Energy storage battery compartment status assessment method, device, medium and product

Abstract

The present invention discloses a method, device, medium and product for evaluating the state of an energy storage battery compartment, and relates to the technical field of battery compartment state evaluation. The method comprises: for each battery cell in the energy storage battery compartment, calculating the SOH value of the battery cell according to the calendar aging attenuation parameter and the cycle aging attenuation parameter; constructing a multi-state model set of the battery cell according to the SOH value of the battery cell and the normal distribution of the battery cell performance; using a universal generating function method, constructing the UGF function of the battery cell according to the multi-state model set of the battery cell; constructing the UGF function of the energy storage battery compartment according to the UGF functions of all battery cells; extracting the state distribution information of the energy storage battery compartment according to the UGF function of the energy storage battery compartment. The present invention constructs a multi-state model that takes into account the calendar aging attenuation and cycle aging attenuation of the battery cell performance, accurately reflects the operating status of the energy storage system, and improves the reliability evaluation accuracy of the energy storage battery compartment.

Description

Technical Field

[0001] The present invention relates to the technical field of battery compartment status assessment, and in particular to a method, device, medium and product for assessing the status of an energy storage battery compartment. Background Art

[0002] Renewable energy such as wind and solar energy are widely used in power systems. As energy storage batteries are their core components, their reliability is crucial to the operation of the entire system. With the expansion of energy storage scale, the number of battery cells increases and the hierarchical structure becomes complex. Their performance degradation and changes in connection structure will affect the reliability of the energy storage system and the power system. Therefore, it is crucial to conduct a comprehensive and accurate reliability assessment of the battery energy storage system, which requires considering the multi-state model, uncertainty and fuzzy characteristics of the battery. Reliability assessment of power systems is a key step in ensuring safe and stable operation of power supply. With the rapid development and application of new energy technologies, energy storage batteries are an important component, and their reliability assessment is particularly critical. Traditional power system reliability assessment models often fail to effectively take into account the particularity of energy storage batteries. Therefore, a more accurate energy storage battery compartment status assessment method is urgently needed. Summary of the invention

[0003] The purpose of the present invention is to provide a method, device, medium and product for evaluating the state of an energy storage battery compartment, which can improve the accuracy of reliability evaluation of the energy storage battery compartment.

[0004] To achieve the above object, the present invention provides the following solution.

[0005] A method for evaluating the state of an energy storage battery compartment comprises the following steps.

[0006] For each battery cell in the energy storage battery compartment, the calendar aging attenuation parameter and the cycle aging attenuation parameter of the battery cell are obtained; the SOH value of the battery cell is calculated according to the calendar aging attenuation parameter and the cycle aging attenuation parameter; the energy storage battery compartment includes a plurality of battery cells; the calendar aging attenuation parameters include battery activation energy and temperature; the cycle aging attenuation parameters include the temperature during the battery cycle and the equivalent number of cycles of the energy released by charging and discharging relative to the rated capacity.

[0007] A multi-state model set of the battery cell is constructed according to the SOH value of the battery cell and the normal distribution of the battery cell performance.

[0008] The UGF function of the battery cell is constructed according to the multi-state model set of the battery cell by using the universal generating function method.

[0009] The UGF function of the energy storage battery compartment is constructed according to the UGF functions of all the battery cells.

[0010] A multi-state reliability model of the energy storage battery compartment is established according to the UGF function of the energy storage battery compartment, and the state distribution information of the energy storage battery compartment is extracted according to the multi-state reliability model of the energy storage battery compartment; the state distribution information is used to evaluate the reliability of the energy storage battery compartment.

[0011] A computer device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-mentioned method for evaluating the state of an energy storage battery compartment.

[0012] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above-mentioned method for evaluating the state of an energy storage battery compartment.

[0013] A computer program product includes a computer program, which, when executed by a processor, implements the steps of the above-mentioned method for evaluating the state of an energy storage battery compartment.

