A power supply data monitoring and analysis method and system for uninterruptible power supply

Abstract

The present application discloses a power data monitoring and analysis method and system for an uninterruptible power supply, which belongs to the field of computer technology. When the target uninterruptible power supply is in a loaded state, in response to a monitoring instruction for the target uninterruptible power supply, the electrolyte parameters and energy storage component parameters of the energy storage component of the target uninterruptible power supply are obtained, and the heat dissipation component parameters, operating parameters and inverter parameters of the uninterruptible power supply are obtained at the same time. The battery health status is determined using the electrolyte parameters and energy storage component parameters, and the power supply operating status is determined using the heat dissipation component parameters, operating parameters and inverter parameters, thereby achieving monitoring of the target uninterruptible power supply in two dimensions. In combination with the battery health status and the power supply operating status, the monitoring results of the target uninterruptible power supply are determined, thereby completing the monitoring of the target uninterruptible power supply. Due to the combination of data from multiple dimensions and targeted data processing methods, the accuracy of the monitoring results obtained is relatively high.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a power supply data monitoring and analysis method and system for an uninterruptible power supply. Background Art

[0002] With the growing demand for power supply continuity in fields such as data centers, medical equipment, and industrial automation, the reliability and stability of uninterruptible power supplies (UPS), as key power supply equipment, have attracted much attention.

[0003] Traditional uninterruptible power supply monitoring methods usually focus on the collection and analysis of single-dimensional parameters, such as monitoring only basic indicators such as battery voltage, current or temperature.

[0004] However, the above monitoring methods are relatively simple and have low accuracy. Summary of the Invention

[0005] The present application provides a method and system for monitoring and analyzing power data for an uninterruptible power supply (UPS), which can enrich the dimensions of UPS monitoring and improve monitoring accuracy. The technical solution is as follows:

[0006] In one aspect, a method for monitoring and analyzing power supply data for an uninterruptible power supply is provided, the method comprising:

[0007] When a target uninterruptible power supply is in a loaded state, in response to a monitoring instruction for the target uninterruptible power supply, obtaining electrolyte parameters and energy storage component parameters of an energy storage component of the target uninterruptible power supply, obtaining heat dissipation component parameters, operating parameters, and inverter parameters of the target uninterruptible power supply, wherein the energy storage component is a lithium-ion battery;

[0008] Determining a battery health state of the energy storage component based on the electrolyte parameter and the energy storage component parameter, where the battery health state is used to indicate a health level;

[0009] Determining a power supply operating state of the target uninterruptible power supply based on the heat dissipation component parameters, the operating parameters, and the inverter parameters, wherein the power supply operating state is used to indicate an operating condition;

[0010] Based on the battery health status and the power supply operating status, a monitoring result of monitoring the target uninterruptible power supply is determined, where the monitoring result is used to indicate whether there is an abnormality.

[0011] In one aspect, a power supply data monitoring and analysis system for an uninterruptible power supply is provided, the system comprising:

[0012] a parameter acquisition module for acquiring, in response to a monitoring instruction for the target uninterruptible power supply when the target uninterruptible power supply is in a loaded state, electrolyte parameters and energy storage component parameters of the energy storage component of the target uninterruptible power supply, and acquiring heat dissipation component parameters, operating parameters, and inverter parameters of the target uninterruptible power supply, wherein the energy storage component is a lithium-ion battery;

[0013] a health status determination module, configured to determine a battery health status of the energy storage assembly based on the electrolyte parameters and the energy storage assembly parameters, wherein the battery health status is used to indicate a health level;

[0014] a working state determining module, configured to determine a power supply working state of the target uninterruptible power supply based on the heat dissipation component parameters, the working parameters, and the inverter parameters, wherein the power supply working state is used to indicate a working condition;

[0015] A monitoring result determination module is used to determine a monitoring result of monitoring the target uninterruptible power supply based on the battery health status and the power supply working status, wherein the monitoring result is used to indicate whether an abnormality exists.

[0016] On the one hand, a computer device is provided, which includes one or more processors and one or more memories, wherein at least one computer program is stored in the one or more memories, and the computer program is loaded and executed by the one or more processors to implement the power data monitoring and analysis method for an uninterruptible power supply.

[0017] In one aspect, a computer-readable storage medium is provided, wherein at least one computer program is stored in the computer-readable storage medium, and the computer program is loaded and executed by a processor to implement the power data monitoring and analysis method for an uninterruptible power supply.

[0018] On the one hand, a computer program product or computer program is provided, which includes a program code, which is stored in a computer-readable storage medium. A processor of a computer device reads the program code from the computer-readable storage medium, and the processor executes the program code, so that the computer device performs the above-mentioned power data monitoring and analysis method for an uninterruptible power supply.

[0019] Through the technical solution provided by the embodiment of the present application, when the target uninterruptible power supply is in a loaded state, in response to the monitoring instruction of the target uninterruptible power supply, the electrolyte parameters and energy storage component parameters of the energy storage component of the target uninterruptible power supply are obtained, and the heat dissipation component parameters, operating parameters and inverter parameters of the uninterruptible power supply are obtained at the same time. The battery health status is determined using the electrolyte parameters and energy storage component parameters, and the power supply working status is determined using the heat dissipation component parameters, operating parameters and inverter parameters, thereby realizing the monitoring of the target uninterruptible power supply in two dimensions. In combination with the battery health status and the power supply working status, the monitoring results of the target uninterruptible power supply are determined, thereby completing the monitoring of the target uninterruptible power supply. Due to the combination of data from multiple dimensions and targeted data processing methods, the accuracy of the monitoring results obtained is relatively high. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0021] Figure 1 Schematic diagram of an implementation environment of a power data monitoring and analysis method for an uninterruptible power supply provided in an embodiment of the present application;

[0022] Figure 2 This is a flow chart of a power data monitoring and analysis method for an uninterruptible power supply provided in an embodiment of the present application;

[0023] Figure 3 This is a flow chart of another power data monitoring and analysis method for an uninterruptible power supply provided in an embodiment of the present application;

[0024] Figure 4 This is a schematic diagram of the structure of a power data monitoring and analysis system for an uninterruptible power supply provided in an embodiment of the present application;

[0025] Figure 5 This is a schematic diagram of the structure of a controller provided in an embodiment of the present application. DETAILED DESCRIPTION

[0026] In order to make the objectives, technical solutions and advantages of this application clearer, the implementation methods of this application will be further described in detail below with reference to the accompanying drawings.

[0027] In this application, the terms "first", "second", etc. are used to distinguish identical or similar items with substantially the same effects and functions. It should be understood that there is no logical or temporal dependency between "first", "second", and "nth", nor is there any limitation on the quantity and execution order.

[0028] Uninterruptible Power Supply: A power supply device that contains an energy storage device (such as a battery), mainly used to provide continuous and stable power to equipment that requires high power stability.

[0029] IGBT (Insulated Gate Bipolar Transistor): It is a composite power semiconductor device that combines the advantages of MOSFET (high input impedance, fast switching) and BJT (low conduction loss). Structurally, the MOSFET gate controls the bipolar transistor output.

[0030] Inverter: An inverter is a power conversion device that converts direct current (DC) into alternating current (AC). Its core functions include voltage regulation, frequency control, and waveform optimization.

[0031] Electrolyte: It is the carrier for ion transport in the battery.

[0032] In related technologies, monitoring of uninterruptible power supplies typically involves analyzing single-dimensional parameters, such as the battery voltage, current, or temperature of the uninterruptible power supply. For example, if the battery voltage is too high or too low, it can be determined that the uninterruptible power supply is abnormal. Alternatively, if the current is too high or too low, it can be determined that the uninterruptible power supply is abnormal.

[0033] However, this monitoring method is relatively simple and has low accuracy.

[0034] Figure 1 This is a schematic diagram of an implementation environment of a power data monitoring and analysis method for an uninterruptible power supply provided in an embodiment of the present application, see Figure 1 , the implementation environment may include a controller 110 and a server 140 .

[0035] The controller 110 is connected to the server 140 via a wireless network or a wired network. Optionally, the controller 110 is a smart phone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited thereto. The controller 110 has an application installed and running that supports power data monitoring and analysis for the uninterruptible power supply.

[0036] Server 140 is a standalone physical server, or a server cluster or distributed system consisting of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, a Content Delivery Network (CDN), and big data and artificial intelligence platforms. Server 140 can provide background services for applications running on controller 110. In this embodiment of the present application, server 140 provides background services for controller 110.

[0037] The following describes a method for monitoring and analyzing power data for an uninterruptible power supply provided in an embodiment of the present application. Figure 2 This is a flow chart of a method for monitoring and analyzing power data for an uninterruptible power supply provided in an embodiment of the present application. Figure 2 , taking the execution subject as a controller as an example, the method includes the following steps.

