A management method for power battery packs

Abstract

This application relates to a management method for a power battery pack, belonging to the field of vehicle manufacturing technology. The method includes: for each cell in the power battery pack to be tested, performing AC internal resistance deviation diagnosis, capacity decay diagnosis, and voltage change rate trajectory anomaly diagnosis on the cell, obtaining the cell's AC internal resistance value, internal resistance anomaly judgment value, cell capacity estimate, capacity anomaly judgment value, and voltage cumulative anomaly judgment value, respectively. Based on the internal resistance anomaly judgment value, capacity anomaly judgment value, and voltage cumulative anomaly judgment value, the cell is determined to be faulty; the number and location of faulty cells are counted; if the number of faulty cells is less than or equal to a preset maximum allowable short-circuit number, the faulty cells are short-circuited based on their location, and the system parameters of the short-circuited power battery pack are reconstructed; if the number of faulty cells is greater than the maximum allowable short-circuit number, the power battery pack to be tested is replaced. Using this application can improve the accuracy of faulty cell identification.

Description

Technical Field

[0001] This application relates to the field of vehicle manufacturing technology, and in particular to a method for managing a power battery pack. Background Technology

[0002] Lithium-ion battery packs typically consist of dozens to hundreds of cells connected in series and parallel. Due to manufacturing defects, harsh operating environments, and long-term cyclic aging, individual cells in a battery pack may fail before the entire pack.

[0003] Currently, power battery packs commonly employ potting encapsulation for structural strength, thermal management, and safety considerations. While potting materials effectively secure the cells and enhance thermal conductivity and insulation, they also completely seal the cells within the battery pack, preventing individual cell replacement and repair. Due to these encapsulation limitations, repairs to power battery packs often require replacing the entire pack, resulting in resource waste. Without repair, failed cells become performance bottlenecks, leading to reduced capacity and power, and creating a risk of thermal runaway. Summary of the Invention

[0004] Therefore, it is necessary to provide a method for managing a power battery pack to address the aforementioned technical problems. The method includes: For each cell in the power battery pack to be tested, AC internal resistance deviation diagnosis, capacity decay diagnosis and voltage change rate trajectory anomaly diagnosis are performed on the cell to obtain the cell's AC internal resistance value, internal resistance anomaly judgment value, cell capacity estimate value, capacity anomaly judgment value and voltage cumulative anomaly judgment value, respectively. Based on the internal resistance abnormality judgment value, the capacity abnormality judgment value, and the cumulative voltage abnormality judgment value, the cell is determined to be faulty. The number and location of failed battery cells are counted. If the number of failed battery cells is less than or equal to the preset maximum allowable number of short circuits, the failed battery cells are short-circuited based on their location, and the system parameters of the power battery pack after short circuit are reconstructed. If the number of failed battery cells exceeds the maximum allowable number of short circuits, then the power battery pack under test shall be replaced.

[0005] As an optional implementation, the AC internal resistance deviation diagnosis includes: During the vehicle stationary phase or charging interval phase, a sinusoidal alternating current of a preset frequency is applied to each cell in the power battery pack to be tested. Measure the voltage response amplitude of each of the battery cells to the sinusoidal alternating current, and calculate the AC internal resistance of each of the battery cells; Calculate the average value and standard deviation of the AC internal resistance of each of the aforementioned cells; The deviation of the AC internal resistance of each cell is calculated based on the AC internal resistance value, the average value, and the standard deviation of each cell. For each of the aforementioned cells, if the AC internal resistance deviation of the cell is less than or equal to a preset internal resistance deviation threshold, then the preset normal value is assigned to the internal resistance abnormality judgment value. If the AC internal resistance deviation of the battery cell is greater than the preset internal resistance deviation threshold, then the preset abnormal value is assigned to the internal resistance abnormality judgment value.

[0006] As an optional implementation, the capacity decay diagnosis includes: For each of the aforementioned battery cells, the voltage, current, and temperature of the battery cell are collected; Based on a pre-established first-order RC equivalent circuit model of the battery cell, the current of the battery cell is used as the state prediction input, the voltage is used as the observation, and the model parameters of the first-order RC equivalent circuit model are corrected by combining temperature. The estimated value of the battery cell capacity is calculated by the extended Kalman filter algorithm. Calculate the average and standard deviation of the estimated cell capacity for each of the aforementioned cells; The capacity deviation of the battery cell is calculated based on the estimated cell capacity, the average value, and the standard deviation. If the capacity deviation of the battery cell is less than or equal to the preset capacity deviation threshold, then the preset normal value is assigned to the capacity anomaly determination value. If the capacity deviation of the battery cell is greater than the capacity deviation threshold, then a preset abnormal value is assigned to the capacity abnormality judgment value.

[0007] As an optional implementation, the voltage change rate trajectory anomaly diagnosis includes: During the constant current charging or constant current discharging phase, the voltage of each battery cell is collected. Calculate the rate of voltage change of the battery cell at each sampling time based on the collected voltage. At the same acquisition time, the median value of the voltage change rate of each of the battery cells is obtained; The instantaneous voltage deviation of the battery cell at each sampling moment is determined based on the voltage change rate of the battery cell and the median value. During the constant current charging phase or the constant current discharging phase, the instantaneous voltage deviation of the battery cell is accumulated to determine the cumulative voltage deviation of the battery cell. If the cumulative voltage deviation of the battery cell is less than or equal to the preset cumulative deviation threshold, then the preset normal value is assigned to the cumulative voltage abnormality judgment value. If the cumulative voltage deviation of the battery cell is greater than the cumulative deviation threshold, then a preset abnormal value is assigned to the cumulative voltage abnormality judgment value.

[0008] As an optional implementation, the step of determining the cell's failure based on the internal resistance anomaly determination value, the capacity anomaly determination value, and the cumulative voltage anomaly determination value includes: The failure confidence level of the battery cell is calculated based on the internal resistance anomaly determination value, the capacity anomaly determination value, and the cumulative voltage anomaly determination value. If the failure confidence level is greater than or equal to the preset failure confidence level threshold, the cell is determined to be a failed cell. If the failure confidence level is less than the failure confidence level threshold, the cell is determined to be a valid cell.

