A flow control system for a flow battery

Abstract

The present invention relates to the field of flow control technology, and specifically discloses a flow control system for a liquid flow battery, comprising a flow data acquisition module, a first flow analysis module, a second flow analysis module, a flow prediction and analysis module, a flow control judgment module, a flow control adjustment module, and a flow control optimization module; the present invention collects flow data, analyzes to obtain a first flow influence coefficient and a second flow influence coefficient, and then obtains a flow prediction index, analyzes the flow prediction index to obtain a predicted flow, compares the predicted flow with the actual flow, analyzes to obtain a flow control deviation coefficient, and judges whether to perform flow control adjustment, and controls and adjusts the flow deviation abnormal data through a controller; the present invention not only improves the intelligence level of liquid flow battery flow control, but also improves the operating efficiency, reliability and economy of the system, and is of great significance for promoting the further development and application of liquid flow battery technology.

Description

Technical Field

[0001] The present invention relates to the technical field of flow control, and in particular to a flow control system of a liquid flow battery. Background Art

[0002] As the global energy structure shifts toward cleaner, lower-carbon energy, flow batteries have become a research hotspot in large-scale energy storage due to their advantages, including large energy storage capacity, long cycle life, and high safety. Flow batteries operate based on the flow of electrolyte between electrodes to achieve the conversion between electrical and chemical energy. Their performance is closely related to the electrolyte flow rate. A suitable flow rate ensures timely replenishment of active substances on the electrode surface, maintaining a stable electrochemical reaction rate and improving the battery's charge and discharge efficiency and capacity retention.

[0003] In actual operation, the working environment of flow batteries is complex and changeable. Factors such as temperature, pressure, and electrolyte concentration will affect the flow rate. However, traditional systems find it difficult to fully and real-timely consider the changes in these factors, resulting in certain errors in flow control and affecting the stability of battery performance.

[0004] First, the control algorithm parameters of the flow control system of traditional liquid flow batteries are fixed. When faced with complex operating conditions such as temperature changes and electrolyte composition fluctuations during the operation of liquid flow batteries, it is impossible to dynamically optimize the adjustment strategy, which can easily lead to flow control deviations and affect the stability of battery performance. Secondly, the monitoring and analysis capabilities are insufficient. Traditional systems only focus on monitoring a single parameter of flow, and lack comprehensive monitoring and analysis of related parameters such as the internal resistance of the battery stack and the balance of electrolyte concentration. It is difficult to accurately locate the cause of flow abnormalities from multiple dimensions, which reduces the accuracy of flow control. In addition, traditional systems mostly use open-loop or simple closed-loop control, and have not established a flow prediction model based on multiple influence coefficients, making it impossible to predict the trend of flow demand changes in advance. At the same time, there is a lack of real-time evaluation and optimization iteration of the control effect, which can easily lead to accumulation of flow control deviations due to sudden changes in operating conditions or equipment aging, affecting the long-term operating performance of the battery. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a flow control system for a flow battery to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above-mentioned object, the present invention provides the following technical solutions: a flow control system for a liquid flow battery, comprising a flow data acquisition module, a first flow analysis module, a second flow analysis module, a flow prediction and analysis module, a flow control judgment module, a flow control adjustment module, and a flow control optimization module;

[0007] Flow data acquisition module: used to collect flow data during the operation of the flow battery and divide the flow battery operation process into n monitoring sub-areas;

[0008] The first flow analysis module is used to analyze the electrolyte flow rate deviation rate, pipeline pressure mutation rate and electrolyte temperature deviation to obtain the first flow influence coefficient of the flow battery in each monitoring sub-area;

[0009] The second flow analysis module is used to analyze the electrolyte concentration, stack internal resistance and current density to obtain the second flow influence coefficient of the flow battery in each monitoring sub-area;

[0010] Flow prediction analysis module: Based on the first flow influence coefficient and the second flow influence coefficient of the flow battery in each monitoring sub-area, a flow prediction index model is established to analyze and obtain the flow prediction index of the flow battery in each monitoring sub-area;

[0011] Flow control judgment module: Based on the flow prediction index of the flow battery in each monitoring sub-area, the predicted flow of the flow battery in each monitoring sub-area is obtained, and the predicted flow is compared with the actual flow, and the flow control deviation coefficient of the flow battery in each monitoring sub-area is analyzed to determine whether to perform flow control adjustment;

[0012] Flow control and regulation module: used to receive data on flow deviation anomalies from the flow control judgment module, and control and regulate the flow of the flow battery in each monitoring sub-area through the controller;

[0013] Flow control optimization module: used to optimize the flow data after control and adjustment, and display the flow control results of the flow battery in each monitoring sub-area in real time.

