Method, device, monitoring system and equipment for determining failure rate of energy storage system

Abstract

The application relates to a method and device for determining failure rate of an energy storage system, a failure monitoring system and equipment. The method comprises: obtaining environmental monitoring data and system monitoring data of the energy storage system; determining failure rates of multiple components in the energy storage system according to the environmental monitoring data, the system monitoring data and a pre-established component failure model; determining failure rates of multiple subsystems corresponding to each energy storage submodule in the energy storage system according to the failure rates of the multiple components and a pre-established subsystem failure model; wherein the subsystem failure model comprises an association relationship between the multiple components; and determining an overall failure rate of the energy storage system according to the failure rates of the multiple subsystems corresponding to each energy storage submodule and a pre-established overall failure model; wherein the overall failure model comprises an association relationship between multiple energy storage submodules. The application can improve the accuracy of the overall failure rate of the energy storage system.

Description

Technical Field

[0001] This application relates to the field of energy storage system technology, specifically to a method, apparatus, failure monitoring system and equipment for determining the failure rate of an energy storage system. Background Technology

[0002] With the development of power electronic devices, battery energy storage technology, and control technology, the voltage and capacity levels of energy storage systems in power systems are constantly being improved. Direct-connected energy storage system technology draws on traditional flexible DC systems, enabling large-capacity single-unit designs; however, the performance and reliability of the power grid also place higher demands on the failure rate of direct-connected energy storage systems.

[0003] Currently, there are several ways to determine the failure rate of an energy storage system. For example, the failure rate can be calculated based on the scores of multiple evaluation indicators; or, a deep learning model can be used to determine the failure rate of the energy storage system.

[0004] However, the above methods are not comprehensive enough in analyzing the failure rate of energy storage systems, and therefore the failure rate is not accurate enough. Summary of the Invention

[0005] To address the aforementioned issues, this application provides a method, apparatus, failure monitoring system, and device for determining the failure rate of an energy storage system, which can improve the accuracy of the overall failure rate of the energy storage system.

[0006] In a first aspect, this application provides a method for determining the failure rate of an energy storage system. The method includes: acquiring environmental monitoring data and system monitoring data of the energy storage system; determining the failure rate of multiple components in the energy storage system based on the environmental monitoring data, system monitoring data, and a pre-established component failure model; determining the failure rate of multiple subsystems corresponding to each energy storage submodule in the energy storage system based on the failure rates of the multiple components and a pre-established subsystem failure model; wherein the subsystem failure model includes the correlation relationships between multiple components; and determining the overall failure rate of the energy storage system based on the failure rates of the multiple subsystems corresponding to each energy storage submodule and a pre-established overall failure model; wherein the overall failure model includes the correlation relationships between multiple energy storage submodules.

[0007] In the technical solution of this application embodiment, the structure of the energy storage system is outlined, from components to subsystems of energy storage submodules, and then to the energy storage system, deriving the overall failure rate of the energy storage system step by step; furthermore, the component failure model used in the derivation process fully considers the influence of the operating environment, and the subsystem failure model and the overall failure model cover the correlation between components and subsystems, so that this application embodiment fully considers various factors in the process of determining the failure rate, thereby greatly improving the accuracy of the overall failure rate of the energy storage system.

[0008] In some embodiments, the failure rate of multiple components in the energy storage system is determined based on environmental monitoring data, system monitoring data, and a pre-established component failure model. This includes: obtaining the basic failure rate for each component; determining multiple correction coefficients based on environmental monitoring data and system monitoring data; and calculating the failure rate of the component based on the basic failure rate, the multiple correction coefficients, and the component failure model corresponding to the component. The multiple correction coefficients include at least two of the following: altitude correction coefficient, temperature correction coefficient, humidity correction coefficient, load rate correction coefficient, stress correction coefficient, cumulative operating time correction coefficient, cumulative cycle count correction coefficient, vibration and impact intensity correction coefficient, dirt level correction coefficient, and insect count correction coefficient. In the technical solutions of this application embodiment, considering the impact of environmental factors on the failure rate of the energy storage system is crucial because environmental conditions such as temperature, humidity, vibration, and insect infestation can significantly accelerate material aging, wear, and failure processes. Ignoring these factors may lead to premature component failure during actual use, increasing maintenance costs and safety risks. Furthermore, considering the wide range of applications for energy storage systems, especially in special geographical and climatic environments such as deserts, Gobi, and arid lands, high requirements are placed on the high-temperature resistance, low-temperature resistance, dust resistance, and vibration resistance of these systems. Therefore, to accurately and comprehensively describe the working profile of energy storage systems, various correction coefficients are provided to correct the basic failure rates of components, thereby improving the accuracy of component failure rates and ultimately enhancing the overall accuracy of the energy storage system's failure rate.

[0009] In some embodiments, the multiple subsystems of the energy storage submodule include a power module, a combiner cabinet, and an electrical cabinet, with the combiner cabinet connected to both the power module and the electrical cabinet. The failure rate of the multiple subsystems corresponding to each energy storage submodule in the energy storage system is determined based on the failure rates of multiple components and a pre-established subsystem failure model. This includes: determining the failure rate of the power module based on the failure rates of multiple components, the components in the power module, and the subsystem failure model corresponding to the power module; determining the failure rate of the combiner cabinet based on the failure rates of multiple components, the components in the combiner cabinet, and the subsystem failure model corresponding to the combiner cabinet; and determining the failure rate of the electrical cabinet based on the failure rates of multiple components, the components in the electrical cabinet, and the subsystem failure model corresponding to the electrical cabinet. In the technical solution of this application embodiment, the subsystem failure model corresponding to the power module fully considers the correlation between the components in the power module, the subsystem failure model corresponding to the combiner cabinet fully considers the correlation between the components in the combiner cabinet, and the subsystem failure model corresponding to the electrical cabinet fully considers the correlation between the components in the electrical cabinet. In this way, the structure of each subsystem in the energy storage submodule is sorted out, and the influence of structure on failure rate is fully considered, making it more accurate to deduce the failure rate of the subsystem from the failure rate of the components, thereby improving the accuracy of the overall failure rate of the energy storage system.

[0010] In some embodiments, determining the failure rate of a power module based on the failure rates of multiple components, the components in the power module, and the failure model of the subsystem corresponding to the power module includes: determining the failure rate of each component in the power module based on the failure rates of multiple components; wherein, the components in the power module include multiple types of power devices, power supplies, water circuits, stacks, connecting blocks, power driving devices, bypass driving devices, submodule control boards, support capacitors, and bypass switches; and determining the failure rate of the power module based on the failure rates of each component in the power module and the failure model of the subsystem corresponding to the power module. In the technical solution of this application embodiment, the subsystem failure model corresponding to the power module fully considers the correlation between power devices, power supplies, water circuits, stacks, connecting blocks, power driving devices, bypass driving devices, submodule control boards, support capacitors, and bypass switches, and derives the failure rate of the power module from the failure rates of the aforementioned components, which can improve the accuracy of the failure rate of the power module, thereby improving the accuracy of the overall failure rate of the energy storage system.

[0011] In some embodiments, the power supply includes a main power supply and a redundant power supply belonging to the power module; determining the failure rate of each component in the power module based on the failure rates of multiple components includes: determining the failure rate of the power supply in the power module based on the failure rate of the main power supply belonging to the power module and the failure rate of the redundant power supply. The technical solution of this application embodiment takes into account the redundancy relationship between power supplies, which can improve the accuracy of the failure rate of the power supply, thereby improving the accuracy of the failure rate of the power module subsystem in the energy storage submodule, and further improving the accuracy of the overall failure rate of the energy storage system.

[0012] In some embodiments, determining the failure rate of the combiner cabinet based on the failure rates of multiple components, the components in the combiner cabinet, and the failure model of the subsystem corresponding to the combiner cabinet includes: determining the failure rate of each component in the combiner cabinet based on the failure rates of multiple components; wherein, the components in the combiner cabinet include multiple components such as structural components, disconnecting switches, insulation detection modules, clamping circuits, battery management controllers, switch driver boards, relays, and combiner cabinet power supplies; and determining the failure rate of the combiner cabinet based on the failure rates of each component in the combiner cabinet and the failure model of the subsystem corresponding to the combiner cabinet. In the technical solution of this application embodiment, the failure model of the subsystem corresponding to the combiner cabinet fully considers the correlation between structural components, disconnecting switches, insulation detection modules, clamping circuits, battery management controllers, switch driver boards, relays, and combiner cabinet power supplies, and derives the failure rate of the combiner cabinet from the failure rates of the aforementioned components, which can improve the accuracy of the combiner cabinet's failure rate, thereby improving the accuracy of the overall failure rate of the energy storage system.

[0013] In some embodiments, the combiner cabinet power supply includes a main power supply, redundant power supplies, and redundant modules belonging to the combiner cabinet. Determining the failure rate of each component in the combiner cabinet based on the failure rates of multiple components includes: determining the failure rate of the combiner cabinet power supply in the combiner cabinet based on the failure rate of the main power supply, the failure rate of the redundant power supply, and the failure rate of the redundant modules. The technical solution of this application embodiment considers the redundancy relationship between power supplies, which can improve the accuracy of the combiner cabinet power supply failure rate, thereby improving the accuracy of the failure rate of the combiner cabinet subsystem in the energy storage submodule, and further improving the accuracy of the overall failure rate of the energy storage system.