[0014] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects: the present invention provides a method, device, medium and product for evaluating the state of an energy storage battery compartment. First, for each battery cell in the energy storage battery compartment, the calendar aging attenuation parameter and the cycle aging attenuation parameter of the battery cell are obtained; the SOH value of the battery cell is calculated according to the calendar aging attenuation parameter and the cycle aging attenuation parameter; the energy storage battery compartment includes a plurality of battery cells; the calendar aging attenuation parameter includes the battery activation energy and the temperature; the cycle aging attenuation parameter includes the temperature during the battery cycle and the energy released by charging and discharging relative to the equivalent number of cycles of the rated capacity; a multi-state model set of the battery cell is constructed according to the SOH value of the battery cell and the normal distribution of the battery cell performance; a UGF function of the battery cell is constructed according to the multi-state model set of the battery cell by using the universal generating function method; a UGF function of the energy storage battery compartment is constructed according to the UGF functions of all battery cells; the state distribution information of the energy storage battery compartment is extracted according to the UGF function of the energy storage battery compartment; the state distribution information is used to evaluate the reliability of the energy storage battery compartment. The present invention constructs a multi-state model that takes into account the calendar aging decay and cycle aging decay of battery cell performance, accurately reflects the operating status of the energy storage system, and improves the reliability assessment accuracy of the energy storage battery compartment. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 A schematic flow chart of a method for evaluating the status of an energy storage battery compartment provided in Example 1 of the present invention.

[0017] Figure 2 A schematic diagram of the specific implementation process of the energy storage battery compartment status assessment method provided in Example 1 of the present invention.

[0018] Figure 3 Schematic diagram of the multi-level recursive model of the energy storage battery compartment provided in Example 1 of the present invention.

[0019] Figure 4 An internal structure diagram of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] The purpose of the present invention is to provide a method, device, medium and product for evaluating the state of an energy storage battery compartment, aiming to construct a multi-state model that takes into account the calendar aging decay and cycle aging decay of battery cell performance, accurately reflects the operating status of the energy storage system, and improves the accuracy of reliability evaluation of the energy storage battery compartment.

[0022] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0023] Example 1: Figure 1 and Figure 2 As shown, this embodiment is used to provide a method for evaluating the status of an energy storage battery compartment, including the following steps.

[0024] S1: For each battery cell in the energy storage battery compartment, obtain the calendar aging attenuation parameter and the cycle aging attenuation parameter of the battery cell; calculate the SOH value of the battery cell according to the calendar aging attenuation parameter and the cycle aging attenuation parameter; the energy storage battery compartment includes a plurality of battery cells; the calendar aging attenuation parameters include battery activation energy and temperature; the cycle aging attenuation parameters include the temperature during the battery cycle and the equivalent number of cycles of the energy released by charging and discharging relative to the rated capacity.

[0025] S2: constructing a multi-state model set of the battery cell according to the SOH value of the battery cell and the normal distribution of the battery cell performance.

[0026] S3: constructing a UGF function of the battery cell according to the multi-state model set of the battery cell using a universal generating function method.

[0027] S4: Constructing the UGF function of the energy storage battery compartment according to the UGF functions of all the battery cells.

[0028] S5: Establish a multi-state reliability model of the energy storage battery compartment according to the UGF function of the energy storage battery compartment, and extract the state distribution information of the energy storage battery compartment according to the multi-state reliability model of the energy storage battery compartment; the state distribution information is used to evaluate the reliability of the energy storage battery compartment.

[0029] Step S1 is used to construct a battery cell SOH attenuation model to calculate the SOH value of the battery cell: the performance attenuation of the battery can be reflected based on the SOH (battery health, which is the percentage of the current capacity of the battery cell to the factory capacity) of the battery cell. The performance attenuation of the battery cell includes calendar aging attenuation and cycle aging attenuation. Considering the two aging attenuations, the calculation formula of the SOH value of the battery cell is as follows.

[0030] (1).

[0031] (2).

[0032] (3).

[0033] in, The capacity decay of battery cycle aging; , is the cycle aging attenuation parameter related to SOC (i.e., the percentage of remaining battery power); is a parameter related to temperature; It is the equivalent number of cycles of energy released by charging and discharging during battery cycling relative to the rated capacity; The battery calendar aging capacity decay; is the calendar aging parameter related to SOC; is the battery activation energy; is the Boltzmann constant; is temperature; for SOH value of battery cells at the moment; is a function of time, and in this embodiment, it is linearly related to time, that is, = ; is the battery SOH value at the initial moment. The SOH of the battery cell at the initial moment is 100%.

[0034] The different states of the battery cells are divided according to the different SOH values ​​of the battery cells, and each state corresponds to a certain SOH range.

[0035] (4).

[0036] in, For battery cells status, and The battery cells are The upper and lower limits of the SOH range corresponding to each state.

[0037] In step S2, a multi-state model set of the battery cell is constructed according to the SOH value of the battery cell and the normal distribution of the battery cell performance, specifically including: taking the SOH value of the battery cell as the SOH mean, and constructing the multi-state model set of the battery cell according to the SOH mean and the normal distribution of the battery cell performance.