[0038] 201. When a target uninterruptible power supply is in a loaded state, in response to a monitoring instruction for the target uninterruptible power supply, a controller obtains electrolyte parameters and energy storage component parameters of an energy storage component of the target uninterruptible power supply, and obtains heat dissipation component parameters, operating parameters, and inverter parameters of the target uninterruptible power supply, where the energy storage component is a lithium-ion battery.

[0039] The target uninterruptible power supply is in a loaded state, indicating that the target uninterruptible power supply is supplying power to the power-consuming equipment, that is, the target uninterruptible power supply is providing power to the outside. The target uninterruptible power supply is an uninterruptible mobile power supply to be monitored. The target uninterruptible power supply can be used to ensure power supply in various scenarios, such as ensuring power supply for critical meetings, ensuring power supply for critical equipment, and ensuring power supply for critical buildings. The target uninterruptible power supply includes an energy storage component, a heat dissipation component, and a control component. The energy storage component is mainly used to store electrical energy and then release it when power is needed. The heat dissipation component is used to dissipate heat from the energy storage component. This is because the energy storage component generates heat during operation due to the existence of internal resistance. If the temperature of the energy storage component is too high, it will affect the performance of the electrolyte of the energy storage component, so the heat dissipation component is required to dissipate heat. The control component plays the core control function, and the controller belongs to the control component. Electrolyte parameters reflect the characteristics of the electrolyte in the energy storage assembly. As the core component of the target UPS, the electrolyte is a key component of the energy storage assembly. Electrolyte parameters critically impact the performance of the energy storage assembly and are therefore considered key parameters for monitoring the target UPS. Energy storage assembly parameters reflect the actual performance of the energy storage assembly, which can also affect the operation of the target UPS. Therefore, they are also considered key parameters for monitoring the target UPS. Heat dissipation assembly parameters reflect the actual performance of the heat dissipation assembly, which affects the operation of the target UPS. Therefore, heat dissipation also affects the operation of the target UPS and are therefore also key parameters for monitoring the target UPS. Operating parameters reflect the overall operating status of the target UPS, while inverter parameters reflect the actual inverter performance. Both parameters are crucial for monitoring the target UPS.

[0040] 202. The controller determines a battery health status of the energy storage assembly based on the electrolyte parameters and the energy storage assembly parameters, where the battery health status is used to indicate a health level.

[0041] The energy storage component's state of health (SOH) indicates its health. If its SOH is poor, the amount of energy it can store decreases, potentially preventing it from meeting power demands. Therefore, in this embodiment, determining the SOH of the energy storage component is a key aspect of monitoring the target uninterruptible power supply. In related art, assessing SOH is difficult. In this embodiment, SOH is assessed using electrolyte parameters and energy storage component parameters, aiming to obtain a more accurate SOH.

[0042] 203. The controller determines a power supply operating state of the target uninterruptible power supply based on the heat dissipation component parameter, the operating parameter, and the inverter parameter, where the power supply operating state is used to indicate an operating condition.

[0043] Among them, the power supply working status is the core parameter that reflects the actual situation of the target uninterruptible power supply. In the embodiment of the present application, the power supply working status of the target uninterruptible power supply is determined in combination with the heat dissipation component parameters, operating parameters and inverter parameters, so that the evaluation of the power supply working status is as comprehensive as possible, thereby improving the monitoring effect of the target uninterruptible power supply.

[0044] 204. The controller determines a monitoring result of the target uninterruptible power supply based on the battery health status and the power supply operating status. The monitoring result is used to indicate whether an abnormality exists.

[0045] Among them, the monitoring result is determined based on the battery health status and the power supply working status, that is, in the embodiment of the present application, the monitoring of the target uninterruptible power supply is ultimately achieved by monitoring the battery health status and the power supply working status.

[0046] Through the technical solution provided by the embodiment of the present application, when the target uninterruptible power supply is in a loaded state, in response to the monitoring instruction of the target uninterruptible power supply, the electrolyte parameters and energy storage component parameters of the energy storage component of the target uninterruptible power supply are obtained, and the heat dissipation component parameters, operating parameters and inverter parameters of the uninterruptible power supply are obtained at the same time. The battery health status is determined using the electrolyte parameters and energy storage component parameters, and the power supply working status is determined using the heat dissipation component parameters, operating parameters and inverter parameters, thereby realizing the monitoring of the target uninterruptible power supply in two dimensions. In combination with the battery health status and the power supply working status, the monitoring results of the target uninterruptible power supply are determined, thereby completing the monitoring of the target uninterruptible power supply. Due to the combination of data from multiple dimensions and targeted data processing methods, the accuracy of the monitoring results obtained is relatively high.

[0047] The above steps 201-204 are a brief introduction to the power data monitoring and analysis method for an uninterruptible power supply provided in an embodiment of the present application. The following will combine some examples to more clearly illustrate the power data monitoring and analysis method for an uninterruptible power supply provided in an embodiment of the present application. Figure 3 , taking the execution subject as a controller as an example, the method includes the following steps.

[0048] 301. When a target uninterruptible power supply is in a loaded state, in response to a monitoring instruction for the target uninterruptible power supply, a controller obtains electrolyte parameters and energy storage component parameters of an energy storage component of the target uninterruptible power supply, and obtains heat dissipation component parameters, operating parameters, and inverter parameters of the target uninterruptible power supply, where the energy storage component is a lithium-ion battery.

[0049] Among them, the target uninterruptible power supply is in a loaded state, which means that the target uninterruptible power supply is supplying power to the power-consuming equipment, that is, the target uninterruptible power supply is providing electric energy to the outside. The monitoring instruction is used to instruct the monitoring of the target uninterruptible power supply. The monitoring instruction is manually triggered by a technician or automatically triggered by a controller. This embodiment of the present application is not limited to this. The target uninterruptible power supply is an uninterruptible mobile power supply to be monitored. The target uninterruptible power supply can be used for power guarantee in various scenarios, such as power guarantee for key meetings, power guarantee for key equipment, and power guarantee for key buildings. The target uninterruptible power supply includes an energy storage component, a heat dissipation component, and a control component. The energy storage component is mainly used to store electrical energy and then release electrical energy when power is needed. The heat dissipation component is used to dissipate heat from the energy storage component. This is because due to the existence of internal resistance, the energy storage component will generate heat during operation. If the temperature of the energy storage component is too high, it will affect the performance of the electrolyte of the energy storage component. Therefore, the heat dissipation component is required to dissipate heat. The control component plays the core control function, and the controller belongs to the control component. Electrolyte parameters reflect the characteristics of the electrolyte in the energy storage component. As the core component of the target uninterruptible power supply (UPS), the electrolyte is a key component of the UPS. Electrolyte parameters are crucial to the performance of the UPS and therefore serve as a key parameter for monitoring the UPS. Energy storage component parameters reflect the actual performance of the UPS and can affect the operation of the UPS. Therefore, they serve as a key parameter for monitoring the UPS. Heat dissipation component parameters reflect the actual performance of the UPS and can affect the heat dissipation of the UPS. Heat dissipation affects the operation of the UPS and therefore serves as a key parameter for monitoring the UPS. Operating parameters reflect the overall operating status of the UPS, while inverter parameters reflect the actual performance of the inverter. Both parameters are crucial for monitoring the UPS. Lithium-ion batteries are secondary batteries (rechargeable batteries) that primarily rely on the movement of lithium ions between the positive and negative electrodes. During the charge and discharge process, lithium ions are intercalated and deintercalated between the two electrodes.

[0050] In some embodiments, electrolyte parameters include electrolyte density change rate, electrolyte temperature, and electrolyte material characteristic coefficient. The electrolyte density change rate refers to the degree to which the density of the electrolyte changes over time or other factors under specific conditions. It is usually expressed as the change in density per unit time. The electrolyte temperature refers to the degree of hotness or coldness of the electrolyte, usually expressed in degrees Celsius (°C) or degrees Fahrenheit (°F). The electrolyte material characteristic coefficient is determined based on various parameters that describe the characteristics of the electrolyte material, including conductivity, viscosity, ion migration number, and electrochemical stability. These parameters reflect the physical and chemical properties of the electrolyte under different conditions.

[0051] In some embodiments, the energy storage component parameters include the temperature difference gradient between poles, the distance between poles of battery cells, the internal resistance, and the average temperature of the battery. The temperature difference gradient between poles of battery cells refers to the ratio of the temperature difference between the positive and negative poles of the battery cell to the distance between the poles, and the unit is usually ℃ / m or ℃ / cm. The distance between poles of battery cells refers to the straight-line distance between the positive and negative poles of the battery cell, and the unit is usually mm, cm, etc. The internal resistance refers to the resistance encountered by the current passing through the battery when the battery is working, and the unit is usually ohm (Ω). The average temperature of the battery refers to the average temperature of each part inside the energy storage component, and the unit is usually ℃.