[0009] As an optional implementation, the system parameter reconstruction of the short-circuited power battery pack includes: Collect the total voltage and total internal resistance of the power battery pack; Based on the ratio between the number of effective cells after shorting and the total number of cells before shorting, the original lower limit of total voltage and the original upper limit of total voltage are scaled and updated to update the lower limit of total voltage and the upper limit of total voltage of the power battery pack. Obtain the open-circuit voltage and state of charge of the effective battery cell at the same temperature; For each temperature, the open-circuit voltage and state of charge at that temperature are fitted to determine the voltage-state of charge fitting curve. Calculate the total internal resistance of the effective cells to obtain the equivalent internal resistance of the power battery pack after short-circuiting; For each of the effective cells, based on the estimated capacity and temperature of the effective cell, the allowable charging current and allowable discharging current of the cell are looked up in a preset charging and discharging current lookup table. The allowable charging power boundary is determined based on the total voltage limit, the allowable charging current, and the equivalent internal resistance; Calculate the allowable discharge power boundary based on the total voltage lower limit, the allowable discharge current, and the equivalent internal resistance; The minimum value among the estimated capacity values ​​of each effective cell is determined as the total capacity of the power battery pack.

[0010] As an optional implementation, after reconstructing the system parameters of the short-circuited power battery pack, the method further includes: Coordinated control of the entire vehicle operation; The power battery pack is subjected to safety verification, and enters a degraded operation mode after the verification is passed. During the degraded operation, the effective cells of the power battery pack are monitored, and an early warning is issued when an abnormal trend is detected.

[0011] As an optional implementation, the coordinated control of the vehicle operation includes: Based on the total voltage upper limit and total voltage lower limit obtained from the reconstructed system parameters, adjust the operating state of the motor controller; Based on the allowable discharge power boundary, the power of the drive system and the power of the accessories are allocated and controlled according to a preset priority. During the charging process, the allowable charging current and the total voltage limit are sent to the on-board charger so that the on-board charger can adjust the output voltage and current. When an abnormality is detected in the valid battery cell, a graded power reduction is performed.

[0012] As an optional implementation, the safety verification includes electrical safety verification and functional safety verification. The step of performing safety verification on the power battery pack and entering a degraded operation mode after successful verification includes: Obtain the total voltage and insulation resistance of the power battery pack; If the total voltage is between the lower limit and the upper limit of the total voltage, and the insulation resistance is greater than the preset insulation threshold, then the power battery pack is determined to have passed the electrical safety verification. The power battery pack is tested by charging and discharging with a small current. If the total capacity and power limit response of the power battery pack meet the preset consistency requirements, the power battery pack is determined to have passed the functional safety verification. After verification, the downgrade level is determined based on the proportion of the number of failed cells to the original total number of cells; The maximum output power of the power battery pack, the maximum vehicle speed, and the charging and discharging capacity are limited according to the downgrade level.

[0013] As an optional implementation, the monitoring of the effective cells of the power battery pack during degraded operation and the issuance of early warnings when abnormal trends are detected include: Collect the voltage, temperature, and internal resistance of the effective battery cells; The voltage dispersion, temperature change rate, and internal resistance change trend of the effective battery cell are determined respectively. A cell degradation assessment model is constructed to predict the failure risk of the effective cells; When the predicted failure risk of the effective battery cell exceeds the preset failure risk threshold, an early warning message is generated, prompting the user to perform maintenance.

[0014] This application provides a management method for a power battery pack, comprising: for each cell in the power battery pack to be tested, performing AC internal resistance deviation diagnosis, capacity decay diagnosis, and voltage change rate trajectory anomaly diagnosis on the cell, respectively obtaining the cell's AC internal resistance value, internal resistance anomaly determination value, cell capacity estimate value, capacity anomaly determination value, and voltage cumulative anomaly determination value. Based on the internal resistance anomaly determination value, the capacity anomaly determination value, and the voltage cumulative anomaly determination value, the cell is determined to be faulty; the number and location of the faulty cells are counted; if the number of faulty cells is less than or equal to a preset maximum allowable short-circuit number, the faulty cells are short-circuited based on their location, and the system parameters of the short-circuited power battery pack are reconstructed; if the number of faulty cells is greater than the maximum allowable short-circuit number, the power battery pack to be tested is replaced.

[0015] The technical solutions provided by the embodiments of this application bring at least the following beneficial effects: First, this application performs AC internal resistance deviation diagnosis, capacity decay diagnosis, and voltage change rate trajectory anomaly diagnosis on each cell in the power battery pack under test. This obtains cell status information from three different dimensions: internal resistance characteristics, capacity characteristics, and dynamic voltage response characteristics, yielding AC internal resistance values, estimated capacity values, and voltage change-related parameters. Since different failure mechanisms (such as increased internal resistance, capacity decay, or micro-short circuits) manifest differently across different characteristic dimensions, obtaining multi-source judgment results through multiple diagnostic methods avoids misjudgments or omissions caused by relying on a single indicator, thereby improving the accuracy of identifying failed cells.

[0016] Then, the cell is further evaluated by combining the internal resistance anomaly judgment value, capacity anomaly judgment value, and cumulative voltage anomaly judgment value to achieve a comprehensive assessment of the cell's failure state. This combined judgment method improves the reliability of failure judgment by jointly analyzing multiple anomaly judgment results, ensuring that the cell is only judged as a failed cell when it exhibits abnormalities in multiple dimensions.

[0017] Subsequently, this application statistically analyzes the number and location of failed battery cells, and when the number of failed cells is less than or equal to the preset maximum allowable short-circuit number, short-circuit the failed cells based on their location. Since the short-circuit operation allows current to bypass the failed cells, it avoids the limiting effect of the failed cells on the overall battery pack voltage and power output, allowing the remaining healthy and effective cells to continue operating, thus restoring the basic function of the battery pack without disassembling it. After short-circuiting the failed cells, the system parameters of the power battery pack are reconfigured. By redetermining the key parameters of the battery pack based on the number of effective cells after short-circuiting, the battery management system can manage the battery pack based on the updated parameters, ensuring that subsequent operation matches the new battery structure. This avoids voltage estimation errors or inaccurate power control caused by parameter mismatch, improving the stability and safety of system operation.

[0018] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 A schematic diagram of the structure of a power battery pack management system provided in an embodiment of this application; Figure 2 A flowchart illustrating a method for managing a power battery pack, as provided in an embodiment of this application; Figure 3 A flowchart illustrating an AC internal resistance deviation diagnosis method provided in this application embodiment; Figure 4 A flowchart of a capacity decay diagnosis method provided in an embodiment of this application; Figure 5 This is a flowchart of a voltage change rate trajectory anomaly diagnosis method provided in an embodiment of this application. Detailed Implementation

[0021] 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.

