CN117134040B - Intelligent operation and maintenance method and device for liquid cooling energy storage system - Google Patents
Intelligent operation and maintenance method and device for liquid cooling energy storage system Download PDFInfo
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- 239000007788 liquid Substances 0.000 title claims abstract description 344
- 238000001816 cooling Methods 0.000 title claims abstract description 332
- 238000004146 energy storage Methods 0.000 title claims abstract description 155
- 238000012423 maintenance Methods 0.000 title claims abstract description 64
- 238000000034 method Methods 0.000 title claims abstract description 54
- 230000008859 change Effects 0.000 claims abstract description 199
- 238000012544 monitoring process Methods 0.000 claims abstract description 133
- 239000000110 cooling liquid Substances 0.000 claims abstract description 99
- 238000001514 detection method Methods 0.000 claims abstract description 73
- 230000017525 heat dissipation Effects 0.000 claims abstract description 69
- 230000003213 activating effect Effects 0.000 claims abstract description 35
- 238000013461 design Methods 0.000 claims abstract description 23
- 230000004913 activation Effects 0.000 claims description 26
- 239000002826 coolant Substances 0.000 claims description 24
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 23
- 238000012549 training Methods 0.000 claims description 22
- 238000003491 array Methods 0.000 claims description 19
- 238000004891 communication Methods 0.000 claims description 12
- 238000004364 calculation method Methods 0.000 claims description 8
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- 238000010276 construction Methods 0.000 claims description 6
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- 230000001360 synchronised effect Effects 0.000 claims description 3
- 238000005265 energy consumption Methods 0.000 abstract description 8
- 230000008569 process Effects 0.000 abstract description 8
- 230000002035 prolonged effect Effects 0.000 abstract description 3
- 230000006870 function Effects 0.000 description 43
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- 230000002159 abnormal effect Effects 0.000 description 4
- 230000000694 effects Effects 0.000 description 3
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- 230000001105 regulatory effect Effects 0.000 description 3
- 238000010801 machine learning Methods 0.000 description 2
- 238000013021 overheating Methods 0.000 description 2
- 230000005856 abnormality Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000013528 artificial neural network Methods 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 230000033228 biological regulation Effects 0.000 description 1
- 239000012809 cooling fluid Substances 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M10/00—Secondary cells; Manufacture thereof
- H01M10/60—Heating or cooling; Temperature control
- H01M10/63—Control systems
- H01M10/633—Control systems characterised by algorithms, flow charts, software details or the like
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M10/00—Secondary cells; Manufacture thereof
- H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
- H01M10/4285—Testing apparatus
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M10/00—Secondary cells; Manufacture thereof
- H01M10/60—Heating or cooling; Temperature control
- H01M10/61—Types of temperature control
- H01M10/613—Cooling or keeping cold
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M10/00—Secondary cells; Manufacture thereof
- H01M10/60—Heating or cooling; Temperature control
- H01M10/63—Control systems
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M10/00—Secondary cells; Manufacture thereof
- H01M10/60—Heating or cooling; Temperature control
- H01M10/65—Means for temperature control structurally associated with the cells
- H01M10/656—Means for temperature control structurally associated with the cells characterised by the type of heat-exchange fluid
- H01M10/6567—Liquids
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/10—Energy storage using batteries
Abstract
The application provides an intelligent operation and maintenance method and device of a liquid cooling energy storage system, and relates to the technical field of intelligent operation and maintenance, wherein the method comprises the following steps: firstly, obtaining system operation parameters, then obtaining global temperature rise change rate, then synchronizing to a liquid cooling control analyzer, obtaining liquid cooling control parameters, thereby generating a liquid cooling heat dissipation execution node, then activating a liquid cooling control module when the duration reaches the liquid cooling heat dissipation execution node, presetting a temperature control operation and maintenance monitoring window, then obtaining a temperature time-varying sequence, activating a leakage detection module, and then carrying out leakage operation and maintenance on the system. The application solves the problems that the prior art cannot monitor leakage of cooling liquid in time, and cannot predict and protect the influence of the leakage of the cooling liquid on a system and the energy consumption of a heat dissipation process is high. By analyzing the temperature time-varying sequence, other sensor data and the design of the liquid cooling heat dissipation execution node, whether leakage exists in the cooling liquid is identified, the cost and the energy consumption of the system are reduced, and the service life of the system is prolonged.
Description
Technical Field
The invention relates to the technical field of intelligent operation and maintenance, in particular to an intelligent operation and maintenance method and device of a liquid cooling energy storage system.
Background
Liquid-cooled energy storage systems are an important technology for battery temperature management, which cools the battery in a liquid-cooled manner to maintain the normal temperature and safety of the battery. In the use process of the liquid cooling energy storage system, the running state of the system needs to be monitored in real time, the temperature of the battery is guaranteed to be in a normal range, and meanwhile, the flow and the temperature of the cooling liquid are monitored, so that the safety problems of failure or insufficient cooling of the liquid cooling energy storage system are prevented.
The prior art monitors the running state of the liquid cooling energy storage system in real time, including the temperature of the liquid cooling energy storage battery, the temperature and pressure of the liquid cooling system, and the running state of the safety protection system and the intelligent management system, and maintains the running state according to the monitoring result in time.
The prior art also has the problems that the leakage of the cooling liquid cannot be monitored in time, the influence on the system caused by the leakage of the cooling liquid cannot be predicted, and the energy consumption in the protection and heat dissipation processes is high.
Disclosure of Invention
The application mainly solves the problems that the prior art cannot monitor leakage of cooling liquid in time, and cannot predict and protect the influence of the leakage of the cooling liquid on a system and the energy consumption of a heat dissipation process is high.
In view of the foregoing, the present application provides a smart operation and maintenance method and apparatus for a liquid cooling energy storage system, and in a first aspect, an embodiment of the present application provides a smart operation and maintenance method for a liquid cooling energy storage system, where the method includes: and the liquid cooling energy storage system is interacted to obtain a system operation parameter set, wherein the system operation parameter set comprises a system operation state and a system safety temperature. And if the system operation state is an electric energy release state, activating the temperature monitoring network to monitor the temperature rise of the liquid cooling energy storage system, and obtaining the global temperature rise change rate. And synchronizing the global temperature rise change rate to a liquid cooling control analyzer to obtain liquid cooling control parameters, wherein the liquid cooling control parameters comprise a liquid cooling circulation speed parameter and a liquid cooling flow control parameter. And generating a liquid cooling heat dissipation execution node, wherein the liquid cooling heat dissipation execution node is obtained by calculation according to the global temperature rise change rate and the system safety temperature. When the duration of the state that the liquid cooling energy storage system is in the electric energy release state reaches the liquid cooling heat dissipation execution node, activating the liquid cooling control module, performing operation control of the liquid cooling control module based on the liquid cooling control parameter, and performing temperature control operation maintenance on the liquid cooling energy storage system based on a cooling liquid leakage identification result. And presetting a temperature control operation and maintenance monitoring window, and controlling the temperature monitoring network to acquire temperature variable data of the liquid cooling energy storage system based on the Wen Kongyun-dimensional monitoring window to obtain a temperature time-varying sequence. Activating the leak detection module according to the temperature time-varying sequence. And carrying out cooling liquid leakage identification on the liquid cooling energy storage system according to the leakage detection module, and carrying out leakage operation and maintenance on the liquid cooling energy storage system based on a cooling liquid leakage identification result.