[0014] In some embodiments, determining the failure rate of the power cabinet based on the failure rates of multiple components, the components in the power cabinet, and the failure model of the subsystem corresponding to the power cabinet includes: determining the failure rate of each component in the power cabinet based on the failure rates of multiple components; wherein, the components in the power cabinet include multiple components such as the power box, main control box, thermal management bend, and cabinet body; the power box includes multiple components such as battery cells, lower enclosure, converter sampling assembly, and fuses; the main control box includes multiple components such as power cabinet power supply, battery slave management unit, relay, and current sensor; and determining the failure rate of the power cabinet based on the failure rates of each component in the power cabinet and the failure model of the subsystem corresponding to the power cabinet. In the technical solution of this application embodiment, the subsystem failure model corresponding to the power cabinet fully considers the relationship between the power box, main control box, thermal management bend, and cabinet body, as well as the relationships between the components in the power box and main control box, and derives the failure rate of the power cabinet from the failure rates of the aforementioned components, which can improve the accuracy of the power cabinet failure rate, thereby improving the accuracy of the overall failure rate of the energy storage system.

[0015] In some embodiments, the power supply of the electrical cabinet includes a main power supply and a redundant power supply belonging to the electrical cabinet; determining the failure rate of each component in the electrical cabinet based on the failure rate of multiple components includes: determining the failure rate of the electrical cabinet power supply in the electrical cabinet based on the failure rate of the main power supply belonging to the electrical cabinet and the failure rate of the redundant power supply. The technical solution of this application embodiment takes into account the redundancy relationship between power supplies, which can improve the accuracy of the failure rate of the electrical cabinet power supply, thereby improving the accuracy of the failure rate of the electrical cabinet subsystem in the energy storage submodule, and further improving the accuracy of the overall failure rate of the energy storage system.

[0016] In some embodiments, the overall failure rate of the energy storage system is determined based on the failure rates of multiple subsystems corresponding to each energy storage submodule and a pre-established overall failure model. This includes: determining the failure rate of the power supply system of the energy storage submodule; wherein the power supply system includes a power supply, a combiner cabinet power supply, and an electrical cabinet power supply; determining the failure rate of the energy storage submodule based on the failure rates of its power supply system, power module, combiner cabinet, and electrical cabinet; and determining the overall failure rate of the energy storage system based on the failure rates of the energy storage submodule and the overall failure model. In the technical solution of this application embodiment, the cross-redundant power supply system is analyzed separately, and the failure rate of the power supply system including the main power supply path and the backup power supply path is studied to ensure that the quantitative results of the failure rate are not overly conservative and to maximize the utilization of the energy storage system's working capacity. Furthermore, the overall failure rate of the energy storage system is derived based on the failure rates of the energy storage submodules, fully considering the impact of environmental and structural factors on the failure rate, thus improving the accuracy of the overall failure rate of the energy storage system.

[0017] In some embodiments, the method further includes: outputting an alarm signal when the overall failure rate of the energy storage system is detected to be inconsistent with preset performance requirements. The technical solution of this application embodiment can detect situations where the failure rate of the energy storage system does not meet operational requirements, and promptly issue an alarm, thereby ensuring the safe operation of the energy storage system and improving its safety and reliability.

[0018] Secondly, this application also provides a failure rate determination device for an energy storage system, the device comprising:

[0019] The data acquisition module is used to acquire environmental monitoring data and system monitoring data of the energy storage system;

[0020] The component failure rate determination module is used to determine the failure rate of multiple components in the energy storage system based on environmental monitoring data, system monitoring data, and pre-established component failure models.

[0021] The subsystem failure rate determination module is used to determine the failure rate of multiple subsystems corresponding to each energy storage submodule in the energy storage system based on the failure rates of multiple components and the pre-established subsystem failure model; wherein, the subsystem failure model includes the correlation between multiple components;

[0022] The overall failure rate determination module is used to determine the overall failure rate of the energy storage system based on the failure rates of multiple subsystems corresponding to each energy storage submodule and the pre-established overall failure model; wherein, the overall failure model includes the correlation between multiple energy storage submodules.

[0023] Thirdly, this application also provides a failure monitoring system, which includes multiple data acquisition devices and a computer device;

[0024] Data acquisition devices are used to collect environmental monitoring data or system monitoring data.

[0025] Computer equipment for performing methods as described in any of the first aspects.

[0026] Fourthly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method of any one of the first aspects.

[0027] Fifthly, this application also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method of any one of the first aspects.

[0028] Sixthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the method of any one of the first aspects. Attached Figure Description

[0029] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the alternative embodiments below. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0030] Figure 1 This is a schematic diagram of the structure of an energy storage system according to an embodiment of this application;

[0031] Figure 2 This is a flowchart illustrating a method for determining the failure rate of an energy storage system according to an embodiment of this application.

[0032] Figure 3 This is a flowchart illustrating the steps for determining the failure rate of multiple components according to an embodiment of this application;

[0033] Figure 4 This is a flowchart illustrating the steps for determining the failure rate of multiple subsystems according to an embodiment of this application;

[0034] Figure 5 This is a flowchart illustrating the steps for determining the failure rate of a power module according to an embodiment of this application.

[0035] Figure 6 This is a flowchart illustrating the steps for determining the failure rate of a combiner cabinet according to an embodiment of this application.

[0036] Figure 7 This is a flowchart illustrating the steps for determining the failure rate of an electrical cabinet according to an embodiment of this application.

[0037] Figure 8This is a flowchart illustrating the steps for determining the overall failure rate of an energy storage system according to an embodiment of this application;

[0038] Figure 9 This is a schematic diagram of the coupling relationship of the power supply section in an energy storage submodule according to an embodiment of this application;

[0039] Figure 10 This is a structural block diagram of a failure rate determination device for an energy storage system according to an embodiment of this application;

[0040] Figure 11 This is a structural block diagram of a failure rate determination device for an energy storage system according to another embodiment of this application;

[0041] Figure 12 This is an internal structural diagram of a computer device according to an embodiment of this application. Detailed Implementation

[0042] The embodiments of the technical solution of this application will now be described in detail with reference to the accompanying drawings. These embodiments are only used to more clearly illustrate the technical solution of this application and are therefore merely examples, and should not be used to limit the scope of protection of this application.

[0043] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0044] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0045] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0046] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0047] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).

[0048] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0049] With the development of power electronic devices, battery energy storage technology, and control technology, the voltage and capacity levels of energy storage systems in power systems are constantly being improved. Direct-connected energy storage system technology draws on traditional flexible DC systems, enabling large-capacity single-unit designs; however, the performance and reliability of the power grid also place higher demands on the failure rate of direct-connected energy storage systems.

[0050] Currently, there are various methods to determine the failure rate of energy storage systems. For example, the failure rate can be calculated based on the scores of multiple evaluation indicators; or, a deep learning model can be used to determine the failure rate. However, the evaluation indicator method does not consider the coupling relationship between components, and the deep learning model method struggles to reveal the mechanism of the failure chain in the energy storage system, nor does it consider the impact of the operating environment. Therefore, the above methods are not comprehensive enough in their analysis of the failure rate of energy storage systems, resulting in inaccurate failure rate figures.

[0051] To address the aforementioned problems, this application provides a method for determining the failure rate of an energy storage system. The method involves acquiring environmental monitoring data and system monitoring data of the energy storage system; determining the failure rates of multiple components in the energy storage system based on the environmental monitoring data, system monitoring data, and pre-established component failure models; determining the failure rates of multiple subsystems corresponding to each energy storage submodule based on the failure rates of multiple components and pre-established subsystem failure models; and determining the overall failure rate of the energy storage system based on the failure rates of multiple subsystems corresponding to each energy storage submodule and a pre-established overall failure model. The technical solution of this application clarifies the structure of the energy storage system, deriving the overall failure rate of the energy storage system step-by-step from components to subsystems of energy storage submodules, and then to the energy storage system itself. Furthermore, the component failure models used in the derivation process fully consider the influence of the operating environment, and the subsystem failure models and overall failure models encompass the relationships between components and subsystems. This ensures that the failure rate determination process fully considers various factors, thereby significantly improving the accuracy of the overall failure rate of the energy storage system.

[0052] The failure rate determination method for energy storage systems provided in this application embodiment can be applied to, for example... Figure 1 The application environment shown includes an energy storage system 10, which comprises multiple energy storage sub-modules (SMs) connected in series. Each energy storage sub-module SM includes multiple subsystems such as a power module 101, a combiner cabinet 102, and a power cabinet 103. The combiner cabinet 102 is connected to both the power module 101 and the power cabinet 103. The power module 101 includes, but is not limited to, power devices (such as IGBTs), supporting capacitors, a sub-module control board (SMC), and a power supply. The combiner cabinet 102 includes, but is not limited to, a battery management controller (BMC), a switch driver board, and a combiner cabinet power supply. The power cabinet 103 includes, but is not limited to, battery cells, a power supply, and a slave battery management unit (SBMU).

[0053] The energy storage system 10 also includes a failure monitoring system, which comprises multiple data acquisition devices 104 and a computer device 105. The computer device 105 is connected to each data acquisition device 104. The data acquisition devices 104 include, but are not limited to, humidity sensors, temperature sensors, altitude sensors, stress sensors, dirt sensors, insect counters, vibration and shock intensity sensors, cumulative operating time timers, cumulative cycle count counters, and power sensors. The data acquisition devices 104 can be respectively installed in the valve hall, power module 101, combiner cabinet 102, and electrical cabinet 103 of the energy storage system 10, thereby collecting data on the overall operating environment and status of the energy storage system 10, the power module 101, the combiner cabinet 102, and the electrical cabinet 103. The computer device can obtain the current environmental monitoring data and system monitoring data from the data acquisition devices, and then, based on the current environmental monitoring data and system monitoring data, determine the overall failure rate of the energy storage system step by step, from components to subsystems of energy storage submodules, and then to the energy storage system itself.