[0014] Preferably, the execution mode of the flow data acquisition module is as follows:

[0015] Acquiring flow data during the operation of the flow battery through a sensor, the flow data including first flow data and second flow data, the first flow data including electrolyte flow rate, pipeline pressure, and electrolyte temperature; the second flow data including electrolyte concentration, stack internal resistance, and current density;

[0016] The target flow battery is determined as the target monitoring object, the target flow battery operation process is determined as the target monitoring area, and the target flow battery operation process is divided into n monitoring sub-areas, which are numbered 1, 2, ..., i, ..., n, where i is the number of each monitoring sub-area.

[0017] Preferably, the execution mode of the first traffic analysis module is as follows:

[0018] Obtaining an electrolyte flow rate deviation rate, a pipeline pressure mutation rate, and an electrolyte temperature deviation based on the first flow data;

[0019] The first step is to obtain the electrolyte flow rate deviation rate, specifically: obtain the electrolyte flow rate of the flow battery in each monitoring sub-area, and extract the electrolyte benchmark flow rate of the flow battery from the management database , respectively substitute them into the formula , get the electrolyte flow rate deviation rate of the flow battery in the i-th monitoring sub-area Vdr i ,in, Fv i represents the electrolyte flow rate of the flow battery in the i-th monitoring sub-area, i=1, 2, 3, ..., n, where i is the number of each monitoring sub-area;

[0020] The second step is to obtain the pipeline pressure mutation rate, specifically: obtain the pipeline pressure value of the flow battery in each monitoring sub-area, and use the formula , calculate the pipeline pressure mutation rate of the flow battery in the i-th monitoring sub-area Pmr i ,in, Indicates the i-th monitoring sub-area at the initial moment t 1Measured pipeline pressure value, Indicates the i-th monitoring sub-area at the end time t 2. Measured pipeline pressure value;

[0021] The third step is to obtain the electrolyte temperature deviation, specifically: obtain the electrolyte temperature of the flow battery in each monitoring sub-area, and extract the electrolyte reference temperature of the flow battery from the management database , respectively substitute them into the formula , get the electrolyte temperature deviation of the flow battery in the i-th monitoring sub-area Tdr i ,in, T i represents the electrolyte temperature of the flow battery in the i-th monitoring sub-area;

[0022] The fourth step is to read the electrolyte flow rate deviation rate, pipeline pressure mutation rate and electrolyte temperature deviation of the flow battery in each monitoring sub-area, and analyze them to obtain the first flow influence coefficient of the flow battery in each monitoring sub-area. The calculation formula is as follows:

[0023] ,in, FIC i represents the first flow rate influence coefficient of the flow battery in the i-th monitoring sub-area, Indicates the preset maximum allowable electrolyte flow rate deviation rate, Indicates the preset maximum allowable pipeline pressure mutation rate, Indicates the preset maximum allowable electrolyte temperature deviation, are the weight coefficients of the electrolyte flow rate deviation rate, pipeline pressure mutation rate and electrolyte temperature deviation, respectively, and .

[0024] Preferably, the execution mode of the second traffic analysis module is as follows:

[0025] The first step is to obtain the stack internal resistance and current density of the flow battery in each monitoring sub-area, and use the formula , calculate the growth rate of the internal resistance of the flow battery stack in the i-th monitoring sub-area ,in, represents the internal resistance of the flow battery stack in the i-th monitoring sub-area, represents the initial resistance of the flow battery, represents the current density of the flow battery in the i-th monitoring sub-area, represents the initial current density of the flow battery;

[0026] The second step is to read the stack internal resistance growth rate and electrolyte concentration of the flow battery in each monitoring sub-area, analyze them, and obtain the second flow influence coefficient of the flow battery in each monitoring sub-area. The calculation formula is as follows:

[0027] ,in, SIC i represents the second flow rate influence coefficient of the flow battery in the i-th monitoring sub-area, Indicates the electrolyte concentration balance of the flow battery in the i-th monitoring sub-area.

[0028] Preferably, the electrolyte concentration balance of the flow battery in the i-th monitoring sub-area is obtained in the following manner:

[0029] Calculate the average electrolyte concentration of the flow battery in the i-th monitoring sub-area , the calculation formula is ,in, represents the electrolyte concentration of the jth sampling unit in the i-th monitoring sub-area, j represents the number of each sampling unit, j = 1, 2, 3, ..., m i , m i represents the total number of sampling units in the i-th monitoring sub-area, where i is the number of each monitoring sub-area;

[0030] Calculate the electrolyte concentration balance of the flow battery in the i-th monitoring sub-area , the calculation formula is: .

[0031] Preferably, the execution mode of the traffic prediction and analysis module is as follows:

[0032] The first flow influence coefficient and the second flow influence coefficient of the flow battery in each monitoring sub-area are read, a flow prediction index model is established, and the flow prediction index of the flow battery in each monitoring sub-area is obtained by analysis. The calculation formula is as follows:

[0033] ,in, TPI i represents the flow prediction index of the flow battery in the i-th monitoring sub-area, FIC i represents the first flow rate influence coefficient of the flow battery in the i-th monitoring sub-area, SIC i represents the second flow rate influence coefficient of the flow battery in the i-th monitoring sub-area, is an exponential function.