In a second aspect, the application provides a smart operation and maintenance device for a liquid-cooled energy storage system, the device comprising: the parameter set acquisition module is used for interacting the liquid cooling energy storage system to obtain a system operation parameter set, wherein the system operation parameter set comprises a system operation state and a system safety temperature. The global temperature rise change rate acquisition module is characterized in that the liquid cooling energy storage system is preconfigured with a temperature monitoring network, and if the system operation state is an electric energy release state, the temperature monitoring network is activated to monitor the temperature rise of the liquid cooling energy storage system, so that the global temperature rise change rate is obtained. The liquid cooling control parameter acquisition module is used for synchronizing the global temperature rise change rate to the liquid cooling control analyzer to obtain liquid cooling control parameters, wherein the liquid cooling control parameters comprise a liquid cooling circulation speed parameter and a liquid cooling flow control parameter. The liquid cooling heat dissipation execution node generation module is used for generating a liquid cooling heat dissipation execution node, wherein the liquid cooling heat dissipation execution node is obtained through calculation according to the global temperature rise change rate and the system safety temperature. And the liquid cooling control module activation module is used for activating the liquid cooling control module when the duration of the liquid cooling energy storage system in the electric energy release state reaches the liquid cooling heat dissipation execution node, controlling the operation of the liquid cooling control module based on the liquid cooling control parameter, and controlling the temperature of the liquid cooling energy storage system based on a cooling liquid leakage identification result. The temperature time-varying sequence acquisition module is used for presetting a temperature control operation and maintenance monitoring window, controlling the temperature monitoring network to acquire temperature variable data of the liquid cooling energy storage system based on the Wen Kongyun-dimensional monitoring window, and acquiring a temperature time-varying sequence. And the leakage detection activation module is used for activating the leakage detection module according to the temperature time-varying sequence. And the leakage operation and maintenance module is used for carrying out cooling liquid leakage identification on the liquid cooling energy storage system according to the leakage detection module and carrying out leakage operation and maintenance on the liquid cooling energy storage system based on a cooling liquid leakage identification result.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
the application provides an intelligent operation and maintenance method and device of a liquid cooling energy storage system, and relates to the technical field of intelligent operation and maintenance, wherein the method comprises the following steps: firstly, obtaining system operation parameters, then obtaining global temperature rise change rate, then synchronizing to a liquid cooling control analyzer, obtaining liquid cooling control parameters, thereby generating a liquid cooling heat dissipation execution node, then activating a liquid cooling control module when the duration reaches the liquid cooling heat dissipation execution node, presetting a temperature control operation and maintenance monitoring window, then obtaining a temperature time-varying sequence, activating a leakage detection module, and then carrying out leakage operation and maintenance on the system.
The application mainly solves the problems that the prior art cannot monitor leakage of cooling liquid in time, and cannot predict and protect the influence of the leakage of the cooling liquid on a system and the energy consumption of a heat dissipation process is high. By analyzing the temperature time-varying sequence, other sensor data and the design of the liquid cooling heat dissipation execution node, whether leakage exists in the cooling liquid is identified, the cost and the energy consumption of the system are reduced, and the service life of the system is prolonged.
The foregoing description is merely an overview of the technical solutions of the present application, and may be implemented according to the content of the specification in order to make the technical means of the present application more clearly understood, and in order to make the above-mentioned and other objects, features and advantages of the present application more clearly understood, the following detailed description of the present application will be given.
Drawings
For a clearer description of the present disclosure or of the prior art, the drawings used in the description of the embodiments or of the prior art will be briefly described, it being obvious that the drawings in the description below are only exemplary and that other drawings may be obtained, without inventive effort, by a person skilled in the art, from the provided drawings.
Fig. 1 is a schematic flow chart of an intelligent operation and maintenance method of a liquid cooling energy storage system according to an embodiment of the present application;
FIG. 2 is a schematic flow chart of a method for obtaining a global temperature rise change rate in an intelligent operation and maintenance method of a liquid cooling energy storage system according to an embodiment of the present application;
fig. 3 is a schematic flow chart of a method for obtaining the liquid cooling control parameter in the intelligent operation and maintenance method of the liquid cooling energy storage system according to the embodiment of the present application;
fig. 4 is a schematic structural diagram of an intelligent operation and maintenance device of a liquid cooling energy storage system according to an embodiment of the present application.
Reference numerals illustrate: the system comprises a parameter set acquisition module 10, a global temperature rise change rate acquisition module 20, a liquid cooling control parameter acquisition module 30, a liquid cooling heat dissipation execution node generation module 40, a liquid cooling control module activation module 50, a temperature time-varying sequence acquisition module 60, a leakage detection activation module 70 and a leakage operation and maintenance module 80.
Detailed Description
The application mainly solves the problems that the prior art cannot monitor leakage of cooling liquid in time, and cannot predict and protect the influence of the leakage of the cooling liquid on a system and the energy consumption of a heat dissipation process is high. By analyzing the temperature time-varying sequence, other sensor data and the design of the liquid cooling heat dissipation execution node, whether leakage exists in the cooling liquid is identified, the cost and the energy consumption of the system are reduced, and the service life of the system is prolonged.
In order to better understand the above technical solutions, the following detailed description will refer to the accompanying drawings and specific embodiments.
Example 1
An intelligent operation and maintenance method of a liquid cooling energy storage system as shown in fig. 1, the method comprises the following steps:
the liquid cooling energy storage system is interacted to obtain a system operation parameter set, wherein the system operation parameter set comprises a system operation state and a system safety temperature;
specifically, by interacting the liquid-cooled energy storage system, a set of system operating parameters may be obtained, wherein the set of system operating parameters includes a system operating state and a system safety temperature. The system operating conditions may include parameters such as battery pack temperature, coolant pressure, liquid level, etc. The battery pack temperature is the average temperature of all the battery cells in the battery pack, and the battery pack temperature sensor is arranged at the middle position of the bottom of the battery pack and adopts an NTC thermistor type. The cooling liquid temperature sensor is arranged at the connection port of the liquid inlet and outlet pipeline and adopts a PT1000 type temperature sensor. The cooling hydraulic pressure sensor and the liquid level sensor are arranged in the liquid cooling unit, the pressure sensor adopts a digital pressure sensor, and the liquid level sensor adopts an electrode type liquid level sensor. The safety temperature of the system is to ensure that the temperature of the battery pack is within the normal working temperature range, namely the temperature of the battery is between 0 and 60 ℃, and the temperature of the cooling liquid is between 0 and 45 ℃. And meanwhile, an early warning threshold value and a limit threshold value need to be set. The early warning threshold is generally set to be 35-40 ℃ of the temperature of the battery pack; the temperature of the cooling liquid is 25-35 ℃; liquid level low-level early warning value: 20% -40%. Cooling fluid pressure: normal operating pressure range: 0-5 bar, and the limiting pressure is 12bar.
The liquid cooling energy storage system is preconfigured with a temperature monitoring network, and if the running state of the system is an electric energy release state, the temperature monitoring network is activated to monitor the temperature rise of the liquid cooling energy storage system, so that the global temperature rise change rate is obtained;
specifically, in the liquid cooling energy storage system, the system can be used for monitoring and regulating the temperature by pre-configuring a temperature monitoring network. Under the electric energy release state, the battery pack can generate heat, and at the moment, the temperature monitoring network is activated to monitor the temperature rise of the liquid cooling energy storage system. The global temperature rise change rate is the temperature change rate of the liquid cooling energy storage system in the electric energy release state, and if the global temperature rise change rate is too high, the system is likely to have a heat dissipation problem, or the speed of generating heat by the battery pack is too high, and the system needs to be checked and adjusted at the moment. Meanwhile, the global temperature rise change rate can also be used for controlling the starting and the closing of the cooling system so as to prevent the overheat of the cooling liquid or the overhigh temperature of the battery pack. The liquid cooling energy storage system is subjected to temperature monitoring and regulation through the temperature monitoring network, so that the safe operation of the system can be ensured, and meanwhile, the reliability and stability of the system are improved.