[0054] It should be noted that the data acquisition devices are not limited to the examples above. In practical applications, the data acquisition devices can be adapted to different application scenarios of the energy storage system to obtain different environmental monitoring data and system monitoring data.

[0055] According to some embodiments of this application, refer to Figure 2 This paper provides a method for determining the failure rate of an energy storage system. Taking the application of this method to a computer device in a failure monitoring system as an example, the method may include the following steps:

[0056] Step 201: Obtain environmental monitoring data and system monitoring data of the energy storage system.

[0057] Environmental monitoring data may include, but is not limited to, altitude data, temperature data, humidity data, dirt level, number of flying insects, vibration and impact intensity data, etc.; system monitoring data may include, but is not limited to, load rate data, stress data, cumulative working time and cumulative cycle count, etc.

[0058] The categories that need to be monitored are determined based on the application scenarios of the energy storage system, and a monitoring category library is generated. The monitoring categories in the monitoring category library include, but are not limited to, altitude, temperature, humidity, load rate, stress, cumulative working time, cumulative cycle count, vibration and shock intensity, dirtiness, and number of flying insects.

[0059] The computer equipment can acquire environmental and system monitoring data of the energy storage system in real time based on a monitoring category library. In some embodiments, the computer equipment can also determine whether the current time is within a preset monitoring period. If the current time is not within the preset monitoring period, no data is acquired; if the current time is within the preset monitoring period, the computer equipment acquires humidity, temperature, altitude, vibration and shock intensity, dirtiness, and insect count data of the valve hall from the acquisition devices installed in the valve hall of the energy storage system, based on the monitoring category library. It can also receive monitoring data uploaded from individual power modules, combiner cabinets, and electrical cabinets, including but not limited to temperature, humidity, load rate, stress, cumulative operating time, vibration and shock intensity, and dirtiness. The sources of the above data include, but are not limited to, submodule control boards (SMC), battery management controllers (BMC) located in combiner cabinets, battery slave management units (SBMU) located in electrical cabinets, and insulation detection modules.

[0060] Step 202: Based on environmental monitoring data, system monitoring data, and pre-established component failure models, determine the failure rate of multiple components in the energy storage system.

[0061] Failure models for each component in the energy storage system are established in advance, and a component failure model library is obtained by aggregating multiple component failure models. For example, failure models are established for power devices, supporting capacitors, and submodule control boards in the power module; failure models are established for battery management controllers and switch driver boards in the combiner cabinet; and failure models are established for battery cells, main control box, and battery slave management units in the power cabinet.

[0062] After acquiring environmental and system monitoring data, these data are substituted into the component failure models for each part to calculate the failure rate. The monitoring data includes environmental and system monitoring data for the valve chamber, power module, combiner cabinet, and electrical cabinet. When calculating the component failure rate, the corresponding environmental and system monitoring data are determined based on the component's location, and then the failure rate is calculated based on this location-specific data.

[0063] For example, if the component is a power device in a power module, then the environmental monitoring data and system monitoring data in the power module are retrieved, and the failure rate of the power device is calculated based on the environmental monitoring data and system monitoring data in the power module.

[0064] Traditional technologies often employ a limited number of sensors for environmental monitoring. Therefore, even when environmental influences are considered in failure rate calculations, the monitored data is not particularly relevant to each component. For example, using only a single temperature sensor in the valve chamber to collect ambient temperature data, and then applying the same ambient temperature to calculate the failure rates of components in the power module, combiner cabinet, and electrical cabinet, can easily lead to inaccurate failure rate calculations. This application, however, places sensors not only in the valve chamber but also in the power module, combiner cabinet, and electrical cabinet. This allows for the acquisition of monitoring data that more closely reflects the environmental conditions of each component when calculating failure rates, resulting in more accurate failure rate calculations.

[0065] Step 203: Based on the failure rates of multiple components and the pre-established subsystem failure model, determine the failure rates of multiple subsystems corresponding to each energy storage submodule in the energy storage system.

[0066] The subsystem failure model includes the relationships between multiple components. These relationships include at least one of coupling and redundancy. For example, the power module of an energy storage submodule includes power devices, supporting capacitors, bypass switches, and power supplies. The subsystem failure model covers the coupling relationships between power devices and supporting capacitors and bypass switches, as well as the redundancy relationships between the main power supply and redundant power supplies in the power supply.

[0067] For each subsystem of the energy storage submodule, the failure rate of each component in the subsystem is selected from the failure rates of multiple components, or the failure rate of each component in the subsystem is calculated based on the failure rates of multiple components; then, the failure rate of each component is substituted into the failure model of the subsystem to calculate the failure rate of the subsystem.

[0068] Step 204: Determine the overall failure rate of the energy storage system based on the failure rates of multiple subsystems corresponding to each energy storage submodule and the pre-established overall failure model.

[0069] The overall failure model includes the relationships between multiple energy storage sub-modules. These relationships include at least one of coupling and redundancy. For example, in an energy storage system, multiple energy storage sub-modules are connected in series, with some sub-modules serving as redundant modules. The overall failure model covers the connection relationships and redundancy settings of these energy storage sub-modules.

[0070] The failure rate of the energy storage sub-module can be calculated based on the failure rates of multiple subsystems; then, by substituting the failure rates of each energy storage sub-module into the overall failure model, the overall failure model of the energy storage system can be calculated.

[0071] In the above embodiments, environmental monitoring data and system monitoring data of the energy storage system are acquired; based on the environmental monitoring data, system monitoring data, and pre-established component failure models, the failure rates of multiple components in the energy storage system are determined; based on the failure rates of multiple components and pre-established subsystem failure models, the failure rates of multiple subsystems corresponding to each energy storage submodule in the energy storage system are determined; based on the failure rates of multiple subsystems corresponding to each energy storage submodule and pre-established overall failure models, the overall failure rate of the energy storage system is determined. In the technical solution of this application embodiment, the structure of the energy storage system is outlined, deriving the overall failure rate of the energy storage system step by step from components to subsystems of energy storage submodules, and then to the energy storage system itself. Furthermore, the component failure models used in the derivation process fully consider the influence of the operating environment, and the subsystem failure models and overall failure models cover the relationships between components and subsystems. This allows the embodiments of this application to fully consider various factors in determining the failure rate, thereby greatly improving the accuracy of the overall failure rate of the energy storage system.

[0072] According to some embodiments of this application, refer to Figure 3 In the above embodiments, "determining the failure rate of multiple components in the energy storage system based on environmental monitoring data, system monitoring data, and pre-established component failure models" may include the following steps:

[0073] Step 301: For each component, obtain the basic failure rate corresponding to the component.

[0074] The basic failure rate refers to the probability that a component will fail within a specified time under specific standard conditions.

[0075] Each component, due to factors such as its design, manufacturing process, and material properties, has a relatively stable basic failure rate. Therefore, reliability testing can be conducted in advance, or the basic failure rate can be obtained by statistical analysis based on historical data and stored in a database or cloud server.

[0076] When determining the overall failure rate of an energy storage system, the basic failure rates of individual components can be obtained from a database or cloud server. For example, the basic failure rates of components such as power devices, supporting capacitors, bypass switches, submodule control boards, battery management controllers, and battery slave management units can be obtained from the database.

[0077] Step 302: Determine multiple correction coefficients based on environmental monitoring data and system monitoring data.

[0078] The correction factor is used to correct for the base failure rate. In some embodiments, the plurality of correction factors includes at least two of the following: altitude correction factor, temperature correction factor, humidity correction factor, load rate correction factor, stress correction factor, cumulative working time correction factor, cumulative cycle count correction factor, vibration and shock intensity correction factor, dirtiness correction factor, and flying insect count correction factor.

[0079] The computer equipment can initialize each correction coefficient, that is, determine the initial value of the correction coefficient. Then, based on environmental monitoring data and system monitoring data, the correction coefficients are adjusted to obtain the adjusted correction coefficients, that is, the target values ​​of the correction coefficients. In some embodiments, the initial value of the correction coefficient can be set to 1, the sampling step size can be set to T, and the numerical range of each monitoring category can be set. Then, each acquisition device starts sampling to obtain the real-time values ​​of environmental monitoring data and system monitoring data, and the correction coefficients are adjusted based on the real-time values.

[0080] Taking the temperature correction coefficient as an example, the Arrhenius model can be used, as shown in formula (1):

[0081] ------------------(1)

[0082] Where Ea is the activation energy of the material corresponding to the component, k is the Boltzmann constant, and T and T0 are the absolute temperatures in Kelvin. T0 is the absolute temperature corresponding to the initial value of the correction coefficient, and T is the absolute temperature at the current time in the environmental monitoring data.

[0083] Based on the above formula, the temperature correction factor corresponding to the current time can be calculated.

[0084] Step 303: Calculate the failure rate of the component based on the basic failure rate, multiple correction coefficients, and the component failure model corresponding to the component.

[0085] Among them, the component failure model includes the correspondence between the component failure rate, the basic failure rate, and multiple correction coefficients, that is, the component failure rate is the product of the basic failure rate and multiple correction coefficients, as shown in formula (2):

[0086] ---------------(2)

[0087] Where λ is the failure rate of the component, λ0 is the basic failure rate, φ is the altitude correction factor, α is the temperature correction factor, β is the humidity correction factor, γ is the load rate correction factor, δ is the stress correction factor, ε is the cumulative working time correction factor, ϵ is the cumulative cycle number correction factor, θ is the vibration and impact intensity correction factor, μ is the dirtiness correction factor, and σ is the flying insect number correction factor.

