System fault judgment method based on intrinsic characteristics and system sensing characteristics of flow battery and digital system of flow battery

Abstract

The invention relates to the technical field of flow batteries, in particular to a system fault judgment method based on intrinsic characteristics and system sensing characteristics of a flow battery and a digital system of the flow battery. The invention provides a system fault judgment method based on intrinsic characteristics and system perception characteristics of a flow battery, and the method comprises the steps: constructing a standard parameter operation model, and simulating different fault parameter operation models according to the standard parameter operation model; establishing a corresponding relationship between different fault parameter models and fault parameters, and setting and judging the running state of the flow battery system and the similarity between the running state and a standard state according to the corresponding relationship; and setting a similarity threshold value, an alarm threshold value and an energy-saving threshold value to enable the flow battery system to operate in a reasonable state, and predicting possible faults, or providing elimination, overhaul or maintenance information for the possible faults.

Description

Technical Field

[0001] The present disclosure relates to the technical field of liquid flow batteries, and in particular to a system fault judgment method based on intrinsic characteristics of liquid flow batteries and system perception characteristics, and a digital system of liquid flow batteries. Background Art

[0002] As a new type of large-scale electrochemical energy storage device, redox flow battery (RFB) has the characteristics of high capacity, wide application field, and long cycle life. It plays a positive role in alleviating fluctuations in power supply and distribution networks, shaving peaks and filling valleys, and rationally storing and converting renewable energy. However, there are inconsistencies in the manufacturing process of redox flow batteries, such as materials and manufacturing processes, which lead to inconsistencies in battery characteristics such as voltage, internal resistance and capacity of the redox flow battery cells (battery units) that make up the battery stack. During the charging and discharging process, the different working environments of the redox flow battery cells (such as working temperature, working conditions of other redox flow battery cells in contact with the surroundings, etc.) will further lead to gradual changes and differences in their respective working states and aging degrees. The individual differences of the redox flow battery cells lead to the existence of the barrel effect in the integrated single battery stack (battery module, Module) and multi-battery stack (battery pack, Pack) energy storage system, which makes the redox flow energy storage system unable to effectively replenish energy (during charging) and release energy (during discharging), thereby greatly reducing the utilization rate of the system. For large-scale megawatt-class liquid flow battery energy storage systems, there are a large number of liquid flow battery units connected in series and parallel, so the above problems are difficult to avoid. The key to solving this problem is to reasonably arrange and control the balance within and between the battery stacks, which is the key technology to ensure the long-term and effective operation of the liquid flow battery energy storage system.

[0003] From the perspective of battery balancing evaluation indicators, in related research at home and abroad, some studies use battery voltage inconsistency as an evaluation indicator to study balancing control strategies; some use battery capacity as a research object and improve capacity utilization through balancing control strategies; and some use balancing control strategies to improve battery state of charge (SOC) inconsistency, thereby achieving optimal configuration of battery pack energy and improving battery pack safety. The balanced layout of the flow battery energy storage system is mainly reflected in the planning of the system structure, while the balancing control technology is mainly reflected in the design of the balancing control hardware and the formulation of the balancing control strategy. The balancing control technology of the flow battery energy storage system is the basis of battery balancing control management in the flow battery management system (BMS), and the information collection and analysis of the flow battery unit by the battery management system is the basis for the system to perform balancing control.

[0004] Battery SOH (State of Health) refers to the health status of the battery, including performance such as capacity, power, and internal resistance. In more cases, it is a prediction of the life of the battery pack. The SOH value is the ratio of the measured actual capacity of the battery to the rated capacity. At present, the main methods for estimating the SOH of energy storage batteries include direct measurement, model-based methods, and data-driven methods. Establishing an accurate and comprehensive simulation prediction model is the basis for accelerating the progress of R&D testing, judging battery performance and capacity attenuation, and improving the efficiency of the battery stack.

[0005] The above characteristics and failure modes of flow batteries may affect the reliability and safety of related systems. It is necessary to consider the comprehensive use of multiple fault judgment methods and evaluation indicators to timely judge the status of the battery, discover potential faults, and take corresponding maintenance measures to ensure the stable operation of the flow battery system. Summary of the invention

[0006] The present disclosure provides a system fault judgment method based on the intrinsic characteristics of a liquid flow battery and the system perception characteristics and a digital system of a liquid flow battery, so as to at least solve the above technical problems existing in the prior art.

[0007] In a first aspect, the present disclosure provides a system fault judgment method based on intrinsic characteristics and system perception characteristics of a liquid flow battery, wherein the liquid flow battery comprises a positive electrode storage tank, a negative electrode storage tank, a battery stack having a positive electrode chamber and a negative electrode chamber, a positive electrode liquid inlet pipe and a positive electrode liquid outlet pipe connected between the positive electrode storage tank and the positive electrode chamber, a circulating pump and auxiliary equipment installed on the positive electrode liquid inlet pipe, a negative electrode liquid inlet pipe and a negative electrode liquid outlet pipe connected between the negative electrode storage tank and the negative electrode chamber, a circulating pump and auxiliary equipment installed on the negative electrode liquid inlet pipe, and the system fault judgment method comprises:

[0008] Constructing a standard parameter operation model, and simulating different fault parameter operation models according to the standard parameter operation model;

[0009] Establishing the corresponding relationship between different fault parameter models and fault parameters, and judging the operating state of the flow battery system and the similarity between the operating state and the standard state according to the corresponding relationship;

[0010] Set similarity thresholds, alarm thresholds and energy-saving thresholds to make the flow battery system operate in a reasonable state, and predict possible faults, or provide troubleshooting, inspection or maintenance information for possible faults.

[0011] Furthermore, through real-time comparison and optimization between the fault parameter model and the constructed standard parameter operation model, the association probability value between the physical model and the digital model of the flow battery system, and the correlation coefficient and weight coefficient between the auxiliary equipment are adjusted.

[0012] Furthermore, the method of constructing the parameter operation model includes:

[0013] Determine the electrochemical characteristics corresponding to the liquid flow battery system according to the intrinsic physical model of the liquid flow battery system, the intrinsic physical model includes the second-order equivalent circuit model corresponding to the liquid flow battery unit in the liquid flow battery system during the charging and discharging process and the bypass current model corresponding to the liquid flow battery unit, and obtain the intrinsic physical model of the liquid flow battery stack composed of multiple liquid flow battery units in the liquid flow battery system according to the second-order equivalent circuit model corresponding to the liquid flow battery unit during the charging and discharging process and the bypass current model corresponding to the liquid flow battery unit;

[0014] Determining physical characteristics of the flow battery system during the charging and discharging process according to a physical perception model of the flow battery system;

[0015] The analysis results of the liquid flow battery system are determined based on the electrochemical characteristics and the physical characteristics, and compared with the actual measured data.

[0016] Furthermore, a second-order equivalent circuit model is established for each liquid flow battery unit in the liquid flow battery system;

[0017] According to Kirchhoff's circuit law, the circuit dynamic model of the second-order differential network is obtained:

[0018]

[0019] According to the definition of SOC:

[0020] Where Δt is the sampling period, Q n is the rated capacity of the battery, ξ is the charge and discharge efficiency;

[0021] The parameter matrix composed of parameters SOC, U1, and U2 [SOC U1 U2] T As the state variable, the state space equation of the battery cell can be obtained through equations (1) and (2), and the calculation process is:

[0022]

[0023] Get parameter U L The observation equation K(*):

[0024] U L =K(f(SOC),U1,U2)=f(SOC)-U1-U2-I L R o (4)

[0025] The parameters R of the equivalent circuit model are obtained by analyzing the electrochemical impedance test experimental data of the battery cell. o , R1, R2, C1 and C2 and their changes with the state of charge during the charging and discharging process;

[0026] The closed-circuit voltage frequency domain representation is:

[0027]

[0028] Composition voltage difference (U L -U oc ) is constantly changing during the charge and discharge process. L -U oc ) as the output of the dynamic system, and the current parameter I L As the input of the dynamic system, the dynamic system transfer function G(s) is obtained as:

[0029]

[0030] Among them, U oc is the open circuit voltage, R o is the ohmic internal resistance, R1 is the polarization internal resistance of the battery cell, C1 is the polarization capacitance, R2 is the surface equivalent resistance of the battery cell, C2 is the surface equivalent capacitance, I(r) is the circuit current, U L It is the closed circuit voltage when external load is connected.

[0031] Furthermore, based on the electrochemical impedance spectroscopy experimental data of the liquid flow battery cell, the dynamic system characteristics based on the liquid flow battery cell are established, and the second-order equivalent circuit model and the bypass current model are combined to form the intrinsic physical model of the liquid flow battery cell. The intrinsic physical model is combined with the physical perception model of the liquid flow battery system to determine the characteristics of the liquid flow battery system during the charging and discharging process.

[0032] Furthermore, the equivalent impedance Z of each flow battery unit is i =Z i (R Ωi , R cti , R di , C dli , C dt ), i=1~n+1;

[0033] Among them, Z t It is the impedance value converted from the second-order equivalent circuit model and electrochemical impedance spectroscopy parameters.

[0034] Furthermore, the electrochemical impedance spectroscopy parameter R of the liquid flow battery cell is obtained. Ω , R ct , R d , C dl and Cd And the bypass current model is used to obtain the circuit model of the flow battery unit.

