A method and apparatus for determining a battery pack discharge cutoff

Abstract

The present disclosure provides a method and device for determining the discharge cutoff of a battery pack, relating to the technical field of battery management. The method comprises: in the case that the voltage of any single cell of the battery pack is less than the trigger voltage, determining the average voltage and the voltage standard deviation of all single cells; based on the voltage standard deviation, determining the safety factor of each single cell in combination with the state of health; based on the safety factor, the average voltage and the voltage standard deviation, determining the voltage reference value of each single cell; in the case that the voltage reference value of any single cell is less than or equal to the corresponding reference safety threshold, determining that the battery pack meets the discharge cutoff; wherein the trigger voltage, the safety factor and the reference safety threshold are updated by a particle swarm algorithm. By triggering the dynamic calculation of the voltage reference value of each single cell in the battery pack, and taking each voltage reference value as one of the criteria for discharge cutoff, the maximum discharge depth of the battery pack throughout its life cycle is realized under the premise of ensuring the safety of the cells.

Description

Technical Field

[0001] This disclosure relates to the field of battery management technology, and specifically to a method and apparatus for determining the discharge cutoff of a battery pack. Background Technology

[0002] With the rapid development of electric vehicles, large-scale energy storage, and other fields, energy storage batteries, especially lithium-ion batteries, are widely used due to their high energy density and long cycle life. At the end of the battery pack's discharge cycle, the usable capacity and depth of discharge are determined by the worst-performing cell with the fastest voltage drop.

[0003] Traditional methods typically use a fixed voltage as the discharge cutoff condition for the entire battery pack. Specifically, when the voltage of the worst-performing cell in the battery pack drops to this cutoff voltage, the BMS (Battery Management System) will stop discharging to protect that cell.

[0004] However, because the "shortest board" cell will reach the cutoff voltage prematurely at the end of the battery pack's discharge, while most other cells still have a large amount of remaining charge, using this traditional method to determine the battery pack's discharge cutoff will limit the depth of discharge throughout the battery pack's entire lifespan. Summary of the Invention

[0005] This disclosure addresses the problems existing in the prior art by providing a method and apparatus for determining the discharge cutoff of a battery pack, thereby solving the technical problem that the depth of discharge of the battery pack is limited throughout its entire life cycle due to the "shortest board" cell reaching the cutoff voltage too early in traditional methods.

[0006] To achieve the above objectives, the technical solution adopted in this disclosure is as follows:

[0007] In a first aspect, this disclosure provides a method for determining the discharge cutoff of a battery pack, comprising: determining the average voltage and standard deviation of all individual cells when the voltage of any single cell in the battery pack is less than a trigger voltage; wherein the trigger voltage includes any voltage value in the range of 3.1V to 3.3V; for each individual cell, determining a safety factor for each individual cell based on the standard deviation of voltage and the health state of the individual cell; the safety factor is a parameter characterizing the safety state of the individual cell; determining a voltage reference value for each individual cell based on the safety factor, the average voltage, and the standard deviation of voltage; the voltage reference value is a reference characterizing the voltage consistency of each individual cell; determining that the battery pack meets the discharge cutoff condition when the voltage reference value of any individual cell is less than or equal to the corresponding reference safety threshold; wherein the voltage reference value of each individual cell corresponds one-to-one with the reference safety threshold; the reference safety threshold is a critical value characterizing the safety state of the corresponding individual cell; wherein the trigger voltage, safety factor, and reference safety threshold are updated using a particle swarm optimization algorithm.

[0008] In some embodiments, the safety factor includes a first safety factor, a second safety factor, and a third safety factor. Determining the safety factor of a single battery cell based on the voltage standard deviation and the health status of the individual cell includes: determining the safety factor of the individual battery cell as the first safety factor when the voltage standard deviation and the health status of the individual battery cell meet a first preset condition; determining the safety factor of the individual battery cell as the second safety factor when the voltage standard deviation and the health status of the individual battery cell meet a second preset condition; and determining the safety factor of the individual battery cell as the third safety factor when the health status of the individual battery cell and the voltage standard deviation meet a third preset condition. Wherein, the first safety factor is less than the second safety factor, and the second safety factor is less than the third safety factor. The first safety factor includes any value in the range of 1.6 to 1.8, the second safety factor includes any value in the range of 1.9 to 2.2, and the third safety factor includes any value in the range of 2.3 to 2.6.

[0009] In some embodiments, the first preset condition includes: the voltage standard deviation is less than a first standard deviation threshold, and the health status of a single cell is greater than a second health threshold; the second preset condition includes: the voltage standard deviation is greater than or equal to the first standard deviation threshold and less than the second standard deviation threshold, and the health status of a single cell is greater than the first health threshold; or, the voltage standard deviation is less than the second standard deviation threshold, and the health status of a single cell is greater than the first health threshold and less than or equal to the second health threshold; the third preset condition includes: the voltage standard deviation is greater than or equal to the second standard deviation threshold; or, the health status of a single cell is less than or equal to the first health threshold; wherein, the first standard deviation threshold is less than the second standard deviation threshold; the first health threshold is less than the second health threshold; the first standard deviation threshold includes any value in the range of 0.04V to 0.06V, and the second standard deviation threshold includes any value in the range of 0.09V to 0.11V; the first health threshold is greater than or equal to 80% and not greater than 90%, and the second health threshold is greater than 90% and less than or equal to 100%.

[0010] In some embodiments, the method further includes: the reference safety threshold of a single battery cell includes a first reference safety threshold, a second reference safety threshold, or a third reference safety threshold, and the reference safety threshold is determined based on the temperature of the single battery cell, including: determining the reference safety threshold of the single battery cell as the first reference safety threshold when the temperature of the single battery cell is less than or equal to the first temperature threshold; determining the reference safety threshold of the single battery cell as the second reference safety threshold when the temperature of the single battery cell is greater than the first temperature threshold and less than or equal to the second temperature threshold; and determining the reference safety threshold of the single battery cell as the third reference safety threshold when the temperature of the single battery cell is greater than the second temperature threshold; wherein the first reference safety threshold is greater than the second reference safety threshold, the second reference safety threshold is greater than the third reference safety threshold; the first temperature threshold is less than the second temperature threshold; the first temperature threshold includes any temperature value in the range of -1℃ to 1℃; and the second temperature threshold includes any temperature value in the range of 24℃ to 26℃.

[0011] In some embodiments, the voltage reference value of each individual cell is determined based on a safety factor, an average voltage value, and a standard voltage deviation, including: substituting the safety factor, the average voltage value, and the standard voltage deviation into the formula. The voltage reference value of each individual cell is obtained, where, This is the voltage reference value. For the average voltage, For safety factor, This represents the standard deviation of voltage.