[0022] The power battery pack management method provided in this application embodiment can be applied to the power battery pack management system. For example... Figure 1 As shown, the management system of this power battery pack includes a battery management system 110 and a vehicle controller 120. The battery management system 110 and the vehicle controller 120 can be connected via an onboard communication bus 130, which can be a CAN bus, LIN bus, or Ethernet bus, etc. The battery management system 110 sends battery status information and reconstructed system parameters to the vehicle controller 120. The vehicle controller 120 controls the vehicle operation based on the system parameters and sends control requests or operating commands to the battery management system 110, thereby achieving coordinated control between the power battery pack and the vehicle system.

[0023] The following will describe in detail a method for managing a power battery pack provided in this application, with reference to specific implementation methods. Figure 2 A flowchart illustrating a power battery pack management method provided in this application embodiment is shown below. Figure 2 As shown, the specific steps are as follows: S201, for each cell in the power battery pack to be tested, perform AC internal resistance deviation diagnosis, capacity decay diagnosis and voltage change rate trajectory anomaly diagnosis on the cell, and obtain the AC internal resistance value, internal resistance anomaly judgment value, cell capacity estimate value, capacity anomaly judgment value and voltage cumulative anomaly judgment value of the cell respectively.

[0024] In practice, the internal resistance of the cells within a power battery pack is a parameter strongly correlated with temperature. During normal operation, the internal resistance of a cell naturally fluctuates with temperature changes. For example, when the battery pack is in a low-temperature environment (such as winter), the internal resistance of all cells will normally increase. In a high-temperature environment, the internal resistance of all cells will normally decrease. If only a fixed internal resistance threshold is set for monitoring, the battery management system may falsely report that all cells are abnormal, generating numerous false alarms, or it may falsely report that all cells are normal, masking true early-stage faults. Temperature sensors are typically placed at the module level or on the cell surface, which introduces delays and errors. When side reactions begin to occur inside the cell (such as SEI film thickening or lithium dendrite growth), leading to an increase in internal resistance, the heat generation power increases. However, it takes time for the heat to transfer to the surface and be detected by the temperature sensor. By the time the temperature becomes significantly abnormal, the fault may have already progressed to a mid-to-late stage. Furthermore, cell temperature is affected by the unevenness of the cooling system, adjacent cells, and ambient temperature, meaning that an individual cell with a higher temperature may not necessarily be faulty; it may simply be located in an unfavorable heat dissipation position. Therefore, in this embodiment of the application, the battery management system can collect data such as voltage, current and temperature of each cell in the power battery pack to be tested, and perform AC internal resistance deviation diagnosis, capacity decay diagnosis and voltage change rate trajectory anomaly diagnosis, respectively generate corresponding internal resistance anomaly judgment value, capacity anomaly judgment value and voltage cumulative anomaly judgment value, analyze the cell from multiple dimensions, and avoid false alarms and missed alarms of cell faults.

[0025] As an optional implementation method, Figure 3 A flowchart of an AC internal resistance deviation diagnosis method provided in this application embodiment is shown below. Figure 3 As shown, the specific steps for diagnosing AC internal resistance deviation in S201 are as follows: S301 applies a sinusoidal alternating current of a preset frequency to each cell in the power battery pack under test during vehicle stationary phases or charging intervals.

[0026] In practice, the battery cell exhibits an approximately linear response under small-signal AC excitation, with the voltage response and current satisfying an Ohmic relationship. By applying a small-amplitude AC current, the battery's equivalent internal resistance information can be extracted without altering its operating state. Simultaneously, during vehicle stationary periods or charging intervals, the battery current fluctuation is minimal, reducing noise interference and improving measurement accuracy. The preset frequency of the sinusoidal AC current can be 5Hz-20Hz, with an amplitude of a small-signal current to avoid affecting normal battery operation.

[0027] S302 measures the voltage response amplitude of each cell to a sinusoidal alternating current and calculates the AC internal resistance of each cell.

[0028] In practice, the change in battery terminal voltage is mainly determined by its ohmic internal resistance. Polarization effects have a relatively small impact on high-frequency, small-amplitude signals; therefore, the voltage-to-current ratio can reflect the equivalent internal resistance of the cell. When a cell ages or its internal structure degrades, its internal resistance typically increases, leading to an increase in the voltage response amplitude. Therefore, the AC internal resistance can be calculated by collecting the voltage response amplitude of each cell under AC excitation signal and combining it with the known AC current amplitude. The specific formula is as follows: R i =ΔV i / ΔI; Among them, R i Let ΔV be the AC internal resistance of cell i. i Let ΔI be the voltage response amplitude of cell i, and ΔI be the AC current amplitude.

[0029] S303 calculates the average and standard deviation of the AC internal resistance of each cell.

[0030] In practice, under normal circumstances, the consistency of cells within the same battery is relatively good. Their internal resistance values ​​are distributed within a certain range and approximately follow a statistical distribution. The overall level can be reflected by calculating the average value, while the degree of dispersion can be reflected by the standard deviation. Therefore, the AC internal resistance values ​​of all cells within the same battery can be statistically processed to calculate the average value R. avg and standard deviation σ.

[0031] S304 calculates the AC internal resistance deviation of each cell based on its AC internal resistance, average value, and standard deviation.

[0032] In practice, by comparing the AC internal resistance of a single cell with the overall average and normalizing it using the standard deviation, the degree to which the cell deviates from the overall level can be quantified. A greater deviation indicates a more significant difference between the cell and a normal cell, thus suggesting a higher likelihood of an anomaly. The formula for calculating the AC internal resistance deviation is as follows: δ i =∣R i -R avg | / σ; Where, δ i R is the deviation of the AC internal resistance of cell i. i R is the AC internal resistance of cell i. avg σ is the average value of the AC internal resistance, and σ is the standard deviation.

[0033] S305: For each cell, if the AC internal resistance deviation of the cell is less than or equal to the preset internal resistance deviation threshold, then the preset normal value is assigned to the internal resistance abnormality judgment value.

[0034] In practice, when the AC internal resistance deviation of a battery cell is less than or equal to a preset internal resistance deviation threshold, it indicates that the cell is in good overall consistency with the power battery pack, and its internal structure has not deteriorated significantly. Therefore, it is judged as a normal or effective cell. The normal value is used to indicate that the cell has not experienced any abnormalities.

[0035] S306 If the AC internal resistance deviation of the battery cell is greater than the preset internal resistance deviation threshold, then the preset abnormal value is assigned to the internal resistance abnormality judgment value.

[0036] In practice, when the AC internal resistance deviation of a battery cell exceeds a preset internal resistance deviation threshold, it indicates that its internal resistance has significantly deviated from the normal range for battery cells. This phenomenon is usually related to problems such as cell aging, electrode damage, or poor internal contact. Preferably, the normal value is 0, and the abnormal value is 1.

