Method, device and equipment for evaluating pulse discharge performance of power battery system

Abstract

This application discloses a method, apparatus, and device for evaluating the pulse discharge performance of a power battery system, relating to the field of power battery technology. The method includes: constructing a corresponding cell pulse discharge current optimization model based on the relationship between cell operating voltage and pulse discharge current under different characteristic operating conditions; solving the cell pulse discharge current optimization model to obtain the maximum pulse discharge current of the cell under different characteristic operating conditions; determining the maximum pulse discharge current of the power battery system under different characteristic operating conditions based on the system's limiting discharge current, system peak current, and maximum cell pulse discharge current; calculating the pulse discharge power of the power battery system under different characteristic operating conditions; and formulating and verifying the pulse discharge power MAP. Through the above method, the pulse discharge power of the power battery system under different characteristic operating conditions is accurately determined, the pulse discharge capability of the power battery system is quickly and accurately evaluated, and the pulse discharge power MAP is formulated.

Description

Technical Field

[0001] This application relates to the field of power battery technology, and in particular to methods, apparatus and equipment for evaluating the pulse discharge performance of power battery systems. Background Technology

[0002] A single battery cell is the most basic unit of a power battery system, serving as the fundamental unit for absorbing, storing, and supplying electrical energy. To meet the energy supply demands of automobiles, a certain number of cells are typically connected in series and parallel to form modules, and multiple modules are combined to form a battery pack. One or more battery packs, electronic and electrical components, and structural components together constitute a power battery system. The pulse discharge power of a cell characterizes its short-term discharge capability, and the magnitude of the pulse discharge current directly determines the pulse discharge power. Therefore, determining the maximum pulse discharge current of a cell is crucial for evaluating its pulse discharge performance. Thus, the key to evaluating the pulse discharge performance of a power battery system lies in determining the maximum pulse discharge current of the cell, defining its pulse discharge performance, ensuring safety throughout its entire lifespan, and comprehensively considering the safety of the electronic and electrical systems, high-voltage systems, and structural components within the system, thereby achieving safe and efficient operation of the power battery system.

[0003] In the existing technology, there are few studies on methods for rapidly evaluating the pulse discharge current of power battery systems, and the evaluation of the pulse discharge performance of power battery systems has problems such as multiple test conditions, long test cycles, and high test resource and manpower costs.

[0004] The above content is only used to help understand the technical solution of the present invention and does not represent an admission that the above content is prior art. Summary of the Invention

[0005] The main objective of this application is to provide a method, apparatus, and equipment for evaluating the pulse discharge performance of a power battery system, aiming to solve the technical problems that the traditional methods for evaluating the pulse discharge performance of a power battery system are relatively complex, costly, and difficult to achieve quickly and accurately.

[0006] To achieve the above objectives, this application provides a method for evaluating the pulse discharge performance of a power battery system, the method comprising:

[0007] Based on the relationship between cell operating voltage and pulse discharge current under different characteristic operating conditions, a corresponding cell pulse discharge current optimization model is constructed. The characteristic operating conditions consist of characteristic pulse time, characteristic temperature and characteristic state of charge.

[0008] The positions of gray wolves in the population are initialized using a chaotic mapping mechanism, and a fitness function is constructed, where position is used to characterize pulse discharge current;

[0009] Based on the fitness function and the position of the gray wolves in the population, the gray wolves in the population are divided into alpha wolves, suboptimal wolves, third-best wolves, and the remaining wolves. Based on the similarity between the suboptimal wolves and the alpha wolf, and the similarity between the third-best wolves and the alpha wolf, the weights of the suboptimal level and the third-best level are determined respectively. Based on the weights of the alpha wolf level, the suboptimal level weights, and the third-best level weights, the positions of the remaining wolves are updated. The alpha wolves, suboptimal wolves, third-best wolves, and the remaining wolves in the population are re-divided. This process is repeated until the iteration termination condition is met, and the target alpha wolf is obtained.

[0010] The pulse discharge current represented by the position of the target wolf is used as the solution of the corresponding cell pulse discharge current optimization model to obtain the maximum pulse discharge current of the cell under different characteristic working conditions.

[0011] Based on the system's ultimate discharge current, the system's peak current, and the cell's maximum pulse discharge current, the maximum pulse discharge current of the power battery system under different characteristic operating conditions is determined.

[0012] Based on the maximum pulse discharge current of the power battery system under different characteristic operating conditions, the pulse discharge power of the power battery system under different characteristic operating conditions is determined, and the pulse discharge power MAP is formulated and verified.

[0013] In one embodiment, the step of classifying gray wolves in the population into alpha wolves, sub-alpha wolves, third-best wolves, and the remaining wolves based on the fitness function and the position of the gray wolves in the population includes:

[0014] Based on the fitness function and the position of the gray wolves in the population, calculate the fitness value corresponding to the position of the gray wolf in the population.

[0015] Based on the fitness values ​​corresponding to the positions of the gray wolves in the population, the gray wolves in the population are sorted in descending order to obtain the individual sequence of the population.

[0016] The alpha wolf is selected from the individual sequences based on the alpha wolf level weight, the second best wolf is selected from the individual sequences other than the alpha wolf based on the preset second best ratio, and the third best wolf is selected from the individual sequences other than the alpha wolf and the second best wolf based on the preset third best ratio.

[0017] Based on the selected alpha wolf, second-best wolf, and third-best wolf, the remaining wolves in the individual sequence are determined.

[0018] In one embodiment, the steps of determining the weights of the second-best and third-best levels based on the similarity between the second-best wolf and the alpha wolf, and the similarity between the third-best wolf and the alpha wolf, respectively, include:

[0019] Obtain the similarity between the second-best wolf and the alpha wolf, as well as the similarity between the third-best wolf and the alpha wolf;

[0020] Obtain the similarity between the second-best wolf and the alpha wolf, the similarity between the third-best wolf and the alpha wolf, and the first correspondence between the alpha wolf level weight and the second-best level weight;

[0021] Obtain the similarity between the second-best wolf and the alpha wolf, the similarity between the third-best wolf and the alpha wolf, and the second correspondence between the alpha wolf level weight and the third-best level weight;

[0022] The weight of the second-best wolf level is determined based on the similarity between the second-best wolf and the alpha wolf, the similarity between the third-best wolf and the alpha wolf, the alpha wolf level weight, and the first correspondence.

[0023] The weight of the third best wolf level is determined based on the similarity between the second best wolf and the alpha wolf, the similarity between the third best wolf and the alpha wolf, the alpha wolf level weight, and the second correspondence.

[0024] In one embodiment, the steps of obtaining the similarity between the second-best wolf and the alpha wolf, and the similarity between the third-best wolf and the alpha wolf, include:

[0025] Obtain the third correspondence between location distance, number of individuals, and similarity;

[0026] The similarity between the second-best wolf and the alpha wolf is determined based on the positional distance between them, the number of second-best wolves, and the third correspondence.

[0027] The similarity between the third-ranked wolf and the alpha wolf is determined based on the positional distance between them, the number of third-ranked wolves, and the third correspondence.

[0028] In one embodiment, the step of updating the positions of the remaining wolves based on the alpha wolf level weight, the second-best level weight, and the third-best level weight includes:

[0029] The position of the alpha wolf is taken as the first position, the position of a randomly selected second-best wolf is taken as the second position, the position of a randomly selected third-best wolf is taken as the third position, and the positions of the remaining wolves after the update are taken as the fourth position.

[0030] Obtain the fourth correspondence between the first position, second position, third position, alpha wolf level weight, second best level weight, third best level weight, and fourth position;

[0031] Based on the first position, second position, third position, alpha wolf level weight, second best level weight, third best level weight, and the fourth correspondence, the fourth position is determined, and the updated positions of the remaining wolves are obtained.

[0032] In one embodiment, the cell pulse discharge current optimization model includes at least the following constraints:

[0033] The cell's operating voltage is equal to the open-circuit voltage at the initial moment of discharge minus the product of the cell's dynamic internal resistance and the pulse discharge current.

[0034] The dynamic internal resistance of a battery cell is equal to the sum of its ohmic internal resistance and polarization internal resistance.

[0035] The dynamic internal resistance of the battery cell conforms to the internal resistance function relationship obtained by fitting.

[0036] The operating voltage of the cell at the discharge end is greater than or equal to the discharge cutoff voltage.

[0037] The pulse discharge current is greater than zero;

[0038] The relationship between the cell operating voltage and the pulse discharge current is linear.

[0039] The temperature rise of the battery cell during a single pulse is less than or equal to the preset temperature rise safety threshold.

[0040] In one embodiment, the step of determining the maximum pulse discharge current of the power battery system under different characteristic operating conditions based on the system's limiting discharge current, the system's peak current, and the cell's maximum pulse discharge current includes:

[0041] Obtain the system limit voltage, system peak current, and system internal resistance of the power battery system;

[0042] Based on the number of cells connected in series and the cell open-circuit voltage under different characteristic operating conditions, the system open-circuit voltage under different characteristic operating conditions;

[0043] Based on the system open-circuit voltage, system limit voltage and system internal resistance of the power battery system, the system limit discharge current under different characteristic operating conditions is determined.