[0052] In some embodiments, the heat dissipation component parameters include the standard deviation of the heat sink surface temperature distribution, the heat dissipation fluid flow rate, the heat dissipation pipeline pressure change rate, and the heat dissipation fluid viscosity coefficient. The standard deviation is a statistic used to measure the degree of dispersion of a set of data. The standard deviation of the heat sink surface temperature distribution reflects the fluctuation of the heat sink surface temperature at different locations. The heat dissipation fluid flow rate refers to the speed at which the heat dissipation fluid flows in the heat dissipation system. It is usually expressed in terms of volume or mass flowing through per unit time, such as cubic meters per second or kilograms per second. The heat dissipation pipeline pressure change rate refers to the rate of change of pressure in the heat dissipation pipeline over time. It is usually expressed in terms of the change in pressure per unit time, such as Pascals per second. The heat dissipation fluid viscosity coefficient is a physical quantity that describes the viscosity of the heat dissipation fluid. It reflects the ability of the heat dissipation fluid to resist deformation during flow.

[0053] In some embodiments, the operating parameters include power device operating parameters, output power parameters, and a fault log. The power device refers to the device powered by the target uninterruptible power supply, and the power device operating parameters represent the operating status of the power device. Output power parameters include the output voltage, output current, and output power of the target uninterruptible power supply. The fault log records fault conditions of the target uninterruptible power supply.

[0054] In some embodiments, the inverter parameters include multiple harmonic voltage RMS values, a fundamental voltage RMS value, a temperature compensation coefficient, and IGBT temperature. Harmonic voltage RMS values ​​refer to the RMS values ​​of each harmonic component in a voltage signal. In AC circuits, a voltage signal typically consists of a fundamental wave and a series of harmonic components. The fundamental wave is the component with the same frequency as the power supply, while the harmonics are components with frequencies that are integer multiples of the fundamental frequency. The fundamental voltage RMS value refers to the RMS value of the fundamental component in the voltage signal. It is the primary component of an AC voltage signal and reflects its basic characteristics and energy transfer capability. The temperature compensation coefficient is a temperature-dependent coefficient. IGBT (Insulated Gate Bipolar Transistor) temperature refers to the internal temperature of an IGBT device during operation. IGBTs are semiconductor devices widely used in power electronics, and temperature changes can affect their performance and reliability. IGBTs are the core components of inverters, converting DC to AC to power electrical devices.

[0055] In order to more clearly illustrate the above step 301, the following describes how the controller obtains the electrolyte parameters and energy storage component parameters of the target uninterruptible power supply's energy storage component, as well as the heat dissipation component parameters, operating parameters, and inverter parameters of the target uninterruptible power supply.

[0056] First, the method for the controller to obtain electrolyte parameters is described.

[0057] In one possible implementation, the controller uses a microfluidic sensor in the energy storage assembly to obtain the rate of change of the electrolyte density in the energy storage assembly. The controller also uses a temperature sensor in the energy storage assembly to obtain the electrolyte temperature in the energy storage assembly. The controller then determines the electrolyte material characteristic coefficient for the energy storage assembly based on the electrolyte material type.

[0058] The microfluidic sensor can be a thermal microfluidic density sensor, an oscillating microfluidic density sensor, an optical microfluidic density sensor, or a capacitive microfluidic density sensor. The relationship between the electrolyte material type and the electrolyte material characteristic coefficient is determined by a skilled person based on actual conditions and is not limited in this embodiment of the present application.

[0059] The principles of measuring electrolyte density using the above-mentioned various types of microfluidic sensors are described below.

[0060] Thermal microfluidic density sensors: These sensors employ heat conduction principles to measure electrolyte density by placing a heating wire and temperature sensor within a microchannel. When current passes through the heating wire, the heat generated raises the temperature of the surrounding electrolyte. The thermal microfluidic density sensor measures the temperature difference between the upstream and downstream channels, calculates the thermal conductivity based on the heat conduction equation, and thus determines the electrolyte density.

[0061] Oscillatory microfluidic density sensors: These sensors stimulate oscillations in the electrolyte within a microchannel and measure density using the relationship between the oscillation frequency or amplitude and density. These sensors are highly sensitive and suitable for measuring minute density changes.

[0062] Optical microfluidic density sensor: Utilizes the relationship between the refractive index and density of the electrolyte to perform measurements using optical methods. For example, a microfluidic sensor based on Mach-Zehnder interferometer (MZI) measures the refractive index change of the electrolyte by detecting the movement of interference fringes, thereby obtaining density information.

[0063] Capacitive microfluidic density sensors determine density by measuring changes in capacitance based on the relationship between the electrolyte's permittivity and density. When the electrolyte fills the space between the capacitor plates, the capacitance changes due to changes in the electrolyte's density. By measuring this change in capacitance, the electrolyte's density can be calculated.

[0064] It should be noted that technicians can use any of the above-mentioned microfluidic sensors to measure the density of the electrolyte in combination with cost requirements, and the embodiments of the present application are not limited to this.

[0065] In addition, after obtaining the electrolyte density using the microfluidic sensor, the electrolyte density change rate can be determined using multiple electrolyte densities measured at adjacent moments. For example, there are three moments, T1, T2, and T3. The controller subtracts the electrolyte density at T3 from the electrolyte density at T2 and divides the result by the electrolyte density at T2 to obtain a first electrolyte density change rate. The controller subtracts the electrolyte density at T2 from the electrolyte density at T1 and divides the result by the electrolyte density at T1 to obtain a second electrolyte density change rate. The controller determines the average of the first electrolyte density change rate and the second electrolyte density change rate as the electrolyte density change rate. The electrolyte density change rate can reflect the electrolyte activity decay rate. The reduction in electrolyte density may be caused by lithium salt decomposition or solvent volatilization, which directly affects the ion migration efficiency.

[0066] Among them, the number of adjacent moments and the interval duration are set by technical personnel according to actual conditions, and the embodiments of this application do not limit this.

[0067] The following describes how to obtain energy storage component parameters.

[0068] In one possible implementation, the controller obtains the inter-cell post distances and electrode temperatures of multiple battery cells in the energy storage assembly. Based on the inter-cell post distances and electrode temperatures of each battery cell, the controller determines the inter-cell post temperature gradient, the internal resistance of the energy storage assembly, and the average battery temperature.

[0069] Among them, the electrode temperature includes the positive electrode temperature and the negative electrode temperature, which can be directly measured by a temperature sensor. The distance between battery cell columns is an inherent property of the battery cell, and can be obtained by direct query. For example, the distance between battery cell columns is stored in a storage medium in advance and can be read directly from the storage medium. The internal resistance of the energy storage component is closely related to temperature. In the embodiment of the present application, the internal resistance of the energy storage component is determined based on the internal resistance of multiple battery cells, and the internal resistance of the battery cell is determined based on the electrode temperature of the battery cell. The average temperature of the battery is determined based on the electrode temperature of multiple battery cells. The temperature difference gradient between the battery cell poles is used to indicate the degree of uneven heat generation inside the energy storage component. Excessive temperature gradient may cause local lithium precipitation or electrolyte drying.

[0070] The following is divided into several parts to describe the method of determining the temperature difference gradient between battery cell poles, the internal resistance of the energy storage assembly and the average battery temperature based on the distance between battery cell poles and the electrode temperature of each battery cell in the above embodiment.

[0071] In the first part, the method of determining the temperature difference gradient between the battery cell poles is explained.

[0072] In a possible implementation, for any battery cell among the multiple battery cells, the controller subtracts the positive electrode temperature from the negative electrode temperature of the battery cell and divides the result by the inter-battery cell column distance of the battery cell to obtain the inter-battery cell column temperature difference gradient of the battery cell.

[0073] The second part explains how to determine the internal resistance of the energy storage component.

[0074] In one possible implementation, for any battery cell among the multiple battery cells, the controller determines the average of the positive and negative electrode temperatures of the battery cell as the battery cell temperature of the battery cell. Based on the battery cell temperature, the controller determines the internal resistance of the battery cell. Based on the internal resistances and connection configurations of the multiple battery cells, the controller determines the contents of the energy storage assembly.

[0075] The connection modes include parallel and series, and there are corresponding methods for determining internal resistance under parallel and series connections, which are not limited in the present embodiment. The corresponding relationship between the internal resistance of the battery cell and the battery cell temperature is set by technicians based on actual conditions and is not limited in the present embodiment.

[0076] Part III describes the method for determining the average battery temperature.

[0077] In one possible embodiment, for any battery cell among the plurality of battery cells, the controller determines the average of the positive electrode temperature and the negative electrode temperature of the battery cell as the battery cell temperature of the battery cell. The controller determines the average of the battery cell temperatures of the plurality of battery cells as the battery average temperature.

[0078] The following describes how to obtain the parameters of the heat dissipation component.

[0079] In one possible implementation, the controller obtains surface temperatures at multiple locations on the heat sink surface using a temperature sensor. Based on the surface temperatures at the multiple locations on the heat sink surface, the controller determines the standard deviation of the heat sink surface temperature distribution. The controller obtains the cooling fluid flow rate using a flow rate sensor within the cooling pipe. The controller obtains the cooling pipe pressure using a pressure sensor within the cooling pipe. Based on the cooling pipe pressures at multiple times, the controller determines the cooling pipe pressure change rate. The controller determines the cooling fluid viscosity coefficient based on the cooling fluid type and cooling fluid temperature.