Synchronizing the global temperature rise change rate to a liquid cooling control analyzer to obtain liquid cooling control parameters, wherein the liquid cooling control parameters comprise a liquid cooling circulation speed parameter and a liquid cooling flow control parameter;
specifically, the global temperature rise change rate is synchronized to a liquid cooling control analyzer, so that liquid cooling control parameters can be obtained. The liquid cooling circulation speed parameter represents the circulation speed of cooling liquid in the liquid cooling energy storage system, and the parameter can be calculated by the liquid cooling control analyzer. The liquid cooling circulation speed parameter can reflect the heat dissipation effect of the system, and if the liquid cooling circulation speed is too low, the system may have heat dissipation problem and the circulation speed of the cooling liquid needs to be increased. If the liquid cooling circulation speed is too high, the system may have excessive heat dissipation problem, and the circulation speed of the cooling liquid needs to be reduced. The liquid cooling flow control parameter represents the flow control of the cooling liquid in the liquid cooling energy storage system, and the parameter can be calculated by a liquid cooling control analyzer. The liquid cooling flow control parameter can reflect the cooling effect of the system, and if the liquid cooling flow control parameter is too high, the system may have the problem of excessive cooling, and the flow of the cooling liquid needs to be reduced. If the liquid cooling flow control parameter is too low, the system may have insufficient cooling problem, and the flow of the cooling liquid needs to be increased. The liquid cooling control parameters are calculated through the liquid cooling control analyzer, so that the temperature of the liquid cooling energy storage system can be better regulated and controlled, the safe operation of the system is ensured, and meanwhile, the reliability and stability of the system are improved.
Generating a liquid cooling heat dissipation execution node, wherein the liquid cooling heat dissipation execution node is obtained by calculation according to the global temperature rise change rate and the system safety temperature;
specifically, the initial temperature and the current temperature of the liquid cooling system are obtained through the data acquisition device. And calculating the temperature difference between the initial temperature and the current temperature, and calculating the global temperature rise change rate according to the temperature difference and the time. The temperature rise change rate is the temperature change amount in unit time, and the global temperature rise change rate is compared with the system safety temperature. If the global temperature rise change rate is smaller than the system safety temperature, the system safety temperature is the maximum acceptable temperature for the normal discharging of the system battery, the current time is set as a liquid cooling heat dissipation execution node, and corresponding liquid cooling heat dissipation operation is executed. If the global temperature rise change rate is greater than or equal to the system safety temperature, the liquid cooling heat dissipation execution node is set as the next time node. And calculating and obtaining a temperature difference divided by the temperature rise change rate based on the current temperature and the system safety temperature, and obtaining the liquid cooling heat dissipation execution node for which the temperature control is still performed for a long time.
When the duration of the state that the liquid cooling energy storage system is in the electric energy release state reaches the liquid cooling heat dissipation execution node, activating the liquid cooling control module, performing operation control of the liquid cooling control module based on the liquid cooling control parameter, and performing temperature control operation maintenance on the liquid cooling energy storage system based on a cooling liquid leakage identification result;
Specifically, when the duration of the liquid cooling energy storage system in the electric energy release state reaches the liquid cooling heat dissipation execution node, the liquid cooling control module can be activated, the operation of the liquid cooling control module is controlled based on the liquid cooling control parameter, and meanwhile, the temperature control operation and maintenance are performed on the liquid cooling energy storage system based on the cooling liquid leakage identification result. The liquid cooling control module may include a sensor, a controller, and an actuator. The sensor is used for monitoring state parameters of the liquid cooling energy storage system, such as battery pack temperature, cooling liquid temperature, pressure and the like, and transmitting the monitored data to the controller. And the controller processes and analyzes the sensor data according to the liquid cooling control parameters and the cooling liquid leakage identification result to generate corresponding control instructions. The actuating mechanism controls the liquid cooling energy storage system according to the control instruction, such as adjusting the flow of the cooling liquid, changing the circulation speed of the cooling liquid and the like. In terms of operation control, corresponding operation parameters such as a coolant leakage identification threshold value, an alarm threshold value and the like need to be set. During operation, it is necessary to periodically check the state of the liquid-cooled energy storage system, such as the battery pack temperature, the coolant temperature and pressure, and the leakage of the coolant. If abnormal conditions are found, measures are needed to be taken in time for maintenance and treatment so as to ensure the safe operation of the system.
Presetting a temperature control operation and maintenance monitoring window, and controlling the temperature monitoring network to acquire temperature variable data of the liquid cooling energy storage system based on the Wen Kongyun dimensional monitoring window to obtain a temperature time-varying sequence;
specifically, a temperature control operation and maintenance monitoring window can be preset, and the temperature monitoring network is controlled to collect temperature variable data of the liquid cooling energy storage system based on the temperature control operation and maintenance monitoring window, so that a temperature time-varying sequence is obtained. The Wen Kongyun dimension monitoring window can set a certain time range, and in the time range, the temperature monitoring network collects temperature data of the liquid cooling energy storage system according to a set time interval. The temperature change data of the liquid cooling energy storage system in different time periods can be obtained by controlling the acquisition frequency and the acquisition time of the temperature monitoring network, so that a temperature time-varying sequence is obtained. The temperature time-varying sequence can reflect the temperature variation trend of the liquid cooling energy storage system in different time periods, and the temperature variation rule and variation trend of the liquid cooling energy storage system can be known by analyzing the temperature time-varying sequence, so that abnormal temperature variation can be found in time and corresponding control measures can be taken. For example, in a certain period of time, the temperature time-varying sequence of the liquid cooling energy storage system shows a rapid rising trend, and at this time, the temperature of the system can be reduced by controlling the flow of the cooling liquid, changing the circulation speed of the cooling liquid and other measures, so as to prevent the battery pack from overheating or the cooling liquid from overheating. In summary, the temperature control operation and maintenance monitoring window is preset, and temperature data acquisition and control are performed based on the window, so that the temperature change condition of the liquid cooling energy storage system can be better known, abnormal temperature change can be found in time, corresponding control measures are taken, and the safe operation of the system is ensured.
Activating the leak detection module according to the temperature time-varying sequence;
specifically, the leakage detection module is activated according to the temperature time-varying sequence, so that the leakage condition of the cooling liquid in the liquid cooling energy storage system can be detected. The temperature time-varying sequence reflects the temperature variation of the liquid-cooled energy storage system over time. If there is a leak in the coolant, the amount of coolant gradually decreases, which may cause the system temperature to rise. Therefore, by analyzing the temperature time-varying sequence, it is possible to determine whether there is a leakage of the cooling liquid. Then, a leak detection module is activated, which is a module that activates a leak detection device, which is a pressure detection sensor provided on the pipe.
And carrying out cooling liquid leakage identification on the liquid cooling energy storage system according to the leakage detection module, and carrying out leakage operation and maintenance on the liquid cooling energy storage system based on a cooling liquid leakage identification result.
Specifically, the liquid cooling energy storage system is subjected to cooling liquid leakage identification according to the leakage detection module, and leakage operation and maintenance can be performed on the liquid cooling energy storage system based on a cooling liquid leakage identification result. The leak detection module activates a corresponding pressure detection sensor in the module, and if the pressure is abnormal, a leak occurs. If a leak exists, the leak detection module may output a corresponding alarm signal for timely maintenance and handling. In terms of leakage operation and maintenance, corresponding treatment measures can be adopted according to the leakage degree and the leakage position of the cooling liquid. For example, if the coolant leakage is small, it may be checked whether the coolant lines and interfaces are loose or broken and corresponding fastening or repair measures taken. If the leakage degree of the cooling liquid is large, whether the components such as the cooling liquid pump, the liquid cooling plate and the like have faults or not needs to be checked, and corresponding maintenance measures are taken. Meanwhile, in the maintenance and processing process, corresponding maintenance records and alarm information are required to be recorded so as to evaluate and optimize the performance and maintenance condition of the liquid cooling energy storage system. For example, the liquid cooling energy storage system can be periodically checked and maintained according to maintenance records and alarm information so as to ensure the safe and stable operation of the system. In summary, the leakage detection module is used for identifying the leakage of the cooling liquid of the liquid-cooled energy storage system, and performing leakage operation and maintenance based on the identification result of the leakage of the cooling liquid, so that the safe and stable operation of the liquid-cooled energy storage system can be effectively ensured, and the reliability and stability of the system are improved.
