Discrete coefficient-based ups battery pack failure assessment method, system, and related devices

Abstract

The application provides a discrete coefficient-based UPS battery pack fault evaluation method, system and related device, including the following steps: acquiring a plurality of key operating parameters of each single battery in the UPS battery pack; calculating the discrete coefficient of each key operating parameter on all single batteries; comparing the obtained discrete coefficient with a set dynamic baseline, and performing fault evaluation according to the comparison result; the application can not only find the consistency differentiation trend in advance when the overall performance of the battery pack does not decrease obviously, but also accurately locate the single battery with abnormal performance, greatly improving the pertinence and efficiency of maintenance.

Description

Technical Field

[0001] This invention belongs to the field of wind power, specifically relating to a UPS battery pack fault assessment method, system, and related devices based on the coefficient of variation. Background Technology

[0002] Uninterruptible power supplies (UPS) in wind farm transformer substations are critical auxiliary equipment ensuring the reliable operation of wind turbines. Their core function is to provide a continuous, stable, and clean power supply to the transformer substation and its associated monitoring, control, and protection systems. As an energy conversion hub connecting individual wind turbines or photovoltaic arrays to the site's power collection lines, the transformer substation's internal intelligent control units, communication modules, protection devices, and other secondary equipment require extremely high power reliability. Once power is lost, these systems will malfunction, leading to the inability to monitor wind turbines properly, and even damage due to protection failure during grid fluctuations. The UPS intervenes immediately when the main power supply is interrupted or when power quality issues such as voltage dips or surges occur. Through its internal battery storage, it achieves zero-millisecond switching, providing uninterrupted backup power to critical loads.

[0003] The battery bank in a UPS system is the core of backup energy, and its performance directly affects the continued operation of critical loads during power outages. A battery bank typically consists of multiple individual cells connected in series, and its overall capacity and reliability are limited by the weakest link cell. Current methods for monitoring battery banks in UPS systems have the following problems. Reliance on absolute thresholds: Current mainstream monitoring methods mostly rely on absolute thresholds (such as too high or too low) of individual battery voltage for alarms. However, battery voltage is greatly affected by load, temperature, and equalization / float charging status, and fixed thresholds have poor adaptability, making them prone to false alarms or missed alarms.

[0004] Ignoring consistency degradation: Battery pack failures often stem from the consistent degradation of performance between individual cells, which is a precursor to overall degradation. Existing methods lack sufficient quantitative assessment of the key indicator of "consistency," failing to provide early warning.

[0005] Passive and inefficient maintenance: Maintenance or replacement is usually carried out only after the battery has shown significant performance degradation or failure. This is an after-the-fact approach, which may cause unexpected downtime risks and cannot achieve predictive maintenance.

[0006] Limited parameters: It only monitors voltage and fails to comprehensively utilize multi-dimensional data such as voltage, internal resistance, and temperature, resulting in a single evaluation dimension and limited accuracy. Summary of the Invention

[0007] The purpose of this invention is to provide a UPS battery pack fault assessment method, system, and related apparatus based on discrete coefficients, thereby overcoming the aforementioned shortcomings in the prior art.

[0008] To achieve the above objectives, the technical solution adopted by the present invention is as follows: In a first aspect, the UPS battery pack fault assessment method based on discrete coefficients provided by the present invention includes the following steps: Obtain multiple key operating parameters for each individual cell in the UPS battery pack; Calculate the coefficient of variation of each key operating parameter across all individual cells; The obtained discrete coefficients are compared with the set dynamic baseline, and the fault assessment is performed based on the comparison results.

[0009] Preferably, the key operating parameters are terminal voltage and surface temperature.

[0010] Preferably, the coefficient of variation for each key operating parameter across all individual cells includes the coefficient of variation for voltage and temperature values ​​across all individual cells.

[0011] Preferably, the dynamic baseline is obtained by: During the initial health phase of the UPS battery pack's operation, acquire multiple key operating parameters for each individual cell in the UPS battery pack. Calculate the coefficient of variation of each key operating parameter across all individual cells to form an initial baseline of the coefficient of variation. The set dynamic baseline is obtained based on the initial discrete coefficient baseline, where the set dynamic baseline is a range value or a statistical value.

[0012] Preferably, the discrete coefficients are calculated based on the following formula: .

[0013] Secondly, the UPS battery pack fault assessment system based on discrete coefficients provided by the present invention includes: The parameter acquisition unit is used to acquire multiple key operating parameters of each individual battery cell in the UPS battery pack. The discrete coefficient calculation unit is used to calculate the discrete coefficient of each key operating parameter across all individual cells; The fault assessment unit is used to compare the obtained discrete coefficients with the set dynamic baseline and perform fault assessment based on the comparison results.