[0080] The heat dissipation fluid flows through the heat dissipation pipes, thereby achieving heat transfer. The type of heat dissipation fluid is selected by technicians based on actual conditions and is not limited in this embodiment of the present application. The viscosity of the heat dissipation fluid is primarily determined by the type of heat dissipation fluid, but is also affected by the heat dissipation fluid temperature, which is detected by a temperature sensor within the heat dissipation pipe. For example, the controller queries the heat dissipation fluid type to obtain a baseline heat dissipation fluid viscosity coefficient. Based on the heat dissipation fluid temperature, the controller determines a viscosity correction factor. The controller multiplies the baseline heat dissipation fluid viscosity coefficient by the viscosity correction factor to obtain the heat dissipation fluid viscosity coefficient. The correspondence between the heat dissipation fluid type and the baseline heat dissipation fluid viscosity coefficient is set by technicians based on actual conditions, and the correspondence between the viscosity correction factor and the heat dissipation fluid temperature is set by technicians based on actual conditions and is not limited in this embodiment of the present application. The standard deviation of the heat sink surface temperature distribution is used to measure heat dissipation uniformity. The larger the standard deviation, the lower the heat dissipation efficiency. The heat dissipation pipe pressure change rate is used to indicate the dynamic response capability of the pump power adjustment. The pump is the component in the heat dissipation assembly that drives the heat dissipation fluid flow.

[0081] The following describes how to obtain the working parameters.

[0082] In one possible implementation, the controller obtains operating parameters of the power-consuming device through a device management module of the power-consuming device. The controller obtains output electrical parameters of the target uninterruptible power supply through an electrical parameter management module of the target uninterruptible power supply. The controller also obtains a fault log of the target uninterruptible power supply from a storage medium.

[0083] The following describes how to obtain inverter parameters.

[0084] In one possible implementation, the controller obtains the inverter output voltage via a voltage sensor. Based on the output voltage, the controller determines the effective values ​​of the multiple harmonic voltages and the effective value of the fundamental voltage. The controller obtains the IGBT temperature via a temperature sensor. Based on the IGBT temperature, the controller determines the temperature compensation coefficient.

[0085] Since the IGBT is the core component of the inverter, in the embodiments of the present application, the inverter temperature is represented by the IGBT temperature. The correspondence between the IGBT temperature and the temperature compensation coefficient is set by technicians based on actual conditions and is not limited in the embodiments of the present application.

[0086] 302. The controller determines a battery health status of the energy storage component based on the electrolyte parameters and the energy storage component parameters, where the battery health status is used to indicate the health level.

[0087] The energy storage component's state of health (SOH) indicates its health. If its SOH is poor, the amount of energy it can store decreases, potentially preventing it from meeting power demands. Therefore, in this embodiment, determining the SOH of the energy storage component is a key aspect of monitoring the target uninterruptible power supply. In related art, assessing SOH is difficult. In this embodiment, SOH is assessed using electrolyte parameters and energy storage component parameters, aiming to obtain a more accurate SOH.

[0088] In one possible embodiment, the electrolyte parameters include the electrolyte density change rate, the electrolyte temperature, and the electrolyte material characteristic coefficient. The energy storage assembly parameters include the temperature gradient between battery cell poles, the distance between battery cell poles, the internal resistance, and the average battery temperature. The controller determines a first state-of-health parameter based on the electrolyte density change rate, the electrolyte temperature, the average battery temperature, and the first sub-coefficient of the electrolyte material characteristic coefficient. The first sub-coefficient is used to represent the attenuation characteristics of the electrolyte related to the electrolyte density. The controller determines a second state-of-health parameter based on the temperature gradient between battery cell poles, the distance between battery cell poles, the internal resistance, the average battery temperature, and the second sub-coefficient of the electrolyte material characteristic coefficient. The second sub-coefficient is used to represent the attenuation characteristics of the electrolyte related to the temperature difference between battery cell poles. The controller determines the battery state of health of the energy storage assembly based on the first and second state-of-health parameters.

[0089] The first health parameter represents the health of the energy storage component in the electrolyte dimension, and the second health parameter represents the health of the energy storage component in the temperature dimension. The first and second sub-coefficients are calibrated by technicians based on actual conditions and are not limited in this embodiment.

[0090] In order to explain the above embodiment more clearly, the above embodiment will be described in several parts below.

[0091] In the first part, a controller determines a first health status parameter based on the electrolyte density change rate, the electrolyte temperature, the average battery temperature, and a first sub-coefficient of the electrolyte material characteristic coefficient.

[0092] In one possible implementation, the controller determines a first state-of-health correction coefficient based on the electrolyte density change rate and the electrolyte temperature. The controller determines a second state-of-health correction coefficient based on the electrolyte temperature and the average battery temperature. The controller multiplies the electrolyte density change rate, the first sub-coefficient, the first state-of-health correction coefficient, and the second state-of-health correction coefficient to obtain the first state-of-health parameter.

[0093] Among them, the first health state correction coefficient is a coefficient for correcting the health state from two dimensions: electrolyte density change and electrolyte temperature. The second health state correction coefficient is a coefficient for correcting the health state from two dimensions: electrolyte temperature and battery average temperature.

[0094] In the above embodiment, the first health state correction coefficient is determined using the electrolyte density change rate and the electrolyte temperature, and the second health state correction coefficient is determined using the electrolyte temperature and the average battery temperature. The first health state correction coefficient and the second health state correction coefficient can be used to perform corrections subsequently to improve the accuracy of the determined first health state parameter.

[0095] For example, the controller substitutes the electrolyte density change rate and the electrolyte temperature into the first relationship data to obtain the first health state correction coefficient. The controller substitutes the electrolyte temperature and the average battery temperature into the second relationship data to obtain the second health state correction coefficient. The controller multiplies the electrolyte density change rate, the first sub-coefficient, the first health state correction coefficient, and the second health state correction coefficient to obtain the first health state parameter.

[0096] Among them, the first relationship data and the second relationship data are both relationship functions. The first relationship data is used to express the correspondence between the electrolyte density change rate and the electrolyte temperature and the first health state correction coefficient, and the second relationship data is used to express the correspondence between the electrolyte temperature and the average battery temperature and the second health state correction coefficient. The first relationship data and the second relationship data are calibrated by technicians based on experimental results, or are obtained by fitting experimental data. The embodiments of the present application do not limit this.

[0097] It should be noted that, in the above process of determining the first health state parameter, the parameters used are dimensionless, and the dimension of the first health state parameter finally obtained is the same as that of the battery health state.

[0098] In the second part, the controller determines a second health status parameter based on the temperature difference gradient between the battery cell poles, the distance between the battery cell poles, the internal resistance, the average temperature of the battery and the second sub-coefficient of the electrolyte material characteristic coefficient.

[0099] In one possible implementation, the controller determines a third state-of-health parameter based on the temperature gradient between the battery cell poles, the internal resistance, and the average battery temperature. The controller determines a third state-of-health correction coefficient based on the internal resistance and the distance between the battery cell poles. The controller multiplies the third state-of-health parameter, the second sub-coefficient, and the third state-of-health correction coefficient to obtain the second state-of-health parameter.

[0100] In this way, the temperature difference gradient between the battery cell poles, the internal resistance, and the average temperature of the battery are used to determine the third health status parameter. Subsequently, the third health status correction coefficient is determined based on the internal resistance and the distance between the battery cell poles. Finally, the second sub-coefficient and the third health status correction coefficient are used to correct the third health status parameter, thereby obtaining a more accurate second health status parameter.

[0101] For example, the controller multiplies the internal resistance by the preset power of the average battery temperature to obtain a first intermediate parameter. The controller divides the temperature gradient between the battery cell poles by the first intermediate parameter to obtain a third health state parameter. The controller substitutes the internal resistance and the distance between the battery cell poles into third relationship data to obtain a third health state correction coefficient. The controller multiplies the third health state parameter, the second sub-coefficient, and the third health state correction coefficient to obtain the second health state parameter.

[0102] The preset power is a hyperparameter, which is calibrated by technicians based on experimental results. Generally speaking, the preset power is 0.5.

[0103] It should be noted that, in the above process of determining the second health state parameter, the parameters used are dimensionless, and the dimension of the second health state parameter finally obtained is the same as the battery health state.

[0104] Part three: The controller determines the battery health state of the energy storage component based on the first health state parameter and the second health state parameter.

[0105] In a possible implementation, the controller adds the first health state parameter and the second health state parameter to obtain the battery health state of the energy storage component.