[0044] Based on the number of modules in parallel and the maximum pulse discharge current of the cells under different characteristic operating conditions, the maximum pulse discharge current of the cell group under different characteristic operating conditions is determined.

[0045] Following the principle of safety first, the minimum value among the system limit discharge current, system peak current, and cell pack maximum pulse discharge current is taken as the system maximum pulse discharge current of the power battery system under the corresponding characteristic operating conditions.

[0046] In one embodiment, the step of determining the pulse discharge power of the power battery system under different characteristic operating conditions based on the maximum pulse discharge current of the power battery system under different characteristic operating conditions includes:

[0047] Obtain the fifth correspondence between the system's maximum pulse discharge current, system open-circuit voltage, system internal resistance, internal resistance correction coefficient, and pulse discharge power;

[0048] Based on the fifth correspondence, the maximum pulse discharge current of the power battery system under different characteristic operating conditions, as well as the system open-circuit voltage, system internal resistance, and internal resistance correction coefficient of the power battery system, the pulse discharge power of the power battery system under different characteristic operating conditions is determined.

[0049] Furthermore, to achieve the above objectives, this application also proposes an evaluation device for the pulse discharge performance of a power battery system, the evaluation device for the pulse discharge performance of a power battery system comprising:

[0050] The data solving module is used to construct a corresponding cell pulse discharge current optimization model based on the relationship between cell operating voltage and pulse discharge current under different characteristic operating conditions. The characteristic operating conditions consist of characteristic pulse time, characteristic temperature and characteristic state of charge.

[0051] The data solving module is also used to initialize the position of gray wolves in the population using a chaotic mapping mechanism and to construct a fitness function, where the position is used to characterize the pulse discharge current.

[0052] The data solving module is also used to divide the gray wolves in the population into alpha wolves, suboptimal wolves, third-best wolves, and the remaining wolves based on the fitness function and the position of the gray wolves in the population. Based on the similarity between the suboptimal wolves and the alpha wolf, and the similarity between the third-best wolves and the alpha wolf, the weights of the suboptimal level and the third-best level are determined respectively. Based on the weights of the alpha wolf level, the suboptimal level, and the third-best level, the position of the remaining wolves is updated, and the alpha wolves, suboptimal wolves, third-best wolves, and the remaining wolves in the population are re-divided. This process is repeated until the iteration termination condition is met, and the target alpha wolf is obtained.

[0053] The data solving module is also used to take the pulse discharge current represented by the position of the target wolf as the solution of the corresponding cell pulse discharge current optimization model, and obtain the maximum pulse discharge current of the cell under different characteristic working conditions.

[0054] The performance evaluation module is used to determine the maximum pulse discharge current of the power battery system under different characteristic operating conditions based on the system's limit discharge current, the system's peak current, and the cell's maximum pulse discharge current.

[0055] The performance evaluation module is also used to determine the pulse discharge power of the power battery system under different characteristic operating conditions based on the maximum pulse discharge current of the power battery system under different characteristic operating conditions, and to formulate and verify the pulse discharge power MAP.

[0056] In addition, to achieve the above objectives, this application also proposes an evaluation device for the pulse discharge performance of a power battery system. The evaluation device for the pulse discharge performance of a power battery system includes: a memory, a processor, and a computer program stored in the memory and executable on the processor. The computer program is configured to implement the steps of the evaluation method for the pulse discharge performance of a power battery system as described above.

[0057] In addition, to achieve the above objectives, the present invention also proposes a storage medium, which is a computer-readable storage medium, and stores a computer program on the storage medium. When the computer program is executed by a processor, it implements the steps of the method for evaluating the pulse discharge performance of a power battery system as described above.

[0058] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the method for evaluating the pulse discharge performance of a power battery system as described above.

[0059] This application provides a method for evaluating the pulse discharge performance of a power battery system. Based on the relationship between cell operating voltage and pulse discharge current under different characteristic operating conditions, a corresponding cell pulse discharge current optimization model is constructed. The characteristic operating conditions consist of characteristic pulse time, characteristic temperature, and characteristic state of charge. A chaotic mapping mechanism is used to initialize the positions of gray wolves in the population, and a fitness function is constructed, with position used to characterize the pulse discharge current. Based on the fitness function and the positions of gray wolves in the population, the gray wolves are divided into alpha wolves, suboptimal wolves, third-optimal wolves, and the remaining wolves. Based on the similarity between suboptimal wolves and alpha wolves, and the similarity between third-optimal wolves and alpha wolves, the weights of suboptimal level and third-optimal level are determined respectively. Based on the weights of alpha wolf level and suboptimal level, the weights of suboptimal level and third-optimal level are determined. The weights and third-best-level weights are used to update the positions of the remaining wolves, reclassifying the alpha wolf, second-best wolf, third-best wolf, and other wolves in the population. This process is iterated until the iteration termination condition is met, yielding the target alpha wolf. The pulse discharge current represented by the position of the target alpha wolf is used as the solution to the corresponding cell pulse discharge current optimization model, obtaining the maximum pulse discharge current of the cell under different characteristic operating conditions. Based on the system limit discharge current, system peak current, and cell maximum pulse discharge current, the maximum pulse discharge current of the power battery system under different characteristic operating conditions is determined. Based on the maximum pulse discharge current of the power battery system under different characteristic operating conditions, the pulse discharge power of the power battery system under different characteristic operating conditions is determined, and a pulse discharge power MAP is developed and verified. This application utilizes the relationship between cell operating voltage and pulse discharge current to construct a cell pulse discharge current optimization model. By solving the model, the maximum pulse discharge current of the cell under different pulse times, temperatures, and states of charge is found, enabling a rapid and accurate assessment of the cell's pulse discharge capability. Based on the cell's pulse discharge capability and following the principle of safety priority, the maximum pulse discharge current of the power battery system is determined, and the pulse discharge power of the power battery system is calculated. This allows for a rapid and accurate assessment of the power battery system's pulse discharge capability, the establishment of a discharge power MAP, and ensures the safety of the cell throughout its entire life cycle. This enables the power battery to operate safely and efficiently, solving the technical problems of traditional methods being complex, costly, and difficult to implement quickly and accurately when evaluating the pulse discharge performance of power battery systems. Attached Figure Description

[0060] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0061] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0062] Figure 1 This is a flowchart illustrating an embodiment of the method for evaluating the pulse discharge performance of a power battery system according to this application.

[0063] Figure 2 This is a flowchart illustrating Embodiment 2 of the method for evaluating the pulse discharge performance of the power battery system in this application;

[0064] Figure 3 This is a schematic diagram of the module structure of the evaluation device for the pulse discharge performance of a power battery system according to an embodiment of this application;

[0065] Figure 4 This is a schematic diagram of the equipment structure of the hardware operating environment involved in the evaluation method of pulse discharge performance of the power battery system in the embodiments of this application.

[0066] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0067] It should be understood that the specific embodiments described herein are merely used to explain the technical solutions of the present application and are not intended to limit the present application.

[0068] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0069] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device capable of performing the above functions, such as an evaluation device for the pulse discharge performance of a power battery system. This embodiment does not specifically limit it in this regard. The following uses an evaluation device for the pulse discharge performance of a power battery system as an example to describe this embodiment and the following embodiments.

[0070] This application provides a method for evaluating the pulse discharge performance of a power battery system, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the method for evaluating the pulse discharge performance of a power battery system according to this application.

[0071] In this embodiment, the method for evaluating the pulse discharge performance of the power battery system includes steps S10 to S60:

[0072] Step S10: Based on the relationship between cell operating voltage and pulse discharge current under different characteristic operating conditions, construct the corresponding cell pulse discharge current optimization model. The characteristic operating conditions consist of characteristic pulse time, characteristic temperature and characteristic state of charge.

