dynamic impedance fitting as claimed in claim 1, characterized in that: Performing residual fitting and deviation analysis on the real-time impedance observation value and the real-time impedance prediction value to obtain battery abnormal change monitoring data, including: Obtaining an impedance residual by subtracting the real-time impedance observation value from the real-time impedance prediction value; Fitting the impedance residual by minimizing the residual square sum to obtain a fitting residual; The residual distribution and residual size of the fitting residual are analyzed to obtain battery abnormal change monitoring data.

6. A cell fault early warning method based on dynamic impedance fitting as claimed in claim 5, characterized in that: The method of issuing an early warning when a target battery cell fails based on the battery abnormal change monitoring data includes: Based on the battery abnormal change monitoring data, calculating the absolute value of the impedance residual at each time point to obtain the absolute value of the impedance residual; If the absolute value of the impedance residual is greater than the fitting residual, it is determined that the target battery cell has failed and an early warning is issued; If the distribution of the impedance residual does not meet the fitting residual distribution requirement, it is determined that the target battery cell has failed and an early warning is issued.

7. A battery cell fault warning system based on dynamic impedance fitting, characterized in that: Said, including: Initial impedance test module, impedance observation module, impedance prediction module, abnormal change analysis module and early warning module; The initial impedance test module is used to perform an impedance test on the target battery, obtain an impedance value at the initial moment and charge the target battery; The impedance observation module is used to record the impedance of the target battery at various time points through an excitation current of a preset frequency to obtain a real-time impedance observation value; The impedance prediction module is used to construct an exponential decay model and perform impedance fitting prediction on the real-time impedance observation value at each time point to obtain a real-time impedance prediction value; The abnormal change analysis module is used to perform residual fitting and deviation analysis on the real-time impedance observation value and the real-time impedance prediction value to obtain battery abnormal change monitoring data; The early warning module is used to issue an early warning when a target battery cell fails based on the battery abnormal change monitoring data.

8. A battery cell fault early warning system based on dynamic impedance fitting as claimed in claim 7, characterized in that: The impedance prediction module is used to construct an exponential decay model and perform impedance fitting prediction on the real-time impedance observation value at each time point to obtain a real-time impedance prediction value, including: A model building unit, an impedance prediction unit and an impedance value acquisition unit; The model building unit is used to build an exponential decay model based on the impedance value at the initial moment and a preset decay constant; The impedance prediction unit is used to obtain a second real-time impedance change curve by fitting the real-time impedance observation value at each time point through the exponential decay model during the charging process; The impedance value acquisition unit is used to acquire a real-time impedance prediction value based on the second real-time impedance change curve.

9. A battery cell fault early warning system based on dynamic impedance fitting as claimed in claim 7, characterized in that: The abnormal change analysis module is used to perform residual fitting and deviation analysis on the real-time impedance observation value and the real-time impedance prediction value to obtain battery abnormal change monitoring data, including: Residual calculation unit, residual fitting unit and abnormality analysis unit; The residual calculation unit is used to obtain an impedance residual by subtracting the real-time impedance observation value from the real-time impedance prediction value; The residual fitting unit is used to fit the impedance residual by minimizing the residual square sum to obtain a fitting residual; The abnormality analysis unit is used to analyze the residual distribution and residual size of the fitting residual to obtain battery abnormal change monitoring data.

10. A battery cell fault early warning system based on dynamic impedance fitting as claimed in claim 7, characterized in that: The early warning module is used to issue an early warning when a target battery cell fails based on the battery abnormal change monitoring data, including: A residual absolute value calculation unit, a first warning unit and a second warning unit; The residual absolute value calculation unit is used to calculate the absolute value of the impedance residual at each time point based on the battery abnormal change monitoring data to obtain the impedance residual absolute value; The first warning unit is used to determine that the target battery cell has failed and issue a warning if the absolute value of the impedance residual is greater than the fitting residual; The second warning unit is used to determine that a target battery cell fails and issue a warning if the distribution of the impedance residual does not meet the fitting residual distribution requirement.

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