[0035] Furthermore, a bypass current model in the battery stack is established based on a battery stack composed of n flow battery units in series: the equivalent impedance Z of each flow battery unit i =Z i (R Ωi , R cti , R di , C dli , C di ), i=1~n+1;

[0036] According to Kirchhoff's circuit laws, the following relationship exists:

[0037]

[0038] are the positive electrode common flow channel and the branch channel current, are the negative electrode common flow channel and branch channel current, I t is the input and output current of the battery stack, i n is the internal current through the nth flow battery cell, R MP is the equivalent resistance of the positive electrode common flow channel, R P is the equivalent resistance of the positive electrode branch channel, R MN is the equivalent resistance of the negative electrode common flow channel, R N is the equivalent resistance of the negative electrode branch channel, Z i (i=1~n+1) is the equivalent impedance of each flow battery unit;

[0039] A dynamic simulation model based on the intrinsic electrochemical characteristics of the liquid flow battery unit is established by matching the bypass current model with the second-order equivalent circuit model, and the dynamic system transfer function based on the liquid flow battery unit is obtained;

[0040] The parameters R of the flow battery cell are obtained by analyzing the electrochemical impedance test experimental data of the flow battery cell. Ω , R ct , R d , C dl and C d , and transmit it to the simulation model of the flow battery unit in real time to reflect the intrinsic electrochemical characteristics of the flow battery unit at each stage of the charge and discharge process;

[0041] Among them, R Ω is the ohmic polarization resistance of the flow battery cell, R ct is the electrochemical polarization resistance, R d is the concentration polarization resistance, C dl is the double layer capacitance, Cd is the concentration capacitance;

[0042] Parameter R Ω , R ct , R d , C dl , C d With parameter R o , R1, R2, C1, and C2 correspond one to one.

[0043] Furthermore, a flow battery simulation training module is established with a flow battery unit or a flow battery stack and its battery system as a dynamic system of the research object;

[0044] At different current parameters I L When used as input to a dynamic system, the voltage parameter (U L -U oc ) as the output of the dynamic system, and add the structural characteristic comprehensive factor set M(*) related to the liquid flow battery unit or battery stack, the environmental coupling factor set T(*) and the system parameter set S(*) characterizing the operation of the liquid flow battery system, which is used to comprehensively describe the digital model of a certain actual liquid flow battery system, and obtain the dynamic system transfer function correction value based on the liquid flow battery unit or battery stack: G(s)+ξ(*), where ξ(*) represents the correction factor;

[0045] Thus, an equivalent circuit model of the flow battery based on electrode processes and bypass current and a parameterized description of the flow battery system can be obtained.

[0046] Furthermore, the flow battery system includes a battery stack, a flow circulation system, a battery support system, and a battery management system;

[0047] The auxiliary equipment includes circulating pumps, valves, pressure transmitters, flow meters, electrolyte heaters, thermocouple thermometers, liquid level gauges, liquid leakage sensors, heat exchangers in the state-of-charge battery and battery support system, ventilation systems, safety systems, hydrogen concentration analysis devices, hydrogen exhaust fans, water-gas separators, cabin temperature and humidity sensors, and pH detectors in the liquid circulation system;

[0048] The circulation pump, valve, pressure transmitter, flow meter, electrolyte heater, thermocouple thermometer, liquid level gauge, liquid leakage sensor and hydrogen concentration analyzer, hydrogen exhaust fan, water-gas separator, cabin temperature and humidity sensor and pH detector in the liquid flow circulation system are used to sense and meet the needs of the liquid flow battery system for active substances participating in the redox reaction in the electrolyte during the charging and discharging process, and collect, diagnose and monitor the operating status and health status of the liquid flow circulation system;

[0049] The heat exchangers, ventilation systems, and safety systems in the battery support system are used to respond to emergencies in the flow battery system;

[0050] A physical perception model of the liquid flow battery system is obtained according to the auxiliary equipment.

[0051] Furthermore, a standard parameter operation map and a fault parameter operation map based on each auxiliary device of the flow battery system are established, and the correlation coefficient and weight coefficient between each auxiliary device are determined to construct a fault diagnosis model of the flow battery system;

[0052] According to the fault diagnosis model, the operating status, health status and similarity of the standard status of the flow battery system are judged in real time;

[0053] By setting similarity thresholds, alarm thresholds, and energy-saving thresholds, the flow battery system can be guided to operate in a reasonable state in a timely manner, and possible faults can be predicted, and guidance on troubleshooting, repair, and maintenance can be provided for possible faults;

[0054] The fault diagnosis model can perform machine learning by comparing fault diagnosis guidance with actual fault repair information feedback, and continuously iterate through real-time comparison and optimization of various graphs (parameters), and continuously adjust the association probability value between the physical model and digital model of the flow battery system, and the correlation coefficient and weight coefficient between various auxiliary equipment.

[0055] A second aspect of the present disclosure provides a digital system for a liquid flow battery, using the system fault judgment method based on the intrinsic characteristics of the liquid flow battery and the system perception characteristics described in the first aspect, comprising: the liquid flow battery includes a perception device and an actuator that performs corresponding actions in linkage;

[0056] Acquire the perception information of the perception device, the perception information is used to characterize the battery intrinsic characteristics and system perception characteristics of the flow battery, and transmit the battery intrinsic characteristics and system perception characteristics information to the terminal module, and the terminal module controls the actuator to perform corresponding actions.

[0057] Further, it also includes a management server and a control system;

[0058] The management server is used for the management and backup of task management servers, operation management servers, data management servers, application management servers and service management servers;

[0059] The control system includes a data input terminal and a data processing platform. The data input terminal is used to obtain control data input by a user and transmit it to the data processing platform.

[0060] The data processing platform can process and process the control data and generate corresponding control commands. The control commands are transmitted to the controller via the control command communication module. The controller is connected to the corresponding actuator through the control circuit.

[0061] Furthermore, the task management server is used to manage battery charging and discharging efficiency tasks, battery system perception tasks, computing and operation and maintenance tasks, battery safe operation tasks, and battery intelligent scheduling tasks;

[0062] The computing management server is used for battery stack polarization process computing, battery stack system optimization computing, battery system perception computing, battery system operation and maintenance index computing, battery intelligent scheduling computing, battery maintenance cycle prediction computing, battery life prediction computing, battery overall performance prediction computing, and artificial intelligence computing and training;

[0063] The data management server is used for basic data cleaning and integration analysis, derivative data generation and analysis, virtual data training and simulation, and virtual and real data fusion;

[0064] The application management server is used for battery performance calculation and application, battery life prediction and application, battery simulation training and application, and battery intelligent scheduling and application;

[0065] The service management server is used to provide services to defined user groups according to a plan.

[0066] Further, the data input terminal is used for data level division, data source division, data function division and data module division;

[0067] The data hierarchy includes component level, functional module level, factory test level, laboratory test level, equipment commissioning level, project site operation and maintenance level, and cloud level;

[0068] The data sources include localized device data, cloud upload data, laboratory test data, factory production test data, component and module test data, and component and module design data;

[0069] The data function division includes normal operation of functional modules, system debugging, normal system operation, and abnormal and fault collection;

[0070] The data modules are divided into those for collecting system scheduling information, real-time collection of system operating status, optimization of system operating process, electrical balance within the fuel cell stack and / or between fuel cell stack groups, equipment safety and debugging, overall equipment performance evaluation, equipment abnormality and fault analysis, equipment troubleshooting and bypass, and regular equipment maintenance.

[0071] Furthermore, the data input terminal is used for data processing and processing;

[0072] The data processing and processing include:

[0073] Sampling data storage and reorganization;

[0074] Data identification, cleaning and management;

[0075] Add additional attributes including historical time and climate, geography and meteorology, equipment type and version, project type and data collection point, historical restoration of charging and discharging demand, historical data of equipment and power grid dispatching, and historical data of equipment operation and maintenance;

[0076] Data processing includes the association and integration of basic data, and the generation and application of derived data.

[0077] Furthermore, it also includes a data acquisition module, which is used to collect:

[0078] Intrinsic characteristics of flow battery cells such as ohmic resistance, double layer capacitance, charge transfer resistance, concentration polarization resistance and concentration capacitance, leakage characteristics such as flow channel leakage resistance, flow channel leakage current, positive / negative electrode side potential and current, electrode and electrode liquid reaction interface temperature;

[0079] The charging and discharging voltage, charging and discharging current, equivalent resistance, charging and discharging time, ambient temperature, pressure loss and internal / external leakage of the battery stack;

[0080] Pipeline pressure, pipeline flow, temperature and leakage of flow battery systems;

[0081] The existence and changes of physical quantities such as combustible and toxic gases, smoke, temperature, humidity, light, insulation, lightning protection, electromagnetic interference resistance, noise resistance, and heating and heat preservation of the battery support system;

[0082] Power conversion efficiency of flow battery system and operating parameters of auxiliary equipment.

[0083] Furthermore, it also includes a terminal operation module of the battery management system;

[0084] The terminal computing modules of the battery management system include:

[0085] Fault handling includes fault detection, fault warning, fault protection and fault isolation;

[0086] The charge and discharge process includes scanning of electrode polarization process, tracking of electrolyte composition and concentration, detection of accumulated by-products, detection of gas evolution rate and optimization of charge and discharge process efficiency;

[0087] The overall performance includes the flow battery system status indicator set (SOX) such as state of charge (SOC), state of health (SOH), state of power (SOP), state of life (SOL), state of energy (SOE), remaining life (RUL), end of life (EOL) and other indicators to predict battery life, auxiliary power loss and optimization, and energy regeneration;

[0088] Battery balancing includes intra-stack balancing and / or electrical balancing between stack groups; regular maintenance such as maintenance trigger logic, maintenance mechanism and effect verification.