[0014] Thirdly, the present invention provides an electronic device including a processor and a memory, wherein the memory stores computer instructions, and when the computer instructions are executed by the processor, the electronic device performs the method described thereon.

[0015] Fourthly, the present invention provides a computing device cluster, comprising at least one computing device, each computing device including a processor and a memory; The processor of the at least one computing device is configured to execute instructions stored in the memory of the at least one computing device to cause the cluster of computing devices to perform the method according to the method.

[0016] Fifthly, the present invention provides a computer program product, the computer program product including computer-executable instructions, which, when executed, implement the method described.

[0017] In a sixth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the method described herein.

[0018] Compared with the prior art, the beneficial effects of the present invention are: This invention provides a UPS battery pack fault assessment method based on the coefficient of variation (COP). By introducing the COP as a core assessment indicator, it achieves early and accurate identification of consistent degradation in UPS battery packs, significantly improving the timeliness and reliability of fault warnings. Compared with traditional methods relying on absolute thresholds, the COP, as a relative statistic, effectively reduces false alarms and missed alarms caused by fluctuations in external factors such as load and temperature, enhancing anti-interference capabilities. By simultaneously collecting multi-dimensional parameters such as voltage and temperature and calculating the COP separately, the system can comprehensively reflect the battery status from multiple levels, including electrochemical and thermal aspects, making the assessment results more scientific and comprehensive. The establishment and updating of the dynamic baseline mechanism enables the system to adapt to the normal aging process of the battery pack, avoiding misjudgments of normal performance degradation. Simultaneously, through multi-level comparisons of real-time data with the baseline, it achieves progressive early warnings from "attention" to "serious," strongly supporting predictive maintenance. This method can not only detect the trend of consistency differentiation in advance when the overall performance of the battery pack has not declined significantly, but also accurately locate the individual cells with abnormal performance, which greatly improves the pertinence and efficiency of maintenance. This transforms the traditional passive maintenance into proactive health management, extends the service life of the battery pack, reduces the overall operation and maintenance cost, and ensures the continuous and reliable operation of the UPS system and the critical loads at the back end. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating an embodiment of the present invention; Figure 2 This is a schematic diagram of the evaluation results of an embodiment of the present invention. Detailed Implementation

[0020] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0021] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0022] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0023] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0024] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0025] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0026] Example 1 like Figure 1As shown, the UPS battery pack fault assessment method based on discrete coefficients provided in this embodiment includes the following steps: S1: Real-time acquisition of multi-dimensional parameters: During the operation of the UPS battery pack, multiple key operating parameters of each individual battery cell in the pack are periodically and synchronously acquired, including at least: terminal voltage. Surface temperature Data sampling period And the internal resistance value obtained through online or periodic testing:

[0027]

[0028] S2: Calculation of the coefficient of variation: For each parameter (such as voltage and temperature) within each acquisition cycle, calculate the coefficient of variation of that parameter across all individual cells. .

[0029] The formula for calculating the discrete coefficients is as follows: That is, calculate the coefficient of variation of the voltage values ​​of all individual cells within the cycle. and the coefficient of variation of temperature values .

[0030] S3: Dynamic Baseline Establishment and Update: During the initial health phase of the battery pack's operation (e.g., the first 3 months), the dispersion coefficients of each parameter are continuously calculated and recorded to form an initial dispersion coefficient baseline. This baseline can be a range (e.g., [...]). , This baseline can be set as a statistical value (such as the 80th percentile) or a statistical value. The system can update this baseline periodically (such as monthly) or automatically based on operating conditions to accommodate the normal aging of the battery pack.

[0031] S4: Consistency Status Assessment and Fault Warning: Real-time comparison: The currently calculated real-time discrete coefficients ( , Compare with the corresponding dynamic baseline.

[0032] Multi-level early warning strategy: Attention Level: If the real-time dispersion coefficient of any parameter exceeds the baseline threshold but does not reach the critical threshold (such as 120% of the baseline), the system will issue a "consistency degradation" warning to alert the user.

[0033] Warning level: If the real-time dispersion coefficient of any parameter consistently exceeds a severe threshold (e.g., 120% of the baseline), or and At the same time, the levels are significantly exceeded, and the system issues a "high risk of failure" warning, suggesting a planned inspection.

[0034] Severity Level: If the dispersion coefficient increases sharply and the parameters of a specific individual battery are found to deviate significantly from the group, the system will issue a severe alarm that "a fault is about to occur" and mark the location of the faulty battery.