[0088] After obtaining the base failure rate and multiple correction coefficients, substituting these values ​​into the above formula allows for the calculation of the component failure rate. For example, the failure rate of a power device can be calculated based on its base failure rate and the aforementioned correction coefficients; similarly, the failure rate of a submodule control board can be calculated based on its base failure rate and the aforementioned correction coefficients.

[0089] In the above embodiments, for each component, the basic failure rate corresponding to the component is obtained; multiple correction coefficients are determined based on environmental monitoring data and system monitoring data; and the failure rate of the component is calculated based on the basic failure rate, multiple correction coefficients, and the component failure model corresponding to the component. In the technical solution of this application embodiment, considering the impact of environmental factors on the failure rate of the energy storage system is crucial, because environmental conditions such as temperature, humidity, vibration, and insect infestation can significantly accelerate material aging, wear, and failure processes. Ignoring these factors may lead to premature failure of components in actual use, increasing maintenance costs and safety risks. Furthermore, considering the wide range of application scenarios for energy storage systems, especially in special geographical and climatic environments such as deserts, Gobi, and wastelands, high requirements are placed on the high temperature resistance, low temperature resistance, sand and dust resistance, and vibration resistance characteristics of energy storage systems. Therefore, in order to accurately and comprehensively describe the working profile of the energy storage system, multiple correction coefficients are provided to correct the basic failure rate of the components, which can improve the accuracy of the component failure rate and thus improve the accuracy of the overall failure rate of the energy storage system.

[0090] According to some embodiments of this application, the energy storage submodule includes multiple subsystems such as a power module, a combiner cabinet, and a power supply cabinet, with the combiner cabinet connected to both the power module and the power supply cabinet. Considering that the power module, combiner cabinet, and power supply cabinet are parallel subsystems within the energy storage submodule, the failure rate is calculated for each subsystem separately. (Refer to...) Figure 4 In the above embodiments, "determining the failure rate of multiple subsystems corresponding to each energy storage submodule in the energy storage system based on the failure rate of multiple components and the pre-established subsystem failure model" may include the following steps:

[0091] Step 401: Determine the failure rate of the power module based on the failure rates of multiple components, the failure models of the components in the power module, and the subsystems corresponding to the power module.

[0092] The electrical topology, coupling relationships, and backup, redundancy, and switching strategies among the components in the power module are analyzed in advance, and a subsystem failure model corresponding to the power module is established. The subsystem failure model corresponding to the power module includes the following: the failure rate of the power module is the sum of the failure rates of multiple components within the power module.

[0093] After determining the failure rates of multiple components, the failure rate of each component in the power module can be selected from these failure rates, or the failure rate of the components in the power module can be calculated based on the known failure rates of the other components. Then, by substituting the failure rates of each component in the power module into the failure model of the corresponding subsystem of the power module, the failure rate of the power module can be determined.

[0094] Step 402: Determine the failure rate of the combiner cabinet based on the failure rates of multiple components, the failure models of the components in the combiner cabinet and the subsystem corresponding to the combiner cabinet.

[0095] The electrical topology, coupling relationships, and backup, redundancy, and switching strategies among the components in the combiner cabinet are analyzed in advance, and a subsystem failure model corresponding to the combiner cabinet is established. The subsystem failure model corresponding to the combiner cabinet includes the following: the failure rate of the combiner cabinet is the sum of the failure rates of multiple components within the combiner cabinet.

[0096] After determining the failure rates of multiple components, the failure rate of each component in the combiner cabinet can be selected from these failure rates, or the failure rate of the components in the combiner cabinet can be calculated based on the known failure rates of the other components. Then, by substituting the failure rates of each component in the combiner cabinet into the failure model of the corresponding subsystem, the failure rate of the combiner cabinet can be determined.

[0097] Step 403: Determine the failure rate of the electrical cabinet based on the failure rates of multiple components, the failure models of the components in the electrical cabinet, and the subsystems corresponding to the electrical cabinet.

[0098] The electrical topology, coupling relationships, and backup, redundancy, and switching strategies among the components in the electrical cabinet are analyzed in advance, and a subsystem failure model corresponding to the electrical cabinet is established. The subsystem failure model for the electrical cabinet includes the following: the failure rate of the electrical cabinet is the sum of the failure rates of multiple components within the cabinet.

[0099] After determining the failure rates of multiple components, the failure rate of each component in the electrical cabinet can be selected from these failure rates, or the failure rate of the components in the electrical cabinet can be calculated based on the known failure rates of the components. Then, by substituting the failure rates of each component in the electrical cabinet into the failure model of the corresponding subsystem, the failure rate of the electrical cabinet can be determined.

[0100] It should be noted that steps 401-403 above can also be performed in parallel, and the execution order is not limited in this embodiment.

[0101] In the above embodiments, the failure rate of the power module is determined based on the failure rates of multiple components, the components in the power module, and the failure model of the subsystem corresponding to the power module; the failure rate of the combiner cabinet is determined based on the failure rates of multiple components, the components in the combiner cabinet, and the failure model of the subsystem corresponding to the combiner cabinet; and the failure rate of the electrical cabinet is determined based on the failure rates of multiple components, the components in the electrical cabinet, and the failure model of the subsystem corresponding to the electrical cabinet. In the technical solution of this application embodiment, the subsystem failure model corresponding to the power module fully considers the interrelationships between the components in the power module, the subsystem failure model corresponding to the combiner cabinet fully considers the interrelationships between the components in the combiner cabinet, and the subsystem failure model corresponding to the electrical cabinet fully considers the interrelationships between the components in the electrical cabinet. This clarifies the structure of each subsystem in the energy storage submodule, fully considers the impact of structure on the failure rate, and makes the derivation of the subsystem failure rate from the component failure rate more accurate, thereby improving the accuracy of the overall failure rate of the energy storage system.

[0102] According to some embodiments of this application, refer to Figure 5 In the above embodiments, "determining the failure rate of the power module based on the failure rates of multiple components, the failure models of the components in the power module, and the subsystem corresponding to the power module" may include the following steps:

[0103] Step 4011: Determine the failure rate of each component in the power module based on the failure rates of multiple components.

[0104] The components in the power module include various power devices, power supplies, water circuits, stacks, connecting bars, power drive devices, bypass drive devices, submodule control boards, support capacitors, and bypass switches.

[0105] After determining the failure rates of multiple components, the failure rates of power devices, power supplies, water circuits, stacks, connecting blocks, power drive devices, bypass drive devices, submodule control boards, support capacitors, and bypass switches can be determined based on these failure rates.

[0106] It should be noted that the components in the power module are not limited to the examples above, and can be adjusted according to the actual situation, and the determined failure rate will also be adjusted accordingly.

[0107] Step 4012: Determine the failure rate of the power module based on the failure rates of each component in the power module and the failure model of the subsystem corresponding to the power module.

[0108] Among them, the subsystem failure rate model corresponding to the power module includes: the failure rate of the power module is the sum of the failure rate of the power device, the failure rate of the power supply, the failure rate of the water circuit, the failure rate of the stack, the failure rate of the connection bar, the failure rate of the power drive device, the λ failure rate of the bypass drive device, the failure rate of the submodule control board SMC, the failure rate of the support capacitor and the failure rate of the bypass switch, as shown in formula (3):

[0109] λ power module = 2 * λ IGBT + λ power supply + λ water circuit + λ stack + λ connection bus + λ power drive device + λ bypass drive device + λ SMC + λ support capacitor + λ bypass switch --------------- (3)

[0110] Where λ represents the failure rate and IGBT represents the power device. The above formula indicates that there are two power devices in the power module. It should be noted that the components in the power module are not limited to the example above and can be adjusted according to the actual situation. The failure model of the corresponding subsystem of the power module should also be adjusted accordingly. Furthermore, if the connection relationship and structure of the components in the power module are different from the example above, it will also affect the failure rate of the power module. Therefore, the failure model of the corresponding subsystem of the power module also needs to be adjusted accordingly.

[0111] After determining the failure rates of the aforementioned components, these failure rates are substituted into the above formula for calculation, and the failure rate of the power module can be obtained.

[0112] In the above embodiments, the failure rate of each component in the power module is determined based on the failure rates of multiple components; the failure rate of the power module is determined based on the failure rates of each component in the power module and the failure model of the subsystem corresponding to the power module. In the technical solution of this application embodiment, the failure model of the subsystem corresponding to the power module fully considers the correlation between power devices, power supplies, water circuits, stacks, connecting blocks, power driving devices, bypass driving devices, submodule control boards, supporting capacitors, and bypass switches, and derives the failure rate of the power module from the failure rates of the above components, which can improve the accuracy of the failure rate of the power module, thereby improving the accuracy of the overall failure rate of the energy storage system.

[0113] According to some embodiments of this application, the power supply includes a main power supply and a redundant power supply belonging to the power module; in the above embodiments, "determining the failure rate of each component in the power module based on the failure rate of multiple components" may include: determining the failure rate of the power supply in the power module based on the failure rate of the main power supply belonging to the power module and the failure rate of the redundant power supply.