[0012] In some embodiments, the baseline safety threshold includes any voltage value within the range of 2.65V to 2.75V; the trigger voltage, safety factor, and baseline safety threshold are updated using a particle swarm optimization algorithm, including: setting up a particle swarm; wherein the particle swarm includes multiple particles, and the position vector of each particle includes multiple parameters to be optimized, including the trigger voltage, safety factor, and baseline safety threshold; based on the acquired historical operating data of the battery pack, initializing the position vector of each particle, the velocity vector of each particle, the individual optimal position of each particle, and the global optimal position of the particle swarm; within a preset maximum number of iterations, for each iteration, determining the fitness value of each particle in the current iteration, and updating the individual optimal position of each particle and the global optimal position of the particle swarm based on the fitness value; based on the position vector and velocity vector of each particle in the current iteration, determining the position vector and velocity vector of each particle in the next iteration, and returning to execute the determination of the fitness value of the particle in the current iteration until the convergence condition is met; based on the global optimal position of the converged particle swarm, updating the trigger voltage, safety factor, and baseline safety threshold.

[0013] In some embodiments, determining the fitness value of the particle in the current iteration and updating the individual optimal position of the particle and the global optimal position of the particle swarm includes: determining the fitness value of the particle in the current iteration based on the position vector of the particle in the current iteration using a pre-built battery model; the battery model is a mathematical model used to simulate the safety state and voltage consistency of individual cells in a battery pack; the fitness value is an evaluation index characterizing the combination of parameters corresponding to the particle as the optimal solution for the safety performance of the battery pack in the particle swarm algorithm; if the fitness value of the particle in the current iteration is greater than the fitness value of the individual optimal position of the particle, updating the position vector of the particle in the current iteration to the individual optimal position of the particle; and if the fitness value of the particle in the current iteration is greater than the fitness value of the global optimal position of the particle swarm, updating the position vector of the particle in the current iteration to the global optimal position of the particle.

[0014] In some embodiments, the convergence conditions include any one of the following: reaching a preset maximum number of iterations, the neighboring iteration improvement rate of the fitness value of the global optimal position in consecutive preset number of iterations being less than a preset proportion, and the diversity of the particle swarm being less than a preset threshold; wherein, the preset maximum number of iterations includes any value in the range of 40 to 60, the preset number includes any value in the range of 5 to 10, the preset proportion includes any proportion value in the range of 1% to 2%, and the preset threshold includes any value in the range of 0.005 to 0.05.

[0015] In some embodiments, the method further includes: allowing the battery pack to continue discharging when the voltage reference value of all individual cells is greater than the corresponding reference safety threshold; and determining that the battery pack meets the discharge cutoff condition when the voltage of any individual cell is less than the corresponding absolute shutdown voltage; wherein the absolute shutdown voltage is less than the corresponding reference safety threshold.

[0016] Secondly, this disclosure provides an apparatus for determining the discharge cutoff of a battery pack, comprising: an average difference and standard deviation determination module, used to determine the average voltage and standard deviation of all individual cells when the voltage of any individual cell in the battery pack is less than the trigger voltage; wherein the trigger voltage includes any voltage value in the range of 3.1V to 3.3V; a safety factor determination module, used to determine the safety factor of each individual cell based on the standard deviation of the voltage and the health state of the individual cell; the safety factor is a parameter characterizing the safety state of the individual cell; a voltage reference value determination module, used to determine the voltage reference value of each individual cell based on the safety factor, the average voltage, and the standard deviation of the voltage; the voltage reference value is a reference characterizing the voltage consistency of each individual cell; and a discharge cutoff determination module, used to determine that the battery pack meets the discharge cutoff condition when the voltage reference value of any individual cell is less than or equal to the corresponding reference safety threshold; wherein the voltage reference value of the individual cell corresponds one-to-one with the reference safety threshold; the reference safety threshold is a critical value characterizing the safety state of the corresponding individual cell; wherein the trigger voltage, safety factor, and reference safety threshold are updated using a particle swarm optimization algorithm.

[0017] This disclosure also provides an electronic device, comprising: a memory for storing at least one instruction; and a processor for invoking the instruction stored in the memory to execute the method for determining the discharge cutoff of the battery pack in the first aspect and any embodiment thereof.

[0018] This disclosure also provides a computer-readable storage medium storing at least one executable instruction, which is loaded and executed by a processor to implement the method for determining the discharge cutoff of a battery pack as described in the first aspect and any embodiment of the first aspect.

[0019] This disclosure also provides a computer program product, which includes: computer program code, which, when executed by a computer, causes the computer to perform the method for determining the discharge cut-off of the battery pack as described in the first aspect and any embodiment of the first aspect.

[0020] Compared with the prior art, this disclosure has the following beneficial effects:

[0021] This disclosure calculates the average voltage and standard deviation of the voltage using a trigger voltage, and determines the voltage reference value for each cell by combining it with a safety factor. The discharge cutoff criterion is based on the voltage reference value being less than or equal to a reference safety threshold. Furthermore, the trigger voltage, safety factor, and reference safety threshold are all iteratively updated and optimized using a particle swarm optimization algorithm, achieving accurate and dynamic determination of the battery pack's discharge cutoff. The voltage reference value obtained through the fusion calculation of multiple voltage characteristic parameters and the safety factor more comprehensively reflects the actual working state of the cells, avoiding deviations in cutoff timing caused by single-parameter determination. Simultaneously, relying on the particle swarm optimization algorithm to dynamically update the core determination parameters allows the determination threshold to adapt to changes in cell characteristics throughout the battery pack's entire lifespan, effectively preventing cell over-discharge damage and delaying cell capacity decay. This maximizes the depth of discharge throughout the battery pack's entire lifespan while ensuring the safety of each individual cell during discharge. Attached Figure Description

[0022] Figure 1 This is a flowchart illustrating a method for determining the discharge cutoff of a battery pack according to an embodiment of this disclosure;

[0023] Figure 2 This is a flowchart illustrating another method for determining the discharge cutoff of a battery pack provided in an embodiment of this disclosure;

[0024] Figure 3 This is a flowchart illustrating a parameter update method based on particle swarm optimization provided in an embodiment of this disclosure.

[0025] Figure 4 This is a structural block diagram of a device for determining the discharge cutoff of a battery pack, provided in an embodiment of this disclosure. Detailed Implementation

[0026] The present disclosure will now be further described with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present disclosure and should not be construed as limiting the scope of protection of the present disclosure. It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of this application.

[0027] The acquisition, transmission, storage, use, and processing of data in this disclosed technical solution comply with relevant national laws and regulations. In the embodiments of this disclosure, certain existing industry solutions such as software, components, and models may be mentioned. These should be considered exemplary, intended only to illustrate the feasibility of implementing the technical solution of this disclosure, and do not imply that the applicant has already used or necessarily used such solutions.

[0028] All terms used in this disclosure have the same meaning as understood by one of ordinary skill in the art to which this disclosure pertains, unless otherwise specifically defined. It should also be understood that terms defined in general dictionaries should be interpreted as having meanings consistent with their meanings in the context of the relevant art, and not as idealized or highly formalized, unless expressly defined herein.