[0073] It should be noted that the characteristic operating condition refers to the pre-set operating condition. In this embodiment, the characteristic operating condition consists of characteristic pulse time, characteristic temperature, and characteristic state of charge (SOC). Different characteristic pulse times, different characteristic temperatures, and different characteristic SOCs can form different characteristic operating conditions. The characteristic temperature refers to the pre-set cell operating temperature, and multiple temperatures can usually be set. The specific value and number can be set according to actual needs and are not specifically limited. For example, the set characteristic temperatures are 45℃, 25℃, 10℃, 0℃, -10℃, and -20℃. Generally, the characteristic temperature needs to be set within the cell's operating temperature range. The cell's operating temperature range is the temperature range within which the cell operates normally, and can be set according to actual conditions without specific limitations. The characteristic SOC refers to the pre-set cell SOC value, usually set within a SOC range. Multiple SOCs can be set, and the SOC range is the range of the cell's SOC, typically 0 to 100%. In practical implementation, the characteristic state of charge (SOC) can be selected by setting a SOC gradient. Based on the SOC gradient, a characteristic SOC with a corresponding value is selected within the range of SOC values. The SOC gradient can be 5%, and there is no specific limitation on it. For example, if the set SOC gradient is ΔSOC, then the SOC... i = i·ΔSOC, where i is the i-th SOC value, SOC1 = 0 is the minimum SOC value of the cell, and SOC j =100% is the maximum SOC value of the cell, 0≤i≤j. The characteristic pulse time refers to the preset pulse time, which is the duration of the pulse current; multiple characteristic pulse times can usually be set. The characteristic pulse time can be a short pulse, a standard pulse, or a long pulse. A short pulse can be 2s or 5s, a standard pulse can be 10s, and a long pulse can be 30s, which can be set according to actual needs and are not specifically limited. In this embodiment, the cell is a cell in a power battery system. Cells are connected in series and parallel to form modules. Multiple modules are combined to form a battery pack. One or more battery packs, electronic and electrical components, and structural components together constitute a power battery system.

[0074] It is understood that this embodiment sets multiple characteristic temperatures, multiple characteristic states of charge, and multiple characteristic pulse times. Among them, a characteristic temperature, a characteristic state of charge, and a characteristic pulse time can form a characteristic operating condition. Under different characteristic operating conditions, the corresponding maximum pulse discharge current of the cell is found, the pulse discharge capability of the cell is determined, and the pulse discharge power of the power battery system is calculated to obtain the pulse discharge capability of the power battery system and formulate the pulse discharge power MAP.

[0075] It should be noted that, according to the working principle of the battery, after the power is turned on, the cell operating voltage during the pulse discharge process satisfies the following relationship:

[0076] V(t) = EI·DCR cell

[0077] In the formula, V(t) represents the cell operating voltage during the pulse discharge process, E represents the cell open-circuit voltage at the initial moment of the pulse discharge, i.e., the open-circuit voltage at the initial moment of discharge, I represents the pulse discharge current, and DCR cell This indicates the dynamic internal resistance of the battery cell.

[0078] It is evident that the cell operating voltage and the pulse discharge current have a linear functional relationship of the form y = -k·x + b. Therefore, in the curve of the cell operating voltage versus the pulse discharge current, as the pulse discharge current increases, the cell operating voltage first reaches an inflection point, no longer satisfying the linear relationship. It is considered that the pulse discharge current corresponding to this cell operating voltage is the limiting discharge current, denoted as I. Limit The maximum pulse discharge current of the battery cell during the pulse discharge process is denoted as I. cell,max .

[0079] Therefore, based on the relationship between the cell's operating voltage and the pulse discharge current, this embodiment constructs an optimization model for the cell's pulse discharge current. After solving the optimization model, the corresponding maximum pulse discharge current of the cell can be determined.

[0080] It is understandable that pulse time, temperature, and state of charge have a certain impact on the dynamic internal resistance of the battery cell, and temperature and state of charge have a certain impact on the open-circuit voltage of the battery cell. Therefore, different relationships between the battery cell operating voltage and pulse discharge current can be obtained under different characteristic pulse times, different characteristic temperatures, and different characteristic states of charge. It is necessary to construct corresponding battery cell pulse discharge current optimization models under different characteristic operating conditions.

[0081] It should be understood that in determining the maximum pulse discharge current of a battery cell, in addition to satisfying the relationship between the battery cell's operating voltage and the pulse discharge current, there are usually other requirements that need to be met. All the requirements that need to be met can be set as constraints of the battery cell pulse discharge current optimization model, so that the maximum pulse discharge current obtained by the solution can be reasonably applied.

[0082] In one feasible implementation, the cell pulse discharge current optimization model includes at least the following constraints: the cell operating voltage is equal to the open-circuit voltage at the initial discharge moment minus the product of the cell dynamic internal resistance and the pulse discharge current; the cell dynamic internal resistance is equal to the sum of the ohmic internal resistance and the polarization internal resistance; the cell dynamic internal resistance conforms to the fitted internal resistance function relationship; the cell operating voltage at the end of discharge is greater than or equal to the discharge cutoff voltage; the pulse discharge current is greater than zero; the relationship between the cell operating voltage and the pulse discharge current satisfies a linear relationship; and the cell temperature rise during a single pulse is less than or equal to a preset temperature rise safety threshold.

[0083] It should be noted that the relationship between the cell operating voltage and the pulse discharge current can be described as follows: the cell operating voltage V(t) is equal to the open-circuit voltage E at the initial moment of discharge minus the cell dynamic internal resistance DCR. cell The product of this and the pulse discharge current I is V(t) = EI·DCR cell In this embodiment, the relationship between the cell operating voltage and the pulse discharge current needs to approximately satisfy a linear relationship, which can be expressed as: Wherein, ∈ is a control constant, which can be set according to the actual situation. It is generally a relatively small constant and is not specifically limited.

[0084] Additionally, it should be noted that after the battery is connected to a load, the dynamic internal resistance (DCR) of the battery cell... cell Including ohmic internal resistance R Ω and polarization internal resistance R f This can be expressed as: DCR cell =R Ω +R f Ohmic internal resistance R Ω It can be assumed to remain unchanged, and the polarization internal resistance R f It is dynamically changing. The pulsed discharge process can affect the polarization resistance R. f The main factors include: temperature, state of charge, pulse discharge current, and discharge time (pulse time). Therefore, in this embodiment, the dynamic internal resistance can be expressed as R. f = f(T,SOC,I,t), where f(T,SOC,I,t) is the internal resistance function, the specific form of which can be obtained by fitting test data. For example, using the dynamic current testing method, pulse discharge tests are performed on the battery cell. The specific testing process is as follows: pulse discharge tests are conducted using different pulse discharge currents at different temperatures and under different charging states. The discharge time is equal to the set pulse time. The dynamic internal resistance of the battery cell corresponding to different pulse discharge currents is obtained. Using the test data, the internal resistance function is fitted. Using the internal resistance function, the dynamic internal resistance of the battery cell under different characteristic pulse times, different characteristic temperatures, and different characteristic charging states can be calculated, i.e., the dynamic internal resistance of the battery cell under different characteristic operating conditions.

[0085] Understandably, the longer the discharge time, the lower the cell's operating voltage. During the discharge process, it is necessary to ensure that the cell's operating voltage at the end of the pulse discharge is greater than or equal to the cell's discharge cutoff voltage, that is, the cell's operating voltage V at the end of the discharge is greater than or equal to the discharge cutoff voltage V. cut-off This can be expressed as: V≥V cut-offThis ensures that the cell's operating voltage at other times during the discharge process is always greater than or equal to the discharge cutoff voltage. Since temperature and SOC (State of Charge) can affect the discharge cutoff voltage, it is evident that the discharge cutoff voltage differs at different characteristic temperatures and under different characteristic states of charge, and needs to be determined based on the characteristic temperature and characteristic state of charge used in the specific operating condition. Furthermore, the pulse discharge current needs to be greater than 0.

[0086] It should be understood that, to ensure safety, the temperature rise ΔT of a single pulsed cell must be less than or equal to the preset temperature rise safety threshold T. saf That is, ΔT≤T saf The single-pulse cell temperature rise refers to the temperature rise of the cell under a single pulse. The preset temperature rise safety threshold is a set safe value for the temperature rise, for example, 5℃. It is set according to the actual situation and there is no specific limitation on it.

[0087] It should be noted that, according to the law of conservation of energy, under adiabatic conditions, the following condition must be met: 2 ·R·t=c p From ·m·ΔT, we can obtain the calculation formula for the temperature rise of a single pulse cell, that is, the correspondence between the cell specific heat capacity, cell mass, pulse time, cell dynamic internal resistance, pulse discharge current and the temperature rise of a single pulse cell, as shown below:

[0088]

[0089] In the formula, ΔT represents the temperature rise of the battery cell in a single pulse, and c p The specific heat capacity of the battery cell is represented by m, the mass of the battery cell is represented by t, and the pulse time is represented by DCR. cell The value represents the dynamic internal resistance of the battery cell, and I represents the pulse discharge current.

[0090] It is understandable that the characteristic operating condition (characteristic pulse time t) will be considered. m Characteristic temperature T k and characteristic state of charge (SOC) i Substituting the cell's dynamic internal resistance, pulse discharge current, cell specific heat capacity, cell mass, and pulse time into the above formula, we can obtain the single-pulse cell temperature rise under this characteristic operating condition, and thus calculate the single-pulse cell temperature rise corresponding to the pulse discharge current under different characteristic operating conditions.