[0114] For power supplies, the topological relationship and redundancy strategy between the main power supply and redundant power supplies are analyzed. Taking the parallel configuration of the main power supply and redundant power supply belonging to the power module as an example, the unreliability of the power supply can be determined as shown in formula (4):

[0115] ---(4)

[0116] in, The unreliability of power supplies. This refers to the unreliability of the main power supply belonging to the power module. This refers to the unreliability of redundant power supplies belonging to the power module. Unreliability is a concept corresponding to reliability, used to measure the probability that a product or system cannot perform its intended function under specified conditions and within a specified time.

[0117] By transforming the above formula, we obtain formula (5):

[0118] -(5)

[0119] After determining the failure rate of the main power supply and the failure rate of the redundant power supply belonging to the power module, the failure rate of the power supply can be calculated according to the above formula.

[0120] In the above embodiments, the failure rate of the power supply in the power module is determined based on the failure rate of the main power supply and the failure rate of the redundant power supply belonging to the power module. The technical solution of this application takes into account the redundancy relationship between power supplies, which can improve the accuracy of the failure rate of the power supply, thereby improving the accuracy of the failure rate of the power module subsystem within the energy storage submodule, and further improving the accuracy of the overall failure rate of the energy storage system.

[0121] According to some embodiments of this application, refer to Figure 6 In the above embodiments, "determining the failure rate of the combiner cabinet based on the failure rates of multiple components, the components in the combiner cabinet, and the failure model of the subsystem corresponding to the combiner cabinet" may include the following steps:

[0122] Step 4021: Determine the failure rate of each component in the combiner cabinet based on the failure rates of multiple components.

[0123] The components in the combiner cabinet include structural parts, disconnecting switches, insulation detection modules, clamping circuits, battery management controllers, switch driver boards, relays, and various power supplies for the combiner cabinet.

[0124] After determining the failure rates of multiple components, the failure rates of structural components, disconnect switches, insulation detection modules, clamping circuits, battery management controllers, switch driver boards, relays, and combiner cabinet power supplies can be determined based on these failure rates.

[0125] It should be noted that the components in the combiner cabinet are not limited to the examples above, and can be adjusted according to the actual situation, and the determined failure rate will also be adjusted accordingly.

[0126] Step 4022: Determine the failure rate of the combiner cabinet based on the failure rates of each component in the combiner cabinet and the failure model of the subsystem corresponding to the combiner cabinet.

[0127] Among them, the failure model of the subsystem corresponding to the combiner cabinet includes: the failure rate of the combiner cabinet is the sum of the failure rates of structural components, disconnect switches, insulation detection modules, clamping circuits, battery management controller (BMC), switch drive boards, relays, and combiner cabinet power supply, as shown in formula (6):

[0128] λ combiner cabinet = λ structural components + λ disconnecting switch + λ insulation detection module + λ clamping circuit + λ BMC + λ switch driver board + λ relay + λ combiner cabinet power supply -----------------------------(6)

[0129] Where λ is the failure rate.

[0130] After determining the failure rates of the aforementioned components, these failure rates are substituted into the above formula for calculation, and the failure rate of the combiner cabinet can be obtained.

[0131] It should be noted that the components in the combiner cabinet are not limited to the examples above and can be adjusted according to the actual situation. The failure model of the corresponding subsystem of the combiner cabinet will also be adjusted accordingly. Furthermore, if the connection relationships and structure of the components in the combiner cabinet are different from those in the examples above, it will also affect the failure rate of the combiner cabinet. Therefore, the failure model of the corresponding subsystem of the combiner cabinet also needs to be adjusted accordingly.

[0132] In the above embodiments, the failure rate of each component in the combiner cabinet is determined based on the failure rates of multiple components; the failure rate of the combiner cabinet is determined based on the failure rates of each component in the combiner cabinet and the failure model of the subsystem corresponding to the combiner cabinet. In the technical solution of this application embodiment, the failure model of the subsystem corresponding to the combiner cabinet fully considers the correlation between structural components, disconnecting switches, insulation detection modules, clamping circuits, battery management controllers, switch driver boards, relays, and the combiner cabinet power supply, and derives the failure rate of the combiner cabinet from the failure rates of the above components, which can improve the accuracy of the combiner cabinet's failure rate, thereby improving the accuracy of the overall failure rate of the energy storage system.

[0133] According to some embodiments of this application, the combiner cabinet power supply includes a main power supply, a redundant power supply, and a redundant module belonging to the combiner cabinet; in the above embodiments, "determining the failure rate of each component in the combiner cabinet based on the failure rate of multiple components" may include: determining the failure rate of the combiner cabinet power supply in the combiner cabinet based on the failure rate of the main power supply belonging to the combiner cabinet, the failure rate of the redundant power supply, and the failure rate of the redundant module.

[0134] For the combiner cabinet, the topological relationship and redundancy strategy among the main power supply, redundant power supply, and redundant module are analyzed. Taking the main power supply and redundant power supply belonging to the combiner cabinet as being connected in parallel first, and then connected in series with the redundant module, and the redundant module being able to control whether the main power supply or the redundant power supply is used, the unreliability of the combiner cabinet power supply can be determined as shown in formula (7):

[0135] -(7)

[0136] in, The unreliability of the combiner cabinet power supply. This is attributed to the unreliability of the main power supply in the combiner cabinet. The unreliability of redundant power supplies attributed to the combiner cabinet. This refers to the unreliability of redundant modules belonging to the combiner cabinet.

[0137] By transforming the above formula, we obtain formula (8):

[0138] ------(8)

[0139] After determining the failure rate of the main power supply, the failure rate of the redundant power supply, and the failure rate of the redundant modules belonging to the combiner cabinet, the failure rate of the combiner cabinet power supply can be calculated according to the above formula.

[0140] In the above embodiments, the failure rate of each component in the combiner cabinet is determined based on the failure rate of multiple components. The technical solution of this application embodiment considers the redundancy relationship between power supplies, which can improve the accuracy of the failure rate of the combiner cabinet power supply, thereby improving the accuracy of the failure rate of the combiner cabinet subsystem in the energy storage submodule, and further improving the accuracy of the overall failure rate of the energy storage system.

[0141] According to some embodiments of this application, refer to Figure 7 In the above embodiments, "determining the failure rate of the electrical cabinet based on the failure rates of multiple components, the failure models of the components in the electrical cabinet, and the subsystem corresponding to the electrical cabinet" may include the following steps:

[0142] Step 4031: Determine the failure rate of each component in the electrical cabinet based on the failure rates of multiple components.

[0143] The components in the electrical cabinet include various parts such as the electrical box, main control box, thermal management bend, and cabinet body; the electrical box includes various parts such as battery cells, lower enclosure, converter sampling assembly, and fuses; the main control box includes various parts such as the electrical cabinet power supply, battery management unit (SBMU), relays, and current sensors.

[0144] After determining the failure rates of multiple components, the failure rates of the battery cells, lower enclosure, converter sampling assembly, and fuses can be determined based on these component failure rates, and the overall failure rate of the electrical cabinet can be calculated. Similarly, the failure rates of the power supply, battery management unit (SBMU), relays, and current sensors can be determined based on these component failure rates, and the failure rate of the main control box can be calculated. Finally, the failure rates of the thermal management bend and the cabinet can be determined based on these component failure rates.

[0145] Step 4032: Determine the failure rate of the electrical cabinet based on the failure rates of each component in the cabinet and the failure model of the corresponding subsystem.

[0146] Among them, the failure models of the subsystems corresponding to the electrical cabinet include: the failure rate of the electrical cabinet is the sum of the failure rate of the electrical box, the failure rate of the main control box, the failure rate of the thermal management bend, and the failure rate of the cabinet, as shown in formula (9); the failure rate of the electrical box is the sum of the failure rate of the battery cell, the failure rate of the lower box, the failure rate of the converter sampling component, and the failure rate of the fuse, as shown in formula (10); the failure rate of the main control box is the sum of the failure rate of the electrical cabinet power supply, the failure rate of the battery slave management unit SBMU, the failure rate of the relay, and the failure rate of the current sensor, as shown in formula (11).

[0147] ---------(9)

[0148] --(10)

[0149] ---------(11)

[0150] Where λ is the failure rate, m1 is the number of electrical boxes in the electrical cabinet, and m2 is the number of battery cells in the electrical box.

[0151] After determining the failure rate of the aforementioned components, these failure rates are substituted into the above formula for calculation, and the failure rate of the electrical cabinet can be obtained.

[0152] It should be noted that the components in the electrical cabinet are not limited to the examples above and can be adjusted according to the actual situation. The failure model of the corresponding subsystem of the electrical cabinet will also be adjusted accordingly. Furthermore, if the connection relationships and structure of the components in the electrical cabinet are different from those in the examples above, it will also affect the failure rate of the electrical cabinet. Therefore, the failure model of the corresponding subsystem of the electrical cabinet also needs to be adjusted accordingly.

[0153] In the above embodiments, the failure rate of each component in the electrical cabinet is determined based on the failure rates of multiple components; the failure rate of the electrical cabinet is determined based on the failure rates of each component in the electrical cabinet and the failure model of the corresponding subsystem. In the technical solution of this application embodiment, the failure model of the subsystem corresponding to the electrical cabinet fully considers the electrical box, main control box, thermal management bend, and cabinet body, as well as the correlation between the components in the electrical box and main control box, and derives the failure rate of the electrical cabinet from the failure rates of the aforementioned components, which can improve the accuracy of the failure rate of the electrical cabinet, thereby improving the accuracy of the overall failure rate of the energy storage system.