[0029] Figure 1 This is a flowchart illustrating a method for determining the discharge cutoff of a battery pack according to an embodiment of this disclosure, as shown below. Figure 1 As shown, the method specifically includes the following steps S11 to S14.

[0030] Step S11: If the voltage of any single cell in the battery pack is less than the trigger voltage, determine the average voltage and standard deviation of all single cells.

[0031] It should be noted that, in this embodiment of the disclosure, the battery pack is composed of multiple individual cells connected in series and parallel; an individual cell refers to the smallest independent energy storage unit that makes up the battery pack; the trigger voltage refers to a pre-set voltage threshold used to initiate the subsequent process of the battery pack discharge cutoff determination; when the voltage of an individual cell reaches this threshold, the subsequent discharge cutoff determination operation is triggered; the average voltage refers to the value obtained by arithmetically averaging the voltage values ​​of all individual cells in the battery pack, which is a parameter characterizing the overall voltage level of all individual cells in the battery pack; the voltage standard deviation refers to the value obtained by calculating the dispersion of the voltage values ​​of all individual cells in the battery pack, which is a core parameter characterizing the voltage consistency among the individual cells in the battery pack.

[0032] In some embodiments, the trigger voltage may include any voltage value in the range of 3.1V to 3.3V; the reference safety threshold may include any voltage value in the range of 2.65V to 2.75V.

[0033] By using the trigger voltage as a prerequisite for discharge cutoff determination, the timing of discharge cutoff determination can be precisely controlled. Subsequent refined determination can only be carried out when the battery pack is close to the discharge cutoff state, thereby improving the accuracy of battery pack discharge control.

[0034] In some embodiments, if the voltage of any single cell in the battery pack is less than the trigger voltage, the method further includes: collecting the voltage of all single cells in the battery pack, wherein the sampling period can be set to 100ms, consistent with the sampling period of the BMS stored data; and determining the average voltage and standard deviation of all single cells based on the voltage of all single cells.

[0035] For example, in one specific embodiment, the voltages of all individual cells in the battery pack are collected sequentially as follows: According to Formula 1: Calculate the average voltage Where n is the number of individual battery cells, These correspond to the voltage of each individual battery cell; according to formula 2: Calculate the standard deviation of voltage , where Vi is the voltage of the i-th individual cell.

[0036] By calculating the average voltage and standard deviation of all individual cells, the discharge state of the battery pack can be quantitatively characterized from two dimensions: the overall voltage level and the voltage consistency between cells. This provides comprehensive and objective quantitative parameter support for subsequent discharge cutoff determination, avoids the judgment bias caused by a single parameter, and makes the subsequent discharge cutoff determination results more consistent with the actual discharge state of the battery pack.

[0037] Step S12: For each individual cell, determine the safety factor of each individual cell based on the voltage standard deviation and the health status of the individual cell.

[0038] It should be noted that, in the embodiments disclosed herein, the safety factor is a parameter characterizing the safety status of a single battery cell, providing a quantitative weight for the safety dimension in the subsequent calculation of the voltage reference value, and is an important parameter for achieving accurate determination of discharge cutoff.

[0039] By setting a safety factor based on voltage standard deviation and health status, the performance differences of different individual cells and the actual discharge requirements of the battery pack can be taken into account. This allows the safety factor to accurately match the actual safety protection requirements of each individual cell, avoiding the problem of some cells being over-protected or under-protected due to a uniform factor.

[0040] It should be noted that the safety factor may include a first safety factor, a second safety factor, and a third safety factor. In the embodiments of this disclosure, different safety factors can be determined based on different voltage standard deviations and different health states. For example, in some embodiments, the safety factor can be further subdivided based on the voltage standard deviation and health state to obtain a fourth safety factor, a fifth safety factor, etc., and this disclosure does not specifically limit this aspect.

[0041] In some embodiments, the first safety factor may include any value in the range of 1.6 to 1.8, the second safety factor may include any value in the range of 1.9 to 2.2, and the third safety factor may include any value in the range of 2.3 to 2.6.

[0042] Additionally, it's important to note that voltage standard deviation reflects the inconsistency between individual cells. A larger voltage standard deviation indicates high voltage dispersion among individual cells and poor voltage consistency between cells; a smaller voltage standard deviation indicates low voltage dispersion among individual cells and good voltage consistency between cells. State of Health (SOH) reflects the performance degradation and operating condition of individual cells. A higher SOH indicates low performance degradation of individual cells, with actual usable capacity close to rated capacity and good overall cell operating condition; a lower SOH indicates high performance degradation of individual cells, with actual usable capacity significantly reduced compared to rated capacity and poor overall cell operating condition.

[0043] When the safety factor is determined by the voltage standard deviation When making a decision, the corresponding safety factor can be selected in the following way: when the voltage standard deviation is small (e.g., In cases where the voltage standard deviation is less than 0.05, a first safety factor of 1.8 can be selected to ensure that approximately 96.4% of normal cells fully release their energy; in cases where the voltage standard deviation is moderate (e.g., 0.05 ≤ 0.05), a safety factor of 1.8 can be selected to ensure that approximately 96.4% of normal cells fully release their energy. In cases where the voltage standard deviation is <0.1), a second safety factor of 1.96 can be selected, thereby protecting approximately 97.5% of the battery cells; when the voltage standard deviation is large (e.g., In the case of ≥0.1), a third safety factor of 2.4 can be selected, thereby providing protection for approximately 99.2% of the battery cells.

[0044] When the safety factor is determined by the state of health (SOH), the corresponding safety factor can be selected as follows: When the state of health is good (e.g., SOH > 90%), a first safety factor of 1.8 can be selected to ensure that approximately 96.4% of normal cells fully release energy; when the state of health is normal (e.g., 80% < SOH ≤ 90%), a second safety factor of 1.96 can be selected to protect approximately 97.5% of cells; when the state of health is poor (e.g., SOH ≤ 89%), a third safety factor of 2.4 can be selected to protect approximately 99.2% of cells.

[0045] In this embodiment, the safety factor is determined by both the voltage standard deviation and the health status. If the safety factor of the voltage standard deviation and the health status conflict, a conservative strategy is adopted to select the maximum value in order to maintain the safety of the battery throughout its entire life cycle.

[0046] Assuming the safety factor includes a first safety factor, a second safety factor, and a third safety factor, with the first safety factor being less than the second safety factor and the second safety factor being less than the third safety factor, the safety factor of a single cell can be determined based on the voltage standard deviation and the health status of the individual cell. Specifically, this can include the following scenarios.

[0047] The first method: Under the condition that the voltage standard deviation and the health status of the individual cell meet the first preset conditions, the safety factor of the individual cell is determined as the first safety factor; wherein, the first preset conditions may include: the voltage standard deviation is less than the first standard deviation threshold and the health status of the individual cell is greater than the second health threshold.