[0037] As an optional implementation method, Figure 4 A flowchart of a capacity attenuation diagnosis method provided in an embodiment of this application is shown below. Figure 4 As shown, the specific steps for capacity decay diagnosis in S201 are as follows: S401 collects the voltage, current and temperature of each battery cell.

[0038] In practice, the capacity characteristics of a battery cell cannot be directly measured and must be indirectly estimated using external measurable quantities such as voltage and current. Current determines the charge input and output process, voltage reflects the internal state of the cell, and temperature affects the cell's polarization characteristics and internal resistance parameters. The battery management system can collect the terminal voltage, current, and temperature of each cell at a preset sampling period (e.g., 100ms) and filter the collected data to reduce noise interference.

[0039] S402, based on a pre-established first-order RC equivalent circuit model of the battery cell, uses the current of the battery cell as the state prediction input, the voltage as the observation, and combines the temperature to correct the model parameters of the first-order RC equivalent circuit model. The battery cell capacity estimate is then calculated using the extended Kalman filter algorithm.

[0040] In implementation, the first-order RC equivalent circuit model includes an open-circuit voltage source, an ohmic internal resistance, and an RC network composed of polarization resistors and polarization capacitors. Cell capacity is used as the system state variable, current as the input for state prediction, and actual measured voltage as the observation for state correction. Simultaneously, the internal resistance and polarization parameters in the model are corrected based on temperature lookup tables or functional relationships. Based on this, the extended Kalman filter algorithm is used to recursively estimate the cell capacity, and the estimated cell capacity value is calculated based on the relationship between the change in cell capacity and the cumulative current. The formula for the cell capacity changing with the integral of current is: SOC k =SOC k-1 -I k Δt / Q; Where Q is the cell capacity, and SOC is the state of charge. k Let SOC be the state of charge at the current time k. k-1 For the state of charge at the previous sampling time k-1, I k Let Δt be the cell current at the current time k, and let Δt be the time interval between two adjacent sampling times k and k-1.

[0041] S403 calculates the average and standard deviation of the estimated cell capacity for each cell.

[0042] In practice, under normal circumstances, the capacity decay of cells in the same batch is consistent, and their capacity distribution falls within a certain range. Statistical analysis can establish an overall capacity distribution benchmark, thereby identifying abnormal cells with significant deviations. Therefore, the battery management system can perform statistical analysis on the capacity estimates of all cells within the same battery pack, calculating the average value and standard deviation.

[0043] S404. Calculate the capacity deviation of the battery cell based on its estimated capacity, average value, and standard deviation.

[0044] In practice, by comparing the capacity of a single cell with the overall average capacity and performing standard deviation normalization, the degree to which the cell's capacity deviates from the overall level can be quantified. The greater the deviation, the more severe the capacity degradation of the cell. The formula for calculating the capacity deviation of the cell is as follows: γ i =|Q avg -Q i | / σ q ; Where, γ i Q represents the capacity deviation of cell i. avg Q is the average value. i Let σ be the estimated cell capacity of cell i. q The standard deviation is denoted as .

[0045] S405, if the capacity deviation of the cell is less than or equal to the preset capacity deviation threshold, then the preset normal value is assigned to the capacity abnormality judgment value.

[0046] In practice, when the capacity of a battery cell is significantly lower than the average level, it indicates that the cell has undergone significant aging or loss of active material, resulting in a decrease in its usable capacity and limiting the energy output of the entire battery pack. Therefore, it is identified as an abnormal cell. The capacity deviation threshold can be determined based on experimental calibration, for example, by setting it to 2 or 3.

[0047] S406 If the capacity deviation of the cell is greater than the capacity deviation threshold, the preset abnormal value is assigned to the capacity abnormality judgment value.

[0048] In practice, when the cell capacity is within the normal distribution range, it indicates that its performance has not significantly degraded and can meet normal usage requirements; therefore, it is judged to be a normal cell. Preferably, the normal value is 0, and the abnormal value is 1.

[0049] As an optional implementation method, Figure 5 A flowchart of a voltage change rate trajectory anomaly diagnosis method provided in this application embodiment is shown below. Figure 5 As shown, the specific steps for diagnosing voltage change rate trajectory anomalies in S201 are as follows: S501 collects the voltage of each battery cell during the constant current charging or constant current discharging phase.

[0050] In practice, under constant current conditions, the terminal voltage of the battery cell exhibits a continuous changing trend with the state of charge. Under the same current conditions, the voltage change trajectory of each healthy battery cell should be consistent. In this embodiment, during the constant current charging or discharging phase, the voltage of each battery cell is collected at a preset sampling period (e.g., 100ms), and the collected data is filtered to reduce noise interference.

[0051] S502 calculates the voltage change rate of the battery cell at each sampling time based on the collected voltage.

[0052] In practice, the voltage change rate reflects how quickly the cell voltage changes over time, providing a better characterization of the cell's dynamic response compared to a single voltage value. When a cell experiences capacity decay or abnormal internal resistance, its voltage change rate will deviate from that of a normal cell. Therefore, the battery management system can calculate the voltage change rate based on the voltage difference between adjacent sampling times. The calculation formula is as follows: ΔV i (t)=[V i (t)-V i [(t-Δt)] / Δt; Where, ΔV i (t) represents the rate of change of voltage of cell i at sampling time t, V i (t) represents the voltage of cell i at sampling time t, V. i (t-Δt) represents the voltage of cell i at sampling time t-Δt, where Δt is the sampling time interval.

[0053] S503 acquires the median value of the voltage change rate of each cell at the same acquisition time.

[0054] In implementation, since there may be individual abnormal cells in the battery pack, their voltage change rate may deviate significantly. Using the median value as a statistical benchmark can reduce the impact of extreme values ​​on the overall judgment, thereby improving robustness. At each sampling time, the battery management system sorts the voltage change rates of all cells and selects the median value as the reference benchmark value at that time.

[0055] S504, determine the instantaneous voltage deviation of the cell at each sampling moment based on the voltage change rate and median value of the cell.

[0056] In practice, by comparing the difference between a single cell and the entire cell group, the degree of anomaly of that cell at the current moment can be quantified. The greater the deviation, the more abnormal the dynamic response of that cell. The formula for calculating the instantaneous voltage deviation is as follows: ε i (t)=|dV / dt i -Mdv|; Where, ε i (t) represents the instantaneous voltage deviation of cell i at sampling time t, dV / dt. i Let be the voltage change rate of cell i, and Mdv be the median value.

[0057] S505, during the constant current charging or constant current discharging phase, accumulates the instantaneous voltage deviation of the cell to determine the cumulative voltage deviation of the cell.