[0154] According to some embodiments of this application, the power supply of the electrical cabinet includes a main power supply and a redundant power supply belonging to the electrical cabinet; in the above embodiments, "determining the failure rate of each component in the electrical cabinet based on the failure rate of multiple components" may include: determining the failure rate of the power supply in the electrical cabinet based on the failure rate of the main power supply belonging to the electrical cabinet and the failure rate of the redundant power supply.

[0155] For electrical cabinets, analyze the topological relationship and redundancy strategy between the main power supply and redundant power supply. Taking the parallel connection of the main power supply and redundant power supply belonging to the electrical cabinet as an example, the unreliability of the power supply of the electrical cabinet can be determined first, as shown in formula (12):

[0156] --(12)

[0157] in, The unreliability of the power supply to the electrical cabinet. This is attributed to the unreliability of the main power supply to the electrical cabinet. This refers to the unreliability of redundant power supplies belonging to the electrical cabinet.

[0158] By transforming the above formula, we obtain formula (13):

[0159] -(13)

[0160] Where λ is the failure rate.

[0161] After determining the failure rate of the main power supply and the failure rate of the redundant power supply belonging to the electrical cabinet, the failure rate of the electrical cabinet power supply can be calculated according to the above formula.

[0162] In the above embodiments, the failure rate of the power supply in the power cabinet is determined based on the failure rate of the main power supply and the failure rate of the redundant power supply belonging to the power cabinet. The technical solution of this application takes into account the redundancy relationship between power supplies, which can improve the accuracy of the failure rate of the power supply in the power cabinet, thereby improving the accuracy of the failure rate of the power cabinet subsystem in the energy storage submodule, and further improving the accuracy of the overall failure rate of the energy storage system.

[0163] According to some embodiments of this application, refer to Figure 8 In the above embodiments, "determining the overall failure rate of the energy storage system based on the failure rates of multiple subsystems corresponding to each energy storage submodule and the pre-established overall failure model" may include the following steps:

[0164] Step 501: Determine the failure rate of the power supply system for the energy storage submodule.

[0165] The power supply system includes power supplies, combiner cabinet power supplies, and electrical cabinet power supplies.

[0166] Considering the electrical topology and coupling relationships between multiple subsystems in the energy storage submodule, as well as the backup, redundancy, and switching strategies, the overall failure module of the energy storage system can be derived. Because the subsystems in the energy storage valve submodule are not completely connected in series and parallel, and there is a certain degree of cross-redundancy, the cross-redundant part (power supply system) is analyzed separately.

[0167] Because cross-redundant power supply systems essentially reduce the overall failure rate by introducing backup power paths, this ensures that if one component fails, other backup components can take over its function, thereby reducing the overall failure rate. The cross-redundancy of the power supply system reduces the failure rate of energy storage submodules, achieving fault isolation and fault tolerance, and extending the reliable operating time. Therefore, if this redundancy is not considered when assessing the overall failure rate, the obtained overall failure rate will be too conservative, and the formulated operation and maintenance strategies will not make reasonable use of the energy storage system's operational capacity. Separate analysis of the power supply system ensures the maximization of the operational capacity of the energy storage submodules, preventing the premature disconnection of energy storage submodules that are still operating safely and stably. (Refer to...) Figure 9The diagram illustrates the coupling relationships of the power supply components within the energy storage submodule. In the main power supply circuit, the high-voltage capacitor in the power module is connected to the main power supply belonging to the power module; the high-voltage main busbar of the combiner cabinet is connected to the main power supply belonging to the combiner cabinet, and the main power supply of the combiner cabinet is also connected to the redundant module and the 220V main busbar; the main circuit of the electrical cabinet is connected to the main power supply belonging to the electrical cabinet. In the redundant power supply circuit, the 220V main busbar of the combiner cabinet is connected to the redundant power supply belonging to the combiner cabinet, and the redundant power supply belonging to the combiner cabinet is also connected to the redundant module, the redundant power supply belonging to the power module, and the redundant power supply belonging to the electrical cabinet.

[0168] It should be noted that the main power supply and redundant power supply belonging to the power module are the power supplies for the sub-module control boards of the power module; the main power supply and redundant power supply belonging to the combiner cabinet are the power supplies for the battery management controller of the combiner cabinet; and the main power supply and redundant power supply belonging to the electrical cabinet are the power supplies for the batteries of the electrical cabinet from the management unit.

[0169] The calculation principle of unreliability includes: for each power source, the reliability is the difference between 1 and the unreliability of that power source; for at least two power sources connected in parallel, the unreliability of the parallel circuit is the difference between 1 and the product of the reliability of the at least two power sources; for at least two power sources connected in series, the unreliability of the series circuit is the product of the unreliability of the at least two power sources.

[0170] Based on the above coupling relationship and calculation principle, the unreliability of the power supply system can be determined, as shown in formula (14):

[0171] ----------(14)

[0172] in, The unreliability of power supplies. This refers to the unreliability of the main power supply belonging to the power module. The unreliability of redundant power supplies belonging to the power module. The unreliability of the combiner cabinet power supply. This is attributed to the unreliability of the main power supply in the combiner cabinet. The unreliability of redundant power supplies attributed to the combiner cabinet. The unreliability is attributed to redundant modules in the combiner cabinet. The unreliability of the power supply to the electrical cabinet. This is attributed to the unreliability of the main power supply to the electrical cabinet. This refers to the unreliability of redundant power supplies belonging to the electrical cabinet.

[0173] Step 502: Determine the failure rate of the energy storage submodule based on the failure rate of the power supply system of the energy storage submodule, the failure rate of the power module, the failure rate of the combiner cabinet, and the failure rate of the electrical cabinet.

[0174] The failure rate of the energy storage submodule is the sum of the failure rates of the power supply system, the power module, the combiner cabinet, and the electrical cabinet, minus the repeated calculations of the failure rates of the power supply, the combiner cabinet power supply, and the electrical cabinet power supply, as shown in formula (15).

[0175] λ Energy Storage Submodule = λ Power Module + λ Combiner Cabinet + λ Electrical Cabinet + λ Power Supply System - λ Power Supply - λ Combiner Power Supply - λ Electrical Cabinet Power Supply ------ (15)

[0176] Where λ is the failure rate.

[0177] It should be noted that the failure rate of the above power supply system takes into account the cross-redundancy relationship between the main power supply and the redundant power supply. However, when calculating the failure rate of the power module, the combiner cabinet, and the electrical cabinet, the failure rates of the power supply, the combiner cabinet power supply, and the electrical cabinet power supply are also calculated. Therefore, when calculating the failure rate of the energy storage submodule, the repeatedly calculated failure rates of the power supply, the combiner cabinet power supply, and the electrical cabinet power supply need to be removed in order to more accurately reflect the failure rate of the energy storage submodule.

[0178] Step 503: Determine the overall failure rate of the energy storage system based on the failure rate of the energy storage submodules and the overall failure model.

[0179] The overall failure model includes the relationship between the overall failure rate of the energy storage system and the failure rate of the energy storage sub-modules, the number of energy storage sub-modules, and the number of redundant energy storage sub-modules.

[0180] The unreliability of the energy storage system can be determined based on the failure rate of the energy storage submodules, the number of energy storage submodules, and the number of redundant energy storage submodules, as shown in formula (16):

[0181] ---(16)

[0182] Where N is the number of energy storage submodules in the energy storage system; n is the number of redundant energy storage submodules; and k is the number of remaining energy storage submodules after removing the redundant ones. Due to the unreliability of energy storage systems, Let be the reliability of k energy storage submodules.

[0183] By transforming the above formula, we obtain formula (17):

[0184] -(17)

[0185] Where λ is the failure rate, the above formula is the overall failure model.

[0186] After determining the failure rate of the energy storage submodule, the overall failure rate of the energy storage system can be determined by substituting the failure rate of the energy storage submodule into the above formula.

[0187] In the above embodiments, the failure rate of the power supply system for the energy storage submodule is determined; based on the failure rates of the power supply system, power module, combiner cabinet, and electrical cabinet, the failure rate of the energy storage submodule is determined; and based on the failure rate of the energy storage submodule and the overall failure model, the overall failure rate of the energy storage system is determined. In the technical solution of this application embodiment, the cross-redundant power supply system is analyzed separately, and the failure rate of the power supply system including the main power supply path and the backup power supply path is studied to ensure that the quantitative results of the failure rate are not overly conservative and to maximize the utilization of the energy storage system's working capacity. Furthermore, the overall failure rate of the energy storage system is derived based on the failure rate of the energy storage submodule, fully considering the impact of environmental and structural factors on the failure rate, thus improving the accuracy of the overall failure rate of the energy storage system.

[0188] According to some embodiments of this application, it may also include: outputting an alarm signal when the overall failure rate of the energy storage system does not meet the preset target requirements.

[0189] Among them, the preset indicators are required to characterize the minimum failure rate of the energy storage system during normal operation.

[0190] After calculating the overall failure rate of the energy storage system, the overall failure rate is compared with the preset target requirements. If the overall failure rate does not meet the preset target requirements, i.e., the overall failure rate is lower than the minimum failure rate, an alarm signal is output. If the overall failure rate meets the preset target requirements, i.e., the overall failure rate is not lower than the minimum failure rate, no alarm signal is output.

[0191] There are various ways to output alarm signals, such as displaying the overall failure rate on the screen, illuminating a failure indicator light, or broadcasting the overall failure rate via voice. It should be noted that the output methods for alarm signals are not limited to the examples above and can be configured according to the actual situation.