Further, as shown in fig. 2, in the method of the present application, the liquid cooling energy storage system is preconfigured with a temperature monitoring network, and if the running state of the system is an electric energy release state, the temperature monitoring network is activated to monitor the temperature rise of the liquid cooling energy storage system, so as to obtain a global temperature rise change rate, and the method further includes:
the method comprises the steps of interactively obtaining structural design information of the liquid cooling energy storage system, wherein the structural design information comprises K energy storage battery packs, and the K energy storage battery packs have K battery pack layout orientations;
correspondingly arranging K thermistors according to the arrangement directions of the K battery packs, wherein the K thermistors are in communication connection to form the temperature monitoring network;
when the system operation state is in an electric energy release state, activating the K thermistors of the temperature monitoring network to monitor the temperature rise of the K energy storage battery packs of the liquid cooling energy storage system, and obtaining K temperature rise sequences;
and carrying the K temperature rise sequences into a heat conduction equation to obtain K local temperature rise change rates, serializing the K local temperature rise change rates, and carrying out maximum extraction to obtain the global temperature rise change rate.
Specifically, structural design information of the liquid cooling energy storage system is obtained interactively: this involves interacting with a database, CAD software, or other design tool to obtain structural design information for the liquid cooled energy storage system. Such information includes the layout of the battery pack, the type and specification of the battery, the design of the liquid cooling system, etc. The structural design information comprises K energy storage battery packs, wherein the K energy storage battery packs are provided with K battery pack layout orientations: this means that from the structural design information, K energy storage battery packs are known, each having its specific arrangement position or orientation. And correspondingly arranging K thermistors according to the arrangement directions of the K battery packs, wherein the K thermistors are in communication connection to form the temperature monitoring network: according to the layout position of the battery packs, K thermistors are correspondingly arranged, and the temperature of each battery pack can be monitored by the thermistors. The thermistors are connected through communication to form a temperature monitoring network, so that the temperature condition of the liquid cooling energy storage system can be monitored in real time. When the system running state is in an electric energy release state, activating the K thermistors of the temperature monitoring network to monitor the temperature rise of the K energy storage battery packs of the liquid cooling energy storage system, and obtaining K temperature rise sequences: when the liquid cooling energy storage system starts to run and releases electric energy, a thermistor in the temperature monitoring network is activated, temperature monitoring is carried out on each battery pack, and temperature change of the battery packs is recorded, so that K temperature rise sequences are obtained. And carrying the K temperature rise sequences into a heat conduction equation to obtain K local temperature rise change rates: by bringing each temperature rise sequence into the heat conduction equation, the local temperature rise change rate of each battery pack, which is the change rate of the temperature of each battery pack over time, can be calculated. Assuming that the output power of the liquid cooling heat dissipation system is fixed, namely the temperature of a heat source is fixed, and the structure of the liquid cooling heat dissipation system does not dissipate heat, the following equation is a heat conduction equation and is used for predicting the internal environment temperature change condition of the liquid cooling heat dissipation system in the later period. Temperature rise rate calculation was performed based on the following formula:
Wherein,is a function of temperature over time and spatial position, < >>Is the rate of change of temperature rise, +.>Is the rate of change of temperature in space (Laplacian of Laplacian), and if the value of Laplacian is positive (negative) indicating that the rate of temperature rise (fall) at this point is large, it is expressed by the second derivative of the spatial gradient of temperature. />Is the thermal diffusivity, describing the ability of a material to conduct heat. Serializing the K local temperature rise change rates and carrying out maximum extraction to obtain the global temperature rise change rate: and serializing the local temperature rise change rate, and extracting a maximum value from the local temperature rise change rate, wherein the maximum value is the global temperature rise change rate, and reflects the temperature change condition of the whole liquid cooling energy storage system.
Further, as shown in fig. 3, in the method of the present application, the global temperature rise change rate is synchronized to a liquid cooling control analyzer to obtain a liquid cooling control parameter, where the liquid cooling control parameter includes a liquid cooling circulation speed parameter and a liquid cooling flow control parameter, and the method further includes:
an effective control threshold value of the liquid cooling control module is obtained interactively, wherein the effective control threshold value comprises a speed control threshold value and a flow control threshold value;
Taking the speed control threshold and the flow control threshold as constraints, randomly setting control parameters to obtain a plurality of groups of sample control parameters;
presetting standard electric energy release power, and controlling the liquid cooling energy storage system to be in an electric energy release state based on the standard electric energy release power;
the liquid cooling control module is controlled to control the temperature change of the liquid cooling energy storage system by adopting the plurality of groups of sample control parameters, so that a plurality of sample temperature change rates are obtained;
constructing the liquid cooling control analyzer based on the plurality of sets of sample control parameters and the plurality of sample temperature rates of change;
and synchronizing the global temperature rise change rate to the liquid cooling control analyzer to obtain the liquid cooling control parameters.
Specifically, an effective control threshold of the liquid cooling control module is obtained through interaction, wherein the effective control threshold comprises a speed control threshold and a flow control threshold: interaction here involves communicating with a database or with an engineer of the liquid cooling control module to obtain effective control thresholds for the liquid cooling control module. The speed control threshold refers to a critical speed that controls the start or stop of a particular operation or function in the liquid cooling control module. For example, if there is a pump in the liquid cooling control module, the speed control threshold may be set to the rotational speed of the pump, and when the rotational speed exceeds a certain threshold, the liquid cooling control module will start or stop certain operations, such as starting or stopping the flow of cooling liquid. The flow control threshold refers to the flow rate that controls a particular operation or function in the liquid cooling control module. For example, if there is a coolant line in the liquid cooling control module, the flow control threshold may be set to the flow of coolant in the line, and when the flow exceeds a certain threshold, the liquid cooling control module will start or stop certain operations, such as starting or stopping the operation of the coolant pump. And randomly setting control parameters by taking the speed control threshold and the flow control threshold as constraints to obtain a plurality of groups of sample control parameters: and randomly setting control parameters according to the obtained speed control threshold and flow control threshold, so that a plurality of groups of sample control parameters can be obtained. Presetting standard electric energy release power, and controlling the liquid cooling energy storage system to be in an electric energy release state based on the standard electric energy release power: in this step, a standard electric energy release power is preset, and then the liquid cooling energy storage system is controlled to be in an electric energy release state according to the standard electric energy release power. And controlling the liquid cooling control module to perform temperature change control on the liquid cooling energy storage system by adopting the plurality of groups of sample control parameters to obtain a plurality of sample temperature change rates: the liquid cooling control module is controlled by using a plurality of groups of sample control parameters, so that the liquid cooling control module can control the temperature change of the liquid cooling energy storage system. Each set of control parameters produces a sample rate of temperature change in such a way that a plurality of sample rates of temperature change can be obtained. Constructing the liquid-cooled control analyzer based on the plurality of sets of sample control parameters and the plurality of sample temperature rates of change: this step includes analyzing these parameters and the rate of change of temperature using statistical methods or machine learning algorithms. For example, regression analysis may be used to determine the correlation between control parameters and temperature change rates, or a neural network may be used to train a model to predict the behavior of the liquid-cooled control module. Synchronizing the global temperature rise change rate to the liquid cooling control analyzer to obtain the liquid cooling control parameters: this step involves inputting real-time global temperature rise rate data into a liquid cooling control analyzer, and then outputting corresponding liquid cooling control parameters by the analyzer. These control parameters may be regulatory advice regarding coolant flow, coolant temperature, battery cooling time, etc. to achieve more accurate temperature control of the liquid cooled energy storage system. The temperature change of the liquid cooling energy storage system can be effectively analyzed and optimized, and safe, stable and efficient operation of the liquid cooling energy storage system is ensured.