[0089] Compared with the prior art, the technical solution provided by the embodiments of the present disclosure has the following advantages:

[0090] The present invention starts from the components (stack and system) of the liquid flow battery system, and digitally plans, organizes and manages the intrinsic characteristics and system perception characteristics of the liquid flow battery system by establishing a physical model of the intrinsic characteristics of the liquid flow battery stack and a physical perception model of the liquid flow battery system. By establishing a (virtual) simulation training module and operation, it helps the liquid flow battery management system to make intelligent predictions on the state of the liquid flow battery system, which is of great help to the fault identification and regular maintenance of the system, and has simulation and prediction functions for the performance of the system under unknown working conditions. The digital model of the liquid flow battery system corresponds to the physical model of the liquid flow battery system, and can effectively and in real time restore the operating state of the system. It has certain intelligent analysis and intelligent prediction functions, and can further integrate the component information of different levels and modules of the liquid flow battery system, and the environmental deployment information under different locations and climates, so as to establish a unified digital platform for systematically tracing a series of information of the liquid flow battery system from design, manufacturing, testing, deployment to operation and maintenance, and scheduling.

[0091] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0092] The above and other objects, features and advantages of the exemplary embodiments of the present disclosure will become readily understood by reading the detailed description below with reference to the accompanying drawings. In the accompanying drawings, several embodiments of the present disclosure are shown in an exemplary and non-limiting manner, in which:

[0093] In the drawings, the same or corresponding reference numerals represent the same or corresponding parts.

[0094] Figure 1 is the electrode equivalent circuit 1;

[0095] Figure 2a is the electrode equivalent circuit 2;

[0096] Figure 2b is the electrode equivalent circuit 2;

[0097] Figure 3a is a schematic diagram of the structure of an electrolytic cell;

[0098] Figure 3b It is a structural schematic diagram of a primary battery;

[0099] Figure 4 It is the equivalent circuit of the flow battery unit based on the electrode process;

[0100] Figure 5 It is a situation where there is a potential difference on both sides of an ion exchange membrane due to the presence of electrolytes of different concentrations on both sides of the membrane;

[0101] Figure 6 The series and parallel connection of RC circuits and their equivalent circuit relationships;

[0102] Figure 7 Schematic diagram of the composition of a flow battery unit (single cell);

[0103] Figure 8 It is the equivalent circuit of the electrode process of the flow battery unit (single cell);

[0104] Figure 9a It is a double resistance layer measurement model based on a certain electrode process;

[0105] Figure 9b It is the impedance spectrum characteristics of the double resistance layer based on a certain electrode process;

[0106] Fig.10 A liquid flow battery system based on a single battery stack and its electrochemical impedance test device;

[0107] Fig.11 It is an electrochemical impedance test device for each flow battery unit in the battery stack;

[0108] Fig.12a A second-order equivalent circuit model for the battery cell charging process;

[0109] Figure 12b A second-order equivalent circuit model for the battery cell charging process;

[0110] Fig.13 It is the equivalent model of flow battery based on leakage current (current distribution part);

[0111] Fig.14 It is the equivalent model of flow battery based on leakage current (impedance distribution part);

[0112] Fig.15 Auxiliary equipment (devices) and system fault judgment model in flow battery energy storage system;

[0113] Fig.16 Evolving testing capabilities for flow battery systems;

[0114] Fig.17 Digital model diagram of the flow battery system.

[0115] Explanation of the numbers in the figure: 1. Circulation pump; 2. Negative electrode side filter; 3. Positive electrode side filter; 4. Negative electrode side liquid storage tank; 5. Positive electrode side liquid storage tank; 6. Valve; 7. Insulation layer; 8. Thermocouple thermometer; 9. Liquid storage tank / fuel stack tray; 10. Liquid leakage sensor; 11. Liquid level sensor; 12. Electric heater; 13. Overflow valve / pressure relief valve; 14. Flow sensor; 15. Pressure transmitter; 16. Fuel stack; 161. Fuel stack front end plate; 162. Fuel stack rear end plate; 163. Negative electrode side current collector; 164. Positive electrode side current collector; 165. Liquid flow battery cell; 166. Ion exchange membrane; 167. Bipolar plate; 168. Positive electrode; 169. Negative electrode; 17. SOC battery; 18. Fuel stack Temperature control box; 100, hydrogen concentration analysis device; 120, electric air valve; 130, three-way connector; 140, hydrogen exhaust fan; 150, water-gas separator; 160, external load; 170, external DC power supply; 180, galvanometer; 19, switching switch; 20, exhaust fan; 21, electric shutters; 23, outer wall and insulation layer of energy storage cabin / environmental cabin; 24, cabin temperature and humidity sensor; 25, acid-base concentration detector; 31, flow meter at the cathode side stack inlet; 32, flow meter at the anode side stack inlet; 33, pressure transmitter at the cathode side stack inlet; 34, pressure transmitter at the anode side stack inlet; 35, pressure transmitter at the cathode side stack outlet; 36, pressure transmitter at the anode side stack outlet. DETAILED DESCRIPTION

[0116] In order to make the purpose, features, and advantages of the present disclosure more obvious and easy to understand, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present disclosure.

[0117] 1. Polarization model of flow battery cell 165 during charging and discharging

[0118] 1.1 Equivalent circuit of electrode

[0119] The following charge transfer reactions occur at the electrodes:

[0120] O+ne→R Formula (1′)

[0121] Where: O represents the oxidation state; R represents the reduction state; n is the number of electron transfers in the electrode reaction. When the above reaction occurs on the electrode, the electrode process goes through four basic steps:

[0122] I. Double-layer charging steps

[0123] When current passes through the electrode, the double layer of the electrode is charged first. The impedance generated during the charging process is caused by the double layer, so the double layer capacitance C is used. dl Represents the equivalent capacitance element in the electrode equivalent circuit.

[0124] II. Ion Migration Process

[0125] When current passes through the electrodes, ions in the electrolyte migrate. The resistance to migration is represented by the resistor R. L It is called solution resistance, and its value is the resistance of the electrolyte solution in which the electrode is located.

[0126] III. Diffusion process of reactant O and product R

[0127] The current passes through the electrode, forming a diffusion layer at the electrode interface. The diffusion layer is composed of countless dx thin layers, and the concentration polarization of each layer can be measured by a capacitor C dx and a resistor R dx Indicates. dx Corresponds to the substance capacity in each dx thin layer of solution, and is therefore proportional to the concentration of substance O; R dx The diffusion resistance of the corresponding dx thin layer solution is inversely proportional to the diffusion coefficient and the solution concentration C. Therefore, the equivalent circuit of concentration polarization consists of concentration capacitance and concentration polarization resistance. They are represented by C d and R d It is theoretically proved that they are connected in series to form an equivalent circuit of concentration polarization.

[0128] IV. Charge transfer process

[0129] When an electric potential is applied to an electrode, an electrochemical reaction will occur. The resistance generated by the charge passing through the interface between the electrode and the solution is equivalent to a resistor, represented by R. ct It represents the measure of the ease of charge transfer. ct Large, indicating that the charge transfer process is difficult; R ct Small, indicating that the charge transfer process is easy. ct The size of R is related to the nature of the electrode reaction and the polarization degree of the electrode process. Different electrode reactions and different polarization degrees will have different R ct In the electrochemical literature, R ct becomes a charge transfer resistor.

[0130] The above electrode process is mainly composed of four basic steps, and each step can be equivalently represented by an electrotechnical element. These electrotechnical elements are connected in the order of charge transfer to form a circuit, which is called an electrode equivalent circuit. The ions that undergo electrode reactions diffuse through the diffusion layer, then enter the double layer and discharge at the electrode interface. It can be seen that the concentration difference polarization equivalent circuit and the charge transfer resistance R ct The experiment has proved that when the current passes through the electrode, the double layer is charged first, and then the electrochemical reaction occurs. Therefore, the charge transfer resistance R ct The concentration difference polarization equivalent circuit forms a series equivalent circuit with the double layer capacitor C dl In parallel. Solution resistance R L It refers to the resistance of the electrolyte solution where the electrode is located (also called electrolyte resistance or ohmic resistance), so R L The parallel circuit formed by other electrotechnical equivalent components is connected in series to form the equivalent circuit of the electrode (Warburg circuit model), such as Figure 1 shown.

[0131] In addition, the above electrode equivalent circuit is not unique. Different circuits can have the same number of time constants and can produce mathematically equivalent frequency responses. The other two equivalent circuits shown in Figure 2 are also often used to describe electrode processes. They are obtained by two completely different physical models, but they also have the same frequency response. The equivalent circuit in Figure 2 (a) can be used to describe two resistance layers and as a measurement model. The equivalent circuit in Figure 2 (b) can be used to describe the reaction principle of two electrochemical steps, or to describe the reaction mechanism of the coating and electrode composition system.

[0132] Since the equivalent circuit model corresponding to the electrode process is not unique, the results are uncertain when using inverse analysis to describe the impedance response.

[0133] 1.2 Equivalent circuit of flow battery cell 165

[0134] The flow battery unit 165 is composed of two half-cells. Each half-cell has an independent chamber containing electrodes and electrolyte, and is separated by an ion exchange membrane 166.

[0135] During the charging process of the flow battery, the flow battery stack 16 acts as an electrolytic cell, and when the flow battery is discharging to a load, the flow battery stack 16 acts as a primary cell.