[0192] In the above embodiments, an alarm signal is output when the overall failure rate of the energy storage system is detected to be inconsistent with preset performance requirements. The technical solution of this application embodiment can detect situations where the failure rate of the energy storage system does not meet operational requirements, and promptly issue an alarm, thereby ensuring the safe operation of the energy storage system and improving its safety and reliability.

[0193] According to some embodiments of this application, a method for determining the failure rate of an energy storage system is provided. Taking the application of this method to a computer device in a failure monitoring system as an example, the method may include the following steps:

[0194] Step 1: Decompose the energy storage system step by step to obtain the organizational framework and components of the energy storage system, and establish component failure models to generate a set of component failure models for the energy storage system.

[0195] Step 2: Statistically analyze the environmental monitoring categories and system monitoring categories in the component failure model to generate a monitoring category library.

[0196] Step 3: If the current time is within the preset monitoring period, then obtain the environmental monitoring data and system monitoring data of the energy storage system based on the monitoring category library.

[0197] Step 4: For each component, obtain the basic failure rate corresponding to the component.

[0198] Step 5: Determine multiple correction coefficients based on environmental monitoring data and system monitoring data.

[0199] Among them, multiple correction factors include at least two of the following: altitude correction factor, temperature correction factor, humidity correction factor, load rate correction factor, stress correction factor, cumulative working time correction factor, cumulative cycle number correction factor, vibration and shock intensity correction factor, dirtiness correction factor, and flying insect number correction factor.

[0200] Step 6: Calculate the failure rate of the component based on the basic failure rate, multiple correction coefficients, and the component failure model corresponding to the component.

[0201] Step 7: Determine the failure rate of each component in the power module based on the failure rates of multiple components.

[0202] The components in the power module include various power devices, power supplies, water circuits, stacks, connecting bars, power drive devices, bypass drive devices, submodule control boards, support capacitors, and bypass switches.

[0203] Step 8: Determine the failure rate of the power module based on the failure rates of each component in the power module and the failure model of the subsystem corresponding to the power module.

[0204] Step 9: Determine the failure rate of each component in the combiner cabinet based on the failure rates of multiple components.

[0205] The components in the combiner cabinet include structural parts, disconnecting switches, insulation detection modules, clamping circuits, battery management controllers, switch driver boards, relays, and various power supplies for the combiner cabinet.

[0206] Step 10: Determine the failure rate of the combiner cabinet based on the failure rates of each component in the combiner cabinet and the failure model of the subsystem corresponding to the combiner cabinet.

[0207] Step 11: Determine the failure rate of each component in the electrical cabinet based on the failure rates of multiple components.

[0208] The components in the electrical cabinet include various parts such as the electrical box, main control box, thermal management bend, and cabinet body; the electrical box includes various parts such as battery cells, lower enclosure, converter sampling assembly, and fuses; the main control box includes various parts such as electrical cabinet power supply, battery management unit, relays, and current sensors.

[0209] Step 12: Determine the failure rate of the electrical cabinet based on the failure rates of each component in the cabinet and the failure model of the corresponding subsystem.

[0210] Step 13: Determine the failure rate of the power supply system for the energy storage submodule.

[0211] The power supply system includes power supplies, combiner cabinet power supplies, and electrical cabinet power supplies.

[0212] Step 14: Determine the failure rate of the energy storage submodule based on the failure rate of the power supply system, the failure rate of the power module, the failure rate of the combiner cabinet, and the failure rate of the electrical cabinet.

[0213] Step 15: Determine the overall failure rate of the energy storage system based on the failure rate of the energy storage submodules and the overall failure model.

[0214] Step 16: If the overall failure rate of the energy storage system does not meet the preset target requirements, an alarm signal is output.

[0215] The above embodiments outline the structure of the energy storage system, deriving the overall failure rate of the energy storage system step by step from components to subsystems of energy storage submodules, and then to the energy storage system itself. Furthermore, the component failure models used in the derivation process fully consider the influence of the operating environment, and the subsystem failure models and overall failure models cover the relationships between components and subsystems. This allows the embodiments of this application to fully consider various factors in determining the failure rate, thereby greatly improving the accuracy of the overall failure rate of the energy storage system.

[0216] It should be understood that although the steps in the flowchart above are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowchart above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps.

[0217] Based on the same inventive concept, this application also provides an energy storage system failure rate determination device for implementing the above-described energy storage system failure rate determination method. The solution provided by this device is similar to the solution described in the above-described method. Therefore, the specific limitations in one or more energy storage system failure rate determination device embodiments provided below can be found in the limitations of the energy storage system failure rate determination method described above, and will not be repeated here.

[0218] According to some embodiments of this application, refer to Figure 10 This application provides a failure rate determination device for an energy storage system, the device comprising:

[0219] Data acquisition module 601 is used to acquire environmental monitoring data and system monitoring data of the energy storage system;

[0220] The component failure rate determination module 602 is used to determine the failure rate of multiple components in the energy storage system based on the environmental monitoring data, the system monitoring data, and the pre-established component failure model.

[0221] The subsystem failure rate determination module 603 is used to determine the failure rate of multiple subsystems corresponding to each energy storage submodule in the energy storage system based on the failure rates of the multiple components and a pre-established subsystem failure model; wherein, the subsystem failure model includes the correlation relationships between the multiple components;

[0222] The overall failure rate determination module 604 is used to determine the overall failure rate of the energy storage system based on the failure rates of multiple subsystems corresponding to each energy storage submodule and a pre-established overall failure model; wherein, the overall failure model includes the correlation relationships between multiple energy storage submodules.

[0223] In some embodiments, the component failure rate determination module 602 is specifically used to obtain the basic failure rate corresponding to each component; determine multiple correction coefficients based on environmental monitoring data and system monitoring data; and calculate the failure rate of the component based on the basic failure rate, the multiple correction coefficients, and the component failure model corresponding to the component; wherein, the multiple correction coefficients include at least two of the following: altitude correction coefficient, temperature correction coefficient, humidity correction coefficient, load rate correction coefficient, stress correction coefficient, cumulative working time correction coefficient, cumulative cycle number correction coefficient, vibration and shock intensity correction coefficient, dirtiness correction coefficient, and flying insect number correction coefficient.

[0224] In some embodiments, the energy storage submodule includes multiple subsystems such as a power module, a combiner cabinet, and an electrical cabinet, with the combiner cabinet connected to both the power module and the electrical cabinet. The subsystem failure rate determination module 603 is specifically used to determine the failure rate of the power module based on the failure rates of multiple components, the components in the power module, and the subsystem failure model corresponding to the power module; to determine the failure rate of the combiner cabinet based on the failure rates of multiple components, the components in the combiner cabinet, and the subsystem failure model corresponding to the combiner cabinet; and to determine the failure rate of the electrical cabinet based on the failure rates of multiple components, the components in the electrical cabinet, and the subsystem failure model corresponding to the electrical cabinet.

[0225] In some embodiments, the subsystem failure rate determination module 603 is specifically used to determine the failure rate of each component in the power module based on the failure rates of multiple components; wherein, the components in the power module include various types such as power devices, power supplies, water circuits, stacks, connecting blocks, power driving devices, bypass driving devices, submodule control boards, support capacitors, and bypass switches; the failure rate of the power module is determined based on the failure rate of each component in the power module and the subsystem failure model corresponding to the power module.

[0226] In some embodiments, the power supply includes a main power supply and a redundant power supply belonging to the power module; the subsystem failure rate determination module 603 is specifically used to determine the failure rate of the power supply in the power module based on the failure rate of the main power supply belonging to the power module and the failure rate of the redundant power supply.

[0227] In some embodiments, the subsystem failure rate determination module 603 is specifically used to determine the failure rate of each component in the combiner cabinet based on the failure rates of multiple components; wherein, the components in the combiner cabinet include structural components, disconnect switches, insulation detection modules, clamping circuits, battery management controllers, switch driver boards, relays, and various types of combiner cabinet power supplies; the failure rate of the combiner cabinet is determined based on the failure rate of each component in the combiner cabinet and the subsystem failure model corresponding to the combiner cabinet.

[0228] In some embodiments, the combiner cabinet power supply includes a main power supply, a redundant power supply, and a redundant module belonging to the combiner cabinet; the subsystem failure rate determination module 603 is specifically used to determine the failure rate of the combiner cabinet power supply in the combiner cabinet based on the failure rate of the main power supply belonging to the combiner cabinet, the failure rate of the redundant power supply, and the failure rate of the redundant module.

[0229] In some embodiments, the subsystem failure rate determination module 603 is specifically used to determine the failure rate of each component in the electrical cabinet based on the failure rates of multiple components; wherein, the components in the electrical cabinet include various components such as the electrical box, main control box, thermal management bend, and cabinet body; the electrical box includes various components such as battery cells, lower enclosure, converter sampling assembly, and fuses; the main control box includes various components such as electrical cabinet power supply, battery slave management unit, relay, and current sensor; the failure rate of the electrical cabinet is determined based on the failure rate of each component in the electrical cabinet and the corresponding subsystem failure model of the electrical cabinet.

[0230] In some embodiments, the power supply of the electrical cabinet includes a main power supply and a redundant power supply belonging to the electrical cabinet; the subsystem failure rate determination module 603 is specifically used to determine the failure rate of the power supply in the electrical cabinet based on the failure rate of the main power supply belonging to the electrical cabinet and the failure rate of the redundant power supply.