Further, the method constructs the liquid cooling control analyzer based on the plurality of sets of sample control parameters and the plurality of sample temperature change rates, the method further comprising:
inputting the multiple groups of sample control parameters into a control parameter convolution training layer, wherein the control parameter convolution training layer comprises a multi-layer control parameter kernel function and is used for extracting characteristics of the multiple groups of sample control parameters to obtain multi-layer control parameter convolution output samples;
inputting the temperature change rates of the plurality of samples into a temperature change convolution training layer, wherein the temperature change convolution training layer comprises a temperature change kernel function and is used for extracting characteristics of the temperature change rates of the plurality of samples to obtain a plurality of control parameter convolution output samples;
fitting function construction and training are carried out by using the multi-layer control parameter convolution output sample and the plurality of control parameter convolution output samples, and a temperature change control fitting function is output when training is carried out until convergence;
and constructing and generating a temperature change control inverse solution function based on the temperature change control fitting function, and synchronizing the temperature change control inverse solution function to the liquid cooling control analyzer.
Specifically, a plurality of sets of sample control parameters and a plurality of sample temperature change rates are input into an analysis system for performing a functional relationship of the control parameters and the temperature change rates, the input plurality of sets of sample control parameters are passed through a control parameter convolution training layer comprising a plurality of control parameter kernel functions for feature extraction, each kernel function being capable of capturing a specific feature in input data, and features are extracted from the control parameters by the kernel functions to generate a multi-layer control parameter convolution output sample. The input plurality of sample temperature rates pass through a temperature change convolution training layer comprising temperature change kernel functions for feature extraction of the temperature rates, similar to the control parameter convolution training layer, which extract features from the temperature rates, generating a plurality of control parameter convolution output samples. The multi-layer control parameter convolution output samples and the plurality of control parameter convolution output samples are used to construct a fitting function that is intended to map the numerical variation relationship of the control parameter and the temperature variation rate. And performing functional relation fitting training of the numerical value change relation of the control parameters and the temperature change rate by adopting the existing machine learning method until the parameters of the fitting function are adjusted to the optimal state, and obtaining the temperature change control fitting function. The temperature change control fitting function may characterize the relationship between the control parameters (speed control parameter and flow control parameter) and the rate of temperature change. And constructing a temperature change control inverse solution function based on the temperature change control fitting function. The function of this function is to calculate in reverse, i.e. to derive the respective speed control parameter and flow control parameter, starting from the desired temperature change. And finally synchronizing the temperature change control inverse solution function into the liquid cooling control analyzer, so that the liquid cooling control parameters can be inversely pushed under the condition of obtaining the global temperature rise change rate of the system.
Further, the method activates the leak detection module according to the temperature time-varying sequence, the method further comprising:
pre-constructing a temperature change fluctuation intensity function, wherein the temperature change fluctuation intensity function is as follows:
wherein,for the intensity value of temperature variation fluctuation->For the temperature change mean value of the battery pack, < > and->Temperature change data of single battery pack->The single battery pack temperature variable data is a single battery pack temperature variable sequence;
the temperature time-varying sequence comprises K groups of battery pack temperature varying sequences;
carrying the temperature change sequence of the K groups of battery packs into the temperature change fluctuation intensity function one by one, and calculating to obtain K temperature change fluctuation intensity values;
presetting a temperature change fluctuation intensity constraint, and traversing the K temperature change fluctuation intensity values based on the temperature change fluctuation intensity constraint;
if all the K temperature change fluctuation intensity values meet the temperature change fluctuation intensity constraint, not activating the leakage detection module;
and if the K temperature change fluctuation intensity values do not meet the temperature change fluctuation intensity constraint, generating a leakage detection activation instruction, and activating the leakage detection module based on the leakage detection activation instruction, wherein the leakage detection activation instruction comprises H leakage detection battery packs.
Specifically, the temperature fluctuation condition of the battery pack in the liquid cooling energy storage system can be quantitatively evaluated by pre-constructing the temperature fluctuation intensity function. The function calculates a temperature change fluctuation intensity value according to the temperature change average value of the battery pack and the temperature change variable data of the single battery pack, and judges based on preset temperature change fluctuation intensity constraint. If the temperature fluctuation intensity values of all the battery packs meet the temperature fluctuation intensity constraint, the temperature change of the whole liquid cooling energy storage system is in a controllable range, and the leakage detection module does not need to be activated. However, if any of the temperature variation fluctuation intensity values of the battery packs do not meet the temperature variation fluctuation intensity constraint, the condition that the fluctuation intensity constraint is not met is indicated, and the condition that leakage faults exist in the liquid cooling pipelines corresponding to the battery packs is indicated. The battery packs which do not meet the fluctuation strength constraint are proposed to be H in total, so that a leakage detection activation instruction is formed. In summary, by constructing the temperature change fluctuation intensity function in advance and judging based on the function, the possible temperature abnormality problem in the liquid cooling energy storage system can be found in time, and corresponding treatment measures are taken, so that the safe and stable operation of the system is effectively ensured.
Furthermore, according to the method, the liquid cooling energy storage system is subjected to cooling liquid leakage identification according to the leakage detection module, and leakage operation and maintenance are performed on the liquid cooling energy storage system based on a cooling liquid leakage identification result, and the method further comprises:
The structural design information also comprises K liquid cooling heat dissipation water inlet pipelines;
presetting a pressure sensor interval threshold, and carrying out pressure sensor arrangement on the K liquid cooling heat dissipation water inlet pipelines according to the pressure sensor interval threshold to obtain K pressure monitoring arrays, wherein the K pressure monitoring arrays are provided with K groups of arrangement position identifiers;
the K pressure monitoring arrays are in communication connection to form the leakage detection module;
according to the mapping call of the layout positions of the H leakage detection battery packs and the K battery packs on the K liquid cooling heat dissipation water inlet pipelines, H liquid cooling heat dissipation water inlet pipelines are obtained;
mapping and activating H pressure monitoring arrays on the leak detection module based on the H liquid cooling heat dissipation water inlet pipelines;
acquiring H groups of pressure monitoring data based on the H pressure monitoring arrays;
and carrying out cooling liquid leakage identification according to the H-group pressure monitoring data to obtain the cooling liquid leakage identification result.
Specifically, in the structural design information, K liquid-cooled heat dissipation water inlet pipes are included. According to a preset pressure sensor interval threshold, the pressure sensors can be distributed on the K liquid cooling heat dissipation water inlet pipelines, so that K pressure monitoring arrays are obtained. The pressure monitoring arrays are provided with K groups of layout position identifiers and are connected with each other in a communication mode to form the leakage detection module. According to the mapping call of the layout orientations of the H leakage detection battery packs and the K battery packs, H liquid cooling heat dissipation water inlet pipes can be obtained from the K liquid cooling heat dissipation water inlet pipes. The liquid cooling heat dissipation water inlet pipes can be used as samples for leakage detection and used for mapping and activating the corresponding H pressure monitoring arrays in the leakage detection module. After activation, the H pressure monitoring arrays may obtain corresponding pressure monitoring data. According to the H groups of pressure monitoring data, the identification of the leakage of the cooling liquid can be performed, so that the identification result of the leakage of the cooling liquid is obtained. In summary, through the steps of presetting a pressure sensor interval threshold, arranging a pressure sensor on a liquid cooling heat dissipation water inlet pipeline, activating a corresponding pressure monitoring array, obtaining pressure monitoring data, identifying leakage of cooling liquid and the like, whether the cooling liquid in the liquid cooling energy storage system leaks or not can be detected and identified, and therefore safe and stable operation of the system is guaranteed.