[0106] The first health state parameter is used to represent the health state of the energy storage component in the electrolyte dimension, and the second health state parameter is used to represent the health state of the energy storage component in the temperature dimension. By directly adding the first health state parameter and the second health state parameter, the battery health state of the energy storage component can be assessed from the electrolyte dimension and the temperature dimension, with high accuracy. In the embodiment of the present application, the battery health state is expressed as a percentage, and the battery health state value range is (0% to 100%). Generally speaking, a higher battery health state indicates a healthier energy storage component and a closer storage capacity of the energy storage component; a lower battery health state indicates a worse storage component and a lower storage capacity.

[0107] It should be noted that the above-mentioned method of determining the first health status parameter and the second health status parameter, as well as the method of finally obtaining the battery health status, have been repeatedly verified by the applicant during the experiment. According to the experimental results, the battery health status finally obtained is more accurate than the battery health status determined in the relevant technology. The specific experimental method is to fully charge the energy storage component, calculate its discharge capacity, and compare the discharge capacity with the charge capacity to obtain the actual battery health status. After analysis, the applicant believes that the reason why the method of determining the battery health status provided in this application is more accurate is because it uses more basic parameters, such as the above-mentioned electrolyte density change rate, the temperature difference gradient between the battery cell poles, and the distance between the battery cell poles, which improve the accuracy of the battery health status.

[0108] In the above step 302, the real-time measured data is used to monitor the battery health status of the energy storage component. Battery health status monitoring is an important part of the monitoring method provided in this application.

[0109] 303. The controller determines a power supply operating state of the target uninterruptible power supply based on the heat dissipation component parameter, the operating parameter, and the inverter parameter, where the power supply operating state is used to indicate an operating condition.

[0110] Among them, the power supply working status is the core parameter that reflects the actual situation of the target uninterruptible power supply. In the embodiment of the present application, the power supply working status of the target uninterruptible power supply is determined in combination with the heat dissipation component parameters, operating parameters and inverter parameters, so that the evaluation of the power supply working status is as comprehensive as possible, thereby improving the monitoring effect of the target uninterruptible power supply.

[0111] In one possible implementation, the heat dissipation component parameters include a heat sink surface temperature distribution standard deviation, a heat dissipation fluid flow rate, a heat dissipation pipeline pressure change rate, and a heat dissipation fluid viscosity coefficient. The operating parameters include electrical equipment operating parameters, output electrical parameters, and fault logs. The inverter parameters include multiple harmonic voltage RMS values, a fundamental voltage RMS value, a temperature compensation coefficient, and IGBT temperature. Based on the heat sink surface temperature distribution standard deviation, the heat dissipation fluid flow rate, the heat dissipation pipeline pressure change rate, and the heat dissipation fluid viscosity coefficient, the controller determines a dynamic response parameter of the heat dissipation component of the target uninterruptible power supply. The dynamic response parameter is used to represent the dynamic response speed of the heat dissipation component. The controller determines operating status description information based on the electrical equipment operating parameters, the output electrical parameters, and the fault log. The controller determines the inverter ripple voltage harmonic distortion rate of the inverter of the target uninterruptible power supply based on the multiple harmonic voltage RMS values, the fundamental voltage RMS value, the temperature compensation coefficient, and the IGBT temperature. The controller determines the power supply working state of the target uninterruptible power supply based on the dynamic response parameter, the working state description information and the inverter ripple voltage harmonic distortion rate.

[0112] The dynamic response parameters include the dynamic response time. The shorter the dynamic response time, the faster the heat sink can respond to temperature changes. The longer the dynamic response time, the longer it takes the heat sink to respond to temperature changes, affecting the heat dissipation effect. The operating status description information is a natural language description of the operating status of the electrical equipment, making it easier for technicians to review and for the controller to process. Ripple voltage refers to the periodic fluctuations in the output voltage of a DC power supply, typically caused by changes in the AC input power supply or load. The inverter ripple voltage harmonic distortion rate is an important indicator for measuring the degree of waveform distortion, reflecting the deviation of the actual waveform from the ideal sinusoidal waveform. In related art, for the voltage or current output by the inverter, the inverter ripple voltage harmonic distortion rate represents the ratio of the root mean square value of all harmonic components (the effective value of the harmonic voltage) to the root mean square value of the fundamental component (the effective value of the fundamental voltage). In the embodiments of the present application, a temperature compensation coefficient and IGBT temperature are added to determine the inverter ripple voltage harmonic distortion, achieving higher accuracy.

[0113] In order to explain the above embodiment more clearly, the above embodiment will be described in several parts below.

[0114] In the first part, the controller determines the dynamic response parameters of the heat dissipation component of the target uninterruptible power supply based on the standard deviation of the heat sink surface temperature distribution, the heat dissipation fluid flow rate, the heat dissipation pipeline pressure change rate and the heat dissipation fluid viscosity coefficient.

[0115] In one possible implementation, the controller determines a heat dissipation effect parameter based on the standard deviation of the heat sink surface temperature distribution and the heat dissipation fluid flow rate. The controller also determines a heat dissipation response parameter based on the heat dissipation pipeline pressure change rate and the heat dissipation fluid viscosity coefficient. Based on the heat dissipation effect parameter and the heat dissipation response parameter, the controller determines a dynamic response parameter of the heat dissipation component of the target uninterruptible power supply.

[0116] For example, there are multiple standard deviations of the heat sink surface temperature distribution, and one standard deviation of the heat sink surface temperature distribution corresponds to one acquisition time. There are also multiple heat sink flow rates, and one heat sink flow rate corresponds to one acquisition time. The number of standard deviations of the heat sink surface temperature distribution is the same as the number of heat sink flow rates, and one standard deviation of the heat sink surface temperature distribution corresponds to one heat sink flow rate at the same acquisition time. The controller divides each heat sink surface temperature distribution standard deviation by the corresponding heat sink flow rate to obtain a second intermediate parameter. The controller determines the average of the multiple second intermediate parameters as the heat dissipation effect parameter. The controller multiplies the heat dissipation line pressure change rate by the heat dissipation fluid viscosity coefficient to obtain a heat dissipation response parameter. The controller adds the heat dissipation effect parameter and the heat dissipation response parameter to obtain the dynamic response parameter of the heat dissipation component of the target uninterruptible power supply.

[0117] For example, the controller determines the dynamic response parameter by the following formula (1). (1) Among them, Indicates the dynamic response parameter, which is actually the dynamic response time. It represents the standard deviation of the heat sink surface temperature distribution and the quantity of the heat dissipation fluid flow rate, which is a positive integer. Indicates the The standard deviation of the surface temperature distribution of the heat sink. Indicates the The cooling fluid flow rate. Indicates the viscosity coefficient of the cooling fluid. Indicates the heat dissipation line pressure. Indicates the rate of change of heat dissipation line pressure.

[0118] It should be noted that, in the above process of determining the dynamic response parameters, the parameters used are dimensionless, and the dimension of the dynamic response parameters finally obtained is time.

[0119] In the second part, the controller determines the working status description information based on the working parameters of the electrical equipment, the output electrical parameters and the fault log.

[0120] In one possible implementation, the controller determines baseline operating status description information of the target uninterruptible power supply based on the operating parameters of the power-consuming device and the output power parameters. The controller also determines fault description information based on the fault log. The controller also determines the operating status description information based on the baseline operating status description information and the fault description information.

[0121] The operating parameters of the electrical equipment include input electrical parameters and demand electrical parameters of the electrical equipment. The input electrical parameters include input current, input voltage and input power, and the demand electrical parameters include demand current, demand voltage and demand power.

[0122] For example, the controller determines baseline operating state description information of the target uninterruptible power supply based on first electrical parameter difference information between the input electrical parameter and the output electrical parameter, and second electrical parameter difference information between the input electrical parameter and the required electrical parameter. The controller performs feature extraction on the fault log to obtain fault log features of the fault log. The controller determines the fault description information based on the fault log features. The controller performs feature extraction on the baseline operating state description information and the fault description information, respectively, to obtain a first description feature of the baseline operating state description information and a second description feature of the fault description information. The controller fuses the first description feature and the second description feature to obtain a fused description feature. The controller determines the operating state description information based on the fused description feature.

[0123] The first electrical parameter difference information can represent the deviation between input and output, and the second electrical parameter difference information can represent the deviation between input and demand.

[0124] For example, the controller inputs the first electrical parameter difference information between the input electrical parameter and the output electrical parameter, and the second electrical parameter difference information between the input electrical parameter and the required electrical parameter, into a target prompt text template to obtain target prompt text. The controller then inputs the target prompt text into a target language model and, using the target language model, encodes the target prompt text based on an attention mechanism to obtain prompt text features of the target prompt text. The controller then uses the target language model to perform multiple rounds of iterative decoding on the prompt text features based on an attention mechanism to obtain the baseline working state description information. The controller then inputs the fault log into the target language model and, using the target language model, encodes the fault log based on an attention mechanism to obtain fault log features of the fault log. The controller then uses the target language model to perform multiple rounds of iterative decoding on the fault log features based on an attention mechanism to obtain the fault description information. The controller then inputs the baseline working state description information and the fault description information into the target language model and, using the target language model, performs feature encoding on the baseline working state description information and the fault description information based on an attention mechanism to obtain first description features of the baseline working state description information and second description features of the fault description information. The controller performs weighted fusion of the first description feature and the second description feature to obtain a fused description feature. The controller performs multiple rounds of iterative decoding on the fused description feature based on the target language model and an attention mechanism to obtain the working state description information.