[0058] In practice, deviations at a single moment may be caused by noise or transient disturbances, while persistent deviations better reflect the true abnormal state of the battery cell. Accumulating the deviation over time can improve the stability of anomaly detection. The instantaneous voltage deviations at each moment are accumulated or integrated throughout the constant current phase, for example: D i =∑ε i (t); Among them, D i ε represents the cumulative voltage deviation of cell i. i (t) represents the instantaneous voltage deviation of cell i at sampling time t.

[0059] S506 If the cumulative voltage deviation of the battery cell is less than or equal to the preset cumulative deviation threshold, then the preset normal value is assigned to the voltage cumulative abnormality judgment value.

[0060] In practice, when the voltage variation trajectory of a battery cell is consistent with that of most battery cells, it indicates that its performance has not shown any significant abnormalities. The optimal normal value is 0.

[0061] S507 If the cumulative voltage deviation of the battery cell is greater than the cumulative deviation threshold, the preset abnormal value is assigned to the cumulative voltage abnormality judgment value.

[0062] In practice, when a battery cell continuously deviates from its normal trajectory throughout the entire charging and discharging process, it indicates an abnormal change in its internal state (such as capacity or internal resistance), and therefore it can be identified as an abnormal battery cell. The preferred abnormal value is 1.

[0063] S202, based on the internal resistance abnormality judgment value, capacity abnormality judgment value and voltage cumulative abnormality judgment value, the cell is judged to be faulty.

[0064] In implementation, the battery management system can integrate the internal resistance anomaly judgment values, capacity anomaly judgment values, and cumulative voltage anomaly judgment values ​​of each cell to determine cell failure. For example, a voting mechanism can be used for comprehensive judgment. If two or three of the internal resistance anomaly judgment values, capacity anomaly judgment values, and cumulative voltage anomaly judgment values ​​are abnormal, the cell is determined to be faulty; if only one or zero abnormal results are present, the cell is determined to be normal.

[0065] As an optional implementation, the specific steps in S202 for determining the failure of the battery cell based on the internal resistance anomaly determination value, the capacity anomaly determination value, and the cumulative voltage anomaly determination value are as follows: S601, calculate the failure confidence level of the battery cell based on the internal resistance abnormality judgment value, capacity abnormality judgment value and voltage cumulative abnormality judgment value.

[0066] In practice, different diagnostic methods characterize the cell's condition based on its internal resistance, capacity, and dynamic voltage response characteristics. Individual diagnostic results may be affected by operating conditions or noise, leading to misjudgments. By fusing multi-dimensional diagnostic results, the reliability of failure determination can be improved. The battery management system can weight or equally weight the internal resistance anomaly determination value, capacity anomaly determination value, and cumulative voltage anomaly determination value to calculate the cell's failure confidence level.

[0067] As an optional implementation, the formula for calculating the failure confidence level of the battery cell based on the internal resistance anomaly judgment value, capacity anomaly judgment value, and cumulative voltage anomaly judgment value is as follows: C i =(F i1 +F i2 +F i3 ) / 3; Among them, C i F represents the failure confidence level of cell i. i1 F is the abnormal internal resistance judgment value of cell i. i2 F is the abnormal capacity judgment value for cell i. i3 This is the cumulative abnormal voltage judgment value for cell i.

[0068] S602, if the failure confidence level is greater than or equal to the preset failure confidence level threshold, the cell is determined to be a failed cell.

[0069] In practice, if the failure confidence level is greater than or equal to the preset failure confidence level threshold, it indicates that the cell is abnormal in multiple dimensions, and the cell can be determined to be a failed cell.

[0070] S603, if the failure confidence level is less than the failure confidence level threshold, the cell is determined to be a valid cell.

[0071] In practice, if the failure confidence level is less than the failure confidence level threshold, the cell performs normally in multiple dimensions, with only a few dimensions showing abnormalities. There is a possibility of misjudgment, so the cell can be determined to be a valid cell.

[0072] S203: Count the number and location of failed battery cells. If the number of failed battery cells is less than or equal to the preset maximum allowable number of short circuits, short circuit the failed battery cells based on their location and reconstruct the system parameters of the power battery pack after short circuit.

[0073] In implementation, the battery management system (BMS) first determines the distribution of failed cells within the battery pack based on the failure assessment results. When the number of failed cells is within a controllable range, the positive and negative terminals of the corresponding failed cells are connected to the short-circuit bus via a pre-set external short-circuit interface in the battery pack, allowing current to bypass the failed cell and thus completing the cell short-circuit operation. After the short-circuit is completed, the effective number of series-connected cells in the power battery pack changes, and the voltage characteristics, power capability, and capacity characteristics of the battery pack change accordingly. Therefore, it is necessary to reconstruct the system parameters of the power battery pack so that the BMS can control the battery pack based on the updated battery structure.

[0074] As an optional implementation method, the specific steps for reconstructing the system parameters of the short-circuited power battery pack in S203 are as follows: S701 collects the total voltage and total internal resistance of the power battery pack.

[0075] During implementation, after short-circuiting some cells, the equivalent circuit structure of the power battery pack changes, leading to alterations in the overall voltage level and internal resistance characteristics. Therefore, it is necessary to re-acquire the basic electrical parameters of the current battery pack. The battery management system acquires the total voltage of the power battery pack after short-circuiting, for example, measuring it as 400V. Simultaneously, it can measure the total internal resistance of the battery pack using the pulse current method or AC injection method, for example, measuring it as 180mΩ.

[0076] S702 scales the original lower limit and upper limit of total voltage based on the ratio between the number of effective cells after shorting and the total number of cells before shorting, and updates the lower limit and upper limit of total voltage of the power battery pack.

[0077] In implementation, the battery pack has a series structure, and its total voltage is approximately proportional to the number of cells connected in series. When some cells are short-circuited, the total voltage capability decreases proportionally. The calculation formula is as follows: V min_new =V min_orig ×(nN fail ) / n; V max_new =V max_orig ×(nN fail ) / n; Among them, V min_new The updated lower limit of total voltage, V min_orig V is the lower limit of the original total voltage. max_new V is the updated total voltage limit. max_orig The original total voltage limit is given by N, where n is the total number of battery cells. failThis refers to the number of failed battery cells. For example, if the original battery pack consists of 100 cells connected in series with a voltage range of 300V-420V, and 3 cells are short-circuited, then the number of effective cells is 97, and the updated voltage range is 291V-407.4V.

[0078] Optionally, the battery management system can use a linear ramp method to gradually adjust the voltage limit to a new value within a preset time (such as 30 seconds) to avoid impacting the vehicle's electrical equipment.