Further, according to the method of the present application, the identification of the leakage of the cooling liquid is performed according to the pressure monitoring data of the H group, and the identification result of the leakage of the cooling liquid is obtained, and the method further includes:
acquiring a first group of pressure monitoring data and a first pressure monitoring array based on the H groups of pressure monitoring data, wherein the first group of pressure monitoring data comprises N pressure monitoring parameters, and the N pressure monitoring parameters have N layout position identifiers;
based on the N layout position identifiers, carrying out adjacent comparison on the N pressure monitoring parameters, and positioning a first cooling liquid leakage site, wherein the first cooling liquid leakage site is provided with a first liquid leakage pressure difference identifier;
and by analogy, carrying out cooling liquid leakage identification according to the H groups of pressure monitoring data to obtain H cooling liquid leakage points and H liquid leakage pressure difference identifications;
and serializing the H cooling liquid leakage sites based on the H liquid leakage pressure difference identifiers to generate the cooling liquid leakage identification result.
Specifically, a first set of pressure monitoring data and a first pressure monitoring array are obtained based on the H set of pressure monitoring data calls: first, set H of pressure monitoring data is invoked, which may include pressure readings at various locations and corresponding location information. A first pressure monitoring array is then generated from the data. Wherein the first set of pressure monitoring data includes N pressure monitoring parameters having N layout position identifications: these pressure monitoring parameters may represent pressure readings at various locations, with a placement location identifier being used to record where each pressure monitoring parameter is located. And based on the N layout position identifiers, carrying out adjacent comparison on the N pressure monitoring parameters, and positioning a first cooling liquid leakage site: this step means that pressure data of adjacent locations are compared. If a significant difference in pressure data is found between adjacent locations, it may be the location of a coolant leak. Wherein, first coolant leakage site has first hydraulic pressure differential sign: this differential leakage pressure signature may represent specific information of the severity or location of the coolant leakage. And by analogy, carrying out cooling liquid leakage identification according to the H groups of pressure monitoring data to obtain H cooling liquid leakage sites and H liquid leakage pressure difference identifications: through the steps, all the pressure monitoring data are compared, and possible positions of leakage of the cooling liquid and corresponding identifications of the liquid leakage pressure difference are found out. Serializing the H cooling liquid leakage sites based on the H liquid leakage pressure difference identifiers to generate the cooling liquid leakage identification result: and sequencing and sorting all found coolant leakage positions and corresponding pressure difference identifiers to generate a final coolant leakage identification result. The serialization aims at carrying out operation and maintenance management on each leakage point according to the severity of liquid leakage.
Example two
Based on the same inventive concept as the intelligent operation and maintenance method of the liquid cooling energy storage system in the foregoing embodiment, as shown in fig. 4, the present application provides an intelligent operation and maintenance device of the liquid cooling energy storage system, where the device includes:
the parameter set acquisition module 10 is used for interacting the liquid cooling energy storage system to obtain a system operation parameter set, wherein the system operation parameter set comprises a system operation state and a system safety temperature;
the global temperature rise change rate acquisition module 20 is that the liquid cooling energy storage system is preconfigured with a temperature monitoring network, and if the system operation state is an electric energy release state, the temperature monitoring network is activated to monitor the temperature rise of the liquid cooling energy storage system, so that the global temperature rise change rate is obtained;
the liquid cooling control parameter acquisition module 30 is configured to synchronize the global temperature rise change rate to a liquid cooling control analyzer to obtain a liquid cooling control parameter, where the liquid cooling control parameter includes a liquid cooling circulation speed parameter and a liquid cooling flow control parameter;
the liquid cooling heat dissipation execution node generating module 40 is configured to generate a liquid cooling heat dissipation execution node by using the liquid cooling heat dissipation execution node generating module 40, where the liquid cooling heat dissipation execution node is obtained by calculating according to the global temperature rise change rate and the system safety temperature;
The liquid cooling control module activation module 50 is configured to activate the liquid cooling control module when the duration of the liquid cooling energy storage system in the electric energy release state reaches the liquid cooling heat dissipation execution node, perform operation control of the liquid cooling control module based on the liquid cooling control parameter, and perform temperature control operation maintenance on the liquid cooling energy storage system based on a cooling liquid leakage identification result;
the temperature time-varying sequence acquisition module 60 is used for presetting a Wen Kongyun-dimensional monitoring window, controlling the temperature monitoring network to acquire temperature variable data of the liquid cooling energy storage system based on the Wen Kongyun-dimensional monitoring window, and acquiring a temperature time-varying sequence;
a leak detection activation module 70, the leak detection activation module 70 being configured to activate the leak detection module according to the temperature time-varying sequence;
the leakage operation and maintenance module 80, the leakage operation and maintenance module 80 is used for performing cooling liquid leakage identification on the liquid cooling energy storage system according to the leakage detection module, and performing leakage operation and maintenance on the liquid cooling energy storage system based on a cooling liquid leakage identification result.
Further, the system further comprises:
The design information acquisition module is used for interactively acquiring structural design information of the liquid cooling energy storage system, wherein the structural design information comprises K energy storage battery packs, and the K energy storage battery packs have K battery pack layout orientations;
the resistor communication connection module is used for correspondingly arranging K thermistors according to the arrangement direction of the K battery packs, and the K thermistors are in communication connection to form the temperature monitoring network;
the temperature rise sequence acquisition module is used for activating the K thermistors of the temperature monitoring network to perform temperature rise monitoring on the K energy storage battery packs of the liquid cooling energy storage system when the system operation state is in an electric energy release state, so as to obtain K temperature rise sequences;
and the temperature rise change rate acquisition module is used for bringing the K temperature rise sequences into a heat conduction equation to obtain K local temperature rise change rates, serializing the K local temperature rise change rates and extracting the maximum value to obtain the global temperature rise change rate.
Further, the system further comprises:
the control threshold interaction module is used for interactively obtaining an effective control threshold of the liquid cooling control module, wherein the effective control threshold comprises a speed control threshold and a flow control threshold;
The multi-group sample control parameter acquisition module is used for randomly setting control parameters by taking the speed control threshold and the flow control threshold as constraints to acquire multi-group sample control parameters;
the power release preset module is used for presetting standard electric energy release power and controlling the liquid cooling energy storage system to be in an electric energy release state based on the standard electric energy release power;
the plurality of sample temperature change rate acquisition modules are used for controlling the liquid cooling control module to perform temperature change control on the liquid cooling energy storage system by adopting the plurality of groups of sample control parameters to acquire a plurality of sample temperature change rates;
the liquid cooling control analyzer construction module is used for constructing the liquid cooling control analyzer based on the plurality of groups of sample control parameters and the plurality of sample temperature change rates;
and the liquid cooling control parameter acquisition module is used for synchronizing the global temperature rise change rate to the liquid cooling control analyzer to acquire the liquid cooling control parameters.
Further, the system further comprises:
the sample output module is used for inputting the multiple groups of sample control parameters into a control parameter convolution training layer, wherein the control parameter convolution training layer comprises a multi-layer control parameter kernel function and is used for extracting characteristics of the multiple groups of sample control parameters to obtain a multi-layer control parameter convolution output sample;
The control parameter output module is used for inputting the temperature change rates of the samples into a temperature change convolution training layer, wherein the temperature change convolution training layer comprises a temperature change kernel function and is used for extracting characteristics of the temperature change rates of the samples to obtain a plurality of control parameter convolution output samples;
the fitting function generating module is used for constructing and training fitting functions by using the multi-layer control parameter convolution output samples and the plurality of control parameter convolution output samples, and outputting temperature change control fitting functions when training is carried out until convergence;
and the function synchronization module is used for constructing and generating a temperature change control inverse solution function based on the temperature change control fitting function and synchronizing the temperature change control inverse solution function to the liquid cooling control analyzer.