[0034] Preferably, the execution mode of the flow control judgment module is as follows:

[0035] Read the flow prediction index of the flow battery in the i-th monitoring sub-area TPI i , through the formula , calculate the predicted flow rate of the flow battery in the i-th monitoring sub-area TP i ,in, Indicates the battery design flow rate, represents the correction factor, represents flow efficiency;

[0036] Get the actual flow rate of the flow battery in the i-th monitoring sub-area , the flow control deviation coefficient of the flow battery in each monitoring sub-area is obtained by analysis, and the calculation formula is as follows:

[0037] ,in, CDC i The flow control deviation coefficient of the flow battery in the i-th monitoring sub-area;

[0038] Based on the flow control deviation coefficient of the flow battery in each monitoring sub-area, the flow control deviation of the flow battery in each monitoring sub-area is judged as follows:

[0039] The flow control deviation coefficient of the liquid flow battery in each monitoring sub-area is read and compared with the preset flow control deviation coefficient threshold. If the flow control deviation coefficient of the liquid flow battery in a monitoring sub-area is less than the preset flow control deviation coefficient threshold, it is judged that there is no deviation abnormality in the flow of the liquid flow battery in the monitoring sub-area and no flow control adjustment operation is required; if the flow control deviation coefficient of the liquid flow battery in a monitoring sub-area is greater than or equal to the preset flow control deviation coefficient threshold, it is judged that the flow deviation of the liquid flow battery in the monitoring sub-area is abnormal, and the flow deviation abnormal data of the liquid flow battery in the monitoring sub-area is marked as the flow deviation judgment result of the liquid flow battery in the monitoring sub-area, and the abnormal data is transmitted to the flow control adjustment module for flow control adjustment.

[0040] Preferably, the flow control and regulation module is executed as follows:

[0041] Receive the data of abnormal flow deviation in the flow control judgment module, and control and adjust the flow of the flow battery in each monitoring sub-area through the controller. The formula for control and adjustment by the controller is as follows:

[0042] ,in, It represents the flow control increment output by the controller of the i-th monitoring sub-area at the k-th sampling moment, represents the flow deviation of the flow battery at the kth sampling moment in the i-th monitoring sub-area, represents the flow deviation of the flow battery at the k-1th sampling moment in the i-th monitoring sub-area, represents the flow deviation of the flow battery at the k-2th sampling moment in the i-th monitoring sub-area, represent the proportional, integral and differential coefficients of the i-th monitoring sub-area respectively;

[0043] ,in, represents the control signal of the flow battery in the i-th monitoring sub-area at the k-th sampling moment, represents the control signal of the flow battery in the i-th monitoring sub-area at the k-1th sampling moment, and k represents the number of each sampling moment; , TP i represents the predicted flow rate of the flow battery in the i-th monitoring sub-area, It represents the actual flow rate of the flow battery in the i-th monitoring sub-area at the k-th sampling moment.

[0044] As described above, the flow control system of a flow battery provided by the present invention has at least the following beneficial effects:

[0045] The present invention provides a flow control system for a liquid flow battery. The flow control system divides the operation process of the liquid flow battery into various monitoring sub-areas, collects flow data from each monitoring sub-area, and analyzes the electrolyte flow velocity deviation rate, pipeline pressure mutation rate and electrolyte temperature deviation respectively to obtain a first flow influence coefficient of the liquid flow battery in each monitoring sub-area; analyzes the electrolyte concentration, stack internal resistance and current density to obtain a second flow influence coefficient of the liquid flow battery in each monitoring sub-area; and then establishes a flow prediction index model to analyze and obtain a flow prediction index of the liquid flow battery in each monitoring sub-area. The predicted flow is obtained based on the flow prediction index analysis, and is compared with the actual flow to obtain a flow control deviation coefficient of the liquid flow battery in each monitoring sub-area, and it is judged whether to perform flow control adjustment. The flow deviation abnormal data of the liquid flow battery in each monitoring sub-area is controlled and adjusted by a controller, and the flow data after control and adjustment is controlled and optimized, and the flow control results of the liquid flow battery in each monitoring sub-area are displayed in real time. This invention can quantify the coupled effects of various factors on flow demand in real time, dynamically adjust control strategies, and significantly improve flow control accuracy and system stability under complex operating conditions. It effectively avoids battery performance degradation caused by local flow anomalies and continuously optimizes control parameters through a closed-loop feedback mechanism. This not only shortens response time to sudden changes in operating conditions but also reduces operation and maintenance costs. Furthermore, this invention not only significantly improves the intelligent level of flow battery flow control but also effectively enhances the system's operating efficiency, reliability, and economy, which is of great significance for promoting the further development and application of flow battery technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The present invention is further described with reference to the accompanying drawings. However, the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without inventive effort.