[0048] The second method: Under the condition that the voltage standard deviation and the health status of the individual cell meet the second preset conditions, the safety factor of the individual cell is determined as the second safety factor; wherein, the second preset conditions may include: the voltage standard deviation is greater than or equal to the first standard deviation threshold and less than the second standard deviation threshold, and the health status of the individual cell is greater than the first health threshold; or, the voltage standard deviation is less than the second standard deviation threshold, and the health status of the individual cell is greater than the first health threshold and less than or equal to the second health threshold; wherein, the first standard deviation threshold is less than the second standard deviation threshold, and the first health threshold is less than the second health threshold.

[0049] The third method: Under the condition that the health status and voltage standard deviation of a single cell meet the third preset condition, the safety factor of the single cell is determined as the third safety factor; wherein, the third preset condition may include: the voltage standard deviation is greater than or equal to the second standard deviation threshold; or, the health status of the single cell is less than or equal to the first health threshold.

[0050] In some embodiments, the first standard deviation threshold may include any value in the range of 0.04V to 0.06V, and the second standard deviation threshold may include any value in the range of 0.09V to 0.11V; the first health threshold is greater than or equal to 80% and not greater than 90%, and the second health threshold is greater than 90% and less than or equal to 100%.

[0051] For example, in one specific embodiment, the first safety factor is set to 1.8, the second safety factor to 1.96, and the third safety factor to 2.4; and the first voltage standard deviation is set to 0.05V, the second voltage standard deviation to 0.10V, the first health threshold to 80%, and the second health threshold to 90%. k represents the safety factor, and SOH represents the health status. This represents the standard deviation of voltage. The above situation can be specifically divided into: when... When <0.05 and SOH>90%, k=1.8; when 0.05≤ When <0.1 and SOH>80%, or when When <0.1 and 80%≤SOH<90%, k=1.96; when When ≥0.1 or SOH≤80%, k=2.4.

[0052] Step S13: Determine the voltage reference value for each individual cell based on the safety factor, average voltage value, and voltage standard deviation.

[0053] It should be noted that in this embodiment, the voltage reference value is a reference for the voltage consistency of each individual cell. That is, the voltage reference value integrates multiple parameters such as safety factor, average voltage and voltage standard deviation, and is used to quantify the comprehensive judgment value of the actual discharge safety status of the individual cell. It is the core basis for subsequent battery pack discharge cutoff judgment.

[0054] In some embodiments, according to formula 3: Calculate the voltage reference value ,in, This is the voltage reference value. For the average voltage, For safety factor, This represents the standard deviation of voltage.

[0055] The voltage reference value obtained in this way can avoid the judgment deviation caused by considering a single parameter, and improve the accuracy and reliability of battery pack discharge cutoff judgment.

[0056] Step S14: If the voltage reference value of any single cell is less than or equal to the corresponding reference safety threshold, determine that the battery pack meets the discharge cutoff requirement.

[0057] It should be noted that in the embodiments of this disclosure, the reference safety threshold refers to a pre-set critical value used to characterize the safety state of the corresponding single cell. It is a quantitative standard for determining whether a single cell has reached the discharge safety boundary, and the voltage reference value of the single cell corresponds one-to-one with the reference safety threshold. The discharge cutoff refers to the basis for determining whether the battery pack needs to stop discharging. If the discharge cutoff is met, it indicates that there is a safety risk such as over-discharge of the cells if the battery pack continues to discharge.

[0058] In some embodiments, before determining the discharge cutoff, the method further includes setting a reference safety boundary for the battery pack. The reference safety boundary refers to the overall safety protection boundary set for the discharge safety of the battery pack, which is composed of the reference safety thresholds of all individual cells and is the core safety reference standard for determining the discharge cutoff of the battery pack.

[0059] In some embodiments, the reference safety threshold can be temperature compensated based on the temperature of a single cell, so that the reference safety threshold can be adapted to the discharge characteristics of a single cell under different temperature environments, avoiding the problem of mismatch between the reference safety threshold and the actual safety requirements of the cell due to temperature changes.

[0060] The compensated reference safety threshold for a single battery cell may include a first reference safety threshold, a second reference safety threshold, or a third reference safety threshold, wherein the first reference safety threshold is greater than the second reference safety threshold, and the second reference safety threshold is greater than the third reference safety threshold. The specific compensation steps include: determining the reference safety threshold for the single battery cell as the first reference safety threshold when the temperature of the single battery cell is less than or equal to the first temperature threshold; determining the reference safety threshold for the single battery cell as the second reference safety threshold when the temperature of the single battery cell is greater than the second temperature threshold; and determining the reference safety threshold for the single battery cell as the third reference safety threshold when the temperature of the single battery cell is greater than the second temperature threshold. The first temperature threshold is less than the second temperature threshold.

[0061] In some embodiments, the first temperature threshold includes any temperature value in the range of -1℃ to 1℃; the second temperature threshold includes any temperature value in the range of 24℃ to 26℃.

[0062] For example, in one specific embodiment, let the first temperature threshold be 0°C, the second temperature threshold be 25°C, t represent the temperature, and V_safe represent the baseline safety threshold. Then, when t... At 0℃, V_safe = 2.9V; when At that time, V_safe = 2.8V; when At ℃, V_safe = 2.7V.

[0063] By comparing the comprehensive quantified voltage reference value with the corresponding reference safety threshold, the discharge cutoff time can be made to match the actual discharge state of the battery pack and adapt to the safety protection requirements of each individual cell, thereby maximizing the depth of discharge throughout the battery pack's life cycle while avoiding over-discharge of the cells.

[0064] In some embodiments, the determination of discharge cutoff further includes: allowing the battery pack to continue discharging when the voltage reference value of all individual cells is greater than the corresponding reference safety threshold; and determining that the battery pack meets the discharge cutoff condition when the voltage of any individual cell is less than the corresponding absolute turn-off voltage; wherein the absolute turn-off voltage is less than the corresponding reference safety threshold.

[0065] Figure 2 This is a flowchart illustrating another method for determining the discharge cutoff of a battery pack provided in an embodiment of this disclosure. Figure 2 As shown, the battery pack discharge cutoff determination process includes the following steps S21 to S28.

[0066] Step S21: Collect the voltage of all individual cells; specifically, if the voltage of any individual cell in the battery pack is less than the trigger voltage, determine to enter the battery pack discharge cutoff determination process and execute step S21.

[0067] After this step is initiated, the subsequent discharge cutoff determination main process (steps S22 to S24) and the absolute safety monitoring process (steps S26 to S27) are triggered in parallel.

[0068] Step S22: Calculate the average voltage and the standard deviation of voltage.

[0069] Step S23: Calculate the voltage reference value for each individual cell.

[0070] Step S24: Determine whether the reference voltage value of any cell is greater than the corresponding reference safety threshold; if yes, proceed to step S25; otherwise, proceed to step S28.

[0071] Step S25: Allow continued discharge; if the discharge cutoff condition is not met, return to step S21 to recalculate the voltage reference value based on the real-time collected voltage and re-determine.

[0072] Step S26: Perform absolute safety monitoring; Step S26 is executed in parallel from the start of the process in Step S21 and continues throughout the entire discharge determination process.