[0091] Finally, the pulse discharge current optimization model can be described as follows:

[0092]

[0093] In the formula, V(t) represents the cell operating voltage during the pulse discharge process, E represents the open-circuit voltage at the initial moment of discharge, I represents the pulse discharge current, and DCR cell R represents the dynamic internal resistance of the battery cell. Ω R represents the ohmic internal resistance.f V represents the polarization internal resistance, and V represents the cell voltage at the discharge end. cut-off Let f(T,SOC,I,t) represent the discharge cutoff voltage, f(T,SOC,I,t) represent the internal resistance function relationship, ∈ is the control constant, and T saf c represents the preset temperature rise safety threshold. p ΔT represents the specific heat capacity of the battery cell, m represents the mass of the battery cell, t represents the pulse time, and ΔT represents the temperature rise of the battery cell during a single pulse.

[0094] Step S20: The positions of gray wolves in the population are initialized using a chaotic mapping mechanism, and a fitness function is constructed, where the position is used to characterize the pulse discharge current.

[0095] It should be noted that this embodiment uses an improved gray wolf optimization algorithm to solve the cell pulse discharge current optimization model.

[0096] Understandably, during the solution process, relevant parameters need to be set and the population initialized. The parameters that need to be set typically include: population size, maximum number of iterations, etc., which are set according to the actual situation and are not specifically limited. The population usually consists of multiple individuals, each of which is a gray wolf. The position of each gray wolf can represent the corresponding pulse discharge current. A set of potential solutions is randomly generated as the initial values ​​for the positions of the gray wolves in the population. Initialization can use a chaotic mapping mechanism. For example, Gaussian chaotic mapping is used to initialize the population. Gaussian chaotic mapping increases the randomness of the system by introducing Gaussian white noise, which helps the optimization algorithm escape local optima, enhances global search capabilities, and improves population diversity. This is expressed as:

[0097] g = μ + σ*Gaussian(0,1)

[0098] X i =x min +g*(x max -x min )

[0099] In the formula, μ is the mean, and σ is the variance, which are set according to the actual situation. Typically, μ can be set as the center of the search space or a representative point. A larger σ value can increase the breadth of the search, which is helpful for global search, while a smaller σ value can increase the precision of the search, which is helpful for local search. min x max These are the upper limits for the decision variables in the initial stage, set according to the actual situation, X i This indicates the location of the gray wolves within the population.

[0100] It should be understood that the fitness function is usually constructed based on the actual situation. The value of the pulse discharge current can be used as the fitness function, or other penalty terms or constraints can be added on top of it; there are no restrictions on this. For example, the fitness function can be designed as follows:

[0101]

[0102] In the formula, Fitness represents the fitness function, I represents the pulse discharge current, α and β represent scaling factors, Linearity(I) is a metric between 0 and 1, and V represents the cell operating voltage at the end of the discharge. cut-off This indicates the discharge cutoff voltage.

[0103] Step S30: Based on the fitness function and the position of the gray wolves in the population, the gray wolves in the population are divided into alpha wolves, suboptimal wolves, third-best wolves, and the remaining wolves. Based on the similarity between the suboptimal wolves and the alpha wolves, and the similarity between the third-best wolves and the alpha wolves, the weights of the suboptimal level and the third-best level are determined respectively. The positions of the remaining wolves are updated based on the weights of the alpha wolves, the suboptimal level, and the third-best level. The alpha wolves, suboptimal wolves, third-best wolves, and the remaining wolves in the population are re-divided. This process is repeated until the iteration termination condition is met, and the target alpha wolf is obtained.

[0104] It should be noted that in this embodiment, individuals in the population are divided into four levels: alpha wolf, second-best wolf, third-best wolf, and the remaining wolves. The levels of the alpha wolf, second-best wolf, third-best wolf, and the remaining wolves decrease sequentially, with the alpha wolf being the highest and the remaining wolves the lowest. This embodiment employs an adaptive update strategy to update the alpha wolf, second-best wolf, third-best wolf, and the remaining wolves in the population until the iteration termination condition is met. The alpha wolf at this point is the final required alpha wolf, i.e., the target alpha wolf. The pulse discharge current represented by the position of the target alpha wolf is the pulse discharge current that satisfies all constraints of the cell pulse discharge current optimization model. The iteration termination condition can be reaching the maximum number of iterations or the fitness no longer significantly improving; no specific limitation is made.

[0105] In one feasible implementation, the step of dividing gray wolves in the population into alpha wolves, suboptimal wolves, third-best wolves, and the remaining wolves based on the fitness function and their positions in the population includes: calculating the fitness value corresponding to the position of each gray wolf in the population based on the fitness function and their positions; sorting the gray wolves in the population in descending order based on their fitness values ​​to obtain an individual sequence of the population; selecting an alpha wolf from the individual sequence based on the alpha wolf level weight, selecting suboptimal wolves from the individual sequence excluding the alpha wolf based on a preset suboptimal ratio, and selecting third-best wolves from the individual sequence excluding the alpha wolf and suboptimal wolves based on a preset third-best ratio; and determining the remaining wolves in the individual sequence based on the selected alpha wolf, suboptimal wolves, and third-best wolves.

[0106] It should be noted that the fitness function can be used to calculate the fitness value corresponding to the position of each gray wolf, thus allowing the gray wolves in the population to be sorted according to their fitness values. This embodiment uses descending order sorting, ranking the gray wolves from highest to lowest fitness value; the resulting sequence is the sorted sequence of gray wolves.

[0107] Understandably, the alpha wolf level weight refers to the weight of the alpha wolf, for example, 40%. This weight is not specifically limited and is used as the selection ratio for choosing the alpha wolf in the individual sequence. The preset second-best ratio is the set ratio for selecting the second-best wolves, and the preset third-best ratio is the set ratio for selecting the third-best wolves. Generally, during selection, the alpha wolf is first selected from the individual sequence according to its alpha wolf level weight. Then, from the individual sequence excluding the alpha wolf, the alpha wolf is selected from the top-ranked gray wolves according to the preset second-best ratio. Next, from the individual sequence excluding the alpha wolf and the second-best wolves, the alpha wolf is selected from the top-ranked gray wolves according to the preset third-best ratio. Finally, the remaining gray wolves are the other wolves.

[0108] It should be understood that after identifying the alpha wolf, second-best wolves, third-best wolves, and the remaining wolves, the positions of the remaining wolves need to be updated, thus updating the population and obtaining new alpha wolves, second-best wolves, third-best wolves, and the remaining wolves. In this embodiment, the positions of the remaining wolves are updated based on the differences between the alpha wolf and other wolf ranks; these differences can typically be represented by similarity.

[0109] In one feasible implementation, the steps of determining the suboptimal level weight and the third-optimal level weight based on the similarity between the suboptimal wolf and the alpha wolf, and the similarity between the third-optimal wolf and the alpha wolf, respectively, include: obtaining the similarity between the suboptimal wolf and the alpha wolf, and the similarity between the third-optimal wolf and the alpha wolf; obtaining a first correspondence between the similarity between the suboptimal wolf and the alpha wolf, the similarity between the third-optimal wolf and the alpha wolf, the alpha wolf level weight, and the suboptimal level weight; obtaining a second correspondence between the similarity between the suboptimal wolf and the alpha wolf, the similarity between the third-optimal wolf and the alpha wolf, the alpha wolf level weight, and the third-optimal level weight; determining the suboptimal level weight based on the similarity between the suboptimal wolf and the alpha wolf, the similarity between the third-optimal wolf and the alpha wolf, the alpha wolf level weight, and the first correspondence; and determining the third-optimal level weight based on the similarity between the suboptimal wolf and the alpha wolf, the similarity between the third-optimal wolf and the alpha wolf, the alpha wolf level weight, and the second correspondence.

[0110] It should be noted that the calculation formulas for the first correspondence between the similarity between the second-best wolf and the alpha wolf, the similarity between the third-best wolf and the alpha wolf, and the weights of the alpha wolf level and the second-best level are as follows:

[0111]

[0112] In the formula, β represents the weight of the second-best level, s1 represents the similarity between the second-best wolf and the alpha wolf, s2 represents the similarity between the third-best wolf and the alpha wolf, and α represents the weight of the alpha wolf level. Substituting the similarity between the second-best wolf and the alpha wolf, the similarity between the third-best wolf and the alpha wolf, and the weight of the alpha wolf level into the first correspondence above, the weight of the second-best level can be calculated.

[0113] Understandably, the calculation formulas for the second correspondence between the similarity between the second-best wolf and the alpha wolf, the similarity between the third-best wolf and the alpha wolf, and the weights of the alpha wolf level and the third-best level (i.e., the weights of the third-best level) are as follows:

[0114]

[0115] In the formula, γ represents the weight of the third-best level, s1 represents the similarity between the second-best wolf and the alpha wolf, s2 represents the similarity between the third-best wolf and the alpha wolf, and α represents the weight of the alpha wolf level. Substituting the similarity between the second-best wolf and the alpha wolf, the similarity between the third-best wolf and the alpha wolf, and the weight of the alpha wolf level into the second correspondence above, the weight of the third-best level can be calculated.