[0136] like Figure 3a and Figure 3b As shown, during the charge and discharge process of the flow battery unit 165, there are redox reactions in which the electrolyte active substances on the positive and negative sides of the ion exchange membrane 166 and the positive and negative electrodes participate respectively as follows:

[0137]

[0138] It can be seen that in the process of charging and discharging, the liquid flow battery unit 165 has positive and negative electrode equivalent circuits at the same time. During charging, there is a phenomenon that the negative electrode gains electrons and the positive electrode loses electrons; during discharging, there is a phenomenon that the negative electrode loses electrons and the positive electrode gains electrons, and the number of electrons gained and lost is the same. The corresponding net current flowing through the positive and negative electrodes is the same in magnitude and opposite in direction.

[0139] During the charging process of the flow battery cell 165, the following charge transfer reaction occurs at the interface between the negative electrode 169 and the corresponding electrolyte:

[0140] O1+ne→R1 Formula (4′)

[0141] Where: O represents the oxidation state of the active substance in the electrolyte on the negative electrode side; R represents the reduction state of the active substance in the electrolyte on the negative electrode side; n is the number of electron transfers in the electrode reaction.

[0142] During the charging process of the flow battery cell 165, the following charge transfer reaction occurs at the interface between the positive electrode 168 and the corresponding electrolyte:

[0143] R2-ne→O2 formula (5′)

[0144] Where: O represents the oxidation state of the active substance in the electrolyte on the positive electrode side; R represents the reduction state of the active substance in the electrolyte on the positive electrode side; n is the number of electron transfers in the electrode reaction.

[0145] The battery potential of the flow battery cell 165 can be decomposed into losses corresponding to different aspects of the battery. For example, the potential difference between the two electrodes can be expressed as:

[0146] (V a -V c )=(V a -Φ 0,a )+(Φ 0,a -Φ 0,c )+(Φ 0,c -V c ) Formula (6′)

[0147] In formula 6′, Φ 0,a represents the limiting potential in the anode diffusion layer; Φ 0,c Represents the limiting potential in the cathode diffusion layer. (Φ 0,a -Φ 0,c ) represents the voltage drop across the electrolyte solution. According to the definition here, the numerical calculation of the voltage drop requires the calculation of the change in the conductivity of the electrolyte within the diffusion layer.

[0148] (Va -Φ 0,a ) can be expressed by the surface overpotential, namely:

[0149] η s,a =(V a -Φ 0,a )-(V a -Φ 0,a )0Formula (7′)

[0150] In formula 7′, (V a -Φ 0,a ) is the equilibrium difference between the electrode potential and the electrolyte potential near the electrode, which is generally taken as the inner limit of the diffusion layer. If the equilibrium potential is in a layer of the diffusion layer, i (0) measured, then: (V a -V c ) = η s,a +(V a -Φ 0,a )0+(Φ 0,a -Φ 0,c )-η s,c -(V c -Φ 0,c )0Formula (8′)

[0151] In Formula 6′, it can be seen from the battery potential distribution of the liquid flow battery unit 165 that the equivalent circuit components characterizing the liquid flow battery unit 165 are in a series structure (when the total current is equal to the sum of the individual currents, the components are connected in parallel in the equivalent circuit; when the total voltage drop is equal to the sum of the individual voltages, the components are connected in series in the equivalent circuit). Figure 1 The equivalent circuit of the single-side electrode in Figure 2(a) is combined with the measurement model of the electrode process and Figure 3a and Figure 3b The physical structure of the liquid flow battery unit 165 can be obtained as follows:

[0152] Figure 4 The change process of the equivalent circuit in the liquid flow battery unit 165 is shown in FIG. m is the resistance of the ion exchange membrane 166, R aL is the resistance of the electrolyte on the negative electrode side, R cL is the resistance of the electrolyte on the positive electrode side; R Ω =R aL +R m +R cL , R Ω is the equivalent ohmic resistance of the flow battery cell 165 .

[0153] The conductivity of ion exchange membrane depends on the concentration of mobile ions in the membrane and the mobility of ions in the membrane phase. It is related to the ion exchange capacity, water content and cross-linking degree of the membrane. Because the conductivity of ion exchange membrane depends on the concentration of counter ions and Donnan adsorbed ions in the membrane phase, a membrane with high ion exchange capacity, high water content and low cross-linking degree tends to show higher conductivity. For a 1:1 electrolyte solution, the conductivity of the cation exchange membrane is It can be expressed as:

[0154]

[0155] ①In the formula, Λ + and Λ _ is the equivalent conductance of cations and anions in the membrane; and is the concentration of cations, anions and ion exchange groups in the membrane. Because the adsorbed ions can be ignored in dilute solutions, It can be approximated as:

[0156]

[0157] However, since the flux is obtained from the equation, the current can be expressed as follows using the charge neutralization equation:

[0158]

[0159] The conductivity is:

[0160]

[0161] In the formula, z i and is the valence and mobility of ion i in the membrane phase, (ρ0 is the specific flow resistance; ε is the ratio of the liquid in the membrane to the total volume of the membrane, that is, the pore volume fraction).

[0162] The conductivity of ion exchange membrane is an important property of ion exchange membrane, which is usually described by membrane resistance (the product of the reciprocal of conductivity and membrane thickness, Ω.cm).

[0163] It can be seen that the impedance value of the ion exchange membrane is the product of the reciprocal of the conductivity and the membrane thickness, and the conductivity of the ion exchange membrane (Formula ①) is related to the equivalent conductance of cations and anions in the membrane, and the concentration of cations, anions and ion exchange groups in the membrane. Figure 5 It expresses the situation where there is a potential difference on both sides of an ion exchange membrane due to the presence of electrolytes with different concentrations on both sides of the membrane.

[0164] In addition, according to the equivalent circuit principle, the RC parallel equivalent circuit obtained by connecting two sets of RC parallel circuits in series has the following Figure 6 The relationships shown are:

[0165] like Figure 6 As shown, two RC parallel circuits are connected in series, and there is an equivalent RC parallel circuit. Z1, Z3 and Z5 are pure resistors, and Z2, Z4 and Z6 are pure capacitors. According to the principle of equivalent circuit, the impedance of the parallel arrangement is:

[0166]

[0167] According to the equivalent relationship of formula (9') to (11'), we can get:

[0168]

[0169] From formula (13′), we get:

[0170]

[0171] Depend on Figure 4 (b) and Figure 4 (c) As known, when the equivalent circuits of the electrode processes on the positive and negative sides of the flow battery unit 165 are equivalently merged, the following rule is taken into account: the electrochemical impedance complex plane diagram can show different electrode process rules in different frequency ranges, the high-frequency region shows electrochemical polarization (charge transfer), and the low-frequency region shows concentration polarization (mass transfer) (electrochemical behaviors such as adsorption of material particles or generation of intermediate products will be presented in the medium-frequency region with different spectra). The RC parallel circuits representing electrochemical polarization on the positive and negative sides can be meaningfully equivalently merged, and the RC parallel circuits representing concentration polarization on the positive and negative sides can be meaningfully equivalently merged, thereby obtaining a relationship group similar to Formula 14′, corresponding to Figure 4 (c) Equivalent circuit of the flow battery unit 165:

[0172]

[0173] Among them, R ct is the equivalent electrochemical polarization (charge transfer) resistance of the flow battery cell 165, R d is the equivalent concentration polarization resistance of the flow battery unit 165, C dl is the equivalent double-layer capacitance of the flow battery cell 165; C d is the equivalent concentration difference capacitance of the liquid flow battery unit 165. The four equivalent resistance and capacitance parameters of the liquid flow battery unit 165 are related to the resistance and capacitance parameters of the electrode processes on the positive and negative sides thereof, and have respective functional relationships H i (*).

[0174] 2. Electrochemical impedance test device of liquid flow battery unit 165 in battery stack 16

[0175] The various components in the equivalent circuit of the flow battery unit 165 can be measured by full-frequency impedance scanning.

[0176] like Figure 7 As shown, the liquid flow battery unit 165 (single cell) should include all or part of the following components: a) 1 ion exchange membrane 166; b) 2 electrodes; c) 2 electrode frames; d) 2 bipolar plates 167; e) 2 current collecting plates; f) 2 end plates each with an electrolyte inlet and outlet; g) seals, sealing materials for connecting the above components; h) fasteners, such as bolts, springs and washers; i) other auxiliary components.

[0177] Compare Figure 4 and Figure 7 The equivalent circuit involved in the second-order equivalent circuit model of the battery cell has a reasonable corresponding relationship and physical meaning with each component in the liquid flow battery cell 165 (single cell). In the specific test process, the assembly of the liquid flow battery cell 165 (single cell) is completed first, and the internal and external leakage inspection of the single cell is completed according to certain steps; then the single cell test bench is used to perform charge and discharge experiments on the single cell, and the online monitoring of the charge state of the single cell is completed through the SOC battery 17. Under steady-state conditions, the power supply system on the test bench is responsible for applying a constant current input of a certain current density or a constant voltage input of a certain potential to the single cell in the charging cycle, and controlling the output curve of the single cell by adjusting the external load 160 resistance in the discharge cycle; when trying to increase the influence of frequency on macroscopic measurement, the working electrode of the AC impedance tester can be connected to the positive electrode of the single cell, and its counter electrode and reference electrode can be connected to the negative electrode of the single cell; within a certain frequency range, a certain amplitude AC signal (micro-perturbation) is applied to the single cell to test the full-frequency impedance spectrum (the recommended voltage perturbation is less than 10mV). The full-frequency impedance spectrum is given in the form of Nyquist and Bode diagrams. The built-in simulation software of the AC impedance tester can be used to fit the AC impedance spectrum obtained by the test, thereby calculating the ohmic polarization resistance R of the single cell of the flow battery. Ω , electrochemical polarization (charge transfer) resistance R ct , double layer capacitance C dl and concentration polarization impedance R d and concentration capacitance C d (Among them, C dl , C d It is the capacitance caused by non-Faraday current. For details, please refer to the double-layer charging steps in the electrode process, the diffusion process of reactant O and product R and their equivalent circuit model).