[0073] Step S27: Determine whether the voltage of any cell is less than the corresponding absolute turn-off voltage; if yes, proceed to step S28; otherwise, return to step S26.

[0074] It should be noted that the absolute safety monitoring process has the highest priority lockout authority: that is, in the entire process of relative threshold cyclic judgment and allowing continued discharge in steps S21 to S24, as long as any cell is detected to be lower than the corresponding absolute shutdown voltage in the absolute safety monitoring process, the judgment result of the current step S24 will be ignored, and the discharge cutoff action will be triggered unconditionally to cut off the battery pack discharge circuit.

[0075] Step S28: Issue a discharge cutoff command.

[0076] In some embodiments, the absolute turn-off voltage can also be determined based on the temperature of a single cell. The temperature-compensated absolute turn-off voltage can include a first absolute turn-off voltage, a second absolute turn-off voltage, and a third absolute turn-off voltage. Specific compensation steps can include: determining the absolute turn-off voltage of a single cell as the first absolute turn-off voltage when the temperature of the single cell is less than or equal to a first temperature threshold; it should be noted that the first absolute turn-off voltage is typically less than a first reference safety threshold; determining the absolute turn-off voltage of a single cell as the second absolute turn-off voltage when the temperature of the single cell is greater than the first temperature threshold but less than or equal to a second temperature threshold; it should be noted that the second absolute turn-off voltage is typically less than the first absolute turn-off voltage and typically less than the second reference safety threshold; and determining the absolute turn-off voltage of a single cell as the third absolute turn-off voltage when the temperature of the single cell is greater than the second temperature threshold; it should be noted that the third absolute turn-off voltage is typically less than the second absolute turn-off voltage and typically less than the third reference safety threshold.

[0077] For example, in one specific embodiment, let the first temperature threshold be 0°C, the second temperature threshold be 25°C, t represent temperature, and V_hard_cutoff represent absolute cutoff voltage. Then when At ℃, V_hard_cutoff = 2.7V; when At ℃, V_hard_cutoff = 2.6V; when At 25℃, V_hard_cutoff = 2.5V.

[0078] In some embodiments, the trigger voltage, safety factor, and reference safety threshold are updated using a particle swarm optimization algorithm. Figure 3 This is a flowchart illustrating a parameter update method based on the particle swarm optimization algorithm provided in an embodiment of this disclosure. Figure 3 As shown, the parameter update method specifically includes steps S31 to S35.

[0079] Step S31: Set up a particle swarm; wherein, the particle swarm includes multiple particles, and the position vector of each particle includes multiple parameters to be optimized, including trigger voltage, safety factor and baseline safety threshold.

[0080] It should be noted that in the embodiments of the present disclosure, a particle swarm refers to a set composed of multiple particles, which is the core carrier for implementing parameter optimization in the particle swarm optimization (PSO) algorithm. Each particle is a concrete representation of a combination of parameters to be optimized; a particle refers to an independent individual in the particle swarm, and each particle corresponds to a unique combination of parameters to be optimized, and its position and velocity are dynamically adjusted with the algorithm iteration; a position vector refers to a vector used to represent the position of a single particle, the dimension of the vector is consistent with the number of parameters to be optimized, and each element in the vector corresponds to a specific value of a parameter to be optimized; the parameters to be optimized refer to the core parameters that need to be iteratively optimized by the PSO algorithm to improve the discharge control accuracy of the battery pack. In this embodiment, they specifically include the trigger voltage, the safety factor, and the reference safety threshold.

[0081] In some embodiments, the parameters to be optimized further include a temperature compensation coefficient.

[0082] For example, in a specific embodiment, the position vector of each particle includes 6 parameters to be optimized: the safety factor in 3 health states, the trigger voltage, the reference safety threshold, and the temperature compensation coefficient. That is , where x1 = k_soh_high, that is, the k value corresponding to SOH > 90%, x2 = k_soh_mid, that is, the k value corresponding to 80% < SOH ≤ 90%, x3 = k_soh_low, that is, the k value corresponding to SOH ≤ 80%, x4 = V_trigger, that is, the corresponding trigger voltage, x5 = V_safe, that is, the corresponding reference safety threshold, and x6 = temp_comp_slope, that is, the corresponding temperature compensation coefficient.

[0083] The core purpose of setting the particle swarm is to provide a carrier for the iterative optimization of the parameters to be optimized. Through the parallel search of multiple particles, the global optimization of the combination of parameters to be optimized is achieved, avoiding the local optimum problem caused by a single parameter combination, and ensuring that the optimized parameters can adapt to the multi-scenario requirements of the battery pack discharge control.

[0084] Step S32: Based on the obtained historical operation data of the battery pack, initialize the position vector of each particle, the velocity vector of each particle, the individual optimal position of each particle, and the global optimal position of the particle swarm.

[0085] It should be noted that, in this embodiment, the historical operating data of the battery pack refers to various operating parameter data generated during past discharge and charge cycles, including but not limited to: SOH data, capacity decay data, and voltage distribution data of historical cycles. Initialization refers to the operation of assigning initial values ​​to the position vector, velocity vector, individual optimal position, and global optimal position of the particle swarm before the PSO algorithm starts its iteration. Its core purpose is to provide a reasonable starting benchmark for algorithm iteration, avoiding unreasonable initial values ​​that could lead to slow convergence or getting trapped in local optima. Initialization based on the historical operating data of the battery pack allows the initial parameter combination to closely match the actual operating conditions of the battery pack and the characteristics of the cells, avoiding a disconnect between initial parameters and actual needs, while simultaneously improving the convergence speed and optimization accuracy of the PSO algorithm.

[0086] Initialization requires setting the particle swarm size and the maximum number of iterations. For example, set the particle swarm size N=20 and the maximum number of iterations Tmax=50. The initialization operation specifically includes: randomly initializing the position vector Xi of each particle within the parameter allowable range; randomly initializing the velocity vector Vi of each particle within the velocity range; initializing the individual optimal position pbest i = Xi for each particle i; and initializing the global optimal position gbest = the optimal Xi for all particles.

[0087] Among them, the individual optimal position corresponds to the position vector with the largest fitness value of a single particle during the iteration process, and the global optimal position corresponds to the position vector with the largest fitness value of all particles during the iteration process.

[0088] Step S33: Within the preset maximum number of iterations, for each iteration, determine the fitness value of each particle in the current iteration, and update the individual optimal position of each particle and the global optimal position of the particle swarm based on the fitness value.

[0089] It should be noted that, in this embodiment, the preset maximum number of iterations refers to the upper limit of iteration termination set in advance for the PSO algorithm. Once this number is reached, the algorithm stops iterating and outputs the current globally optimal parameters, regardless of whether the convergence condition is met. Iteration refers to the cyclical process in the PSO algorithm where each particle adjusts its position and velocity to gradually find the optimal parameter combination. Each iteration corresponds to an update of the particle's position, velocity, and optimal position. The fitness value is a quantitative indicator used to evaluate the quality of the parameter combination corresponding to a single particle; the higher the value, the more suitable the parameter combination corresponding to the particle is for the battery pack discharge control requirements.