[0116] In one feasible implementation, the steps of obtaining the similarity between the second-best wolf and the alpha wolf, and the similarity between the third-best wolf and the alpha wolf, include: obtaining a third correspondence between location distance, number of individuals, and similarity; determining the similarity between the second-best wolf and the alpha wolf based on the location distance between the second-best wolf and the alpha wolf, the number of individuals of the second-best wolf, and the third correspondence; and determining the similarity between the third-best wolf and the alpha wolf based on the location distance between the third-best wolf and the alpha wolf, the number of individuals of the third-best wolf, and the third correspondence.

[0117] It should be noted that this embodiment uses Euclidean distance to represent the similarity between wolves of other ranks and the alpha wolf. Location distance refers to the Euclidean distance between the location of an individual gray wolf and the location of the alpha wolf. The third correspondence between location distance, number of individuals, and similarity—that is, the formula for calculating similarity—is as follows:

[0118]

[0119] In the formula, represents the similarity between the j-th level gray wolf and the alpha wolf, and D c-i This represents the positional distance between the i-th gray wolf and the alpha wolf, and n represents the number of gray wolves of the corresponding level.

[0120] It is understandable that by substituting the positional distance between the second-best wolf and the alpha wolf, and the number of second-best wolves into the third correspondence mentioned above, the similarity between the second-best wolf and the alpha wolf can be calculated. Similarly, by substituting the positional distance between the third-best wolf and the alpha wolf, and the number of third-best wolves into the third correspondence mentioned above, the similarity between the third-best wolf and the alpha wolf can be calculated.

[0121] In one feasible implementation, the step of updating the positions of the remaining wolves based on the alpha wolf level weight, the second-best level weight, and the third-best level weight includes: taking the position of the alpha wolf as the first position, taking the position of a randomly selected second-best wolf as the second position, taking the position of a randomly selected third-best wolf as the third position, and taking the updated positions of the remaining wolves as the fourth position; obtaining a fourth correspondence between the first position, the second position, the third position, the alpha wolf level weight, the second-best level weight, the third-best level weight, and the fourth position; and determining the fourth position based on the first position, the second position, the third position, the alpha wolf level weight, the second-best level weight, the third-best level weight, and the fourth correspondence to obtain the updated positions of the remaining wolves.

[0122] It should be noted that the position of the alpha wolf is designated as the first position (X1), the position of a randomly selected second-best wolf is designated as the second position (X2), the position of a randomly selected third-best wolf is designated as the third position (X3), and the positions of the remaining wolves after the update are designated as the fourth position (X). t+1The fourth correspondence between the first position, second position, third position, alpha wolf level weight, second-best level weight, third-best level weight, and fourth position—that is, the calculation formula for the updated positions of the remaining wolves—is shown below:

[0123]

[0124] In the formula, X t+1 Let X1 represent the fourth position, X2 represent the first position, X3 represent the second position, X4 represent the third position, α represent the alpha wolf level weight, β represent the second-best level weight, and γ represent the third-best level weight. By substituting the relevant data into the above fourth correspondence, the positions of the remaining wolves can be calculated.

[0125] It is understandable that updating the position of one of the remaining wolves each time requires updating the positions of all the remaining wolves in turn. The second position X2 and the third position X3 selected in each calculation are random, thus ensuring the diversity and randomness of the generated remaining wolf population and avoiding the algorithm from getting stuck in a local optimum.

[0126] Step S40: The pulse discharge current represented by the position of the target wolf is used as the solution of the corresponding cell pulse discharge current optimization model to obtain the maximum pulse discharge current of the cell under different characteristic working conditions.

[0127] It should be noted that the pulse discharge current represented by the position of the target wolf is the maximum pulse discharge current of the battery cell, which is the solution of the battery cell pulse discharge current optimization model. Thus, the maximum pulse discharge current under different characteristic pulse times, different characteristic temperatures, and different characteristic charging states can be determined in turn, and the maximum pulse discharge current of the battery cell under different characteristic operating conditions can be obtained.

[0128] It can be seen that the characteristic pulse time t m and characteristic temperature T k The maximum pulse discharge current of the battery cell corresponding to different characteristic states of charge, i.e.:

[0129]

[0130] Among them, T k Represents the k-th characteristic temperature, SOC i Represents the i-th characteristic state of charge. Indicates the characteristic temperature T k and characteristic state of charge (SOC) i The maximum pulse discharge current of the battery cell.

[0131] Furthermore, the characteristic pulse time t can be obtained. m The maximum pulse discharge current of the battery cell corresponding to different characteristic temperatures and different characteristic states of charge, i.e.:

[0132]

[0133] In the formula, T1~T l Characteristic temperature, SOC1~SOC j Indicates the characteristic state of charge. I represents the maximum pulse discharge current of the battery cell at different characteristic temperatures and different characteristic states of charge. m (T,SOC) represents the characteristic pulse time t. m Maximum pulse discharge current of battery cells under different characteristic temperatures and different characteristic states of charge.

[0134] Understandably, since the characteristic pulse time can be a long pulse, a standard pulse, or a short pulse, the maximum pulse discharge current of the battery cell corresponding to different characteristic temperatures and different characteristic states of charge under a long pulse, the maximum pulse discharge current of the battery cell corresponding to different characteristic temperatures and different characteristic states of charge under a standard pulse, and the maximum pulse discharge current of the battery cell corresponding to different characteristic temperatures and different characteristic states of charge under a short pulse can be obtained. This allows us to obtain the maximum pulse discharge current of the battery cell under different characteristic operating conditions, which can be used to characterize the pulse discharge capability of the battery cell.

[0135] Step S50: Based on the system's limit discharge current, the system's peak current, and the cell's maximum pulse discharge current, determine the system's maximum pulse discharge current of the power battery system under different characteristic operating conditions.

[0136] In one feasible implementation, step S50 may include steps S501 to S505:

[0137] Step S501: Obtain the system limit voltage, system peak current, and system internal resistance of the power battery system;

[0138] It should be noted that the system's limiting voltage V sys,Limit This refers to the minimum voltage required to ensure the normal operation of components such as the drive motor, generator, air conditioner, and control system in the vehicle; the system peak current I sys,peak This refers to the maximum permissible current that ensures the normal operation of related components in the electronic and electrical systems of the power battery system and the vehicle electrical system; the system internal resistance R sys It refers to the DC resistance in the entire circuit of the battery pack from high voltage positive to high voltage negative. It is determined by factors including bus design, overcurrent capacity, and selection of electrical components, and there are no restrictions on it.

[0139] It is understandable that the system internal resistance is related to the internal resistance of the electrical system, the dynamic internal resistance of the battery cell, the temperature correction factor, the state of charge correction factor, the number of battery cells connected in series, and the number of modules connected in parallel. The calculation relationship is shown below:

[0140]

[0141] In the formula, R sys R represents the internal resistance of the system. sys，ele DCR represents the internal resistance of an electrical system. cell T represents the dynamic internal resistance of the battery cell. f S represents the temperature correction factor. f α represents the state of charge correction factor, α represents the number of cells connected in series, and α represents the number of modules connected in parallel.

[0142] It should be understood that the number of modules connected in parallel and the number of cells connected in series need to be determined based on the configuration of the power battery system. The power battery system configuration is generally expressed as αPβS, where P represents parallel connection, S represents series connection, α is the number of cells connected in series, and β is the number of modules connected in parallel.

[0143] Step S502: Based on the number of cells connected in series and the cell open-circuit voltage under different characteristic operating conditions, determine the system open-circuit voltage under different characteristic operating conditions.

[0144] It is understandable that the system open-circuit voltage is related to the number of cells connected in series and the open-circuit voltage of the cells, and the calculation relationship is shown below:

[0145] V sys,ocV =α·V cell,OCV

[0146] In the formula, V sys,OCV The system open-circuit voltage is represented by V, and α represents the number of cells connected in series. cell,OCV This represents the cell open-circuit voltage. The system open-circuit voltage is calculated using the number of cells connected in series and the cell open-circuit voltages under different operating conditions.

[0147] Step S503: Based on the system open-circuit voltage, system limit voltage, and system internal resistance of the power battery system, determine the system limit discharge current under different characteristic operating conditions.

[0148] It should be noted that the system's limiting discharge current is related to the system's open-circuit voltage, the system's limiting voltage, and the system's internal resistance. The calculation relationship is shown below:

[0149]

[0150] In the formula, I sys,Limit V represents the system's limiting discharge current. sys,OCV V represents the system open-circuit voltage. sys,Limit R represents the system's limiting voltage. sys This represents the system's internal resistance. Using the system's open-circuit voltage, system limiting voltage, and system internal resistance, the system's limiting discharge current under different characteristic operating conditions can be calculated.

[0151] Step S504: Based on the number of modules connected in parallel and the maximum pulse discharge current of the cells under different characteristic operating conditions, determine the maximum pulse discharge current of the cell group under different characteristic operating conditions.