Further, the system further comprises:
the function construction module is used for pre-constructing a temperature change fluctuation intensity function, and the temperature change fluctuation intensity function is as follows:
wherein,for the intensity value of temperature variation fluctuation，/>For the temperature change mean value of the battery pack, < > and->Temperature change data of single battery pack->The single battery pack temperature variable data is a single battery pack temperature variable sequence;
the temperature time-varying sequence comprises K groups of battery pack temperature varying sequences;
The intensity value calculation module is used for carrying the temperature change sequence of the K groups of battery packs into the temperature change fluctuation intensity function one by one, and calculating to obtain K temperature change fluctuation intensity values;
the intensity constraint traversing module is used for presetting temperature change fluctuation intensity constraint and traversing the K temperature change fluctuation intensity values based on the temperature change fluctuation intensity constraint;
the intensity judging module is used for not activating the leakage detecting module if the K temperature change fluctuation intensity values meet the temperature change fluctuation intensity constraint;
and the leakage detection activation module is used for generating a leakage detection activation instruction and activating the leakage detection module based on the leakage detection activation instruction if the K temperature change fluctuation intensity values do not meet the temperature change fluctuation intensity constraint, wherein the leakage detection activation instruction comprises H leakage detection battery packs.
Further, the system further comprises:
the water pipeline module is used for the structural design information and also comprises K liquid cooling heat dissipation water inlet pipelines;
the interval threshold presetting module is used for presetting an interval threshold of the pressure sensor, and carrying out pressure sensor arrangement on the K liquid cooling heat dissipation water inlet pipelines according to the interval threshold of the pressure sensor to obtain K pressure monitoring arrays, wherein the K pressure monitoring arrays are provided with K groups of arrangement position identifiers;
The leakage detection module construction module is used for communication connection of the K pressure monitoring arrays to form the leakage detection module;
the H liquid cooling heat dissipation water inlet pipeline modules are used for mapping and calling the K liquid cooling heat dissipation water inlet pipelines according to the arrangement positions of the H leakage detection battery packs and the K battery packs to obtain H liquid cooling heat dissipation water inlet pipelines;
the H pressure monitoring array activation modules are used for mapping and activating the H pressure monitoring arrays on the basis of the H liquid cooling heat dissipation water inlet pipelines on the leakage detection module;
the H-group pressure monitoring data acquisition module is used for acquiring H-group pressure monitoring data based on the H pressure monitoring arrays;
and the cooling liquid identification result acquisition module is used for carrying out cooling liquid leakage identification according to the H-group pressure monitoring data to obtain the cooling liquid leakage identification result.
Further, the system further comprises:
the position identification acquisition module is used for calling and acquiring a first group of pressure monitoring data and a first pressure monitoring array based on the H groups of pressure monitoring data, wherein the first group of pressure monitoring data comprises N pressure monitoring parameters, and the N pressure monitoring parameters comprise N layout position identifications;
the first coolant leakage site positioning module is used for adjacently comparing the N pressure monitoring parameters based on the N layout position identifiers and positioning a first coolant leakage site, wherein the first coolant leakage site is provided with a first coolant leakage pressure difference identifier;
The differential pressure identification acquisition module is used for identifying leakage of the cooling liquid according to the H groups of pressure monitoring data, so as to obtain H cooling liquid leakage points and H differential pressure identifications of liquid leakage;
and the liquid leakage identification result generation module is used for serializing the H cooling liquid leakage sites based on the H liquid leakage pressure difference identifications and generating the cooling liquid leakage identification result.
Through the foregoing detailed description of the intelligent operation and maintenance method of the liquid cooling energy storage system, those skilled in the art can clearly understand that the intelligent operation and maintenance device of the liquid cooling energy storage system in this embodiment, for the device disclosed in the embodiment, the description is relatively simple because it corresponds to the device disclosed in the embodiment, and the relevant places refer to the description of the method section.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (6)
1. The intelligent operation and maintenance method of the liquid cooling energy storage system is characterized by being applied to an intelligent operation and maintenance system of the liquid cooling energy storage system, wherein the system comprises a liquid cooling control module and a leakage detection module, and the method comprises the following steps:
the liquid cooling energy storage system is interacted to obtain a system operation parameter set, wherein the system operation parameter set comprises a system operation state and a system safety temperature;
the liquid cooling energy storage system is preconfigured with a temperature monitoring network, and if the running state of the system is an electric energy release state, the temperature monitoring network is activated to monitor the temperature rise of the liquid cooling energy storage system, so that the global temperature rise change rate is obtained;
synchronizing the global temperature rise change rate to a liquid cooling control analyzer to obtain liquid cooling control parameters, wherein the liquid cooling control parameters comprise a liquid cooling circulation speed parameter and a liquid cooling flow control parameter;
generating a liquid cooling heat dissipation execution node, wherein the liquid cooling heat dissipation execution node is obtained by calculation according to the global temperature rise change rate and the system safety temperature;
when the duration of the state that the liquid cooling energy storage system is in the electric energy release state reaches the liquid cooling heat dissipation execution node, activating the liquid cooling control module, performing operation control of the liquid cooling control module based on the liquid cooling control parameter, and performing temperature control operation maintenance on the liquid cooling energy storage system based on a cooling liquid leakage identification result;
Presetting a temperature control operation and maintenance monitoring window, and controlling the temperature monitoring network to acquire temperature variable data of the liquid cooling energy storage system based on the Wen Kongyun dimensional monitoring window to obtain a temperature time-varying sequence;
activating the leak detection module according to the temperature time-varying sequence;
performing cooling liquid leakage identification on the liquid cooling energy storage system according to the leakage detection module, and performing leakage operation and maintenance on the liquid cooling energy storage system based on a cooling liquid leakage identification result;
the method comprises the steps of pre-configuring a temperature monitoring network for the liquid cooling energy storage system, activating the temperature monitoring network to monitor the temperature rise of the liquid cooling energy storage system to obtain the global temperature rise change rate if the system operation state is an electric energy release state, and further comprising the steps of:
the method comprises the steps of interactively obtaining structural design information of the liquid cooling energy storage system, wherein the structural design information comprises K energy storage battery packs, and the K energy storage battery packs have K battery pack layout orientations;
correspondingly arranging K thermistors according to the arrangement directions of the K battery packs, wherein the K thermistors are in communication connection to form the temperature monitoring network;
when the system operation state is in an electric energy release state, activating the K thermistors of the temperature monitoring network to monitor the temperature rise of the K energy storage battery packs of the liquid cooling energy storage system, and obtaining K temperature rise sequences;
Carrying the K temperature rise sequences into a heat conduction equation to obtain K local temperature rise change rates, serializing the K local temperature rise change rates, and carrying out maximum extraction to obtain the global temperature rise change rate;
activating the leak detection module according to the temperature time-varying sequence, the method further comprising:
pre-constructing a temperature change fluctuation intensity function, wherein the temperature change fluctuation intensity function is as follows:
wherein (1)>For the intensity value of temperature variation fluctuation->For the temperature change mean value of the battery pack, < > and->Temperature change data of single battery pack->The single battery pack temperature variable data is a single battery pack temperature variable sequence;
the temperature time-varying sequence comprises K groups of battery pack temperature varying sequences;
carrying the temperature change sequence of the K groups of battery packs into the temperature change fluctuation intensity function one by one, and calculating to obtain K temperature change fluctuation intensity values;
presetting a temperature change fluctuation intensity constraint, and traversing the K temperature change fluctuation intensity values based on the temperature change fluctuation intensity constraint;
if all the K temperature change fluctuation intensity values meet the temperature change fluctuation intensity constraint, not activating the leakage detection module;
and if the K temperature change fluctuation intensity values do not meet the temperature change fluctuation intensity constraint, generating a leakage detection activation instruction, and activating the leakage detection module based on the leakage detection activation instruction, wherein the leakage detection activation instruction comprises H leakage detection battery packs.