[0035] like Figure 2 As shown: This battery assembly was classified as a warning level in February, a caution level in April and June, and a severe level in November.

[0036] S5: Comprehensive Health Score and Report Generation: Based on the deviation of each parameter's dispersion coefficient from the baseline, a weighted algorithm is used to calculate the battery pack's comprehensive health score. .

[0037]

[0038] Among them, the real-time discrete coefficient ( , ); The weighting coefficients for the battery pack voltage dispersion are based on a functional relationship with the real-time voltage. ; The weighting coefficients for the battery pack temperature dispersion are based on a functional relationship with the real-time temperature. .

[0039] The system automatically generates assessment reports, including: consistency trend charts, health score change curves, potential faulty battery identification, and maintenance recommendations.

[0040] Example 2 The UPS battery pack fault assessment system based on the coefficient of variation provided in this embodiment includes: Parameter acquisition unit: This unit connects to sensors in each individual cell within the battery pack, and is used to periodically and synchronously acquire multiple key operating parameters of each individual cell. These key operating parameters include terminal voltage. Temperature parameters and data sampling period .

[0041]

[0042]

[0043] Discrete coefficient calculation unit: used to receive collected data, calculate the discrete coefficients of each parameter, and store historical data and dynamic baselines.

[0044] Fault assessment unit: Used to compare the obtained discrete coefficients with the set dynamic baseline, and to perform fault assessment based on the comparison results.

[0045] Human-computer interaction and alarm unit: It provides a visual interface to display battery pack status, consistency trend, health score and alarm information; and pushes alarms through sound and light, software pop-ups, SMS / email and other means.

[0046] Communication interface module: Used to upload evaluation results and alarm information to a remote monitoring center or cloud platform to achieve remote centralized monitoring.

[0047] Example 3 This embodiment also provides a computing device. The computing device includes a bus, a processor, a memory, and a communication interface. The processor, memory, and communication interface communicate with each other via the bus. The computing device can be a server or a terminal device. It should be understood that this application does not limit the number of processors and memory in the computing device.

[0048] A bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, a bus can include a path for transmitting information between various components of a computing device (e.g., memory, processor, communication interfaces).

[0049] The processor may include any one or more of the following: central processing unit (CPU), graphics processing unit (GPU), tensor processing unit (TPU), application specific integrated circuit (ASIC), field-programmable gate array (FPGA), microprocessor (MP), or digital signal processor (DSP).

[0050] Memory can include volatile memory, such as random access memory (RAM). Processors can also include non-volatile memory. volatile memory, such as read-only memory (ROM). ROM (memory only), flash memory, hard disk drive (HDD), or solid state drive (SSD).

[0051] The memory stores executable program code, which the processor executes to implement the functions of the aforementioned units, thereby achieving, for example, the method described in Embodiment 1. That is, the memory may store instructions for the methods and functions relating to the computing device in any of the above embodiments.

[0052] The communication interface uses transceiver modules such as, but not limited to, network interface cards and transceivers to enable communication between computing devices and other devices or communication networks.

[0053] Example 4 This embodiment also provides a computing device cluster. The computing device cluster includes at least one computing device. The computing device can be a server, such as a central server, an edge server, or a local server in a local data center. In some embodiments, the computing device can also be a terminal device such as a desktop computer, a laptop computer, or a smartphone.

[0054] The computing device cluster includes at least one computing device. The memory of one or more computing devices in the computing device cluster may store the same instructions for performing the methods and functions related to the computing devices in any of the above embodiments.

[0055] In some possible implementations, the memory of one or more computing devices in the computing device cluster may also store partial instructions for performing the methods and functions of the computing devices involved in any of the above embodiments. In other words, a combination of one or more computing devices can jointly execute the instructions for performing the methods and functions of the computing devices.

[0056] It should be noted that the memory in different computing devices within a computing device cluster can store different instructions, which are used to execute parts of the device's functions.

[0057] In some possible implementations, one or more computing devices in a computing device cluster can be connected via a network. This network can be a wide area network (WAN) or a local area network (LAN), etc. Two computing devices are connected to each other via the network. Specifically, they connect to the network through communication interfaces in each computing device.

[0058] Embodiments of this disclosure also provide a computer program product containing instructions that, when run on a computer, cause the computer to perform the methods and functions related to a computing device in any of the above embodiments.

[0059] Example 5 This embodiment also provides a computer-readable storage medium storing computer instructions that, when executed by a processor, cause the processor to perform the methods and functions of the computing device involved in any of the above embodiments.