[0152] It is understandable that the maximum pulse discharge current of the battery cell pack is related to the number of modules connected in parallel and the maximum pulse discharge current of the battery cells. The calculation relationship is shown below:

[0153] I cells,max =β·I cell,max

[0154] In the formula, I cells,max I represents the maximum pulse discharge current of the battery cell pack, β represents the number of modules connected in parallel, and I cell,max This represents the maximum pulse discharge current of the battery cell. Using the number of modules connected in parallel and the maximum pulse discharge current of the battery cells, the maximum pulse discharge current of the battery cell assembly under different characteristic operating conditions is calculated.

[0155] Understandably, I cell,max It is the maximum pulse discharge current of the battery cell under different characteristic operating conditions, determined by the cell pulse discharge current optimization model.

[0156] Step S505: Following the principle of safety first, the minimum value among the system limit discharge current, system peak current and cell pack maximum pulse discharge current is taken as the system maximum pulse discharge current of the power battery system under the corresponding characteristic working condition.

[0157] It should be noted that, following the principle of safety first, the smallest of the three current values—the maximum pulse discharge current of the battery pack, the system's limiting discharge current, and the system's peak current—is selected as the maximum pulse discharge current of the power battery system. The calculation formula is shown below:

[0158] I sys,pulse =Min(I) cells,max , I sys,Limit , I sys,peak )

[0159] In the formula, I sys,pulse I represents the system's maximum pulse discharge current. cells,max I represents the maximum pulse discharge current of the battery pack. sys,Limit I represents the system's limiting discharge current. sys,peak This represents the system peak current.

[0160] Step S60: Based on the maximum pulse discharge current of the power battery system under different characteristic operating conditions, determine the pulse discharge power of the power battery system under different characteristic operating conditions, formulate the pulse discharge power MAP, and verify it.

[0161] It should be noted that by using the maximum pulse discharge current of the power battery system under different characteristic operating conditions, the pulse discharge power of the power battery system under different characteristic operating conditions is calculated, and the pulse discharge capability of the power battery system under standard pulse, short pulse and long pulse is obtained, thereby determining the pulse discharge capability of the power battery system, and then formulating the corresponding pulse discharge power MAP based on the pulse discharge capability of the power battery system.

[0162] Understandably, the pulse discharge power MAP is typically in the form of a two-dimensional table, recording the pulse discharge power at different pulse times, temperatures, and states of charge. The MAP table transmits data to the battery management system (BMS), which then retrieves the system's maximum pulse discharge current at the corresponding operating point based on the collected real-time temperature and state of charge.

[0163] It should be understood that the established pulse discharge power MAP usually needs to be verified. Verification typically employs vehicle performance testing and calibration. Based on the vehicle's power demand signal, the battery management system (BMS) records the power usage time and switches between short pulse / standard pulse / long pulse power MPA using an accumulation / subtraction method. The pulse discharge power MAP table is then checked and adjusted to meet the vehicle's performance requirements. In low-temperature and low-SOC conditions, a power limiting protection strategy is employed to prevent cell over-discharge and excessive discharge, thus avoiding cell undervoltage faults.

[0164] This embodiment provides a method for evaluating the pulse discharge performance of a power battery system. It utilizes the relationship between the cell's operating voltage and the pulse discharge current to construct an optimization model for the cell's pulse discharge current. By solving the model, the maximum pulse discharge current of the cell under different pulse durations, temperatures, and states of charge is identified, allowing for a rapid and accurate assessment of the cell's pulse discharge capability. Based on the cell's pulse discharge capability and following the principle of safety priority, the maximum pulse discharge current of the power battery system is determined, and the pulse discharge power of the power battery system is calculated. This allows for a rapid and accurate assessment of the power battery system's pulse discharge capability, and the development of a pulse discharge power MAP to ensure the safety of the cell throughout its entire lifespan, enabling the power battery to operate safely and efficiently.

[0165] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 2 Step S60 may include steps S601 to S602:

[0166] Step S601: Obtain the fifth correspondence between the system's maximum pulse discharge current, system open-circuit voltage, system internal resistance, internal resistance correction coefficient, and pulse discharge power;

[0167] It should be noted that the third correspondence between the system's maximum pulse discharge current, system open-circuit voltage, system internal resistance, internal resistance correction coefficient, and pulse discharge power—that is, the calculation formula for the pulse discharge power of the power battery system—is as follows:

[0168] P sys =(V sys,OCV -I sys,pulse ·R sys ·ε)·I sys,pulse

[0169] In the formula, P sys I represents the pulse discharge power. sys,pulse V represents the system's maximum pulse discharge current. sys,OCV R represents the system open-circuit voltage. sys ε represents the internal resistance of the system, and ε represents the internal resistance correction factor.

[0170] Step S602: Based on the fifth correspondence, the maximum pulse discharge current of the power battery system under different characteristic operating conditions, the open circuit voltage of the power battery system, the internal resistance of the system, and the internal resistance correction coefficient, determine the pulse discharge power of the power battery system under different characteristic operating conditions.

[0171] Understandably, by substituting relevant data under different characteristic operating conditions, the pulse discharge power of the power battery system under different characteristic operating conditions can be calculated.

[0172] This embodiment provides a method for evaluating the pulse discharge performance of a power battery system. It utilizes the relationship between the cell's operating voltage and the pulse discharge current to construct an optimization model for the cell's pulse discharge current. By solving the model, the maximum pulse discharge current of the cell under different pulse durations, temperatures, and states of charge is identified, allowing for a rapid and accurate assessment of the cell's pulse discharge capability. Based on the cell's pulse discharge capability and following the principle of safety priority, the maximum pulse discharge current of the power battery system is determined, and the pulse discharge power of the power battery system is calculated. This allows for a rapid and accurate assessment of the power battery system's pulse discharge capability, and the development of a pulse discharge power MAP to ensure the safety of the cell throughout its entire lifespan, enabling the power battery to operate safely and efficiently.

[0173] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the evaluation method of the pulse discharge performance of the power battery system of this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0174] This application also provides an evaluation device for the pulse discharge performance of a power battery system, please refer to... Figure 3 The evaluation device for the pulse discharge performance of the power battery system includes:

[0175] Data solving module 10 is used to construct a corresponding cell pulse discharge current optimization model based on the relationship between cell working voltage and pulse discharge current under different characteristic operating conditions. The characteristic operating conditions consist of characteristic pulse time, characteristic temperature and characteristic state of charge.

[0176] The data solving module 10 is also used to initialize the position of the gray wolves in the population using a chaotic mapping mechanism and to construct a fitness function, where the position is used to characterize the pulse discharge current.

[0177] The data solving module 10 is also used to divide the gray wolves in the population into alpha wolves, suboptimal wolves, third-best wolves, and the remaining wolves based on the fitness function and the position of the gray wolves in the population. Based on the similarity between the suboptimal wolves and the alpha wolves, and the similarity between the third-best wolves and the alpha wolves, the weights of the suboptimal level and the third-best level are determined respectively. Based on the weights of the alpha wolf level, the suboptimal level, and the third-best level, the position of the remaining wolves is updated. The alpha wolves, suboptimal wolves, third-best wolves, and the remaining wolves in the population are re-divided. This process is repeated until the iteration termination condition is met, and the target alpha wolf is obtained.

[0178] The data solving module 10 is also used to take the pulse discharge current represented by the position of the target wolf as the solution of the corresponding cell pulse discharge current optimization model, and obtain the maximum pulse discharge current of the cell under different characteristic working conditions.

[0179] The performance evaluation module 20 is used to determine the maximum pulse discharge current of the power battery system under different characteristic operating conditions based on the system limit discharge current, the system peak current, and the maximum pulse discharge current of the cell.

[0180] The performance evaluation module 20 is also used to determine the pulse discharge power of the power battery system under different characteristic operating conditions based on the maximum pulse discharge current of the power battery system under different characteristic operating conditions, and to formulate and verify the pulse discharge power MAP.

[0181] In one feasible implementation, the data solving module 10 is also used to calculate the fitness value corresponding to the position of the gray wolf in the population based on the fitness function and the position of the gray wolf in the population.

[0182] Based on the fitness values ​​corresponding to the positions of the gray wolves in the population, the gray wolves in the population are sorted in descending order to obtain the individual sequence of the population.

[0183] The alpha wolf is selected from the individual sequences based on the alpha wolf level weight, the second best wolf is selected from the individual sequences other than the alpha wolf based on the preset second best ratio, and the third best wolf is selected from the individual sequences other than the alpha wolf and the second best wolf based on the preset third best ratio.

[0184] Based on the selected alpha wolf, second-best wolf, and third-best wolf, the remaining wolves in the individual sequence are determined.

[0185] In one feasible implementation, the data solving module 10 is also used to obtain the similarity between the second-best wolf and the alpha wolf, as well as the similarity between the third-best wolf and the alpha wolf.