[0178] Figure 9a and Figure 9bIt is a double resistance layer measurement model based on a certain electrode process and its impedance spectrum characteristics. Figure 9a and Figure 9b As shown in the figure, the dual resistance measurement model and its spectrum characteristics of a certain electrode process are described by using Nyquist diagram and Bode diagram.

[0179] Electrochemical impedance testing device based on liquid flow battery stack 16 and its application

[0180] The electrochemical impedance test device designed for the liquid flow battery unit 165 in the battery stack 16 in the embodiment of the present disclosure can also measure the electrochemical impedance spectrum characteristics of each liquid flow battery unit 165 in a single stack online one by one, so as to calculate, compare and analyze the spectrum characteristics of each liquid flow battery unit 165 during the charging and discharging process of the battery stack 16, so as to understand the inconsistent (unbalanced) characteristics of the liquid flow battery unit 165 in the battery stack 16. Provide sufficient data support and process preparation for the regular maintenance of the battery stack 16 level and the liquid flow battery unit 165 level (internal positive and negative electrodes) in the battery stack 16.

[0181] Fig.10 A liquid flow battery system based on a single battery stack 16 and an electrochemical impedance testing device thereof; Fig.11 It is an electrochemical impedance testing device for each liquid flow battery unit 165 in the battery stack 16.

[0182] The liquid flow battery system based on the single stack 16 and the electrochemical impedance test device thereof include a circulation pump 1, a negative electrode side filter 2, a positive electrode side filter 3, a negative electrode side liquid storage tank 4, a positive electrode side liquid storage tank 5, an electric control valve 6, a liquid storage tank outer insulation layer 7, a thermocouple thermometer 8, a tray 9 for the liquid storage tank / stack 16, a leakage sensor 10, a liquid level sensor 11, an electric heater 12, an overflow valve / pressure relief valve 13, a flow sensor 14, a pressure transmitter 15, a stack 16, a stack front end plate 161, a stack rear end plate 162, a negative electrode side current collector 163, a positive electrode side current collector 164, a liquid flow battery unit 165, a SOC battery 17 and a temperature control box 18 for the stack. The liquid flow battery system based on the single stack 16 and the electrochemical impedance test device thereof include an ion exchange membrane 166, a bipolar plate 167 (center plate), a positive electrode 168 and a negative electrode 169.

[0183] like Fig.10 and Fig.11As shown, the power supply system can provide DC input during the charging process of the flow battery (for example, constant current charging or constant voltage charging), and can also provide an external load 160 during the discharge process of the flow battery. During the electrochemical impedance experiment, the DC component can be superimposed with the micro-perturbation (small amplitude sinusoidal AC component, so all physical quantities in the electrochemical system, such as electrode potential, polarization current, electrolyte concentration, and surface adsorption concentration, contain DC components and AC components. When the DC component is in a stable state, the derivative of the DC component of all physical quantities with respect to the angular frequency ω is zero, indicating that for the electrode (and electrolyte) system with the presence of a DC component, the electrochemical impedance spectroscopy technology can separate the AC component from the physical quantity containing DC and AC components, so that the phase and amplitude of the AC component remain unchanged, and the intrinsic impedance value of the electrode can be accurately determined. The power supply system has a built-in voltage detection device that can monitor the flow Real-time monitoring of the open circuit voltage of the battery stack 16. The SOC battery 17 is connected in parallel with the liquid flow battery circulation system. The state of charge (SOC) value of the liquid flow battery stack 16 can be calculated based on the open circuit voltage value of the battery stack 16, and important background information is provided during the impedance spectrum characteristic test. The electrochemical impedance test device (AC internal resistance meter) is connected to the bipolar plate 167 (center plate) on the positive and negative sides of each liquid flow battery unit 165 in the battery stack 16 through a switch array. Through real-time switching of the switch array, the impedance spectrum characteristics of the liquid flow battery unit 165 composed of the positive and negative electrodes on both sides of a certain ion exchange membrane 166 (ohmic polarization resistance R of the liquid flow battery single cell) are measured. Ω , electrochemical polarization (charge transfer) resistance R ct , double layer capacitance C dl and concentration polarization impedance R d and concentration capacitance C d). Through this device, various internal resistance values ​​and other electrode process parameters of each liquid flow battery unit 165 in the battery stack 16 can be measured under different charge and discharge conditions (under low SOC range (0% to 90%) and high SOC range (90% to 100%), there are large differences in the polarization levels of each liquid flow battery in the battery stack 16, among which the battery polarization level is more serious when the SOC range is (0% to 10%) and (90% to 100%)), which is helpful for comparing the inconsistency (imbalance) of each liquid flow battery unit 165, and for locating the inconsistency (imbalance) characteristics of a certain liquid flow battery unit 165 in the battery stack 16. Since each liquid flow battery unit 165 in the battery stack 16 is an electrical series structure, the above equivalent circuit for each liquid flow battery unit 165 can be further combined (similar to formula 15'), and with the reasonable use of the switch array, it becomes the basis for characterizing the characteristics of the impedance spectrum of a series (combination) of several liquid flow battery units 165 in the battery stack 16, which helps to find the influence of the inconsistent distribution of electrolyte flow in the battery stack 16 on the liquid flow battery units 165 at different positions in the battery stack 16. It can also be extended to directly measure the impedance spectrum characteristics of the entire battery stack 16, which is used as the basis for comparing the inconsistent (unbalanced) characteristics of each battery stack 16 with a circulation pipeline connection and electrolyte distribution relationship in the liquid flow battery system. The above test device can be used in conjunction with a test box that controls the working environment temperature (T) of the battery stack 16 to further test the electrode process level and the inconsistent (unbalanced) level of charge and discharge of each liquid flow battery unit 165 of the battery stack 16 at some extreme temperatures, and further evaluate the influence of extreme temperature on the charge and discharge level of the liquid flow battery.

[0184] The above test device can be connected with the battery management system, combined with Fig.11 The signal information of each sensor in the liquid flow battery circulation system is used to further detect the relevant physical quantities inside and outside the liquid flow battery system stack 16 and match the relationship between the physical quantities, which is helpful to establish a digital model based on the liquid flow battery system and an information analysis and diagnosis system based on such a digital model.

[0185] It can be seen that the intrinsic electrochemical parameter system for the liquid flow battery unit 165 includes (R Ω , R ct , R d , C d; and C d ), combined with the relevant information of the state of charge (SOC) and the working environment temperature (T) of the liquid flow battery unit 165 during the charging and discharging process, can be used to evaluate in real time the inconsistency (imbalance) level of each liquid flow battery unit 165 in the stack 16 during the charging and discharging process, and provide an effective basis for the regular maintenance of the liquid flow battery stack 16.

[0186] The disclosed embodiment provides a system fault judgment method based on the intrinsic characteristics and system perception characteristics of a liquid flow battery. The liquid flow battery comprises a positive electrode storage tank, a negative electrode storage tank, a battery stack 16 having a positive electrode chamber and a negative electrode chamber, a positive electrode liquid inlet pipe and a positive electrode liquid outlet pipe connected between the positive electrode storage tank and the positive electrode chamber, a circulating pump 1 installed on the positive electrode liquid inlet pipe and auxiliary equipment, a negative electrode liquid inlet pipe and a negative electrode liquid outlet pipe connected between the negative electrode storage tank and the negative electrode chamber, a circulating pump 1 installed on the negative electrode liquid inlet pipe and auxiliary equipment. The system fault judgment method comprises: constructing a standard parameter operation model, simulating different fault parameter operation models according to the standard parameter operation model; establishing a corresponding relationship between different fault parameter models and fault parameters, and judging the operating state of the liquid flow battery system and the similarity between the operating state and the standard state according to the corresponding relationship; setting a similarity threshold, an alarm threshold and an energy-saving threshold so that the liquid flow battery system operates in a reasonable state, and predicts possible faults, or proposes troubleshooting, inspection or maintenance information for possible faults.

[0187] The disclosed embodiment starts from the components of the liquid flow battery system (the stack 16 and the system), and by establishing a physical model of the intrinsic characteristics of the liquid flow battery stack 16 and a physical perception model of the liquid flow battery system, the intrinsic characteristics and system perception characteristics of the liquid flow battery system are digitally planned, organized and managed. By establishing a (virtual) simulation training module and operation, it helps the liquid flow battery management system to make intelligent predictions about the state of the liquid flow battery system, which is of great help to the fault identification and regular maintenance of the system, and has simulation and prediction functions for the performance of the system under unknown working conditions. The digital model of the liquid flow battery system corresponds to the physical model of the liquid flow battery system, and can effectively and in real time restore the operating state of the system. It has certain intelligent analysis and intelligent prediction functions, and can further integrate the component information of different levels and modules of the liquid flow battery system, and the environmental deployment information under different locations and climates, so as to establish a unified digital platform for systematically tracing a series of information of the liquid flow battery system from design, manufacturing, testing, deployment to operation and maintenance, and scheduling.