2. The method of claim 1, wherein the global temperature rise rate of change is synchronized to a liquid cooling control analyzer to obtain liquid cooling control parameters, wherein the liquid cooling control parameters include a liquid cooling circulation rate parameter and a liquid cooling flow control parameter, the method further comprising:
an effective control threshold value of the liquid cooling control module is obtained interactively, wherein the effective control threshold value comprises a speed control threshold value and a flow control threshold value;
taking the speed control threshold and the flow control threshold as constraints, randomly setting control parameters to obtain a plurality of groups of sample control parameters;
presetting standard electric energy release power, and controlling the liquid cooling energy storage system to be in an electric energy release state based on the standard electric energy release power;
the liquid cooling control module is controlled to control the temperature change of the liquid cooling energy storage system by adopting the plurality of groups of sample control parameters, so that a plurality of sample temperature change rates are obtained;
constructing the liquid cooling control analyzer based on the plurality of sets of sample control parameters and the plurality of sample temperature rates of change;
and synchronizing the global temperature rise change rate to the liquid cooling control analyzer to obtain the liquid cooling control parameters.
3. The method of claim 2, wherein the liquid-cooled control analyzer is constructed based on the plurality of sets of sample control parameters and the plurality of sample temperature rates of change, the method further comprising:
Inputting the multiple groups of sample control parameters into a control parameter convolution training layer, wherein the control parameter convolution training layer comprises a multi-layer control parameter kernel function and is used for extracting characteristics of the multiple groups of sample control parameters to obtain multi-layer control parameter convolution output samples;
inputting the temperature change rates of the plurality of samples into a temperature change convolution training layer, wherein the temperature change convolution training layer comprises a temperature change kernel function and is used for extracting characteristics of the temperature change rates of the plurality of samples to obtain a plurality of control parameter convolution output samples;
fitting function construction and training are carried out by using the multi-layer control parameter convolution output sample and the plurality of control parameter convolution output samples, and a temperature change control fitting function is output when training is carried out until convergence;
and constructing and generating a temperature change control inverse solution function based on the temperature change control fitting function, and synchronizing the temperature change control inverse solution function to the liquid cooling control analyzer.
4. The method of claim 1, wherein the liquid-cooled energy storage system is identified for leakage of cooling liquid according to the leakage detection module, and the liquid-cooled energy storage system is subjected to leakage operation based on a result of the identification of leakage of cooling liquid, the method further comprising:
The structural design information also comprises K liquid cooling heat dissipation water inlet pipelines;
presetting a pressure sensor interval threshold, and carrying out pressure sensor arrangement on the K liquid cooling heat dissipation water inlet pipelines according to the pressure sensor interval threshold to obtain K pressure monitoring arrays, wherein the K pressure monitoring arrays are provided with K groups of arrangement position identifiers;
the K pressure monitoring arrays are in communication connection to form the leakage detection module;
according to the mapping call of the layout positions of the H leakage detection battery packs and the K battery packs on the K liquid cooling heat dissipation water inlet pipelines, H liquid cooling heat dissipation water inlet pipelines are obtained;
mapping and activating H pressure monitoring arrays on the leak detection module based on the H liquid cooling heat dissipation water inlet pipelines;
acquiring H groups of pressure monitoring data based on the H pressure monitoring arrays;
and carrying out cooling liquid leakage identification according to the H-group pressure monitoring data to obtain the cooling liquid leakage identification result.
5. The method of claim 4, wherein the coolant leak identification is performed based on the H-set of pressure monitoring data to obtain the coolant leak identification result, the method further comprising:
acquiring a first group of pressure monitoring data and a first pressure monitoring array based on the H groups of pressure monitoring data, wherein the first group of pressure monitoring data comprises N pressure monitoring parameters, and the N pressure monitoring parameters have N layout position identifiers;
Based on the N layout position identifiers, carrying out adjacent comparison on the N pressure monitoring parameters, and positioning a first cooling liquid leakage site, wherein the first cooling liquid leakage site is provided with a first liquid leakage pressure difference identifier;
and by analogy, carrying out cooling liquid leakage identification according to the H groups of pressure monitoring data to obtain H cooling liquid leakage points and H liquid leakage pressure difference identifications;
and serializing the H cooling liquid leakage sites based on the H liquid leakage pressure difference identifiers to generate the cooling liquid leakage identification result.
6. An intelligent operation and maintenance device of a liquid cooling energy storage system, the device comprising:
the parameter set acquisition module is used for interacting the liquid cooling energy storage system to acquire a system operation parameter set, wherein the system operation parameter set comprises a system operation state and a system safety temperature;
the global temperature rise change rate acquisition module is characterized in that a temperature monitoring network is preconfigured in the liquid cooling energy storage system, and if the system operation state is an electric energy release state, the temperature monitoring network is activated to monitor the temperature rise of the liquid cooling energy storage system, so that the global temperature rise change rate is obtained;
The liquid cooling control parameter acquisition module is used for synchronizing the global temperature rise change rate to the liquid cooling control analyzer to obtain liquid cooling control parameters, wherein the liquid cooling control parameters comprise a liquid cooling circulation speed parameter and a liquid cooling flow control parameter;
the liquid cooling heat dissipation execution node generation module is used for generating a liquid cooling heat dissipation execution node, wherein the liquid cooling heat dissipation execution node is obtained through calculation according to the global temperature rise change rate and the system safety temperature;
the liquid cooling control module activation module is used for activating the liquid cooling control module when the duration of the liquid cooling energy storage system in the electric energy release state reaches the liquid cooling heat dissipation execution node, performing operation control of the liquid cooling control module based on the liquid cooling control parameter, and performing temperature control operation maintenance on the liquid cooling energy storage system based on a cooling liquid leakage identification result;
the temperature time-varying sequence acquisition module is used for presetting a temperature control operation and maintenance monitoring window, controlling the temperature monitoring network to acquire temperature variable data of the liquid cooling energy storage system based on the Wen Kongyun-dimensional monitoring window, and acquiring a temperature time-varying sequence;
The leakage detection activation module is used for activating the leakage detection module according to the temperature time-varying sequence;
the leakage operation and maintenance module is used for identifying leakage of the cooling liquid of the liquid-cooling energy storage system according to the leakage detection module and carrying out leakage operation and maintenance on the liquid-cooling energy storage system based on a cooling liquid leakage identification result;
the apparatus further comprises:
the design information acquisition module is used for interactively acquiring structural design information of the liquid cooling energy storage system, wherein the structural design information comprises K energy storage battery packs, and the K energy storage battery packs have K battery pack layout orientations;
the resistor communication connection module is used for correspondingly arranging K thermistors according to the arrangement direction of the K battery packs, and the K thermistors are in communication connection to form the temperature monitoring network;
the temperature rise sequence acquisition module is used for activating the K thermistors of the temperature monitoring network to perform temperature rise monitoring on the K energy storage battery packs of the liquid cooling energy storage system when the system operation state is in an electric energy release state, so as to obtain K temperature rise sequences;
the temperature rise change rate acquisition module is used for bringing the K temperature rise sequences into a heat conduction equation to obtain K local temperature rise change rates, serializing the K local temperature rise change rates and extracting the maximum value to obtain the global temperature rise change rate;
The function construction module is used for pre-constructing a temperature change fluctuation intensity function, and the temperature change fluctuation intensity function is as follows:
wherein (1)>For the intensity value of temperature variation fluctuation->For the temperature change mean value of the battery pack, < > and->Temperature change data of single battery pack->The single battery pack temperature variable data is a single battery pack temperature variable sequence;
the temperature time-varying sequence comprises K groups of battery pack temperature varying sequences;
the intensity value calculation module is used for carrying the temperature change sequence of the K groups of battery packs into the temperature change fluctuation intensity function one by one, and calculating to obtain K temperature change fluctuation intensity values;
the intensity constraint traversing module is used for presetting temperature change fluctuation intensity constraint and traversing the K temperature change fluctuation intensity values based on the temperature change fluctuation intensity constraint;
the intensity judging module is used for not activating the leakage detecting module if the K temperature change fluctuation intensity values meet the temperature change fluctuation intensity constraint;
and the leakage detection activation module is used for generating a leakage detection activation instruction and activating the leakage detection module based on the leakage detection activation instruction if the K temperature change fluctuation intensity values do not meet the temperature change fluctuation intensity constraint, wherein the leakage detection activation instruction comprises H leakage detection battery packs.
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