[0186] Obtain the similarity between the second-best wolf and the alpha wolf, the similarity between the third-best wolf and the alpha wolf, and the first correspondence between the alpha wolf level weight and the second-best level weight;

[0187] Obtain the similarity between the second-best wolf and the alpha wolf, the similarity between the third-best wolf and the alpha wolf, and the second correspondence between the alpha wolf level weight and the third-best level weight;

[0188] The weight of the second-best wolf level is determined based on the similarity between the second-best wolf and the alpha wolf, the similarity between the third-best wolf and the alpha wolf, the alpha wolf level weight, and the first correspondence.

[0189] The weight of the third best wolf level is determined based on the similarity between the second best wolf and the alpha wolf, the similarity between the third best wolf and the alpha wolf, the alpha wolf level weight, and the second correspondence.

[0190] In one feasible implementation, the data solving module 10 is also used to obtain a third correspondence between location distance, number of individuals and similarity;

[0191] The similarity between the second-best wolf and the alpha wolf is determined based on the positional distance between them, the number of second-best wolves, and the third correspondence.

[0192] The similarity between the third-ranked wolf and the alpha wolf is determined based on the positional distance between them, the number of third-ranked wolves, and the third correspondence.

[0193] In one feasible implementation, the data solving module 10 is further configured to take the position of the alpha wolf as the first position, the position of a randomly selected second-best wolf as the second position, the position of a randomly selected third-best wolf as the third position, and the updated positions of the remaining wolves as the fourth position.

[0194] Obtain the fourth correspondence between the first position, second position, third position, alpha wolf level weight, second best level weight, third best level weight, and fourth position;

[0195] Based on the first position, second position, third position, alpha wolf level weight, second best level weight, third best level weight, and the fourth correspondence, the fourth position is determined, and the updated positions of the remaining wolves are obtained.

[0196] In one feasible implementation, the cell operating voltage is equal to the open-circuit voltage at the initial moment of discharge minus the product of the cell's dynamic internal resistance and the pulse discharge current.

[0197] The dynamic internal resistance of a battery cell is equal to the sum of its ohmic internal resistance and polarization internal resistance.

[0198] The dynamic internal resistance of the battery cell conforms to the internal resistance function relationship obtained by fitting.

[0199] The operating voltage of the cell at the discharge end is greater than or equal to the discharge cutoff voltage.

[0200] The pulse discharge current is greater than zero;

[0201] The relationship between the cell operating voltage and the pulse discharge current is linear.

[0202] The temperature rise of the battery cell during a single pulse is less than or equal to the preset temperature rise safety threshold.

[0203] In one feasible implementation, the performance evaluation module 20 is also used to obtain the system limit voltage, system peak current and system internal resistance of the power battery system.

[0204] Based on the number of cells connected in series and the cell open-circuit voltage under different characteristic operating conditions, the system open-circuit voltage under different characteristic operating conditions;

[0205] Based on the system open-circuit voltage, system limit voltage and system internal resistance of the power battery system, the system limit discharge current under different characteristic operating conditions is determined.

[0206] Based on the number of modules in parallel and the maximum pulse discharge current of the cells under different characteristic operating conditions, the maximum pulse discharge current of the cell group under different characteristic operating conditions is determined.

[0207] Following the principle of safety first, the minimum value among the system limit discharge current, system peak current, and cell pack maximum pulse discharge current is taken as the system maximum pulse discharge current of the power battery system under the corresponding characteristic operating conditions.

[0208] In one feasible implementation, the performance evaluation module 20 is also used to obtain the fifth correspondence between the system's maximum pulse discharge current, system open-circuit voltage, system internal resistance, internal resistance correction coefficient, and pulse discharge power.

[0209] Based on the fifth correspondence, the maximum pulse discharge current of the power battery system under different characteristic operating conditions, as well as the system open-circuit voltage, system internal resistance, and internal resistance correction coefficient of the power battery system, the pulse discharge power of the power battery system under different characteristic operating conditions is determined.

[0210] The device for evaluating the pulse discharge performance of a power battery system provided in this application employs the evaluation method for the pulse discharge performance of a power battery system described in the above embodiments. This solves the technical problems that traditional methods for evaluating the pulse discharge performance of a power battery system are complex, costly, and difficult to implement quickly and accurately. Compared with the prior art, the beneficial effects of the device for evaluating the pulse discharge performance of a power battery system provided in this application are the same as those of the evaluation method for the pulse discharge performance of a power battery system provided in the above embodiments. Furthermore, other technical features of the device for evaluating the pulse discharge performance of a power battery system are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0211] This application provides an evaluation device for the pulse discharge performance of a power battery system. The evaluation device for the pulse discharge performance of a power battery system includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the evaluation method for the pulse discharge performance of the power battery system in the above embodiment 1.

[0212] The following is for reference. Figure 4 The diagram illustrates a structural schematic of an evaluation device suitable for implementing the pulse discharge performance of a power battery system according to embodiments of this application. The evaluation device for the pulse discharge performance of a power battery system in embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 4 The illustrated device for evaluating the pulse discharge performance of a power battery system is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0213] like Figure 4As shown, the power battery system pulse discharge performance evaluation device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the power battery system pulse discharge performance evaluation device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the power battery system pulse discharge performance evaluation device to communicate wirelessly or wiredly with other devices to exchange data. Although the figure shows a power battery system pulse discharge performance evaluation device with various systems, it should be understood that it is not required to implement or possess all the systems shown. More or fewer systems can be implemented alternatively.

[0214] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0215] The device for evaluating the pulse discharge performance of a power battery system provided in this application employs the evaluation method for the pulse discharge performance of a power battery system described in the above embodiments. This solves the technical problems that traditional methods for evaluating the pulse discharge performance of a power battery system are complex, costly, and difficult to implement quickly and accurately. Compared with the prior art, the beneficial effects of the device for evaluating the pulse discharge performance of a power battery system provided in this application are the same as those of the evaluation method for the pulse discharge performance of a power battery system provided in the above embodiments. Furthermore, other technical features of this device for evaluating the pulse discharge performance of a power battery system are the same as those disclosed in the method of the previous embodiment, and will not be repeated here.

[0216] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0217] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0218] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the method for evaluating the pulse discharge performance of the power battery system in the above embodiments.

[0219] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0220] The aforementioned computer-readable storage medium may be included in the evaluation equipment for the pulse discharge performance of the power battery system; or it may exist independently and not be assembled into the evaluation equipment for the pulse discharge performance of the power battery system.

[0221] The aforementioned computer-readable storage medium carries one or more programs. When these programs are executed by the power battery system pulse discharge performance evaluation device, the power battery system pulse discharge performance evaluation device: constructs a corresponding cell pulse discharge current optimization model based on the relationship between cell operating voltage and pulse discharge current under different characteristic operating conditions. The characteristic operating conditions consist of characteristic pulse time, characteristic temperature, and characteristic state of charge. It initializes the positions of gray wolves in the population using a chaotic mapping mechanism and constructs a fitness function, where position is used to characterize the pulse discharge current. Based on the fitness function and the positions of gray wolves in the population, it divides the gray wolves into alpha wolves, suboptimal wolves, third-optimal wolves, and the remaining wolves. Based on the similarity between suboptimal wolves and alpha wolves, and the similarity between third-optimal wolves and alpha wolves, it determines the suboptimal level. The system uses weights and third-optimal level weights, and updates the positions of the remaining wolves based on the weights of the alpha wolf, second-optimal level, and third-optimal level. It then reclassifies the alpha wolf, second-optimal wolf, third-optimal wolf, and other wolves in the population, iterating until the iteration termination condition is met to obtain the target alpha wolf. The pulse discharge current represented by the position of the target alpha wolf is used as the solution to the corresponding cell pulse discharge current optimization model, obtaining the maximum pulse discharge current of the cell under different characteristic operating conditions. Based on the system limit discharge current, system peak current, and maximum cell pulse discharge current, the maximum system pulse discharge current of the power battery system under different characteristic operating conditions is determined. Based on the maximum system pulse discharge current of the power battery system under different characteristic operating conditions, the pulse discharge power of the power battery system under different characteristic operating conditions is determined, and a pulse discharge power MAP is developed and verified.

[0222] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0223] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0224] The modules described in the embodiments of the present application may be implemented in software or hardware, wherein the name of a module does not necessarily limit the unit itself.

[0225] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described method for evaluating the pulse discharge performance of a power battery system. This solves the technical problems that traditional methods for evaluating the pulse discharge performance of a power battery system are complex, costly, and difficult to implement quickly and accurately. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the power battery system pulse discharge performance evaluation method provided in the above embodiments, and will not be repeated here.

[0226] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described method for evaluating the pulse discharge performance of a power battery system.

[0227] The computer program product provided in this application can solve the technical problems that traditional methods for evaluating the pulse discharge performance of power battery systems are complex, costly, and difficult to implement quickly and accurately. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the power battery system pulse discharge performance evaluation method provided in the above embodiments, and will not be repeated here.