[0090] In some embodiments, determining the fitness value of the particle in the current iteration and updating the individual optimal position of the particle and the global optimal position of the particle swarm can specifically include: determining the fitness value of the particle in the current iteration based on its position vector using a pre-built battery model; updating the position vector of the particle in the current iteration to its individual optimal position if the fitness value of the particle in the current iteration is greater than the fitness value of its individual optimal position; and updating the position vector of the particle in the current iteration to its global optimal position if the fitness value of the particle in the current iteration is greater than the fitness value of the global optimal position of the particle swarm. The battery model is a mathematical model used to simulate the safety state and voltage consistency of individual cells within a battery pack, and the fitness value is an evaluation index characterizing the degree to which the parameter combination corresponding to the particle adapts to the safety performance of the battery pack.

[0091] For example, in one specific embodiment, for each particle i, the position vector Xi is decoded into battery control parameters, and the system performance under these parameters is simulated using a battery model; the fitness value Fi is calculated according to Formula 4: Where Q is the actual discharge capacity, V_benchmark is the standard deviation of the voltage at the end of discharge, V_benchmark is the cell voltage reference value, V_hard_cutoff is the absolute turn-off voltage, and (V_benchmark - V_hard_cutoff) is the safety margin at the end of discharge. w1 is set to 0.6; w2 to 0.3; and w3 to 0.1. If Fi > F(pbest i), then the individual optimal position of particle i, pbest i = Xi, i.e., the individual optimal position is updated; if Fi > F(gbest), then the global optimal position of all particles, gbest = Xi, i.e., the global optimal position is updated.

[0092] The core purpose of this step is to guide the particle swarm to gradually converge toward the globally optimal parameter combination through fitness value evaluation and optimal position update during the iteration process, so as to ensure that the optimized parameters can accurately adapt to the battery pack discharge control requirements.

[0093] Step S34: Based on the position vector and velocity vector of each particle in the current iteration, determine the position vector and velocity vector of each particle in the next iteration, and return to determine the fitness value of the particles in the current iteration until the convergence condition is met.

[0094] In some embodiments, the position and velocity vectors of each particle in the next iteration are updated according to the velocity and position update formulas of the particle swarm optimization algorithm. For example, in one specific embodiment, according to formula 5: Update the velocity vector; according to formula 6: Update the position vector; where v is the velocity vector, x is the position vector, pbest is the individual optimal position of a single particle, gbest is the global optimal position of all particles, i is the particle number, d is the dimension number, t is the iteration number, w is the inertia weight, used to control the tendency of particles to maintain their original velocity, c1 is the cognitive coefficient, used to control the weight of particles moving towards their own historical optimal position, c2 is the social coefficient, used to control the weight of particles moving towards the group's optimal position, and r1 and r2 are random numbers in the range [0,1] to increase the randomness of the search. The PSO parameter table is shown in Table 1.

[0095] Table 1. PSO Parameter Table;

[0096]

[0097] After a particle is updated, its new position needs to be checked to see if it exceeds the preset reasonable range of parameters. If it does, it should be corrected to the boundary to ensure the feasibility of the solution. The boundary conditions are shown in Table 2.

[0098] Table 2 Boundary Condition Parameters;

[0099]

[0100] In some embodiments, the convergence condition may include any one of the following: reaching a preset maximum number of iterations, the adjacent iteration improvement rate of the fitness value of the global optimal position in consecutive preset number of iterations being less than a preset proportion, or the diversity of the particle swarm being less than a preset threshold; wherein, the preset maximum number of iterations includes any value in the range of 40 to 60, the preset number includes any value in the range of 5 to 10, the preset proportion includes any proportion value in the range of 1% to 2%, and the preset threshold includes any value in the range of 0.005 to 0.05.

[0101] For example, in one specific embodiment, the convergence conditions include: Condition 1: reaching the maximum number of iterations of 50 generations; Condition 2: the global optimal fitness improvement is less than 1% for 10 consecutive generations; or Condition 3: the particle swarm diversity is less than 0.01.

[0102] It should be noted that when particles are too concentrated, some particles need to be reinitialized. In this embodiment, dynamic inertial weights are used, focusing on global search in the early stage and local fine-grained search in the later stage.

[0103] Additionally, it should be noted that if the algorithm gets stuck in a local optimum, the global optimum position gbest is retained and other particles are reinitialized, with a maximum restart limit of 3 times.

[0104] If the convergence condition is not met, the particle update step is executed; if the convergence condition is met, the optimization loop is exited and step S35 is entered.

[0105] Step S35: Based on the globally optimal position of the converged particle swarm, update the trigger voltage, safety factor, and baseline safety threshold.

[0106] It should be noted that, in this embodiment of the disclosure, the globally optimal position of the converged particle swarm refers to the particle position vector with the best fitness value in the particle swarm after the PSO algorithm meets the convergence condition. Each element in this position vector corresponds to the optimal value of the three parameters to be optimized: trigger voltage, safety factor, and baseline safety threshold. Parameter update refers to replacing the trigger voltage, safety factor, and baseline safety threshold currently in use in the battery pack discharge control system with the parameter values ​​corresponding to the globally optimal position after convergence, so that the optimized parameters are formally applied to the battery pack discharge cutoff determination process.

[0107] This step outputs the final optimization result, namely the global optimal position gbest and its corresponding control parameters.

[0108] In some embodiments, the method further includes: rigorously simulating and verifying the control parameters corresponding to the optimized global optimal position gbest under a series of extreme but possible operating conditions to check whether the cell voltage will never fall below the absolute turn-off voltage V_hard_cutoff under any circumstances. If the verification passes, the parameter deployment is initiated; if the verification fails, the default parameters are used.

[0109] This embodiment of the disclosure uses the particle swarm optimization algorithm to achieve global optimization of the parameters to be optimized by leveraging the characteristics of multi-particle parallel search. This effectively avoids the problem of local optima and ensures that the updated trigger voltage, safety factor, and baseline safety threshold can accurately adapt to the core requirements of battery pack discharge control, forming the optimal parameter combination.

[0110] Figure 4 This is a structural block diagram of a device for determining the discharge cutoff of a battery pack, as provided in an embodiment of this disclosure. Figure 4 As shown, the device 100 includes a mean difference and standard deviation determination module 110, a safety factor determination module 120, a voltage reference value determination module 130, and a discharge cutoff determination module 140.