[0231] In some embodiments, the overall failure rate determination module 604 is specifically used to determine the failure rate of the power supply system of the energy storage submodule; wherein, the power supply system includes a power supply, a combiner cabinet power supply, and an electrical cabinet power supply; the failure rate of the energy storage submodule is determined based on the failure rate of the power supply system of the energy storage submodule, the failure rate of the power module, the failure rate of the combiner cabinet, and the failure rate of the electrical cabinet; and the overall failure rate of the energy storage system is determined based on the failure rate of the energy storage submodule and the overall failure model.

[0232] In some embodiments, refer to Figure 11 The device also includes:

[0233] The alarm module 605 is used to output an alarm signal when the overall failure rate of the energy storage system does not meet the preset target requirements.

[0234] Each module in the failure rate determination device of the aforementioned energy storage system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of the electronic device in hardware form or independent of it, or stored in the memory of the electronic device in software form, so that the processor can call and execute the operations corresponding to each module.

[0235] According to some embodiments of this application, a failure monitoring system is provided, with reference to... Figure 1 The failure monitoring system includes multiple data acquisition devices and a computer device; the data acquisition devices are used to collect environmental monitoring data or system monitoring data; the computer device is used to implement the technical solutions of the above embodiments.

[0236] According to some embodiments of this application, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 12As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When executed by the processor, the computer program implements a method for determining the failure rate of an energy storage system. The display unit is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0237] Those skilled in the art will understand that Figure 12 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0238] According to some embodiments of this application, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory including instructions that can be executed by a processor of an electronic device to perform the above-described method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0239] According to some embodiments of this application, a computer program product is also provided, which, when executed by a processor, can implement the above-described methods. The computer program product includes one or more computer instructions. When these computer instructions are loaded and executed on a computer, some or all of the above-described methods can be implemented, wholly or partially, according to the processes or functions described in the embodiments of this application.

[0240] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application 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), magnetic 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. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0241] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0242] The embodiments described above merely illustrate several implementation methods of this application to facilitate a detailed understanding of the technical solutions of this application, but should not be construed as limiting the scope of protection of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the scope of protection of this application. It should be understood that technical solutions obtained by those skilled in the art based on the technical solutions provided in this application through logical analysis, reasoning, or limited experimentation are all within the scope of protection of the appended claims. Therefore, the scope of protection of this patent application should be determined by the content of the appended claims, and the specification and drawings can be used to interpret the content of the claims.

Claims

1. A method for determining the failure rate of an energy storage system, characterized in that, The method includes: Acquire environmental monitoring data and system monitoring data of the energy storage system; Based on the environmental monitoring data, the system monitoring data, and the pre-established component failure model, the failure rate of multiple components in the energy storage system is determined. Based on the failure rates of the multiple components and the pre-established subsystem failure model, the failure rates of multiple subsystems corresponding to each energy storage submodule in the energy storage system are determined; wherein, the subsystem failure model includes the correlation relationships between the multiple components; The overall failure rate of the energy storage system is determined based on the failure rates of multiple subsystems corresponding to each energy storage submodule and a pre-established overall failure model; wherein, the overall failure model includes the correlation relationships between multiple energy storage submodules.

2. The method according to claim 1, characterized in that, The step of determining the failure rate of multiple components in the energy storage system based on the environmental monitoring data, the system monitoring data, and the pre-established component failure model includes: For each of the aforementioned components, obtain the basic failure rate corresponding to that component; Multiple correction coefficients are determined based on the environmental monitoring data and the system monitoring data; The failure rate of the component is calculated based on the basic failure rate, multiple correction coefficients, and the component failure model corresponding to the component. Among them, the plurality of correction coefficients include at least two of the following: altitude correction coefficient, temperature correction coefficient, humidity correction coefficient, load rate correction coefficient, stress correction coefficient, cumulative working time correction coefficient, cumulative cycle number correction coefficient, vibration and shock intensity correction coefficient, dirtiness correction coefficient, and flying insect number correction coefficient.

3. The method according to claim 1, characterized in that, The energy storage submodule includes multiple subsystems such as a power module, a combiner cabinet, and a power cabinet, with the combiner cabinet connected to both the power module and the power cabinet. Determining the failure rate of the multiple subsystems corresponding to each energy storage submodule in the energy storage system based on the failure rates of the multiple components and a pre-established subsystem failure model includes: The failure rate of the power module is determined based on the failure rates of the multiple components, the components in the power module, and the failure model of the subsystem corresponding to the power module. The failure rate of the combiner cabinet is determined based on the failure rates of the multiple components, the components in the combiner cabinet, and the failure model of the subsystem corresponding to the combiner cabinet. The failure rate of the electrical cabinet is determined based on the failure rates of the multiple components, the failure models of the components in the electrical cabinet, and the subsystem corresponding to the electrical cabinet.

4. The method according to claim 3, characterized in that, Determining the failure rate of the power module based on the failure rates of the multiple components, the components in the power module, and the subsystem failure model corresponding to the power module includes: Based on the failure rates of the multiple components, the failure rate of each component in the power module is determined; wherein, the components in the power module include multiple types of power devices, power supplies, water circuits, stacks, connecting blocks, power drive devices, bypass drive devices, submodule control cards, support capacitors, and bypass switches; The failure rate of the power module is determined based on the failure rate of each component in the power module and the failure model of the subsystem corresponding to the power module.

5. The method according to claim 4, characterized in that, The power supply includes a main power supply and a redundant power supply belonging to the power module; determining the failure rate of each component in the power module based on the failure rate of the multiple components includes: The failure rate of the power supply in the power module is determined based on the failure rate of the main power supply and the failure rate of the redundant power supply belonging to the power module.

6. The method according to claim 3, characterized in that, The step of determining the failure rate of the combiner cabinet based on the failure rates of the multiple components, the components in the combiner cabinet, and the failure model of the subsystem corresponding to the combiner cabinet includes: Based on the failure rates of the multiple components, the failure rate of each component in the combiner cabinet is determined; wherein, the components in the combiner cabinet include multiple components such as structural parts, disconnect switches, insulation detection modules, clamping circuits, battery management controllers, switch driver boards, relays, and combiner cabinet power supplies; The failure rate of the combiner cabinet is determined based on the failure rate of each component in the combiner cabinet and the failure model of the subsystem corresponding to the combiner cabinet.

7. The method according to claim 6, characterized in that, The combiner cabinet power supply includes a main power supply, a redundant power supply, and a redundant module belonging to the combiner cabinet; determining the failure rate of each component in the combiner cabinet based on the failure rate of the multiple components includes: The failure rate of the power supply in the combiner cabinet is determined based on the failure rate of the main power supply, the failure rate of the redundant power supply, and the failure rate of the redundant module belonging to the combiner cabinet.

8. The method according to claim 3, characterized in that, The step of determining the failure rate of the electrical cabinet based on the failure rates of the multiple components, the components in the electrical cabinet, and the failure model of the subsystem corresponding to the electrical cabinet includes: Based on the failure rates of the multiple components, the failure rate of each component in the electrical cabinet is determined; wherein, the components in the electrical cabinet include multiple components such as the electrical box, main control box, thermal management bend, and cabinet body; the electrical box includes multiple components such as battery cells, lower box body, converter sampling assembly, and fuses; the main control box includes multiple components such as electrical cabinet power supply, battery slave management unit, relay, and current sensor; The failure rate of the electrical cabinet is determined based on the failure rate of each component in the electrical cabinet and the failure model of the corresponding subsystem.

9. The method according to claim 8, characterized in that, The power supply of the electrical cabinet includes a main power supply and a redundant power supply belonging to the electrical cabinet; determining the failure rate of each component in the electrical cabinet based on the failure rate of the multiple components includes: The failure rate of the power supply in the electrical cabinet is determined based on the failure rate of the main power supply and the failure rate of the redundant power supply belonging to the electrical cabinet.

10. The method according to claim 3, characterized in that, The step of determining the overall failure rate of the energy storage system based on the failure rates of multiple subsystems corresponding to each energy storage submodule and a pre-established overall failure model includes: Determine the failure rate of the power supply system of the energy storage submodule; wherein the power supply system includes a power supply, a combiner cabinet power supply, and an electrical cabinet power supply; The failure rate of the energy storage submodule is determined based on the failure rate of the power supply system of the energy storage submodule, the failure rate of the power module, the failure rate of the combiner cabinet, and the failure rate of the electrical cabinet. The overall failure rate of the energy storage system is determined based on the failure rate of the energy storage submodule and the overall failure model.

11. The method according to claim 1, characterized in that, The method further includes: If the overall failure rate of the energy storage system does not meet the preset target requirements, an alarm signal is output.

12. A failure rate determination device for an energy storage system, characterized in that, The device includes: The data acquisition module is used to acquire environmental monitoring data and system monitoring data of the energy storage system; The component failure rate determination module is used to determine the failure rate of multiple components in the energy storage system based on the environmental monitoring data, the system monitoring data, and the pre-established component failure model. The subsystem failure rate determination module is used to determine the failure rate of multiple subsystems corresponding to each energy storage submodule in the energy storage system based on the failure rates of the multiple components and a pre-established subsystem failure model; wherein, the subsystem failure model includes the correlation relationships between the multiple components; The overall failure rate determination module is used to determine the overall failure rate of the energy storage system based on the failure rates of multiple subsystems corresponding to each energy storage submodule and a pre-established overall failure model; wherein, the overall failure model includes the correlation relationships between multiple energy storage submodules.

13. A failure monitoring system, characterized in that, The failure monitoring system includes multiple data acquisition devices and computer equipment; The data acquisition device is used to collect environmental monitoring data or system monitoring data; The computer device is used to perform the method as described in any one of claims 1-11.

14. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 11.

15. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 11.

16. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 11.

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