[0047] Figure 1 This is a structural schematic diagram of a flow control system of a liquid flow battery according to the present invention.

[0048] Figure 2 This is a schematic diagram of the electronic device structure of a flow control system of a liquid flow battery according to the present invention. DETAILED DESCRIPTION

[0049] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0050] Example 1

[0051] See also Figure 1 As shown, the present invention provides a flow control system for a liquid flow battery, comprising a flow data acquisition module, a first flow analysis module, a second flow analysis module, a flow prediction and analysis module, a flow control judgment module, a flow control adjustment module, and a flow control optimization module;

[0052] Flow data acquisition module: used to collect flow data during the operation of the flow battery and divide the flow battery operation process into n monitoring sub-areas;

[0053] In this embodiment, it should be specifically explained that the execution method of the flow data acquisition module is as follows:

[0054] Acquiring flow data during the operation of the flow battery through sensors, the flow data including first flow data and second flow data, the first flow data including electrolyte flow rate, pipeline pressure, and electrolyte temperature; the second flow data including electrolyte concentration, stack internal resistance, and current density, the sensors including but not limited to electrolyte flow rate sensors, temperature sensors, pressure sensors, and electrolyte concentration sensors;

[0055] The target flow battery is determined as the target monitoring object, the target flow battery operation process is determined as the target monitoring area, and the target flow battery operation process is divided into n monitoring sub-areas, which are numbered 1, 2, ..., i, ..., n, where i is the number of each monitoring sub-area.

[0056] The first flow analysis module is used to analyze the electrolyte flow rate deviation rate, pipeline pressure mutation rate and electrolyte temperature deviation to obtain the first flow influence coefficient of the flow battery in each monitoring sub-area;

[0057] In this embodiment, it should be specifically explained that the execution method of the first traffic analysis module is as follows:

[0058] Obtaining an electrolyte flow rate deviation rate, a pipeline pressure mutation rate, and an electrolyte temperature deviation based on the first flow data;

[0059] The first step is to obtain the electrolyte flow rate deviation rate, specifically: obtain the electrolyte flow rate of the flow battery in each monitoring sub-area, and extract the electrolyte benchmark flow rate of the flow battery from the management database , respectively substitute them into the formula , get the electrolyte flow rate deviation rate of the flow battery in the i-th monitoring sub-area Vdr i ,in, Fv irepresents the electrolyte flow rate of the flow battery in the i-th monitoring sub-area, i=1, 2, 3, ..., n, where i is the number of each monitoring sub-area;

[0060] The second step is to obtain the pipeline pressure mutation rate, specifically: obtain the pipeline pressure value of the flow battery in each monitoring sub-area, and use the formula , calculate the pipeline pressure mutation rate of the flow battery in the i-th monitoring sub-area Pmr i ,in, Indicates the i-th monitoring sub-area at the initial moment t 1Measured pipeline pressure value, Indicates the i-th monitoring sub-area at the end time t 2. Measured pipeline pressure value;

[0061] The third step is to obtain the electrolyte temperature deviation, specifically: obtain the electrolyte temperature of the flow battery in each monitoring sub-area, and extract the electrolyte reference temperature of the flow battery from the management database , respectively substitute them into the formula , get the electrolyte temperature deviation of the flow battery in the i-th monitoring sub-area Tdr i ,in, T i represents the electrolyte temperature of the flow battery in the i-th monitoring sub-area;

[0062] The fourth step is to read the electrolyte flow rate deviation rate, pipeline pressure mutation rate and electrolyte temperature deviation of the flow battery in each monitoring sub-area, and analyze them to obtain the first flow influence coefficient of the flow battery in each monitoring sub-area. The calculation formula is as follows:

[0063] ,in, FIC i represents the first flow rate influence coefficient of the flow battery in the i-th monitoring sub-area, Indicates the preset maximum allowable electrolyte flow rate deviation rate, Indicates the preset maximum allowable pipeline pressure mutation rate, Indicates the preset maximum allowable electrolyte temperature deviation, are the weight coefficients of the electrolyte flow rate deviation rate, pipeline pressure mutation rate and electrolyte temperature deviation, respectively, and .

[0064] It should be specifically noted that, in a specific embodiment, It can be set to 0.5, It can be set to 0.3, It can be set to 0.2. The electrolyte flow rate is the core parameter that directly determines the electrolyte circulation efficiency and the mass transfer capacity of the stack. Its deviation rate directly affects the distribution of active substances and the reaction uniformity, and plays a dominant role in flow stability. The pipeline pressure mutation rate reflects the real-time operation risk of the system. Sudden pressure changes may cause sudden failures such as sealing failure or gas-liquid separation. The electrolyte temperature deviation indirectly affects the flow by affecting the viscosity, but the temperature change has a lag and the impact is relatively mild, so the weight is relatively low.