[0188] In some specific embodiments, by using a fault parameter model and performing real-time comparison and optimization with a standard parameter operation model, adjusting the association probability value between the physical model and the digital model of the flow battery system, and the correlation coefficient and weight coefficient between the auxiliary equipment, the flow battery management system can make an intelligent prediction of the state of the flow battery system, which is of great help in the fault identification and regular maintenance of the system, and has simulation and prediction functions for the performance of the system under unknown working conditions.

[0189] In some specific embodiments, the method for constructing a standard parameter operation model includes: determining the electrochemical characteristics of the stack side corresponding to the flow battery system according to the intrinsic physical model of the flow battery system, the intrinsic physical model including the second-order equivalent circuit model corresponding to the flow battery cell 165 in the flow battery system during the charging and discharging process and the bypass current model corresponding to the flow battery cell 165; obtaining the intrinsic physical model of the flow battery stack 16 composed of multiple flow battery cells 165 in the flow battery system according to the second-order equivalent circuit model corresponding to the flow battery cell 165 during the charging and discharging process and the bypass current model corresponding to the flow battery cell 165; determining the system-side physical characteristics of the flow battery system during the charging and discharging process according to the physical perception model of the flow battery system; determining the overall characteristic spectrum of the flow battery system according to the electrochemical characteristics of the stack side and the physical characteristics of the system side, and comparing them with the actual measured data.

[0190] In order to more accurately reflect the changing laws of the input and output characteristics of the battery cell during the charging and discharging process, a second-order equivalent circuit model can be established to parametrically describe its actual discharge process. Fig.12a and Figure 12b In the second-order equivalent circuit model, there are two RC parallel loops, U oc is the open circuit voltage, R o is the ohmic internal resistance, R1 is the polarization internal resistance of the battery cell, C1 is the polarization capacitance, R2 is the surface equivalent resistance of the battery cell, C2 is the surface equivalent capacitance, I(t) is the circuit current, U L is the closed-circuit voltage when an external load is connected. By analyzing the structure of the above equivalent circuit model, its state equation and observation equation can be obtained.

[0191] In some specific embodiments, a second-order equivalent circuit model is established for each flow battery unit 165 in the flow battery system;

[0192] According to Kirchhoff's circuit law, the circuit dynamic model of the second-order differential network is obtained:

[0193]

[0194] According to the definition of SOC:

[0195] Where Δt is the sampling period, Q n is the rated capacity of the battery, ξ is the charge and discharge efficiency;

[0196] The parameter matrix composed of parameters SOC, U1, and U2 [SOC U1 U2] TAs the state variable, the state space equation of the battery cell can be obtained through equations (1) and (2), and the calculation process is:

[0197]

[0198] Get parameter U L The observation equation K(*):

[0199] U L =K(f(SOC),U1,U2)=f(SOC)-U1-U2-I L R o (4)

[0200] The parameters R of the equivalent circuit model are obtained by analyzing the electrochemical impedance test experimental data of the battery cell. o , R1, R2, C1 and C2 and their changes with the state of charge during the charging and discharging process;

[0201] The closed-circuit voltage frequency domain representation is:

[0202]

[0203] Composition voltage difference (U L -U oc ) is constantly changing during the charge and discharge process. L -U oc ) as the output of the dynamic system, and the current parameter I L As the input of the dynamic system, the dynamic system transfer function G(s) is obtained as:

[0204]

[0205] Among them, U oc is the open circuit voltage, R o is the ohmic internal resistance, R1 is the polarization internal resistance of the battery cell, C1 is the polarization capacitance, R2 is the surface equivalent resistance of the battery cell, C2 is the surface equivalent capacitance, I(r) is the circuit current, U L It is the closed circuit voltage when external load is connected.

[0206] In some specific embodiments, based on the electrochemical impedance spectroscopy experimental data of the liquid flow battery cell 165, dynamic system characteristics based on the liquid flow battery cell 165 are established, and the second-order equivalent circuit model and the bypass current model are combined to form an intrinsic physical model of the liquid flow battery cell 165. The intrinsic physical model is combined with the physical perception model of the liquid flow battery system to determine the characteristics of the liquid flow battery system during the charging and discharging process.

[0207] Equivalent circuit model of flow battery based on electrode processes and bypass current.

[0208] The positive and negative electrode frames of each flow battery unit 165 in the battery stack 16 have a common flow channel and a branch channel (distribution flow channel). The distribution flow channel and the distribution port form in the electrode frame determine the distribution of the electrolyte solution in the reaction chamber where the electrode is located, which indirectly affects the overpotential and the secondary current distribution. The local potential and the secondary current distribution are too high or too low. The overall performance of the battery stack has a great impact. When the battery stack 16 is enlarged, the influence of the flow field will be further aggravated; the flow form of the common pipeline of the battery stack 16 is divided into U-shaped and Z-shaped. Different morphological structures have their own rules for the distribution of electrolyte in each flow battery unit 165 in the battery stack 16, and there is non-uniformity, which will affect the intrinsic electrochemical characteristic values ​​of each flow battery unit 165 related to the electrolyte, thereby affecting the concentration polarization level, charge and discharge depth and voltage uniformity of each flow battery unit 165.

[0209] There are two main factors that cause leakage current (bypass current) in flow batteries: a) The positive and negative electrolytes enter the positive and negative electrodes of each flow battery unit 165 through a common flow channel, and ion channels are formed between the flow battery units 165 through the electrolyte; b) The flow battery units 165 in the battery stack 16 are connected in series to form a voltage gradient, and there is an electron channel. Since the ion channel and the electron channel form a closed loop, leakage current is generated. This part of the current does not pass through the useful load, but is consumed in the ion channel, so it will reduce the energy storage capacity and coulomb efficiency of the flow battery system. The calculation of the leakage current in the battery stack 16 is mainly based on Kirchhoff's circuit law, and an equivalent circuit diagram in the battery stack 16 is established. For the battery stack 16 composed of n flow battery units 165 connected in series, its equivalent circuit is as follows Fig.13 As shown, the model of each liquid flow battery unit 165 is simplified (relative to the description in the previous section). The equivalent impedance Z of each liquid flow battery unit 165 i =Z i (R Ωi , R cti , R di , C dli , C di ), i=1~n+1, is a variable that changes continuously during the charging and discharging process of the battery stack 16.

[0210] In some specific embodiments, the electrochemical impedance spectroscopy parameter R of the liquid flow battery unit 165 is obtained by Ω , R ct , R d , C dl and C d And the bypass current model obtains the circuit model of the liquid flow battery unit 165.

[0211] In some specific embodiments, a bypass current model in the battery stack 16 is established based on a battery stack 16 composed of n liquid flow battery units 165 connected in series: the equivalent impedance Z of each liquid flow battery unit 165 i =Z i (R Ωi , R cti , R di 、c dli , C di ), i = 1 to n + 1; where Z i It is the impedance value converted from the second-order equivalent circuit model and electrochemical impedance spectroscopy parameters.

[0212] like Fig.13 and Fig.14 As shown, V n is the voltage of the nth flow battery cell 165 in the battery stack 16, V; Z n is the equivalent impedance of the nth flow battery in the battery stack 16, Ω; They are the positive electrode common flow channel (main pipe) and branch channel (branch) current, A; They are the negative electrode common flow channel (main pipe) and branch channel (branch) current, A; I t is the input and output current of the battery stack 16; i n is the internal current passing through the nth liquid flow battery unit 165, A; R MP ,R P R is the resistance of the positive electrode common flow channel (main pipe) and branch channel (branch), Ω; MN ,R N is the resistance of the positive electrode common flow channel (main pipe), branch channel (branch), Ω; Z i (i=1~n+1) is the equivalent impedance of each flow battery unit 165, Ω. In addition, the electrolyte resistance R is proportional to its resistivity ρ and the length l of a certain flow channel in the battery stack 16, and inversely proportional to the cross-sectional area S of a certain flow channel in the battery stack 16, satisfying:

[0213] According to Kirchhoff's circuit laws, the following relationship exists:

[0214]

[0215] are the positive common flow channel and the branch channel current, are the negative electrode common flow channel and branch channel current, I t is the input and output current of the battery stack 16, i n is the internal current through the nth flow battery cell 165, R MP is the equivalent resistance of the positive electrode common flow channel, R P is the equivalent resistance of the positive electrode branch channel, RMN is the equivalent resistance of the negative electrode common flow channel, R N is the equivalent resistance of the negative electrode branch channel, Z i (i=1-n+1) is the equivalent impedance of each flow battery unit 165;

[0216] By matching the bypass current model with the second-order equivalent circuit model, a dynamic simulation model based on the intrinsic electrochemical characteristics of the flow battery unit 165 is established, and a dynamic system transfer function based on the flow battery stack 16 is obtained;

[0217] The electrochemical impedance spectrum parameter R of the liquid flow battery unit 165 is obtained by analyzing the electrochemical impedance test experimental data of the liquid flow battery unit 165. Ω , R ct , R d , C dl and C d , and transmit it to the simulation model of the liquid flow battery unit 165 in real time, so as to reflect the intrinsic electrochemical characteristics of the liquid flow battery unit 165 at each stage of the charging and discharging process;

[0218] Among them, R Ω is the ohmic polarization resistance of the flow battery cell 165, R ct is the electrochemical polarization resistance, R d is the concentration polarization resistance, C dl is the double layer capacitance, C d is the concentration capacitance;

[0219] Parameter R Ω , R ct , R d , C dl , C d With parameter R o , R1, R2, C1, and C2 correspond one to one.