[0125] Among them, the base model of the target language model is a large language model, and the target language model has the ability to process and generate multimodal data. The embodiment of the present application does not limit the type and structure of the target language model. The target prompt text template is a prompt text template configured by the technician to generate the baseline working state description information. For example, the target prompt text template is "Please combine the given XXX (the filling position of the first electrical parameter difference information) and YYY (the filling position of the second electrical parameter difference information) to generate the baseline working state description information, where XXX represents the difference information between the input electrical parameters of the electrical device and the output electrical parameters of the target uninterruptible power supply, and YYY represents the difference information between the input electrical parameters of the electrical device and the required electrical parameters of the electrical device. The baseline working state description information is used to describe the baseline working state of the target uninterruptible model and is in the form of natural language." Of course, the above-mentioned target prompt text template is only an example. In actual use, it can be adjusted or redesigned according to actual conditions. The embodiment of the present application does not limit this. In addition, the weights of weighted fusion are set by the technician according to actual conditions. The embodiment of the present application does not limit this.

[0126] In the third part, the controller determines the inverter ripple voltage harmonic distortion rate of the inverter of the target uninterruptible power supply based on the multiple harmonic voltage effective values, the fundamental voltage effective value, the temperature compensation coefficient and the IGBT temperature.

[0127] In one possible implementation, the controller determines a reference voltage change rate based on the multiple harmonic voltage RMS values ​​and the fundamental voltage RMS value. The controller also determines a temperature correction coefficient based on the temperature compensation coefficient and the IGBT temperature. Based on the reference voltage change rate and the temperature correction coefficient, the controller determines an inverter ripple voltage harmonic distortion rate of the inverter of the target uninterruptible power supply.

[0128] Among them, the increase in IGBT temperature will aggravate the switching transient oscillation, resulting in an increase in harmonic distortion. The temperature compensation coefficient is used to correct the increase in IGBT switching loss caused by the temperature increase. Generally speaking, the temperature compensation coefficient = 0.05K −1 , it means that the harmonic amplitude increases by 5% for every 10°C increase in IGBT temperature.

[0129] For example, the controller divides the effective value of each harmonic voltage by the effective value of the fundamental voltage to obtain multiple third intermediate parameters. The controller then adds the squares of the multiple third intermediate parameters and takes the square root to obtain the reference voltage change rate. The controller determines a temperature correction coefficient based on a temperature compensation coefficient and the IGBT temperature. The controller then multiplies the reference voltage change rate by the temperature correction coefficient to obtain the inverter ripple voltage harmonic distortion rate of the inverter of the target uninterruptible power supply.

[0130] For example, the controller determines the harmonic distortion rate of the inverter ripple voltage by the following formula (2). (2) Among them, Indicates the harmonic distortion rate of the inverter ripple voltage. Indicates the The effective value of the harmonic voltage. Indicates the effective value of the fundamental voltage. Indicates the temperature compensation coefficient. Indicates the IGBT temperature.

[0131] It should be noted that, in the above process of determining the harmonic distortion rate of the inverter ripple voltage, the parameters used are dimensionless, and the dimension of the inverter ripple voltage harmonic distortion rate finally obtained is 1.

[0132] In the fourth part, the controller determines the power supply working state of the target uninterruptible power supply based on the dynamic response parameter, the working state description information and the inverter ripple voltage harmonic distortion rate.

[0133] In a possible implementation, the controller combines the dynamic response parameter, the operating state description information, and the inverter ripple voltage harmonic distortion rate to obtain the power supply operating state of the target uninterruptible power supply.

[0134] 304. The controller determines a monitoring result of the target uninterruptible power supply based on the battery health status and the power supply operating status. The monitoring result is used to indicate whether an abnormality exists.

[0135] Among them, the monitoring result is determined based on the battery health status and the power supply working status, that is, in the embodiment of the present application, the monitoring of the target uninterruptible power supply is ultimately achieved by monitoring the battery health status and the power supply working status.

[0136] In a possible implementation, the controller integrates the battery health status and the power supply operating status to obtain a monitoring result of the target uninterruptible power supply.

[0137] Optionally, after step 304 , the following step 305 can also be performed.

[0138] 305. The controller controls the target uninterruptible power supply based on a monitoring result of the target uninterruptible power supply.

[0139] In one possible implementation, if the monitoring result indicates that the target uninterruptible power supply is not abnormal, the controller controls the target uninterruptible power supply to operate normally. If the monitoring result indicates that the target uninterruptible power supply is abnormal, the controller controls the target uninterruptible power supply to issue an alarm based on the type of abnormality of the target uninterruptible power supply, thereby alerting technical personnel to handle the problem.

[0140] The monitoring result indicates that the target uninterruptible power supply has an abnormality, including at least one of the following: a battery health state less than a preset health state, a dynamic response parameter greater than a response parameter threshold, the operating state description information indicating an abnormal operating state, and the inverter ripple voltage harmonic distortion rate greater than a distortion rate threshold. The preset health state, response parameter threshold, and distortion rate threshold are set by technicians based on actual conditions and are not limited in this embodiment of the present application. Accordingly, the abnormality types include abnormal battery health state, abnormal dynamic response parameter, abnormal operating state, and abnormal inverter ripple voltage harmonic distortion rate.

[0141] It should be noted that the above description uses the controller as the execution subject as an example. In other possible implementations, the server can also be the execution subject. That is, the controller executes step 301 to obtain data, sends the obtained data to the server, and the server executes steps 302-304. The server returns the obtained monitoring results to the controller, and the controller executes step 305.

[0142] All of the above optional technical solutions can be combined in any way to form optional embodiments of the present application, and will not be described in detail here.

[0143] Through the technical solution provided by the embodiment of the present application, when the target uninterruptible power supply is in a loaded state, in response to the monitoring instruction of the target uninterruptible power supply, the electrolyte parameters and energy storage component parameters of the energy storage component of the target uninterruptible power supply are obtained, and the heat dissipation component parameters, operating parameters and inverter parameters of the uninterruptible power supply are obtained at the same time. The battery health status is determined using the electrolyte parameters and energy storage component parameters, and the power supply working status is determined using the heat dissipation component parameters, operating parameters and inverter parameters, thereby realizing the monitoring of the target uninterruptible power supply in two dimensions. In combination with the battery health status and the power supply working status, the monitoring results of the target uninterruptible power supply are determined, thereby completing the monitoring of the target uninterruptible power supply. Due to the combination of data from multiple dimensions and targeted data processing methods, the accuracy of the monitoring results obtained is relatively high.

[0144] Figure 4 This is a schematic diagram of a power data monitoring and analysis system for an uninterruptible power supply provided in an embodiment of the present application. Figure 4 The system includes: a parameter acquisition module 401, a health status determination module 402, a working status determination module 403 and a monitoring result determination module 404.

[0145] Parameter acquisition module 401 is configured to, when a target uninterruptible power supply is in a loaded state, obtain electrolyte parameters and energy storage component parameters of an energy storage component of the target uninterruptible power supply, as well as heat dissipation component parameters, operating parameters, and inverter parameters of the target uninterruptible power supply in response to a monitoring instruction for the target uninterruptible power supply, where the energy storage component is a lithium-ion battery.

[0146] The health status determination module 402 is used to determine the battery health status of the energy storage component based on the electrolyte parameters and the energy storage component parameters. The battery health status is used to indicate the health level.

[0147] The working state determining module 403 is configured to determine the working state of the target uninterruptible power supply based on the heat dissipation component parameter, the working parameter and the inverter parameter, where the working state of the power supply is used to indicate the working condition.

[0148] The monitoring result determination module 404 is configured to determine a monitoring result of monitoring the target uninterruptible power supply based on the battery health status and the power supply operating status, where the monitoring result indicates whether an abnormality exists.

[0149] In one possible embodiment, the electrolyte parameters include the electrolyte density change rate, the electrolyte temperature, and the electrolyte material characteristic coefficient. The energy storage assembly parameters include the temperature gradient between battery cell poles, the distance between battery cell poles, the internal resistance, and the average battery temperature. The health status determination module 402 is configured to determine a first health status parameter based on the electrolyte density change rate, the electrolyte temperature, the average battery temperature, and a first sub-coefficient in the electrolyte material characteristic coefficient. The first sub-coefficient is used to represent the attenuation characteristics of the electrolyte related to the electrolyte density. The second health status parameter is determined based on the temperature gradient between battery cell poles, the distance between battery cell poles, the internal resistance, the average battery temperature, and a second sub-coefficient in the electrolyte material characteristic coefficient. The second sub-coefficient is used to represent the attenuation characteristics of the electrolyte related to the temperature difference between battery cell poles. The battery health status of the energy storage assembly is determined based on the first health status parameter and the second health status parameter.