[0065] In this embodiment, it should be specifically explained that, in the formula, the electrolyte flow rate deviation rate of the flow battery in the i-th monitoring sub-area is Vdr i The larger the pressure, the greater the pipeline pressure mutation rate. Pmr i The larger the electrolyte temperature deviation is, the Tdr i The larger the value is, the greater the first flow rate influence coefficient of the flow battery in the i-th monitoring sub-area is. FIC i The larger the value is, the greater the impact on the flow rate of the flow battery in the monitoring sub-area is and the more unstable the flow state is; and the electrolyte flow rate deviation rate of the flow battery in the i-th monitoring sub-area is Vdr i , pipeline pressure mutation rate Pmr i , electrolyte temperature deviation Tdr i There will be no mutual impact between them.

[0066] The second flow analysis module is used to analyze the electrolyte concentration, stack internal resistance and current density to obtain the second flow influence coefficient of the flow battery in each monitoring sub-area;

[0067] In this embodiment, it should be specifically explained that the execution method of the second traffic analysis module is as follows:

[0068] The first step is to obtain the stack internal resistance and current density of the flow battery in each monitoring sub-area, and use the formula , calculate the growth rate of the internal resistance of the flow battery stack in the i-th monitoring sub-area ,in, represents the internal resistance of the flow battery stack in the i-th monitoring sub-area, represents the initial resistance of the flow battery, represents the current density of the flow battery in the i-th monitoring sub-area, represents the initial current density of the flow battery;

[0069] It should be noted that in the formula, Corrected the effect of current density change on internal resistance growth, because high current density may accelerate the growth of internal resistance.

[0070] The second step is to read the stack internal resistance growth rate and electrolyte concentration of the flow battery in each monitoring sub-area, analyze them, and obtain the second flow influence coefficient of the flow battery in each monitoring sub-area. The calculation formula is as follows:

[0071] ,in, SIC i represents the second flow rate influence coefficient of the flow battery in the i-th monitoring sub-area, represents the electrolyte concentration balance of the flow battery in the i-th monitoring sub-area;

[0072] It should be noted that in the formula, the electrolyte concentration balance of the flow battery in the i-th monitoring sub-area is The smaller the value, the higher the growth rate of internal resistance of the stack The larger the value is, the more uneven the electrolyte concentration of the flow battery in the monitoring sub-area is and the faster the internal resistance of the battery stack increases. The second flow rate influence coefficient of the flow battery in the i-th monitoring sub-area is SIC i The larger the value is, the greater the impact on the flow rate of the flow battery in the monitoring sub-area is and the more unstable the flow state is; and the electrolyte concentration balance of the flow battery in the i-th monitoring sub-area is , growth rate of internal resistance of the stack There will be no mutual impact between them.

[0073] In this embodiment, it should be specifically explained that the method for obtaining the electrolyte concentration balance of the flow battery in the i-th monitoring sub-area is as follows:

[0074] Obtain the electrolyte concentration data of each sampling unit in the i-th monitoring sub-area. The electrolyte concentration data set expression of each sampling unit is: ,in, m i represents the total number of sampling units in the i-th monitoring sub-area;

[0075] Calculate the average electrolyte concentration of the flow battery in the i-th monitoring sub-area , the calculation formula is ,in, represents the electrolyte concentration of the jth sampling unit in the i-th monitoring sub-area, j represents the number of each sampling unit, j = 1, 2, 3, ..., m i , m i represents the total number of sampling units in the i-th monitoring sub-area, where i is the number of each monitoring sub-area;

[0076] Calculate the electrolyte concentration balance of the flow battery in the i-th monitoring sub-area , the calculation formula is: ;

[0077] It should be noted that the electrolyte concentration balance of the flow battery in the i-th monitoring sub-area is The value range is , The closer the value is to 1, the more uniform the electrolyte concentration distribution of the flow battery in the monitoring sub-area is.

[0078] The electrolyte concentration balance refers to the consistency of concentration in each region of the flow battery electrolyte. The higher the balance, the smaller the concentration difference, the improved reaction stability, and the reduced flow demand.

[0079] Flow prediction analysis module: Based on the first flow influence coefficient and the second flow influence coefficient of the flow battery in each monitoring sub-area, a flow prediction index model is established to analyze and obtain the flow prediction index of the flow battery in each monitoring sub-area;

[0080] In this embodiment, it should be specifically explained that the execution method of the traffic prediction and analysis module is as follows:

[0081] The first flow influence coefficient and the second flow influence coefficient of the flow battery in each monitoring sub-area are read, a flow prediction index model is established, and the flow prediction index of the flow battery in each monitoring sub-area is obtained by analysis. The calculation formula is as follows:

[0082] ,in, TPI i represents the flow prediction index of the flow battery in the i-th monitoring sub-area, FIC i represents the first flow rate influence coefficient of the flow battery in the i-th monitoring sub-area, SIC i represents the second flow rate influence coefficient of the flow battery in the i-th monitoring sub-area, is an exponential function.