[0220] By establishing an electrode process equivalent circuit model of the liquid flow battery unit 165, the parameters can be matched with the second-order equivalent circuit model, and the transfer function of the dynamic system based on the liquid flow battery unit 165 (reference formula 21) can be obtained, thereby establishing a dynamic simulation model based on the intrinsic electrochemical characteristics of the liquid flow battery unit 165. The parameter spectrum (R0, R1, R2, C1 and C2) in the equivalent circuit model is obtained by analyzing the electrochemical impedance test experimental data of the liquid flow battery unit 165, and is transmitted to the simulation model of the liquid flow battery unit 165 in real time to reflect the intrinsic electrochemical characteristics of the liquid flow battery unit 165 at various stages (under different states of charge (SOC)) during the charging and discharging process. Thus, a certain liquid flow battery simulation training module (a dynamic system with the liquid flow battery unit 165 or the liquid flow battery stack 16 and its battery system as the research object) is established under different current parameters I LWhen used as input to a dynamic system, the voltage parameter (U L -U oc ) as the output of the dynamic system, and add the structural characteristic comprehensive factor set M(*) related to the liquid flow battery monomer (or battery stack 16), the environmental coupling factor set T(*) and the system parameter set S(*) characterizing the operation of the liquid flow battery system, etc., to comprehensively describe the digital model of a liquid flow battery system in actual operation, and obtain the dynamic system transfer function correction value based on the liquid flow battery monomer (or battery stack 16): G(s)+ξ(*), where ξ(*) represents the correction factor. In this way, the liquid flow battery equivalent circuit model based on the electrode process and bypass current and the parameterized description of the liquid flow battery system can be obtained.

[0221] In some specific embodiments, a flow battery simulation training module is established by taking the flow battery unit 165 or the flow battery stack 16 and its battery system as a dynamic system of the research object;

[0222] At different current parameters I L When used as input to a dynamic system, the voltage parameter (U L -U oc ) as the output of the dynamic system, and add the structural characteristic comprehensive factor set M(*) related to the liquid flow battery unit 165 or the battery stack 16, the environmental coupling factor set T(*) and the system parameter set S(*) characterizing the operation of the liquid flow battery system, which is used to comprehensively describe the digital model of a certain actual liquid flow battery system, and obtain the dynamic system transfer function correction value based on the liquid flow battery unit 165 or the battery stack 16: G(s)+ξ(*), where ξ(*) represents the correction factor;

[0223] Thus, an equivalent circuit model of the flow battery based on electrode processes and bypass current and a parameterized description of the flow battery system can be obtained.

[0224] Fig.15The auxiliary equipment in the liquid flow battery energy storage system includes a circulation pump 1, a stack 16 / stack group, a cathode electrolyte storage tank, an anode electrolyte storage tank, a cathode electrolyte filter, an anode electrolyte filter, a valve 6, a thermocouple thermometer 8, an insulation layer 7, a hydrogen concentration analyzer 100 (combustible gas detector), a pressure relief valve / drain valve, an electric air valve 120, a three-way connector 130, a hydrogen exhaust fan 140, a water-gas separator 150, an external load 160, an external DC power supply 170, a galvanometer 180, a switch 19, an exhaust fan 20, an electric shutter 21, a hydrogen concentration Analytical device 100 (combustible gas detector), energy storage cabin / environmental cabin outer wall and insulation layer 23, cabin temperature and humidity sensor 24, acid-base concentration detector 25, state of charge battery (SOC battery 17), tray 9 for battery stack 16 / battery stack 16 group, tray 9 for liquid storage tank, liquid leakage sensor, liquid level sensor 11, flow meter 31 at the cathode side battery stack inlet, flow meter 32 at the anode side battery stack inlet, pressure transmitter 33 at the cathode side battery stack inlet, pressure transmitter 34 at the anode side battery stack inlet, pressure transmitter 35 at the cathode side battery stack outlet and pressure transmitter 35 at the anode side battery stack outlet.

[0225] like Fig.15As shown, the auxiliary equipment of the liquid flow battery system mainly includes the circulation pump 1, valve 6, pressure transmitter 15, flow meter, electrolyte heater, thermocouple thermometer 8, liquid level gauge, liquid leakage sensor, etc. in the liquid flow circulation system and the heat exchanger, ventilation system, safety system, hydrogen concentration analysis device, hydrogen exhaust fan, water gas separator, cabin temperature and humidity sensor and pH detector, etc. in the battery support system. The former is mainly used to sense and meet the needs of the liquid flow battery system for the active substances involved in the redox reaction in the electrolyte during the charging and discharging process, and to collect, diagnose and monitor the operating status and health status of the liquid flow circulation system; the latter is mainly used to improve the ability and effect of the liquid flow battery system to respond to sudden (safety) events. By establishing a standard parameter operation map (matrix) and a fault parameter operation map (matrix) based on each auxiliary equipment (device) of the flow battery system, and determining the correlation coefficient and weight coefficient between each operation parameter of each auxiliary equipment (device), a fault diagnosis model of the flow battery system can be constructed, and the similarity between the operation state, health state and standard state of the flow battery system can be judged in real time; by setting parameters such as similarity threshold, alarm threshold, energy-saving threshold, etc., the flow battery system can be guided to operate in a reasonable state in a timely manner, and possible faults can be predicted, and guidance opinions such as elimination, repair and maintenance can be proposed for possible faults. The fault diagnosis model can perform machine learning by comparing the fault diagnosis guidance opinions with the actual fault repair information feedback, and continuously iterates through real-time comparison and optimization of the map, real-time comparison and optimization of parameters (coefficients), etc., and continuously adjusts the association probability value between the physical model and the digital model of the flow battery system, the correlation coefficient and weight coefficient between each auxiliary equipment (device), etc.

[0226] like Fig.16 As shown, the liquid flow battery system includes a battery stack, a liquid flow circulation system, a battery support system and a battery management system.

[0227] The liquid flow battery energy system includes a power conversion system for exchanging electric energy with the energy storage system and the outside. This process is monitored by the liquid flow battery management system. The traditional liquid flow battery system collects the terminal voltage U oc, used by the battery management system to estimate the state of charge (SOC) and other information of the liquid flow battery system during the charging and discharging process. The battery management system will collect sensor signals from the liquid flow battery system in real time to analyze and determine the liquid flow circulation state of the liquid flow battery system; the battery management system will collect sensor signals from the battery support system in real time to analyze and determine the safe operation state of the liquid flow battery system; the battery management system executes the charging and discharging process of the liquid flow battery system through the estimated value of the state of charge and the terminal voltage value of the battery stack 16, and completes the electric energy storage and release of the liquid flow battery system through the power conversion system. For the intelligent liquid flow battery system, in addition to the traditional modules and functions of the liquid flow battery system, the real-time measurement of the intrinsic electrochemical characteristic values ​​of each liquid flow battery unit 165 in the battery stack 16 is added. This type of characteristic value will be combined with various real-time operating conditions of the liquid flow battery to collect information and feedback to the liquid flow battery management in real time for further monitoring the operating state of each battery stack 16 in the system. At the same time, the above-mentioned comprehensive information group will be transmitted to the battery simulation training module located in the cloud device in real time, and by collecting limited historical data, it will further simulate the possible charging and discharging state of the liquid flow battery system under various operating conditions. This digital model (digital twin) based on the real liquid flow battery system and powerful online data storage capabilities, analysis, comparison and calculation functions can simulate the performance of the liquid flow battery system under some unknown conditions based on the performance of the liquid flow battery system under known conditions. The (virtual) simulation training module can help the liquid flow battery management system generate more intelligent analysis and evaluation methods, diagnosis and early warning logic, management and execution calculation schemes, and provide the big data case support and expert-level fault diagnosis services required for long-term maintenance-free operation of offline deployed liquid flow battery systems. Fig.17 As shown, the structure and partial functions of a digital model of a flow battery system.

[0228] In some specific embodiments, the liquid flow battery system includes a battery stack, a liquid flow circulation system, a battery support system, and a battery management system. The auxiliary equipment includes a circulation pump 1, a valve 6, a pressure transmitter 15, a flow meter, an electrolyte heater, a thermocouple thermometer 8, a liquid level meter, a liquid leakage sensor, a state of charge battery and a heat exchanger in the battery support system, a ventilation system, a safety system, a hydrogen concentration analysis device 100, a hydrogen exhaust fan 140, a water vapor separator 150, a cabin temperature and humidity sensor 24, and a pH detector in the liquid flow circulation system; a circulation pump 1, a valve 6, a pressure transmitter 15, a flow meter, an electrolyte heater, a thermocouple thermometer 8, a liquid level meter, a liquid leakage sensor, and The hydrogen concentration analyzer 100, hydrogen exhaust fan 140, water vapor separator 150, cabin temperature and humidity sensor 24 and pH detector in the state of charge battery and battery support system are used to sense and meet the needs of the liquid flow battery system for active substances participating in the redox reaction in the electrolyte during the charging and discharging process, and to collect, diagnose and monitor the operating status and health status of the liquid flow circulation system; the heat exchanger, ventilation system and safety system in the battery support system are used to respond to emergencies in the liquid flow battery system; the physical perception model of the liquid flow battery system is obtained based on the operating parameters of the auxiliary equipment.