[0079] S703 obtains the open-circuit voltage and state of charge of the effective cells at the same temperature.

[0080] In implementation, there is a corresponding relationship between open-circuit voltage and state of charge, and this relationship is greatly affected by temperature. To ensure modeling consistency, data needs to be obtained under the same temperature conditions. For example, at 25°C, the state of charge and corresponding open-circuit voltage data of effective cells can be selected. Table 1 is a table of state of charge and corresponding open-circuit voltage data at 25°C provided in the embodiments of this application, as shown in Table 1: Table 1 It can also obtain the capacity estimate of the corresponding battery cell, such as 95Ah or 100Ah.

[0081] S704 performs data fitting on the open-circuit voltage and state of charge at each temperature to determine the voltage-state of charge fitting curve.

[0082] In practice, polynomial fitting or table lookup interpolation can be used to fit the open-circuit voltage and state of charge data to obtain a new voltage-capacity relationship curve.

[0083] S705 calculates the total internal resistance of the effective cells to obtain the equivalent internal resistance of the power battery pack after short-circuiting.

[0084] In practice, the total internal resistance of a series-connected battery pack is equal to the sum of the internal resistances of each individual cell. After short-circuiting the cells, the total internal resistance changes with the number of effective cells. For example, if the internal resistance of a single cell is 2mΩ and there are 97 effective cells, then the equivalent internal resistance of the power battery pack after short-circuiting is 194mΩ.

[0085] S706: For each valid battery cell, based on the estimated capacity and temperature of the valid battery cell, look up the allowable charging current and allowable discharging current of the battery cell in a preset charging and discharging current lookup table.

[0086] In practice, the safe charging and discharging capability of a battery cell is affected by its capacity and temperature. Its safe current range can be obtained by looking up a table. For example, under conditions of 50% state of charge and a temperature of 25°C, the table shows that the allowable discharge current for a single battery cell is 200A and the allowable charging current is 150A.

[0087] S707 determines the allowable charging power boundary based on the total voltage limit, allowable charging current, and equivalent internal resistance.

[0088] In practice, during charging, the battery terminal voltage will rise due to internal resistance. To prevent exceeding the voltage limit, the influence of internal resistance needs to be considered comprehensively. The formula for calculating the allowable charging power boundary is as follows: P chg =(V max -I chg R sys )I chg ; Among them, P chg To allow charging power boundaries, V max I is the upper limit of the total voltage. chg To allow charging current, R sys This is the equivalent internal resistance.

[0089] S708 calculates the allowable discharge power boundary based on the total voltage lower limit, allowable discharge current, and equivalent internal resistance.

[0090] In practice, during the discharge process, the voltage will drop due to internal resistance. To prevent the voltage from falling below the lower limit, the maximum discharge power needs to be limited. The formula for calculating the allowable discharge power boundary is as follows: P dis =(V min -I dis R sys )I dis ; Among them, P dis To define the allowable discharge power boundary, V min -I is the lower limit of the total voltage. dis To allow the discharge current, R sys This is the equivalent internal resistance.

[0091] S709 determines the minimum value among the estimated capacity values ​​of each effective cell as the total capacity of the power battery pack.

[0092] In practice, in a series system, the capacity is limited by the weakest cell; taking the minimum value avoids the risk of overcharging or over-discharging. For example, if the capacity of each cell ranges from 95Ah to 100Ah, then 95Ah is taken as the total capacity of the power battery pack.

[0093] As an optional implementation, the following steps are also included after S203: S801 performs coordinated control of the entire vehicle's operation.

[0094] During implementation, after the power battery pack completes parameter reconfiguration, its voltage range, power capability, and capacity all change. This necessitates coordination with the vehicle controller to ensure that vehicle operation matches the battery state. The battery management system transmits the reconfigured upper and lower limits of total voltage, allowable charge / discharge power boundaries, and total capacity to the vehicle controller via the CAN bus. The vehicle controller then adjusts the vehicle's operating strategy based on these parameters.

[0095] As an optional implementation method, the specific steps for coordinated control of the vehicle operation in S801 are as follows: S901 adjusts the operating state of the motor controller based on the total voltage upper limit and total voltage lower limit obtained from the system parameter reconstruction.

[0096] In practice, the operating voltage range of the motor drive system is limited by the battery pack voltage. When the battery pack voltage range changes, the motor control strategy needs to be adjusted to avoid undervoltage or overvoltage operation. The vehicle controller can adjust the inverter modulation ratio or PWM duty cycle according to the updated voltage range (e.g., 291V-407V), and limit the maximum speed and output torque of the motor to ensure that the motor operating voltage is always within the voltage range.

[0097] S902 allocates the power of the drive system and the power of the accessories according to the allowable discharge power boundary, and controls them according to the preset priority.

[0098] During implementation, the maximum output power of the battery pack is limited after reconfiguration, requiring coordinated allocation of electrical loads across the vehicle to prioritize core functions. If the allowable discharge power boundary is 50kW, the drive system power is allocated first, for example, 40kW is allocated for driving and the remaining 10kW is allocated for air conditioning or heaters; under rapid acceleration conditions, the power of accessories is temporarily reduced to prioritize drive performance.

[0099] During the charging process, the S903 sends the maximum allowable charging current and total voltage to the on-board charger so that the on-board charger can adjust the output voltage and current.

[0100] In practice, the battery management system will send the allowed charging current (e.g., 150A) and the updated voltage limit (e.g., 407V) to the on-board charger, which will then limit the output current and voltage to avoid overcharging or overvoltage.

[0101] S904 performs graded power reduction when an abnormality is detected in a valid battery cell.

[0102] In practice, when a rapid increase in the internal resistance of a battery cell or an abnormal temperature is detected, the vehicle controller reduces the maximum output power, for example, from 50kW to 30kW, and limits the vehicle's maximum speed to ensure safe operation.

[0103] S802 performs safety verification on the power battery pack and enters a degraded operation mode after the verification is passed.

[0104] During implementation, after the battery pack completes parameter reconfiguration, it is necessary to verify whether it meets the safe operating conditions. Only after the verification is passed can it be put into actual operation.

[0105] As an optional implementation method, safety verification includes electrical safety verification and functional safety verification. The specific steps in S802 for performing safety verification on the power battery pack and entering the degraded operation mode after passing the verification are as follows: S1001, obtain the total voltage and insulation resistance of the power battery pack.

[0106] In practice, the electrical safety of a battery pack depends on its voltage state and insulation performance. Measure the total voltage of the battery pack (e.g., 380V) and the insulation resistance (e.g., 2MΩ).