[0038] The performance levels of a large number of battery cells can be considered to obey a normal distribution, that is, the SOH value of the battery cell calculated by formula (3) is taken as the mean value of the battery SOH at each moment, and the standard deviation is calculated using formula (6).

[0039] (5).

[0040] (6).

[0041] in, for The mean of the time distribution, for Time distribution standard deviation. As time goes by, the distribution mean gradually decreases, indicating that the battery capacity gradually decays; the standard deviation gradually increases, indicating that the differences between batteries gradually increase.

[0042] The performance state distribution of the battery can be expressed as shown in the following formula.

[0043] (7).

[0044] .

[0045] .

[0046] in, is in state The probability of is the normalized cumulative probability density function of the normal distribution, is the cumulative probability density function of the normal distribution.

[0047] Battery status collection It is a two-tuple containing the state value and the number of times the state occurs.

[0048] (8).

[0049] in, A collection of multi-state models representing battery cells; For battery cells status; Indicates status Number of occurrences; for The probability set corresponding to each state at the moment; for Moment The probability value of a state.

[0050] Step S3 is as follows: At present, large-scale battery energy storage is in the form of a container-shaped battery compartment, which contains a large number of battery cells. Considering the advantages in solving multi-state problems, the UGF method is used to establish the multi-state of the energy storage system. According to the state division basis of the battery cell (minimum level unit) in steps S1 and S2, the UGF function of the battery cell is constructed in the form shown in the following formula.

[0051] (9).

[0052] in, Indicates battery cells UGF function at the moment; for At this moment, the battery cell is The probability value of each state; =1, 2, 3... , is the total number of states; For battery cells The state value of each state; Indicates status Number of occurrences.

[0053] Considering the multiple states of each battery cell, the entire battery energy storage system will have a large number of states. Performing UGF calculations on multiple battery cells at the same time takes up a large amount of space, takes a long time, and has low calculation efficiency. Therefore, this embodiment distinguishes different levels of a large number of battery cells in the battery energy storage compartment, and recursively calculates the UGF function of the battery compartment layer by layer.

[0054] like Figure 3As shown, step S4 in this embodiment is used for recursive modeling of the battery compartment based on structural operator definition and splitting operation. The UGF function of the energy storage battery compartment is constructed according to the UGF functions of all the battery cells, which specifically includes the following steps.

[0055] Based on the connection structure inside the energy storage battery compartment, all the battery cells in the energy storage battery compartment are hierarchically divided to obtain a plurality of hierarchies, specifically including: based on the series connection structure and the parallel connection structure inside the energy storage battery compartment, all the battery cells in the energy storage battery compartment are hierarchically divided to obtain a plurality of hierarchies. Each hierarchical level includes one or more hierarchical units; one hierarchical unit corresponds to one battery cell.

[0056] For each level, the UGF function of the level is constructed according to the UGF functions of the level units contained in the previous level of the level, and the UGF function of the energy storage battery compartment is constructed level by level by collective recursive operations.

[0057] According to the serial-parallel connection structure inside the battery compartment, the battery compartment is divided into different levels, and each time it passes through the serial-parallel connection structure, it is counted as one level. According to the two connection forms of series and parallel connection, the UGF function of each level is calculated layer by layer starting from the battery cell.

[0058] (10).

[0059] in, For the Hierarchical UGF function; The Universal Generation Operator (UGO) is used to reflect the serial and parallel connection relationship between the units in the hierarchy; For the Level The UGF function of the level unit, For the The number of hierarchical units connected in series or in parallel in the hierarchy; For the The total number of states of the first level unit in the hierarchy; For the The state of the first level unit in the hierarchy, =1, 2, 3... ; For the Level The total number of states of level units; For the The state of the first level unit in the hierarchy, =1, 2, 3... ; for Level Level unit The probability of a state; is the total number of states; for Level The probability of a state; for Lower level Level unit The state value of each state; for Level The state value of each state; It is part of the representation of the UGF function and is a representation of the z-transform. It means that for each state The operation process of Indicates the operation mode. According to the specific forms of series connection and parallel connection, series connection is min operation and parallel connection is mean operation. For details, see formula (11).

[0060] (11).

[0061] The properties of the synthesis operator depend on the specific operation rules. If the defined operation rules satisfy the associativity, the synthesis operator of the system also satisfies it. Therefore, in order to further realize the recursive operation of the series and parallel structures in each layer, for the operation operator The operation is further split into two stages: addition and division. Only the addition operation is calculated during the recursion.