[0083] Flow control judgment module: Based on the flow prediction index of the flow battery in each monitoring sub-area, the predicted flow of the flow battery in each monitoring sub-area is obtained, and the predicted flow is compared with the actual flow, and the flow control deviation coefficient of the flow battery in each monitoring sub-area is analyzed to determine whether to perform flow control adjustment;

[0084] In this embodiment, it should be specifically explained that the execution method of the flow control judgment module is as follows:

[0085] Read the flow prediction index of the flow battery in the i-th monitoring sub-area TPI i , through the formula , calculate the predicted flow rate of the flow battery in the i-th monitoring sub-area TP i ,in, Indicates the battery design flow rate, represents the correction factor, represents flow efficiency;

[0086] Get the actual flow rate of the flow battery in the i-th monitoring sub-area , the flow control deviation coefficient of the flow battery in each monitoring sub-area is obtained by analysis, and the calculation formula is as follows:

[0087] ,in, CDC i The flow control deviation coefficient of the flow battery in the i-th monitoring sub-area;

[0088] Based on the flow control deviation coefficient of the flow battery in each monitoring sub-area, the flow control deviation of the flow battery in each monitoring sub-area is judged as follows:

[0089] The flow control deviation coefficient of the liquid flow battery in each monitoring sub-area is read and compared with the preset flow control deviation coefficient threshold. If the flow control deviation coefficient of the liquid flow battery in a monitoring sub-area is less than the preset flow control deviation coefficient threshold, it is judged that there is no deviation abnormality in the flow of the liquid flow battery in the monitoring sub-area and no flow control adjustment operation is required; if the flow control deviation coefficient of the liquid flow battery in a monitoring sub-area is greater than or equal to the preset flow control deviation coefficient threshold, it is judged that the flow deviation of the liquid flow battery in the monitoring sub-area is abnormal, and the flow deviation abnormal data of the liquid flow battery in the monitoring sub-area is marked as the flow deviation judgment result of the liquid flow battery in the monitoring sub-area, and the abnormal data is transmitted to the flow control adjustment module for flow control adjustment.

[0090] Flow control and regulation module: used to receive data on flow deviation anomalies from the flow control judgment module, and control and regulate the flow of the flow battery in each monitoring sub-area through the controller;

[0091] In this embodiment, it should be specifically explained that the execution method of the flow control and regulation module is as follows:

[0092] Receive the data of abnormal flow deviation in the flow control judgment module, and control and adjust the flow of the flow battery in each monitoring sub-area through the controller. The formula for control and adjustment by the controller is as follows:

[0093] ,in, It represents the flow control increment output by the controller of the i-th monitoring sub-area at the k-th sampling moment, represents the flow deviation of the flow battery at the kth sampling moment in the i-th monitoring sub-area, represents the flow deviation of the flow battery at the k-1th sampling moment in the i-th monitoring sub-area, represents the flow deviation of the flow battery at the k-2th sampling moment in the i-th monitoring sub-area, represent the proportional, integral and differential coefficients of the i-th monitoring sub-area respectively;

[0094] ,in, represents the control signal of the flow battery in the i-th monitoring sub-area at the k-th sampling moment, represents the control signal of the flow battery in the i-th monitoring sub-area at the k-1th sampling moment, and k represents the number of each sampling moment; , TP i represents the predicted flow rate of the flow battery in the i-th monitoring sub-area, It represents the actual flow rate of the flow battery in the i-th monitoring sub-area at the k-th sampling moment.

[0095] Flow control optimization module: used to optimize the flow data after control and adjustment, and display the flow control results of the flow battery in each monitoring sub-area in real time.

[0096] Example 2

[0097] According to an exemplary embodiment, an electronic device includes: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0098] The processor executes the above-mentioned flow control system of the liquid flow battery by calling the computer program stored in the memory.

[0099] Figure 2 This is a structural diagram of an electronic device provided in an embodiment of the present application. The electronic device may have relatively large differences due to different configurations or performances, and can include one or more processors (Central Processing Units, CPU) and one or more memories, wherein at least one computer program is stored in the memory, and the at least one computer program is loaded and executed by the processor to implement a flow control system of a liquid flow battery provided in each of the above-mentioned method embodiments.

[0100] The electronic device may also include other components for realizing the functions of the device, for example, the electronic device may also include components such as a wired or wireless network interface and an input / output interface for input and output.

[0101] This embodiment also provides a computer program product stored on a computer-readable medium, including a computer-readable program, which, when executed on an electronic device, provides a user input interface to implement the flow control system of the liquid flow battery.

[0102] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0103] It should be understood that determining B based on A does not mean determining B based solely on A. B can also be determined based on A and / or other information.