[0111] The module 110 for determining the average and standard deviation of the battery pack's cells determines the average voltage and standard deviation of all cells when the voltage of any single cell in the battery pack is less than the trigger voltage. The module 120 for determining the safety factor of each cell determines the safety factor based on the standard deviation and the cell's health status. The safety factor is a quantitative parameter characterizing the safety status of a single cell. The module 130 for determining the voltage reference value of each cell determines the voltage reference value based on the safety factor, average voltage, and standard deviation. The voltage reference value is a comprehensive quantitative parameter characterizing the consistency between the safety status and voltage of a single cell. The module 140 for determining the discharge cutoff determines that the battery pack meets the discharge cutoff condition when the voltage reference value of any single cell is less than or equal to the corresponding reference safety threshold. The voltage reference value of each cell corresponds one-to-one with the reference safety threshold. The reference safety threshold is a parameter characterizing the critical value of the corresponding single cell's safety status. The trigger voltage, safety factor, and reference safety threshold are updated using a particle swarm optimization algorithm.

[0112] In this embodiment, a two-layer architecture of a bottom-level real-time control layer and an upper-level parameter optimization layer is adopted. The bottom-level real-time control layer employs a real-time safety control algorithm based on normal distribution theory. When the voltage of any single cell in the battery pack is lower than the trigger voltage, the real-time safety control algorithm is activated. The upper-level parameter optimization layer employs a periodic parameter optimization strategy based on particle swarm optimization. By dynamically optimizing the key parameters of the bottom-level normal distribution model through the upper-level particle swarm optimization algorithm, the system can intelligently tap into the capacity that is confined by traditional fixed threshold strategies at the end of the discharge cycle, thereby improving the usable capacity of each discharge cycle while ensuring the absolute safety of the battery pack.

[0113] Additionally, it should be noted that when potential conflicts arise between upper and lower layer algorithms, the system employs the following resolution strategy:

[0114] If there is a conflict in the safety factor k value: select the largest k value, i.e., max(PSO_k, A conservative strategy is employed, prioritizing safety; where PSO_k is the safety coefficient obtained through optimization using the upper-level particle swarm optimization algorithm. _k is the safety factor calculated using the lower-level normal distribution theory;

[0115] If there is a voltage threshold conflict: force the logical relationship of V_trigger > V_safe + 0.3V to be maintained; where V_trigger is the trigger voltage and V_safe is the reference safety threshold.

[0116] If it is a temperature compensation conflict: ensure that the baseline safety threshold is not lower than 2.9V when the temperature is below 0°C;

[0117] If there is a performance conflict: if the security verification fails, revert to the previous stable parameter version.

[0118] For details and benefits of the apparatus for determining the discharge cutoff of a battery pack provided in the embodiments of this disclosure, please refer to the above description of the method for determining the discharge cutoff of a battery pack, which will not be repeated here.

[0119] This disclosure also provides an electronic device, comprising: a memory for storing at least one instruction; and a processor for invoking the instruction stored in the memory to execute the method for determining the discharge cutoff of the battery pack in any of the above embodiments.

[0120] This disclosure also provides a computer-readable storage medium storing at least one executable instruction, which is loaded and executed by a processor to implement the method for determining the discharge cutoff of a battery pack in any of the above embodiments.

[0121] This disclosure also provides a computer program product, which includes computer program code that, when executed by a computer, causes the computer to perform the method for determining the discharge cut-off of the battery pack in any of the above embodiments.

[0122] Those skilled in the art will understand that embodiments of this disclosure can be provided as methods, systems, or computer program products. Therefore, this disclosure can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this disclosure can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0123] This disclosure is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0124] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0125] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0126] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0127] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0128] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0129] It should be noted that the terms "first," "second," and similar terms used in this disclosure do not indicate any order, quantity, or importance, but are merely used to distinguish different parts. Terms such as "including" or "contains" mean that the element preceding the word covers the element listed after the word, and do not exclude the possibility of covering other elements as well.

[0130] Although operations are described in a specific order in the accompanying drawings in this disclosure, it should not be construed as requiring these operations to be performed in the specific order or serial order shown, or requiring all of the shown operations to obtain the desired result. In certain environments, multitasking and parallel processing may be advantageous.

[0131] Finally, it should be noted that the above content is only used to illustrate the technical solution of this disclosure, and is not intended to limit the scope of protection of this disclosure. Simple modifications or equivalent substitutions made by those skilled in the art to the technical solution of this disclosure do not depart from the substance and scope of the technical solution of this disclosure.

Claims

1. A method for determining the discharge cutoff of a battery pack, characterized in that, include: If the voltage of any single cell in the battery pack is less than the trigger voltage, determine the average voltage and standard deviation of all the single cells; wherein the trigger voltage includes any voltage value in the range of 3.1V to 3.3V. For each individual cell, a safety factor is determined based on the voltage standard deviation and the health status of the individual cell; the safety factor is a parameter characterizing the safety status of the individual cell. Based on the safety factor, the average voltage, and the standard deviation of the voltage, a voltage reference value is determined for each individual cell; the voltage reference value is a benchmark characterizing the voltage consistency of each individual cell. If the voltage reference value of any of the individual cells is less than or equal to the corresponding reference safety threshold, the battery pack is determined to meet the discharge cutoff condition; wherein, the voltage reference value of the individual cells corresponds one-to-one with the reference safety threshold; the reference safety threshold is a critical value characterizing the safety state of the corresponding individual cell. The trigger voltage, the safety factor, and the reference safety threshold are updated using a particle swarm optimization algorithm. The determination of the voltage reference value for each individual cell based on the safety factor, the average voltage value, and the voltage standard deviation includes: Substituting the safety factor, the average voltage, and the standard deviation of the voltage into the formula The voltage reference value of each individual battery cell is obtained, wherein, This is the voltage reference value. For the average voltage, For safety factor, The standard deviation of voltage; The reference safety threshold includes any voltage value within the range of 2.65V to 2.75V; the trigger voltage, the safety factor, and the reference safety threshold are updated using a particle swarm optimization algorithm, including: A particle swarm is set up; wherein the particle swarm includes multiple particles, and the position vector of each particle includes multiple parameters to be optimized, the parameters to be optimized including the trigger voltage, the safety factor and the reference safety threshold; Based on the historical operating data of the acquired battery pack, the position vector of each particle, the velocity vector of each particle, the individual optimal position of each particle, and the global optimal position of the particle swarm are initialized. Within a preset maximum number of iterations, for each iteration, the fitness value of each particle in the current iteration is determined, and the individual optimal position of each particle and the global optimal position of the particle swarm are updated based on the fitness value. Based on the position vector and velocity vector of each particle in the current iteration, determine the position vector and velocity vector of each particle in the next iteration, and return to determine the fitness value of the particle in the current iteration until the convergence condition is met; Based on the globally optimal position of the converged particle swarm, the trigger voltage, the safety factor, and the baseline safety threshold are updated.