[0062] (12).

[0063] Then, the series or parallel operation at each level can be calculated recursively, and the UGF function of the level, that is, the UGF function of the battery compartment is in the form shown in the following formula.

[0064] (13).

[0065] in, for Moment Hierarchical UGF function; A general generation operator that reflects the serial and parallel connection relationship between units in the hierarchy; for time The UGF function of the level, For the The number of level units contained in the level; for Moment Level The probability of a state, n is the total number of states; For the Level The state value of each state; For the Level The number of times a state occurs.

[0066] Finally, based on the UGF function of the battery compartment, that is, formula (13), the state distribution information of the battery compartment is extracted, and the multi-state reliability model of the energy storage battery compartment is shown in formulas (14) and (15).

[0067] (14).

[0068] (15).

[0069] in, is the state set of the battery compartment; For the battery compartment Moment Status value; For the battery compartment Moment The number of occurrences corresponding to each state; is the probability set of the battery compartment; For the battery compartment Moment The probability value of a state.

[0070] The status distribution information of the battery compartment includes the status value The probability value corresponding to the state There are two parts: the state distribution information of the battery compartment is used to calculate the reliability of the battery compartment.

[0071] This embodiment is based on the multi-state multi-level recursive modeling of the energy storage battery compartment based on the structural operator splitting operation. First, based on the SOH state of the energy storage battery, the SOH decay function of the battery cell is calculated under the consideration of calendar aging decay and cycle aging decay, thereby establishing a multi-state model of the energy storage cell considering the battery performance decay; secondly, the state probability of the energy storage battery sample is solved based on the normal distribution, thereby obtaining the fuzzy multi-state probability of the battery cell; then, according to the series-parallel connection structure inside the battery compartment, the battery compartment is divided into different levels, and on the basis of obtaining the multi-state distribution of the battery cell, the universal generation operator (UGO) is used to recursively calculate the UGF function of the system (i.e., the UGF function of the energy storage battery compartment) starting from the battery cell; finally, a multi-state reliability model of the energy storage battery compartment is established based on the UGF function of the battery compartment, and the state distribution information of the battery compartment is extracted.

[0072] The present invention has the following beneficial effects.

[0073] (1) This embodiment considers multiple states in the process of capacity decay of the battery energy storage system, divides the battery state based on the battery cell SOH decay model, considers calendar aging decay and cycle aging decay, and establishes a multi-state model of energy storage cells that considers battery performance decay. Compared with the traditional two-state model and fuzzy multi-state distribution, this method builds a more refined multi-state model of battery cell performance decay, accurately reflects the operating status of the energy storage system, and makes the probability results more accurate and reliable.

[0074] (2) This embodiment considers that the state distribution of a large number of battery cells conforms to the normal distribution. By solving the state probability of the energy storage battery sample based on the normal distribution of the cell performance, the multi-state probability of the battery cell is obtained, which provides a basis for system state evaluation. Compared with the traditional model, the refined simulation of this method can reflect the dynamic change process of the reliability of the energy storage system, making the reliability calculation results more comprehensive and three-dimensional.

[0075] (3) This embodiment takes into account the different functions and structures of each energy storage part. According to the serial and parallel connection structure inside the battery compartment, the battery compartment is divided into different levels, and the UGF function of the universal generation operator (UGO) is recursively calculated level by level. Finally, the state distribution information of the battery compartment is extracted, and a multi-state reliability model of the energy storage battery compartment is established, which provides theoretical support for system reliability evaluation and optimization. Compared with the traditional model, this embodiment can more flexibly participate in the calculation of large-scale and large-capacity energy storage monomers and energy storage power stations while ensuring the accuracy of the calculation results, greatly improving the simulation calculation speed.

[0076] This embodiment introduces a multi-state model to more accurately describe the performance characteristics and operating behavior of the battery under different working conditions. The multi-state model of the battery can more comprehensively describe the working state of the battery. When performing reliability assessment, it is necessary to consider the failure mechanism and probability of the battery under different states, as well as its impact on the reliability of the entire system. By establishing an accurate multi-state model, the performance degradation and life of the battery can be more accurately predicted, thereby guiding the operation and maintenance of the energy storage system. By accurately describing the multi-states of the battery and considering the mutual influence between different battery cells, the reliability of the energy storage system can be improved and the reliable operation of the energy storage battery system can be ensured.

[0077] Embodiment 2: This embodiment provides a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of a method for evaluating the status of an energy storage battery compartment in Embodiment 1.