[0104] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

[0105] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A flow control system for a flow battery, characterized in that: include: Flow data acquisition module: used to collect flow data during the operation of the flow battery and divide the flow battery operation process into n monitoring sub-areas; The first flow analysis module is used to analyze the electrolyte flow rate deviation rate, pipeline pressure mutation rate and electrolyte temperature deviation to obtain the first flow influence coefficient of the flow battery in each monitoring sub-area; The second flow analysis module is used to analyze the electrolyte concentration, stack internal resistance and current density to obtain the second flow influence coefficient of the flow battery in each monitoring sub-area; Flow prediction analysis module: Based on the first flow influence coefficient and the second flow influence coefficient of the flow battery in each monitoring sub-area, a flow prediction index model is established to analyze and obtain the flow prediction index of the flow battery in each monitoring sub-area; Flow control judgment module: Based on the flow prediction index of the flow battery in each monitoring sub-area, the predicted flow of the flow battery in each monitoring sub-area is obtained, and the predicted flow is compared with the actual flow, and the flow control deviation coefficient of the flow battery in each monitoring sub-area is analyzed to determine whether to perform flow control adjustment; Flow control and regulation module: used to receive data on flow deviation anomalies from the flow control judgment module, and control and regulate the flow of the flow battery in each monitoring sub-area through the controller; Flow control optimization module: used to optimize the flow data after control and adjustment, and display the flow control results of the flow battery in each monitoring sub-area in real time.

2. A flow control system for a liquid flow battery according to claim 1, characterized in that: The execution mode of the flow data acquisition module is as follows: Acquiring flow data during the operation of the flow battery through a sensor, the flow data including first flow data and second flow data, the first flow data including electrolyte flow rate, pipeline pressure, and electrolyte temperature; The second flow data includes electrolyte concentration, stack internal resistance and current density; The target flow battery is determined as the target monitoring object, the target flow battery operation process is determined as the target monitoring area, and the target flow battery operation process is divided into n monitoring sub-areas, which are numbered 1, 2, ..., i, ..., n, where i is the number of each monitoring sub-area.

3. The flow control system of a liquid flow battery according to claim 1, characterized in that: The execution mode of the first traffic analysis module is as follows: Obtaining an electrolyte flow rate deviation rate, a pipeline pressure mutation rate, and an electrolyte temperature deviation based on the first flow data; The first step is to obtain the electrolyte flow rate deviation rate, specifically: obtain the electrolyte flow rate of the flow battery in each monitoring sub-area, and extract the electrolyte benchmark flow rate of the flow battery from the management database , respectively substitute them into the formula , get the electrolyte flow rate deviation rate of the flow battery in the i-th monitoring sub-area Vdr i ,in, Fv i represents the electrolyte flow rate of the flow battery in the i-th monitoring sub-area, i=1, 2, 3, ..., n, where i is the number of each monitoring sub-area; The second step is to obtain the pipeline pressure mutation rate, specifically: obtain the pipeline pressure value of the flow battery in each monitoring sub-area, and use the formula , calculate the pipeline pressure mutation rate of the flow battery in the i-th monitoring sub-area Pmr i ,in, Indicates the i-th monitoring sub-area at the initial moment t 1Measured pipeline pressure value, Indicates the i-th monitoring sub-area at the end time t 2. Measured pipeline pressure value; The third step is to obtain the electrolyte temperature deviation, specifically: obtain the electrolyte temperature of the flow battery in each monitoring sub-area, and extract the electrolyte reference temperature of the flow battery from the management database , respectively substitute them into the formula , get the electrolyte temperature deviation of the flow battery in the i-th monitoring sub-area Tdr i ,in, T i represents the electrolyte temperature of the flow battery in the i-th monitoring sub-area; The fourth step is to read the electrolyte flow rate deviation rate, pipeline pressure mutation rate and electrolyte temperature deviation of the flow battery in each monitoring sub-area, and analyze them to obtain the first flow influence coefficient of the flow battery in each monitoring sub-area. The calculation formula is as follows: ,in, FIC i represents the first flow rate influence coefficient of the flow battery in the i-th monitoring sub-area, Indicates the preset maximum allowable electrolyte flow rate deviation rate, Indicates the preset maximum allowable pipeline pressure mutation rate, Indicates the preset maximum allowable electrolyte temperature deviation, are the weight coefficients of the electrolyte flow rate deviation rate, pipeline pressure mutation rate and electrolyte temperature deviation, respectively, and .