[0228] The above are only some embodiments of this application and do not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A method for evaluating the pulse discharge performance of a power battery system, characterized in that, The method includes: Based on the relationship between cell operating voltage and pulse discharge current under different characteristic operating conditions, a corresponding cell pulse discharge current optimization model is constructed. The characteristic operating conditions consist of characteristic pulse time, characteristic temperature, and characteristic state of charge. The positions of gray wolves in the population are initialized using a chaotic mapping mechanism, and a fitness function is constructed, wherein the positions are used to characterize the pulse discharge current; Based on the fitness function and the position of the gray wolves in the population, the gray wolves in the population are divided into alpha wolves, suboptimal wolves, third-best wolves, and the remaining wolves. Based on the similarity between the suboptimal wolves and the alpha wolf, and the similarity between the third-best wolves and the alpha wolf, the suboptimal level weight and the third-best level weight are determined respectively. Based on the alpha wolf level weight, the suboptimal level weight, and the third-best level weight, the position of the remaining wolves is updated. The alpha wolves, suboptimal wolves, third-best wolves, and the remaining wolves in the population are reclassified. This process is repeated until the iteration termination condition is met, and the target alpha wolf is obtained. The pulse discharge current represented by the position of the target wolf is used as the solution of the corresponding cell pulse discharge current optimization model to obtain the maximum pulse discharge current of the cell under different characteristic working conditions. Based on the system's ultimate discharge current, the system's peak current, and the cell's maximum pulse discharge current, the maximum pulse discharge current of the power battery system under different characteristic operating conditions is determined. Based on the maximum pulse discharge current of the power battery system under different characteristic operating conditions, the pulse discharge power of the power battery system under different characteristic operating conditions is determined, and the pulse discharge power MAP is formulated and verified.

2. The method as described in claim 1, characterized in that, The step of dividing the gray wolves in the population into alpha wolves, second-best wolves, third-best wolves, and the remaining wolves based on the fitness function and the position of the gray wolves in the population includes: Based on the fitness function and the position of the gray wolves in the population, calculate the fitness value corresponding to the position of the gray wolf in the population; Based on the fitness values ​​corresponding to the positions of the gray wolves in the population, the gray wolves in the population are sorted in descending order to obtain the individual sequence of the population; The alpha wolf is selected from the individual sequence based on the alpha wolf level weight, the second best wolf is selected from the individual sequence other than the alpha wolf based on a preset second best ratio, and the third best wolf is selected from the individual sequence other than the alpha wolf and the second best wolf based on a preset third best ratio. Based on the selected alpha wolf, second-best wolf, and third-best wolf, the remaining wolves in the individual sequence are determined.

3. The method as described in claim 1, characterized in that, The steps of determining the weights of the second-best and third-best levels based on the similarity between the second-best wolf and the alpha wolf, and the similarity between the third-best wolf and the alpha wolf, respectively, include: Obtain the similarity between the second-best wolf and the alpha wolf, as well as the similarity between the third-best wolf and the alpha wolf; Obtain the similarity between the second-best wolf and the alpha wolf, the similarity between the third-best wolf and the alpha wolf, and the first correspondence between the alpha wolf level weight and the second-best level weight; Obtain the similarity between the second-best wolf and the alpha wolf, the similarity between the third-best wolf and the alpha wolf, and the second correspondence between the alpha wolf level weight and the third-best level weight; The suboptimal level weight is determined based on the similarity between the suboptimal wolf and the alpha wolf, the similarity between the third-best wolf and the alpha wolf, the alpha wolf level weight, and the first correspondence. The third-best level weight is determined based on the similarity between the second-best wolf and the alpha wolf, the similarity between the third-best wolf and the alpha wolf, the alpha wolf level weight, and the second correspondence.

4. The method as described in claim 3, characterized in that, The steps for obtaining the similarity between the second-best wolf and the alpha wolf, and the similarity between the third-best wolf and the alpha wolf, include: Obtain the third correspondence between location distance, number of individuals, and similarity; The similarity between the second-best wolf and the alpha wolf is determined based on the positional distance between them, the number of second-best wolves, and the third correspondence. The similarity between the third superior wolf and the alpha wolf is determined based on the positional distance between them, the number of third superior wolves, and the aforementioned third correspondence.

5. The method as described in claim 1, characterized in that, The step of updating the positions of the remaining wolves based on the alpha wolf level weight, the second-best level weight, and the third-best level weight includes: The position of the alpha wolf is taken as the first position, the position of a randomly selected second-best wolf is taken as the second position, the position of a randomly selected third-best wolf is taken as the third position, and the positions of the remaining wolves after the update are taken as the fourth position. Obtain the fourth correspondence between the first position, second position, third position, alpha wolf level weight, second best level weight, third best level weight, and fourth position; Based on the first position, the second position, the third position, the alpha wolf level weight, the second-best level weight, the third-best level weight, and the fourth correspondence, the fourth position is determined, and the updated positions of the remaining wolves are obtained.

6. The method as described in claim 1, characterized in that, The cell pulse discharge current optimization model includes at least the following constraints: The cell's operating voltage is equal to the open-circuit voltage at the initial moment of discharge minus the product of the cell's dynamic internal resistance and the pulse discharge current. The dynamic internal resistance of a battery cell is equal to the sum of its ohmic internal resistance and polarization internal resistance. The dynamic internal resistance of the battery cell conforms to the internal resistance function relationship obtained by fitting. The operating voltage of the cell at the discharge end is greater than or equal to the discharge cutoff voltage. The pulse discharge current is greater than zero; The relationship between the cell operating voltage and the pulse discharge current is linear. The temperature rise of the battery cell during a single pulse is less than or equal to the preset temperature rise safety threshold.

7. The method as described in claim 1, characterized in that, The steps for determining the maximum pulse discharge current of the power battery system under different characteristic operating conditions based on the system's limiting discharge current, system peak current, and cell maximum pulse discharge current include: Obtain the system limit voltage, system peak current, and system internal resistance of the power battery system; Based on the number of cells connected in series and the cell open-circuit voltage under different characteristic operating conditions, the system open-circuit voltage under different characteristic operating conditions; Based on the system open-circuit voltage, system limit voltage and system internal resistance of the power battery system, the system limit discharge current under different characteristic operating conditions is determined. Based on the number of modules in parallel and the maximum pulse discharge current of the cells under different characteristic operating conditions, the maximum pulse discharge current of the cell group under different characteristic operating conditions is determined. Following the principle of safety first, the minimum value among the system limit discharge current, system peak current, and cell pack maximum pulse discharge current is taken as the system maximum pulse discharge current of the power battery system under the corresponding characteristic operating conditions.

8. The method as described in claim 1, characterized in that, The step of determining the pulse discharge power of the power battery system under different characteristic operating conditions based on the maximum pulse discharge current of the power battery system under different characteristic operating conditions includes: Obtain the fifth correspondence between the system's maximum pulse discharge current, system open-circuit voltage, system internal resistance, internal resistance correction coefficient, and pulse discharge power; Based on the fifth correspondence, the maximum pulse discharge current of the power battery system under different characteristic operating conditions, and the system open-circuit voltage, system internal resistance, and internal resistance correction coefficient of the power battery system, the pulse discharge power of the power battery system under different characteristic operating conditions is determined.

9. A device for evaluating the pulse discharge performance of a power battery system, characterized in that, The device includes: The data solving module is used to construct a corresponding cell pulse discharge current optimization model based on the relationship between cell operating voltage and pulse discharge current under different characteristic operating conditions. The characteristic operating conditions consist of characteristic pulse time, characteristic temperature and characteristic state of charge. The data solving module is also used to initialize the position of the gray wolves in the population using a chaotic mapping mechanism and construct a fitness function, wherein the position is used to characterize the pulse discharge current. The data solving module is further configured to, based on the fitness function and the position of the gray wolves in the population, divide the gray wolves in the population into alpha wolves, suboptimal wolves, third-optimal wolves, and the remaining wolves; determine the suboptimal level weight and the third-optimal level weight based on the similarity between the suboptimal wolves and the alpha wolf, and the similarity between the third-optimal wolves and the alpha wolf, respectively; update the position of the remaining wolves based on the alpha wolf level weight, the suboptimal level weight, and the third-optimal level weight; reclassify the alpha wolves, suboptimal wolves, third-optimal wolves, and the remaining wolves in the population; and iterate continuously until the iteration termination condition is met to obtain the target alpha wolf. The data solving module is also used to take the pulse discharge current represented by the position of the target wolf as the solution of the corresponding cell pulse discharge current optimization model to obtain the maximum pulse discharge current of the cell under different characteristic working conditions. The performance evaluation module is used to determine the maximum pulse discharge current of the power battery system under different characteristic operating conditions based on the system's limit discharge current, the system's peak current, and the cell's maximum pulse discharge current. The performance evaluation module is also used to determine the pulse discharge power of the power battery system under different characteristic operating conditions based on the maximum pulse discharge current of the power battery system under different characteristic operating conditions, formulate the pulse discharge power MAP, and verify it.

10. An evaluation device for the pulse discharge performance of a power battery system, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the method for evaluating the pulse discharge performance of a power battery system as described in any one of claims 1 to 8.

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