[0107] S1002, if the total voltage is between the lower limit and the upper limit of the total voltage, and the insulation resistance is greater than the preset insulation threshold, then the power battery pack is determined to have passed the electrical safety verification.

[0108] During implementation, voltage exceeding limits or insufficient insulation may lead to electric shock risks or system failures; therefore, basic electrical safety conditions must be met. For example, if the voltage is within the range of 291V-407V and the insulation resistance is greater than 1MΩ, the electrical safety verification is considered passed.

[0109] S1003, the power battery pack is tested by charging and discharging with a small current. If the total capacity and power limit response of the power battery pack meet the preset consistency requirements, the power battery pack is determined to have passed the functional safety verification.

[0110] In implementation, low-load testing is used to verify whether the model parameters (capacity, voltage, power) are consistent with the actual response, thereby confirming the effectiveness of parameter reconstruction. Charge-discharge tests are performed with a small current (e.g., 10A) to check if the SOC change trend is consistent with the voltage change trend, if the actual output power does not exceed the allowable power boundary, and if the calculated capacity deviates from the estimated capacity by less than a preset threshold (e.g., 5%). When all the above conditions are met, the functional safety verification is deemed successful.

[0111] S1004, after verification, the downgrade level is determined according to the proportion of the number of failed cells to the original total number of cells.

[0112] In implementation, the vehicle management system can classify the degradation level based on the proportion of failed battery cells to the original total number of battery cells. For example, if the proportion of failed battery cells is 3%, it is classified as a Level 1 degradation. If the proportion exceeds 10%, it is classified as a Level 2 degradation.

[0113] S1005 limits the maximum output power of the power battery pack, the maximum vehicle speed, and the charging and discharging capacity based on the downgrade level.

[0114] In practice, the maximum output power of the power battery pack, the maximum vehicle speed, and the charging and discharging capacity can be limited according to the downgrade level. For example, Level 1 downgrade limits the power output to 80% and the speed to 120 km / h, while Level 2 downgrade limits the power output to 60% and the speed to 80 km / h.

[0115] S803 monitors the effective cells of the power battery pack during degraded operation and issues an early warning when abnormal trends are detected.

[0116] During implementation, the battery management system continuously monitors the cell status and performs degradation trend analysis.

[0117] As an optional implementation, the specific steps in S803 for monitoring the effective cells of the power battery pack during degraded operation and issuing an early warning when an abnormal trend is detected are as follows: S1101 collects the voltage, temperature, and internal resistance of the valid battery cells.

[0118] In practice, the battery management system can periodically collect operating data from each cell, for example, once every second.

[0119] S1102, determine the voltage dispersion, temperature change rate and internal resistance change trend of the effective battery cell respectively.

[0120] In practice, voltage dispersion is the difference between the cell voltage and the average value, temperature change rate is the temperature change per unit time, and internal resistance change trend is the internal resistance growth rate.

[0121] S1103, Construct a cell degradation assessment model to predict the failure risk of effective cells.

[0122] In implementation, regression models or threshold models based on historical data can be used to estimate the future failure probability of the battery cells. Specifically, historical voltage data, historical temperature data, and historical internal resistance data of each effective battery cell within a preset time window can be obtained. The voltage dispersion rate of change for the effective battery cell is calculated based on the historical voltage data; the temperature rate of change is calculated based on the historical temperature data; and the internal resistance growth rate is calculated based on the historical internal resistance data. The voltage dispersion rate of change, temperature rate of change, and internal resistance growth rate are determined as the degradation characteristic parameters of the effective battery cell. A battery cell degradation assessment model is constructed based on the degradation characteristic parameters, and the predicted failure risk value of the effective battery cell is calculated based on the battery cell degradation assessment model. If the predicted failure risk value is greater than a preset failure risk threshold, the effective battery cell is determined to have an abnormal trend. The formula for calculating the predicted failure risk value can be: Risk i =ω1k Vi +ω2k Ti +ω3k Ri ; Among them, Risk i Let k be the predicted failure risk value for cell i. Vi Let k be the rate of change of voltage dispersion of cell i. Ti Let k be the temperature change rate of cell i. Ri ω1, ω2, and ω3 are preset weighting coefficients, where ω1 represents the internal resistance growth rate of cell i.

[0123] S1104 When the predicted value of the failure risk of the effective battery cell exceeds the preset failure risk threshold, an early warning message is generated and the user is prompted to perform maintenance.

[0124] In practice, when the predicted failure probability exceeds the failure risk threshold (e.g., 80%), the user can be prompted to inspect or replace the battery pack in a timely manner via the dashboard or remote system.

[0125] S204 If the number of failed cells exceeds the maximum allowable number of short circuits, replace the power battery pack under test.

[0126] In practice, when the number of failed battery cells exceeds a preset threshold, it indicates that the remaining effective battery cells can no longer meet the voltage or power requirements of the vehicle. At this time, instead of short-circuiting, the current power battery pack is determined to be unusable, and the user is reminded to replace the entire power battery pack.

[0127] It should be understood that, although Figures 2 to 5 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figures 2 to 5At least some of the steps in the process may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but may be executed at different times. The execution order of these steps or stages is not necessarily sequential, but may be executed in turn or alternately with other steps or at least some of the steps or stages in other steps.

[0128] It is understood that the same / similar parts between the various embodiments of the methods described above in this specification can be referred to each other. Each embodiment focuses on the differences from other embodiments, and relevant parts can be referred to the description of other method embodiments.

[0129] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0130] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0131] 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 specification.

[0132] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. 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 patent application should be determined by the appended claims.

Claims

1. A method for managing a power battery pack, characterized in that, The method includes: For each cell in the power battery pack to be tested, AC internal resistance deviation diagnosis, capacity decay diagnosis and voltage change rate trajectory anomaly diagnosis are performed on the cell to obtain the cell's AC internal resistance value, internal resistance anomaly judgment value, cell capacity estimate value, capacity anomaly judgment value and voltage cumulative anomaly judgment value, respectively. Based on the internal resistance abnormality judgment value, the capacity abnormality judgment value, and the cumulative voltage abnormality judgment value, the cell is determined to be faulty. The number and location of failed battery cells are counted. If the number of failed battery cells is less than or equal to the preset maximum allowable number of short circuits, the failed battery cells are short-circuited based on their location, and the system parameters of the power battery pack after short circuit are reconstructed. If the number of failed battery cells exceeds the maximum allowable number of short circuits, then the power battery pack under test shall be replaced.