[0150] In one possible implementation, the health status determination module 402 is configured to determine a first health status correction coefficient based on the electrolyte density change rate and the electrolyte temperature. A second health status correction coefficient is determined based on the electrolyte temperature and the average battery temperature. The first health status parameter is obtained by multiplying the electrolyte density change rate, the first sub-coefficient, the first health status correction coefficient, and the second health status correction coefficient.

[0151] In one possible implementation, the health status determination module 402 is configured to determine a third health status parameter based on the temperature gradient between the battery cell poles, the internal resistance, and the average battery temperature. A third health status correction coefficient is determined based on the internal resistance and the distance between the battery cell poles. The second health status parameter is obtained by multiplying the third health status parameter, the second sub-coefficient, and the third health status correction coefficient.

[0152] In one possible implementation, the heat dissipation component parameters include a heat sink surface temperature distribution standard deviation, a heat dissipation fluid flow rate, a heat dissipation pipeline pressure change rate, and a heat dissipation fluid viscosity coefficient. The operating parameters include electrical equipment operating parameters, output electrical parameters, and fault logs. The inverter parameters include multiple harmonic voltage RMS values, a fundamental voltage RMS value, a temperature compensation coefficient, and an IGBT temperature. The operating state determination module 403 is configured to determine a dynamic response parameter of the heat dissipation component of the target uninterruptible power supply based on the heat sink surface temperature distribution standard deviation, the heat dissipation fluid flow rate, the heat dissipation pipeline pressure change rate, and the heat dissipation fluid viscosity coefficient. The dynamic response parameter represents the dynamic response speed of the heat dissipation component. Operating state description information is determined based on the electrical equipment operating parameters, the output electrical parameters, and the fault log. The inverter ripple voltage harmonic distortion rate of the inverter of the target uninterruptible power supply is determined based on the multiple harmonic voltage RMS values, the fundamental voltage RMS value, the temperature compensation coefficient, and the IGBT temperature. The power supply operating state of the target uninterruptible power supply is determined based on the dynamic response parameter, the operating state description information, and the inverter ripple voltage harmonic distortion rate.

[0153] In one possible implementation, the operating state determination module 403 is configured to determine a heat dissipation effect parameter based on the standard deviation of the heat sink surface temperature distribution and the heat dissipation fluid flow rate. Determine a heat dissipation response parameter based on the heat dissipation pipeline pressure change rate and the heat dissipation fluid viscosity coefficient. Determine dynamic response parameters of the heat dissipation component of the target uninterruptible power supply based on the heat dissipation effect parameter and the heat dissipation response parameter.

[0154] In one possible implementation, the operating status determination module 403 is configured to determine baseline operating status description information of the target uninterruptible power supply based on the operating parameters of the power-consuming device and the output power parameters, determine fault description information based on the fault log, and determine the operating status description information based on the baseline operating status description information and the fault description information.

[0155] In one possible implementation, the operating state determination module 403 is configured to determine a reference voltage change rate based on the multiple harmonic voltage RMS values ​​and the fundamental voltage RMS value, determine a temperature correction coefficient based on the temperature compensation coefficient and the IGBT temperature, and determine an inverter ripple voltage harmonic distortion rate of the inverter of the target uninterruptible power supply based on the reference voltage change rate and the temperature correction coefficient.

[0156] In a possible implementation, the monitoring result determination module 404 is configured to integrate the battery health status and the power supply operating status to obtain a monitoring result of the target uninterruptible power supply.

[0157] It should be noted that the above-described embodiment of the power data monitoring and analysis system for an uninterruptible power supply (UPS) is merely an example of the division of the aforementioned functional modules during monitoring. In actual applications, the aforementioned functions can be assigned to different functional modules as needed, i.e., the internal structure of the computer device can be divided into different functional modules to perform all or part of the functions described above. Furthermore, the power data monitoring and analysis system for an uninterruptible power supply (UPS) provided in the above-described embodiment and the power data monitoring and analysis method for an uninterruptible power supply (UPS) provided in the above-described embodiment are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be further described here.

[0158] Through the technical solution provided by the embodiment of the present application, when the target uninterruptible power supply is in a loaded state, in response to the monitoring instruction of the target uninterruptible power supply, the electrolyte parameters and energy storage component parameters of the energy storage component of the target uninterruptible power supply are obtained, and the heat dissipation component parameters, operating parameters and inverter parameters of the uninterruptible power supply are obtained at the same time. The battery health status is determined using the electrolyte parameters and energy storage component parameters, and the power supply working status is determined using the heat dissipation component parameters, operating parameters and inverter parameters, thereby realizing the monitoring of the target uninterruptible power supply in two dimensions. In combination with the battery health status and the power supply working status, the monitoring results of the target uninterruptible power supply are determined, thereby completing the monitoring of the target uninterruptible power supply. Due to the combination of data from multiple dimensions and targeted data processing methods, the accuracy of the monitoring results obtained is relatively high.

[0159] Figure 5 This is a schematic diagram of the structure of a controller provided in an embodiment of the present application. The controller 500 may have relatively large differences due to different configurations or performances, and may include one or more processors (Central Processing Units, CPU) 501 and one or more memories 502, wherein the one or more memories 502 store at least one computer program, and the at least one computer program is loaded and executed by the one or more processors 501 to implement the methods provided in the above-mentioned various method embodiments. Of course, the controller 500 may also have components such as a wired or wireless network interface, a keyboard, and an input / output interface for input and output. The controller 500 may also include other components for implementing device functions, which will not be described in detail here.

[0160] In an exemplary embodiment, a computer-readable storage medium is also provided, such as a memory including a computer program. The computer program can be executed by a processor to implement the power data monitoring and analysis method for an uninterruptible power supply in the above-described embodiment. For example, the computer-readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, or an optical data storage device.

[0161] In an exemplary embodiment, a computer program product or computer program is also provided, which includes a program code, which is stored in a computer-readable storage medium. A processor of a computer device reads the program code from the computer-readable storage medium, and the processor executes the program code, so that the computer device performs the above-mentioned power data monitoring and analysis method for an uninterruptible power supply.

[0162] In some embodiments, the computer program involved in the embodiments of the present application may be deployed and executed on a computer device, or on multiple computer devices located at one location, or on multiple computer devices distributed at multiple locations and interconnected through a communication network. Multiple computer devices distributed at multiple locations and interconnected through a communication network may constitute a blockchain system.

[0163] Those skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware, or may be accomplished by a program to instruct the relevant hardware, and the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a disk or an optical disk, etc.

[0164] The above are only optional embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should be included in the scope of protection of the present application.

Claims

1. A power data monitoring and analysis method for an uninterruptible power supply, characterized in that: The method comprises: When a target uninterruptible power supply is in a loaded state, in response to a monitoring instruction for the target uninterruptible power supply, obtaining electrolyte parameters and energy storage component parameters of an energy storage component of the target uninterruptible power supply, obtaining heat dissipation component parameters, operating parameters, and inverter parameters of the target uninterruptible power supply, wherein the energy storage component is a lithium-ion battery; Determining a battery health state of the energy storage assembly based on the electrolyte parameters and the energy storage assembly parameters, where the battery health state is used to indicate the health level, the electrolyte parameters include electrolyte density change rate, electrolyte temperature, and electrolyte material characteristic coefficient, and the energy storage assembly parameters include temperature difference gradient between battery cell poles, distance between battery cell poles, internal resistance, and average battery temperature; The determining of the battery health status of the energy storage component based on the electrolyte parameter and the energy storage component parameter includes: Based on the electrolyte density change rate, the electrolyte temperature, the average battery temperature and the first sub-coefficient of the electrolyte material characteristic coefficient, a first health state parameter is determined, the first sub-coefficient is used to represent the attenuation characteristics of the electrolyte related to the electrolyte density, and the first health state parameter is used to represent the health state of the electrolyte dimension energy storage component; based on the temperature difference gradient between the battery cell poles, the distance between the battery cell poles, the internal resistance, the average battery temperature and the second sub-coefficient of the electrolyte material characteristic coefficient, a second health state parameter is determined, the second sub-coefficient is used to represent the attenuation characteristics related to the temperature difference between the electrolyte and the battery cell poles, and the second health state parameter is used to represent the health state of the temperature dimension energy storage component; the first health state parameter and the second health state parameter are added to obtain the battery health state of the energy storage component; The determining a first health status parameter based on the electrolyte density change rate, the electrolyte temperature, the battery average temperature, and a first sub-coefficient of the electrolyte material characteristic coefficient includes: Substituting the electrolyte density change rate and the electrolyte temperature into first relationship data to obtain a first health state correction coefficient, which is a coefficient for correcting the health state from two dimensions: electrolyte density change and electrolyte temperature; substituting the electrolyte temperature and the average battery temperature into second relationship data to obtain a second health state correction coefficient, which is a coefficient for correcting the health state from two dimensions: electrolyte temperature and average battery temperature; multiplying the electrolyte density change rate, the first sub-coefficient, the first health state correction coefficient, and the second health state correction coefficient to obtain the first health state parameter, the first relationship data being used to represent the corresponding relationship between the electrolyte density change rate and the electrolyte temperature and the first health state correction coefficient, and the second relationship data being used to represent the corresponding relationship between the electrolyte temperature and the average battery temperature and the second health state correction coefficient; The determining of the second health status parameter based on the temperature difference gradient between the battery cell poles, the distance between the battery cell poles, the internal resistance, the average battery temperature, and the second sub-coefficient of the electrolyte material characteristic coefficient includes: Multiplying the internal resistance by a preset power of the average battery temperature to obtain a first intermediate parameter; dividing the temperature difference gradient between the battery cell poles by the first intermediate parameter to obtain a third health state parameter; substituting the internal resistance and the distance between the battery cell poles into third relationship data to obtain a third health state correction coefficient; and multiplying the third health state parameter, the second sub-coefficient, and the third health state correction coefficient to obtain the second health state parameter; Determining a power supply operating state of the target uninterruptible power supply based on the heat dissipation component parameters, the operating parameters, and the inverter parameters, wherein the power supply operating state is used to indicate an operating condition; Based on the battery health status and the power supply operating status, a monitoring result of monitoring the target uninterruptible power supply is determined, where the monitoring result is used to indicate whether there is an abnormality.