[0060] Generally, the various embodiments of this disclosure can be implemented in hardware or dedicated circuitry, software, logic, or any combination thereof. Some aspects can be implemented in hardware, while others can be implemented in firmware or software, which can be executed by a controller, microprocessor, or other computing device. Although various aspects of the embodiments of this disclosure are shown and described as block diagrams, flowcharts, or represented using some other illustration, it should be understood that the blocks, apparatuses, systems, techniques, or methods described herein can be implemented as, as non-limiting examples, in hardware, software, firmware, dedicated circuitry or logic, general-purpose hardware or controllers or other computing devices, or some combination thereof.

[0061] Example 6 This embodiment provides at least one computer program product tangibly stored on a non-transitory computer-readable storage medium. The computer program product includes computer-executable instructions, such as instructions included in program modules, which execute in a device on a target real or virtual processor to perform the processes / methods as described above with reference to the accompanying drawings. Typically, program modules include routines, programs, libraries, objects, classes, components, data structures, etc., that perform specific tasks or implement specific abstract data types. In various embodiments, the functionality of program modules can be combined or divided among program modules as needed. The machine-executable instructions for the program modules can execute within a local or distributed device. In a distributed device, the program modules can reside in both local and remote storage media.

[0062] Computer program code used to implement the methods of this disclosure may be written in one or more programming languages. This computer program code may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus, such that when executed by the computer or other programmable data processing apparatus, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be performed. The program code may be executed entirely on a computer, partially on a computer, as a stand-alone software package, partially on a computer and partially on a remote computer, or entirely on a remote computer or server.

[0063] In the context of this disclosure, computer program code or related data may be carried on any suitable carrier to enable a device, apparatus, or processor to perform the various processes and operations described above. Examples of carriers include signals, computer-readable media, and so on. Examples of signals may include electrical, optical, radio, sound, or other forms of propagation signals, such as carrier waves, infrared signals, etc.

[0064] Computer-readable media can be any tangible medium that contains or stores programs for or relating to an instruction execution system, apparatus, or device, or a data storage device such as a data center containing one or more available media. Computer-readable media can be computer-readable signal media or computer-readable storage media. Computer-readable media can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. More detailed examples of computer-readable storage media include electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0065] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A UPS battery pack fault assessment method based on discrete coefficients, characterized in that, Includes the following steps: Obtain multiple key operating parameters for each individual cell in the UPS battery pack; Calculate the coefficient of variation of each key operating parameter across all individual cells; The obtained discrete coefficients are compared with the set dynamic baseline, and the fault assessment is performed based on the comparison results.

2. The UPS battery pack fault assessment method based on discrete coefficients according to claim 1, characterized in that, Several key operating parameters are terminal voltage and surface temperature.

3. The UPS battery pack fault assessment method based on discrete coefficients according to claim 1, characterized in that, The coefficient of variation for each key operating parameter across all individual cells includes the coefficient of variation for both voltage and temperature values ​​across all individual cells.

4. The UPS battery pack fault assessment method based on discrete coefficients according to claim 1, characterized in that, The dynamic baseline is set and obtained by: During the initial health phase of the UPS battery pack's operation, acquire multiple key operating parameters for each individual cell in the UPS battery pack. Calculate the coefficient of variation of each key operating parameter across all individual cells to form an initial baseline of the coefficient of variation. The set dynamic baseline is obtained based on the initial discrete coefficient baseline, where the set dynamic baseline is a range value or a statistical value.

5. The UPS battery pack fault assessment method based on discrete coefficients according to claim 1, characterized in that, The coefficients of variation are calculated based on the following formula: 。 6. A UPS battery pack fault assessment system based on discrete coefficients, characterized in that, include: The parameter acquisition unit is used to acquire multiple key operating parameters of each individual battery cell in the UPS battery pack. The discrete coefficient calculation unit is used to calculate the discrete coefficient of each key operating parameter across all individual cells; The fault assessment unit is used to compare the obtained discrete coefficients with the set dynamic baseline and perform fault assessment based on the comparison results.

7. An electronic device, characterized in that, It includes a processor and a memory, the memory storing computer instructions that, when executed by the processor, cause the electronic device to perform the method of any one of claims 1 to 5.

8. A computing device cluster, characterized in that, It includes at least one computing device, each computing device including a processor and memory; The processor of the at least one computing device is configured to execute instructions stored in the memory of the at least one computing device to cause the cluster of computing devices to perform the method according to any one of claims 1 to 5.

9. A computer program product, characterized in that, The computer program product includes computer-executable instructions that, when executed, implement the method of any one of claims 1 to 5.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions that, when executed by a processor, implement the method of any one of claims 1 to 5.

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