2. The method according to claim 1, characterized in that, The AC internal resistance deviation diagnosis includes: During the vehicle stationary phase or charging interval phase, a sinusoidal alternating current of a preset frequency is applied to each cell in the power battery pack to be tested. Measure the voltage response amplitude of each of the battery cells to the sinusoidal alternating current, and calculate the AC internal resistance of each of the battery cells; Calculate the average value and standard deviation of the AC internal resistance of each of the aforementioned cells; The deviation of the AC internal resistance of each cell is calculated based on the AC internal resistance value, the average value, and the standard deviation of each cell. For each of the aforementioned cells, if the AC internal resistance deviation of the cell is less than or equal to a preset internal resistance deviation threshold, then the preset normal value is assigned to the internal resistance abnormality judgment value. If the AC internal resistance deviation of the battery cell is greater than the preset internal resistance deviation threshold, then the preset abnormal value is assigned to the internal resistance abnormality judgment value.

3. The method according to claim 1, characterized in that, The capacity decay diagnosis includes: For each of the aforementioned battery cells, the voltage, current, and temperature of the battery cell are collected; Based on a pre-established first-order RC equivalent circuit model of the battery cell, the current of the battery cell is used as the state prediction input, the voltage is used as the observation, and the model parameters of the first-order RC equivalent circuit model are corrected by combining temperature. The estimated value of the battery cell capacity is calculated by the extended Kalman filter algorithm. Calculate the average and standard deviation of the estimated cell capacity for each of the aforementioned cells; The capacity deviation of the battery cell is calculated based on the estimated cell capacity, the average value, and the standard deviation. If the capacity deviation of the battery cell is less than or equal to the preset capacity deviation threshold, then the preset normal value is assigned to the capacity anomaly determination value. If the capacity deviation of the battery cell is greater than the capacity deviation threshold, then a preset abnormal value is assigned to the capacity abnormality judgment value.

4. The method according to claim 1, characterized in that, The voltage change rate trajectory anomaly diagnosis includes: During the constant current charging or constant current discharging phase, the voltage of each battery cell is collected. Calculate the rate of voltage change of the battery cell at each sampling time based on the collected voltage. At the same acquisition time, the median value of the voltage change rate of each of the battery cells is obtained; The instantaneous voltage deviation of the battery cell at each sampling moment is determined based on the voltage change rate of the battery cell and the median value. During the constant current charging phase or the constant current discharging phase, the instantaneous voltage deviation of the battery cell is accumulated to determine the cumulative voltage deviation of the battery cell. If the cumulative voltage deviation of the battery cell is less than or equal to the preset cumulative deviation threshold, then the preset normal value is assigned to the cumulative voltage abnormality judgment value. If the cumulative voltage deviation of the battery cell is greater than the cumulative deviation threshold, then a preset abnormal value is assigned to the cumulative voltage abnormality judgment value.

5. The method according to claim 1, characterized in that, The step of determining the failure of the battery cell based on the internal resistance anomaly determination value, the capacity anomaly determination value, and the cumulative voltage anomaly determination value includes: The failure confidence level of the battery cell is calculated based on the internal resistance anomaly determination value, the capacity anomaly determination value, and the cumulative voltage anomaly determination value. If the failure confidence level is greater than or equal to the preset failure confidence level threshold, the cell is determined to be a failed cell. If the failure confidence level is less than the failure confidence level threshold, the cell is determined to be a valid cell.

6. The method according to claim 1, characterized in that, The system parameter reconstruction of the short-circuited power battery pack includes: Collect the total voltage and total internal resistance of the power battery pack; Based on the ratio between the number of effective cells after shorting and the total number of cells before shorting, the original lower limit of total voltage and the original upper limit of total voltage are scaled and updated to update the lower limit of total voltage and the upper limit of total voltage of the power battery pack. Obtain the open-circuit voltage and state of charge of the effective battery cell at the same temperature; For each temperature, the open-circuit voltage and state of charge at that temperature are fitted to determine the voltage-state of charge fitting curve. Calculate the total internal resistance of the effective cells to obtain the equivalent internal resistance of the power battery pack after short-circuiting; For each of the effective cells, based on the estimated capacity and temperature of the effective cell, the allowable charging current and allowable discharging current of the cell are looked up in a preset charging and discharging current lookup table. The allowable charging power boundary is determined based on the total voltage limit, the allowable charging current, and the equivalent internal resistance; Calculate the allowable discharge power boundary based on the total voltage lower limit, the allowable discharge current, and the equivalent internal resistance; The minimum value among the estimated capacity values ​​of each effective cell is determined as the total capacity of the power battery pack.

7. The method according to claim 6, characterized in that, After reconstructing the system parameters of the short-circuited power battery pack, the method further includes: Coordinated control of the entire vehicle operation; The power battery pack is subjected to safety verification, and enters a degraded operation mode after the verification is passed. During the degraded operation, the effective cells of the power battery pack are monitored, and an early warning is issued when an abnormal trend is detected.

8. The method according to claim 7, characterized in that, The coordinated control of the vehicle's operation includes: Based on the total voltage upper limit and total voltage lower limit obtained from the reconstructed system parameters, adjust the operating state of the motor controller; Based on the allowable discharge power boundary, the power of the drive system and the power of the accessories are allocated and controlled according to a preset priority. During the charging process, the allowable charging current and the total voltage limit are sent to the on-board charger so that the on-board charger can adjust the output voltage and current. When an abnormality is detected in the valid battery cell, a graded power reduction is performed.

9. The method according to claim 7, characterized in that, The safety verification includes electrical safety verification and functional safety verification. The safety verification of the power battery pack, followed by entering a degraded operation mode after successful verification, includes: Obtain the total voltage and insulation resistance of the power battery pack; If the total voltage is between the lower limit and the upper limit of the total voltage, and the insulation resistance is greater than the preset insulation threshold, then the power battery pack is determined to have passed the electrical safety verification. The power battery pack is tested by charging and discharging with a small current. If the total capacity and power limit response of the power battery pack meet the preset consistency requirements, the power battery pack is determined to have passed the functional safety verification. After verification, the downgrade level is determined based on the proportion of the number of failed cells to the original total number of cells; The maximum output power of the power battery pack, the maximum vehicle speed, and the charging and discharging capacity are limited according to the downgrade level.

10. The method according to claim 7, characterized in that, During the degraded operation process, the effective cells of the power battery pack are monitored, and an early warning is issued when an abnormal trend is detected, including: Collect the voltage, temperature, and internal resistance of the effective battery cells; The voltage dispersion, temperature change rate, and internal resistance change trend of the effective battery cell are determined respectively. A cell degradation assessment model is constructed to predict the failure risk of the effective cells; When the predicted failure risk of the effective battery cell exceeds the preset failure risk threshold, an early warning message is generated, prompting the user to perform maintenance.

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