2. The power data monitoring and analysis method for an uninterruptible power supply according to claim 1, characterized in that: There are multiple standard deviations of the heat sink surface temperature distribution, each standard deviation of the heat sink surface temperature distribution corresponds to one acquisition time. There are also multiple heat sink flow rates, each heat sink flow rate corresponds to one acquisition time. The number of standard deviations of the heat sink surface temperature distribution is the same as the number of heat sink flow rates, each standard deviation of the heat sink surface temperature distribution corresponds to one heat sink flow rate at the same acquisition time. The heat sink component parameters include the standard deviation of the heat sink surface temperature distribution, the heat sink flow rate, the heat sink pipeline pressure change rate, and the heat sink viscosity coefficient. The operating parameters include electrical equipment operating parameters, output electrical parameters, and fault logs. The inverter parameters include multiple harmonic voltage effective values, fundamental voltage effective values, temperature compensation coefficients, and IGBT temperatures. Determining the power supply operating status of the target uninterruptible power supply based on the heat sink component parameters, the operating parameters, and the inverter parameters includes: Determining the dynamic response parameters of the heat dissipation component of the target uninterruptible power supply based on the standard deviation of the heat sink surface temperature distribution, the heat dissipation fluid flow rate, the heat dissipation pipeline pressure change rate, and the heat dissipation fluid viscosity coefficient includes: Dividing the standard deviation of the surface temperature distribution of each heat sink by the corresponding heat dissipation fluid flow rate to obtain a second intermediate parameter; determining the average of the plurality of second intermediate parameters as a heat dissipation effect parameter; multiplying the heat dissipation pipeline pressure change rate by the heat dissipation fluid viscosity coefficient to obtain a heat dissipation response parameter; adding the heat dissipation effect parameter and the heat dissipation response parameter to obtain a dynamic response parameter of the heat dissipation component of the target uninterruptible power supply, wherein the dynamic response parameter is used to represent the dynamic response speed of the heat dissipation component; Determining working status description information based on the working parameters of the electrical equipment, the output electrical parameters, and the fault log; Dividing the effective value of each harmonic voltage by the effective value of the fundamental voltage to obtain a plurality of third intermediate parameters; summing the squares of the plurality of third intermediate parameters and taking the square root thereof to obtain a reference voltage change rate; determining, by a controller, a temperature correction coefficient based on a temperature compensation coefficient and the IGBT temperature; and multiplying the reference voltage change rate by the temperature correction coefficient to obtain an inverter ripple voltage harmonic distortion rate of the inverter of the target uninterruptible power supply; The dynamic response parameter, the working state description information, and the inverter ripple voltage harmonic distortion rate are spliced ​​together to obtain the power supply working state of the target uninterruptible power supply.

3. The power data monitoring and analysis method for an uninterruptible power supply according to claim 2, characterized in that: The operating parameters of the electrical equipment include input electrical parameters and demand electrical parameters of the electrical equipment, the input electrical parameters include input current, input voltage, and input power, and the demand electrical parameters include demand current, demand voltage, and demand electrical power. Determining the operating status description information based on the operating parameters of the electrical equipment, the output electrical parameters, and the fault log includes: Determining reference operating state description information of the target uninterruptible power supply based on first electrical parameter difference information between the input electrical parameter and the output electrical parameter, and second electrical parameter difference information between the input electrical parameter and the required electrical parameter; Performing feature extraction on the fault log to obtain a fault log feature of the fault log; Determining fault description information based on the fault log characteristics; Performing feature extraction on the reference working state description information and the fault description information respectively to obtain a first description feature of the reference working state description information and a second description feature of the fault description information; Fusing the first description feature and the second description feature to obtain a fused description feature; Based on the fusion description feature, the working status description information is determined.

4. The power data monitoring and analysis method for an uninterruptible power supply according to claim 1, characterized in that: The determining, based on the battery health status and the power supply operating status, a monitoring result of monitoring the target uninterruptible power supply includes: The battery health status and the power supply working status are integrated to obtain a monitoring result of the target uninterruptible power supply.

5. An energy storage system, characterized in that: The system comprises: a parameter acquisition module for acquiring, in response to a monitoring instruction for the target uninterruptible power supply when the target uninterruptible power supply is in a loaded state, electrolyte parameters and energy storage component parameters of the energy storage component of the target uninterruptible power supply, and acquiring heat dissipation component parameters, operating parameters, and inverter parameters of the target uninterruptible power supply, wherein the energy storage component is a lithium-ion battery; a health status determination module, configured to determine the battery health status of the energy storage assembly based on the electrolyte parameters and the energy storage assembly parameters, wherein the battery health status is used to indicate the health level, the electrolyte parameters include the electrolyte density change rate, the electrolyte temperature, and the electrolyte material characteristic coefficient, and the energy storage assembly parameters include the temperature difference gradient between battery cell poles, the distance between battery cell poles, the internal resistance, and the average battery temperature; The health status determination module is configured to determine a first health status parameter based on the electrolyte density change rate, the electrolyte temperature, the average battery temperature, and a first sub-coefficient in the electrolyte material characteristic coefficient, the first sub-coefficient being used to represent the attenuation characteristics of the electrolyte related to the electrolyte density, and the first health status parameter being used to represent the health status of the energy storage component in the electrolyte dimension; determine a second health status parameter based on the temperature difference gradient between the battery cell poles, the distance between the battery cell poles, the internal resistance, the average battery temperature, and a second sub-coefficient in the electrolyte material characteristic coefficient, the second sub-coefficient being used to represent the attenuation characteristics related to the temperature difference between the electrolyte and the battery cell poles, and the second health status parameter being used to represent the health status of the energy storage component in the temperature dimension; and add the first health status parameter and the second health status parameter to obtain the battery health status of the energy storage component; The health state determination module is configured to substitute the electrolyte density change rate and the electrolyte temperature into first relationship data to obtain a first health state correction coefficient, where the first health state correction coefficient is a coefficient for correcting the health state from two dimensions: electrolyte density change and electrolyte temperature; substitute the electrolyte temperature and the average battery temperature into second relationship data to obtain a second health state correction coefficient, where the second health state correction coefficient is a coefficient for correcting the health state from two dimensions: electrolyte temperature and average battery temperature; multiply the electrolyte density change rate, the first sub-coefficient, the first health state correction coefficient, and the second health state correction coefficient to obtain the first health state parameter; and The internal resistance is multiplied by a preset power of the average battery temperature to obtain a first intermediate parameter; the temperature difference gradient between the battery cell poles is divided by the first intermediate parameter to obtain a third health state parameter; the internal resistance and the distance between the battery cell poles are substituted into third relationship data to obtain a third health state correction coefficient; the third health state parameter, the second sub-coefficient, and the third health state correction coefficient are multiplied to obtain the second health state parameter, the first relationship data being used to represent a corresponding relationship between the electrolyte density change rate and the electrolyte temperature and the first health state correction coefficient, and the second relationship data being used to represent a corresponding relationship between the electrolyte temperature and the average battery temperature and the second health state correction coefficient; a working state determining module, configured to determine a power supply working state of the target uninterruptible power supply based on the heat dissipation component parameters, the working parameters, and the inverter parameters, wherein the power supply working state is used to indicate a working condition; A monitoring result determination module is used to determine a monitoring result of monitoring the target uninterruptible power supply based on the battery health status and the power supply working status, wherein the monitoring result is used to indicate whether an abnormality exists.

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