[0078] Embodiment 3: This embodiment provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of a method for evaluating the state of an energy storage battery compartment in Embodiment 1 are implemented.

[0079] Embodiment 4: This embodiment provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of a method for evaluating the state of an energy storage battery compartment in Embodiment 1.

[0080] Embodiment 5: This embodiment provides a computer device, which may be a database, and its internal structure diagram may be as follows: Figure 4 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store pending transactions. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for evaluating the state of an energy storage battery compartment in Example 1 is implemented.

[0081] It should be noted that the object information (including but not limited to object device information, object personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in the present invention are all information and data authorized by the object or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0082] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided by the present invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided by the present invention may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided by the present invention may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0083] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0084] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for evaluating the state of an energy storage battery compartment, characterized in that: include: For each battery cell in the energy storage battery compartment, obtaining a calendar aging attenuation parameter and a cycle aging attenuation parameter of the battery cell; The SOH value of the battery cell is calculated according to the calendar aging attenuation parameter and the cycle aging attenuation parameter; the energy storage battery compartment includes a plurality of battery cells; the calendar aging attenuation parameter includes battery activation energy and temperature; the cycle aging attenuation parameter includes the temperature during the battery cycle and the equivalent number of cycles of energy released by charge and discharge relative to the rated capacity; Constructing a multi-state model set of the battery cell according to the SOH value of the battery cell and the normal distribution of the battery cell performance; Using a universal generating function method, constructing a UGF function of the battery cell according to a multi-state model set of the battery cell; The UGF function of the energy storage battery compartment is constructed according to the UGF functions of all the battery cells; the UGF function of the battery cell is as follows: ； in, Indicates battery cells UGF function at the moment; for At this moment, the battery cell is The probability value of a state, =1, 2, 3... , is the total number of states; For battery cells The state value of each state; Indicates status Number of occurrences; The UGF function of the energy storage battery compartment is shown as follows: ； in, for Moment Hierarchical UGF function; A general generation operator that reflects the serial and parallel connection relationship between units in the hierarchy; for time Hierarchical UGF function, For the The number of level units contained in the level; for Moment Level The probability of a state, n is the total number of states; For the Level The state value of each state; For the Level The number of times a state appears; A multi-state reliability model of the energy storage battery compartment is established according to the UGF function of the energy storage battery compartment, and the state distribution information of the energy storage battery compartment is extracted according to the multi-state reliability model of the energy storage battery compartment; the state distribution information is used to evaluate the reliability of the energy storage battery compartment.

2. A method for evaluating the state of an energy storage battery compartment according to claim 1, characterized in that: The UGF function of the energy storage battery compartment is constructed according to the UGF functions of all the battery cells, specifically including: Based on the connection structure inside the energy storage battery compartment, all battery cells in the energy storage battery compartment are divided into several levels; each level includes one or more level units; and one level unit corresponds to one battery cell; For each level, the UGF function of the level is constructed according to the UGF functions of the level units contained in the previous level of the level, and the UGF function of the energy storage battery compartment is constructed level by level by collective recursive operations.

3. A method for evaluating the state of an energy storage battery compartment according to claim 2, characterized in that: Based on the connection structure inside the energy storage battery compartment, all battery cells in the energy storage battery compartment are divided into several levels, specifically including: Based on the series connection structure and the parallel connection structure inside the energy storage battery compartment, all battery cells in the energy storage battery compartment are divided into several levels.

4. A method for evaluating the state of an energy storage battery compartment according to claim 2, characterized in that: The hierarchical UGF function is as follows: ； in, for Moment Hierarchical UGF function; A general generation operator that reflects the serial and parallel connection relationship between units in the hierarchy; for time Level The UGF function of the level unit, For the The number of level units contained in the level; for Moment Level The probability of a state, is the total number of states; For the Level The state value of each state; For the Level The number of times a state occurs.

5. The method for evaluating the state of an energy storage battery compartment according to claim 1, characterized in that: A multi-state model set of the battery cell is constructed according to the SOH value of the battery cell and the normal distribution of the battery cell performance, specifically including: The SOH value of the battery cell is taken as the SOH mean value, and a multi-state model set of the battery cell is constructed according to the SOH mean value and the normal distribution of the battery cell performance.

6. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of a method for evaluating the status of an energy storage battery compartment as described in any one of claims 1 to 5.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of a method for evaluating the state of an energy storage battery compartment described in any one of claims 1 to 5 are implemented.

8. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of a method for evaluating the state of an energy storage battery compartment described in any one of claims 1 to 5 are implemented.

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