4. The flow control system of a liquid flow battery according to claim 1, characterized in that: The execution mode of the second traffic analysis module is as follows: The first step is to obtain the stack internal resistance and current density of the flow battery in each monitoring sub-area, and use the formula , calculate the growth rate of the internal resistance of the flow battery stack in the i-th monitoring sub-area ,in, represents the internal resistance of the flow battery stack in the i-th monitoring sub-area, represents the initial resistance of the flow battery, represents the current density of the flow battery in the i-th monitoring sub-area, represents the initial current density of the flow battery; The second step is to read the stack internal resistance growth rate and electrolyte concentration of the flow battery in each monitoring sub-area, analyze them, and obtain the second flow influence coefficient of the flow battery in each monitoring sub-area. The calculation formula is as follows: ,in, SIC i represents the second flow rate influence coefficient of the flow battery in the i-th monitoring sub-area, Indicates the electrolyte concentration balance of the flow battery in the i-th monitoring sub-area.

5. A flow control system for a liquid flow battery according to claim 4, characterized in that: The method for obtaining the electrolyte concentration balance of the flow battery in the i-th monitoring sub-area is specifically as follows: Calculate the average electrolyte concentration of the flow battery in the i-th monitoring sub-area , the calculation formula is ,in, represents the electrolyte concentration of the jth sampling unit in the i-th monitoring sub-area, j represents the number of each sampling unit, j = 1, 2, 3, ..., m i , m i represents the total number of sampling units in the i-th monitoring sub-area, where i is the number of each monitoring sub-area; Calculate the electrolyte concentration balance of the flow battery in the i-th monitoring sub-area , the calculation formula is: .

6. The flow control system of a liquid flow battery according to claim 1, characterized in that: The execution mode of the traffic prediction and analysis module is as follows: The first flow influence coefficient and the second flow influence coefficient of the flow battery in each monitoring sub-area are read, a flow prediction index model is established, and the flow prediction index of the flow battery in each monitoring sub-area is obtained by analysis. The calculation formula is as follows: ,in, TPI i represents the flow prediction index of the flow battery in the i-th monitoring sub-area, FIC i represents the first flow rate influence coefficient of the flow battery in the i-th monitoring sub-area, SIC i represents the second flow rate influence coefficient of the flow battery in the i-th monitoring sub-area, is an exponential function.

7. The flow control system of a flow battery according to claim 1, characterized in that: The execution mode of the flow control judgment module is as follows: Read the flow prediction index of the flow battery in the i-th monitoring sub-area TPI i , through the formula , calculate the predicted flow rate of the flow battery in the i-th monitoring sub-area TP i ,in, Indicates the battery design flow rate, represents the correction factor, represents flow efficiency; Get the actual flow rate of the flow battery in the i-th monitoring sub-area , the flow control deviation coefficient of the flow battery in each monitoring sub-area is obtained by analysis, and the calculation formula is as follows: ,in, CDC i The flow control deviation coefficient of the flow battery in the i-th monitoring sub-area; Based on the flow control deviation coefficient of the flow battery in each monitoring sub-area, the flow control deviation of the flow battery in each monitoring sub-area is judged as follows: The flow control deviation coefficient of the liquid flow battery in each monitoring sub-area is read and compared with the preset flow control deviation coefficient threshold. If the flow control deviation coefficient of the liquid flow battery in a monitoring sub-area is less than the preset flow control deviation coefficient threshold, it is judged that there is no deviation abnormality in the flow of the liquid flow battery in the monitoring sub-area and no flow control adjustment operation is required; if the flow control deviation coefficient of the liquid flow battery in a monitoring sub-area is greater than or equal to the preset flow control deviation coefficient threshold, it is judged that the flow deviation of the liquid flow battery in the monitoring sub-area is abnormal, and the flow deviation abnormal data of the liquid flow battery in the monitoring sub-area is marked as the flow deviation judgment result of the liquid flow battery in the monitoring sub-area, and the abnormal data is transmitted to the flow control adjustment module for flow control adjustment.

8. The flow control system of a flow battery according to claim 1, characterized in that: The execution mode of the flow control and regulation module is as follows: Receive the data of abnormal flow deviation in the flow control judgment module, and control and adjust the flow of the flow battery in each monitoring sub-area through the controller. The formula for control and adjustment by the controller is as follows: ,in, It represents the flow control increment output by the controller of the i-th monitoring sub-area at the k-th sampling moment, represents the flow deviation of the flow battery at the kth sampling moment in the i-th monitoring sub-area, represents the flow deviation of the flow battery at the k-1th sampling moment in the i-th monitoring sub-area, represents the flow deviation of the flow battery at the k-2th sampling moment in the i-th monitoring sub-area, represent the proportional, integral and differential coefficients of the i-th monitoring sub-area respectively; ,in, represents the control signal of the flow battery in the i-th monitoring sub-area at the k-th sampling moment, represents the control signal of the flow battery in the i-th monitoring sub-area at the k-1th sampling moment, and k represents the number of each sampling moment; , TP i represents the predicted flow rate of the flow battery in the i-th monitoring sub-area, It represents the actual flow rate of the flow battery in the i-th monitoring sub-area at the k-th sampling moment.

Images