2. The method according to claim 1, characterized in that, The safety factor includes a first safety factor, a second safety factor, and a third safety factor; determining the safety factor of a single battery cell based on the voltage standard deviation and the health status of the individual cell includes: If the voltage standard deviation and the health status of the individual battery cell meet the first preset conditions, the safety factor of the individual battery cell is determined to be the first safety factor. If the voltage standard deviation and the health status of the individual battery cell meet the second preset condition, the safety factor of the individual battery cell is determined to be the second safety factor. If the health status of the individual battery cell and the voltage standard deviation meet the third preset condition, the safety factor of the individual battery cell is determined as the third safety factor. Wherein, the first safety factor is less than the second safety factor, and the second safety factor is less than the third safety factor; the first safety factor includes any value in the range of 1.6 to 1.8, the second safety factor includes any value in the range of 1.9 to 2.2, and the third safety factor includes any value in the range of 2.3 to 2.

6.

3. The method according to claim 2, characterized in that, The first preset conditions include: the voltage standard deviation is less than a first standard deviation threshold, and the health status of the individual battery cell is greater than a second health threshold; The second preset condition includes: the voltage standard deviation is greater than or equal to the first standard deviation threshold and less than the second standard deviation threshold, and the health status of the individual cell is greater than the first health threshold; or, the voltage standard deviation is less than the second standard deviation threshold, and the health status of the individual cell is greater than the first health threshold and less than or equal to the second health threshold; The third preset condition includes: the voltage standard deviation is greater than or equal to the second standard deviation threshold; or, the health status of the individual battery cell is less than or equal to the first health threshold. Wherein, the first standard deviation threshold is less than the second standard deviation threshold; the first health threshold is less than the second health threshold; the first standard deviation threshold includes any value in the range of 0.04V to 0.06V, and the second standard deviation threshold includes any value in the range of 0.09V to 0.11V; the first health threshold is greater than or equal to 80% and not greater than 90%, and the second health threshold is greater than 90% and less than or equal to 100%.

4. The method according to claim 1, characterized in that, The reference safety threshold of the single cell includes a first reference safety threshold, a second reference safety threshold, or a third reference safety threshold, and the reference safety threshold is determined based on the temperature of the single cell, including: If the temperature of the individual battery cell is less than or equal to a first temperature threshold, the reference safety threshold of the individual battery cell is determined to be the first reference safety threshold. If the temperature of a single battery cell is greater than the first temperature threshold and less than or equal to the second temperature threshold, the reference safety threshold of the single battery cell is determined to be the second reference safety threshold. If the temperature of the single cell is greater than the second temperature threshold, the reference safety threshold of the single cell is determined as the third reference safety threshold. Wherein, the first reference safety threshold is greater than the second reference safety threshold, and the second reference safety threshold is greater than the third reference safety threshold; the first temperature threshold is less than the second temperature threshold; the first temperature threshold includes any temperature value within the range of -1℃ to 1℃; and the second temperature threshold includes any temperature value within the range of 24℃ to 26℃.

5. The method according to any one of claims 1-4, characterized in that, Determining the fitness value of the particle in the current iteration and updating the individual optimal position of the particle and the global optimal position of the particle swarm includes: Based on the position vector of the particle in the current iteration, the fitness value of the particle in the current iteration is determined through a pre-built battery model; the battery model is a mathematical model used to simulate the safety state and voltage consistency of individual cells in the battery pack; the fitness value is an evaluation index characterizing the combination of parameters corresponding to the particle as the optimal solution for the safety performance of the battery pack in the particle swarm algorithm. If the fitness value of the particle in the current iteration is greater than the fitness value of the particle's individual optimal position, then the position vector of the particle in the current iteration is updated to the particle's individual optimal position. If the fitness value of the particle in the current iteration is greater than the fitness value of the global optimal position of the particle swarm, the position vector of the particle in the current iteration is updated to the global optimal position of the particle.

6. The method according to any one of claims 1-4, characterized in that, The convergence conditions include any one of the following: reaching the preset maximum number of iterations, the adjacent iteration improvement rate of the fitness value of the global optimal position in a consecutive preset number of iterations being less than a preset proportion, or the diversity of the particle swarm being lower than a preset threshold. Wherein, the preset maximum number of iterations includes any value in the range of 40 to 60, the preset number includes any value in the range of 5 to 10, the preset ratio includes any ratio value in the range of 1% to 2%, and the preset threshold includes any value in the range of 0.005 to 0.

05.

7. The method according to any one of claims 1-4, characterized in that, Also includes: The battery pack is allowed to continue discharging if the voltage reference value of all individual cells is greater than the corresponding reference safety threshold. as well as, If the voltage of any of the individual cells is less than the corresponding absolute shutdown voltage, the battery pack is determined to meet the discharge cutoff condition; wherein the absolute shutdown voltage is less than the corresponding reference safety threshold.

8. A device for determining the discharge cutoff of a battery pack, characterized in that, include: The average difference and standard deviation determination module is used to determine the average voltage and standard deviation of all the individual cells in the battery pack when the voltage of any individual cell in the battery pack is less than the trigger voltage; wherein the trigger voltage includes any voltage value in the range of 3.1V to 3.3V. A safety factor determination module is used to determine the safety factor of each individual cell based on the voltage standard deviation and the health status of the individual cell; the safety factor is a parameter characterizing the safety status of the individual cell. The voltage reference value determination module is used to determine the voltage reference value of each of the individual cells based on the safety factor, the average voltage value, and the standard deviation of the voltage value; the voltage reference value is a reference characterizing the voltage consistency of each of the individual cells. The discharge cutoff determination module is used to determine that the battery pack meets the discharge cutoff condition when the voltage reference value of any of the individual cells is less than or equal to the corresponding reference safety threshold; wherein, the voltage reference value of the individual cell corresponds one-to-one with the reference safety threshold; the reference safety threshold is a critical value characterizing the safety state of the corresponding individual cell; The trigger voltage, the safety factor, and the reference safety threshold are updated using a particle swarm optimization algorithm. The determination of the voltage reference value for each individual cell based on the safety factor, the average voltage value, and the voltage standard deviation includes: Substituting the safety factor, the average voltage, and the standard deviation of the voltage into the formula The voltage reference value of each individual battery cell is obtained, wherein, This is the voltage reference value. For the average voltage, For safety factor, The standard deviation of voltage; The reference safety threshold includes any voltage value within the range of 2.65V to 2.75V; the trigger voltage, the safety factor, and the reference safety threshold are updated using a particle swarm optimization algorithm, including: A particle swarm is set up; wherein the particle swarm includes multiple particles, and the position vector of each particle includes multiple parameters to be optimized, the parameters to be optimized including the trigger voltage, the safety factor and the reference safety threshold; Based on the historical operating data of the acquired battery pack, the position vector of each particle, the velocity vector of each particle, the individual optimal position of each particle, and the global optimal position of the particle swarm are initialized. Within a preset maximum number of iterations, for each iteration, the fitness value of each particle in the current iteration is determined, and the individual optimal position of each particle and the global optimal position of the particle swarm are updated based on the fitness value. Based on the position vector and velocity vector of each particle in the current iteration, determine the position vector and velocity vector of each particle in the next iteration, and return to determine the fitness value of the particle in the current iteration until the convergence condition is met; Based on the globally optimal position of the converged particle swarm, the trigger voltage, the safety factor, and the baseline safety threshold are updated.

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