[0229] In some specific embodiments, a standard parameter operation map and a fault parameter operation map based on each auxiliary equipment of the liquid flow battery system are established, and the correlation coefficient and weight coefficient between each operating parameter of each auxiliary equipment are determined to construct a fault diagnosis model of the liquid flow battery system; the similarity between the operating state, health state and standard state of the liquid flow battery system is judged in real time according to the fault diagnosis model; by setting a similarity threshold, an alarm threshold and an energy-saving threshold, the liquid flow battery system is timely guided to operate in a reasonable state, and possible faults are predicted, and guidance opinions such as elimination, inspection and maintenance are proposed for possible faults; the fault diagnosis model can perform machine learning by comparing the fault diagnosis guidance opinions with the actual fault inspection and repair information feedback, and continuously iterates through methods such as real-time comparison and optimization of various maps (parameters), and continuously adjusts the association probability value between the physical model and the digital model of the liquid flow battery system, and the correlation coefficient and weight coefficient between the auxiliary equipment.

[0230] The digital system of the liquid flow battery provided by the embodiment of the present disclosure uses the system fault judgment method based on the intrinsic characteristics of the liquid flow battery and the system perception characteristics provided by the embodiment of the present disclosure, including: the liquid flow battery includes a perception device and an actuator that performs corresponding actions in a linked manner; the perception information of the perception device is obtained, and the perception information is used to characterize the battery intrinsic characteristics and system perception characteristics of the liquid flow battery, and the battery intrinsic characteristics and system perception characteristics information are transmitted to the terminal module, and the terminal module controls the actuator to perform corresponding actions.

[0231] In some specific implementations, a management server and a control system are also included; the management server includes a task management server, an operation management server, a data management server, an application management server, and a service management server. The management server is used for the management and backup of the task management server, the operation management server, the data management server, the application management server, and the service management server; the control system includes a data input terminal and a data processing platform, the data input terminal is used to obtain the control data input by the user and transmit it to the data processing platform, the data processing platform can process and process the control data and generate corresponding control commands, the control commands are transmitted to the controller via the control command communication module, and the controller is connected to the corresponding actuator through the control circuit.

[0232] In some specific implementations, the task management server is used for the management of battery charging and discharging efficiency tasks, battery system perception tasks, calculation and operation and maintenance tasks, battery safe operation tasks, and battery intelligent scheduling tasks; the calculation management server is used for the calculation of the polarization process of the battery stack 16, the calculation of the battery stack 16 system optimization, the battery system perception calculation, the battery system operation and maintenance index calculation, the battery intelligent scheduling calculation, the battery maintenance cycle prediction calculation, the battery life prediction calculation, the battery overall performance prediction calculation, and artificial intelligence calculation and training; the data management server is used for basic data cleaning and integration analysis, derivative data generation and analysis, virtual data training and simulation, virtual and real data fusion; the application management server is used for battery performance calculation and application, battery life prediction and application, battery simulation training and application, battery intelligent scheduling and application; the service management server is used to provide services to defined user groups as planned.

[0233] In some specific embodiments, the data input terminal is used for data hierarchy division, data source division, data function division and data module division; the data hierarchy division includes component level, functional module level, factory test level, laboratory test level, equipment debugging level, project site operation and maintenance level, and cloud level; the data source division includes data in localized equipment, cloud upload data, laboratory test data, factory production test data, component and module test data, and component and module design data; the data function division includes normal operation of functional modules, system debugging, normal operation of the system, and abnormality and fault collection; the data module division includes system scheduling information collection, real-time collection of system operation status, optimization of system operation process, electrical balance within the battery stack 16 and / or between battery stack groups, equipment safety and debugging, overall equipment performance evaluation, equipment abnormality and fault analysis, equipment troubleshooting and bypass, and equipment regular maintenance.

[0234] In some specific embodiments, the data input terminal is used for data processing and processing; data processing and processing include: warehousing and reorganization of sampled data; data identification, cleaning and management; adding additional attributes including historical time and climate, geography and meteorology, equipment type and version, project type and data collection points, historical restoration of charging and discharging demand, historical data of equipment and power grid dispatch, and historical data of equipment operation and maintenance; data processing includes the association and integration of basic data, and the generation and application of derivative data.

[0235] In some specific embodiments, a data acquisition module is also included, and the data acquisition module is used to collect: intrinsic characteristic quantities of the liquid flow battery unit 165 such as ohmic resistance, double-layer capacitance, charge transfer resistance, concentration polarization resistance and concentration capacitance, leakage characteristic quantities such as flow channel leakage resistance, flow channel leakage current, positive / negative electrode side potential and current, electrode and electrode liquid reaction interface temperature; charge and discharge voltage, charge and discharge current, equivalent resistance, charge and discharge time, ambient temperature, pressure loss and internal / external leakage of the battery stack 16; pipeline pressure, pipeline flow, temperature and leakage of the liquid flow battery system; the existence and changes of physical quantities such as combustible and toxic gases, smoke, temperature, humidity, light, insulation, lightning protection, anti-electromagnetic interference, anti-noise and heating and insulation of the battery support system; power conversion efficiency of the liquid flow battery system, auxiliary equipment operating parameters, etc.

[0236] In some specific implementations, it also includes a terminal operation module of the battery management system;

[0237] The terminal operation module of the battery management system includes fault handling including fault detection, fault warning, fault protection and fault isolation; charging and discharging processes such as electrode polarization process scanning, electrolyte composition, concentration tracking, by-product cumulative amount detection, gas evolution rate detection and charging and discharging process efficiency optimization; overall performance includes liquid flow battery system status indicator set (SOX) such as state of charge (SOC), state of health (SOH), state of power (SOP), state of life (SOL), state of energy (SOE), battery remaining life (RUL), battery end of life (EOL) and other indicators for predicting battery life, etc., indicator evaluation, auxiliary power loss and optimization and energy regeneration; battery balancing includes balancing within the battery stack 16 and / or electrical balancing between groups of the battery stack 16; regular maintenance includes maintenance trigger logic, maintenance mechanism and effect verification, etc.

[0238] The present invention starts from the components of the liquid flow battery system (the battery stack 16 and the system), and by establishing a physical model of the intrinsic characteristics of the liquid flow battery stack 16 and a physical perception model of the liquid flow battery system, the intrinsic characteristics and system perception characteristics of the liquid flow battery system are digitally planned, organized and managed. By establishing a (virtual) simulation training module and operation, it helps the liquid flow battery management system to make intelligent predictions on the state of the liquid flow battery system, which is of great help to the fault identification and regular maintenance of the system, and has simulation and prediction functions for the performance of the system under unknown working conditions. The digital model of the liquid flow battery system corresponds to the physical model of the liquid flow battery system, and can effectively and real-time restore the operating state of the system. It has certain intelligent analysis and intelligent prediction functions, and can further integrate the component information of different levels and modules of the liquid flow battery system, and the environmental deployment information under different locations and climates, so as to establish a unified digital platform for systematically tracing a series of information of the liquid flow battery system from design, manufacturing, testing, deployment to operation and maintenance, and scheduling.

[0239] The present invention starts from the components of the liquid flow battery system (the battery stack 16 and the system), and by establishing a physical model of the intrinsic characteristics of the liquid flow battery stack 16 and a physical perception model of the liquid flow battery system, the intrinsic characteristics and system perception characteristics of the liquid flow battery system are digitally planned, organized and managed. By establishing a (virtual) simulation training module and operation, it helps the liquid flow battery management system to make intelligent predictions on the state of the liquid flow battery system, which is of great help to the fault identification and regular maintenance of the system, and has simulation and prediction functions for the performance of the system under unknown working conditions. The digital model of the liquid flow battery system corresponds to the physical model of the liquid flow battery system, and can effectively and real-time restore the operating state of the system. It has certain intelligent analysis and intelligent prediction functions, and can further integrate the component information of different levels and modules of the liquid flow battery system, and the environmental deployment information under different locations and climates, so as to establish a unified digital platform for systematically tracing a series of information of the liquid flow battery system from design, manufacturing, testing, deployment to operation and maintenance, and scheduling.

[0240] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0241] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of the present disclosure, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0242] The above are only specific embodiments of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present disclosure, which should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A system fault judgment method based on the intrinsic characteristics and system perception characteristics of a liquid flow battery, wherein the liquid flow battery comprises a positive electrode storage tank, a negative electrode storage tank, a battery stack having a positive electrode chamber and a negative electrode chamber, a positive electrode liquid inlet pipe and a positive electrode liquid outlet pipe connected between the positive electrode storage tank and the positive electrode chamber, a circulating pump installed on the positive electrode liquid inlet pipe and auxiliary equipment; a negative electrode liquid inlet pipe and a negative electrode liquid outlet pipe connected between the negative electrode storage tank and the negative electrode chamber, a circulating pump installed on the negative electrode liquid inlet pipe and auxiliary equipment, characterized in that: The system fault judgment method comprises: Constructing a standard parameter operation model, and simulating different fault parameter operation models according to the standard parameter operation model; Establishing the corresponding relationship between different fault parameter models and fault parameters, and judging the operating state of the flow battery system and the similarity between the operating state and the standard state according to the corresponding relationship; Set similarity thresholds, alarm thresholds and energy-saving thresholds to make the flow battery system operate in a reasonable state, and predict possible faults, or provide troubleshooting, inspection or maintenance information for possible faults.

2. The system fault judgment method based on the intrinsic characteristics of the flow battery and the system perception characteristics according to claim 1 is characterized in that: Through real-time comparison and optimization of the fault parameter model and the constructed standard parameter operation model, the association probability value between the physical model and the digital model of the flow battery system, and the correlation coefficient and weight coefficient between the auxiliary equipment are adjusted.

3. The system fault judgment method based on the intrinsic characteristics of the flow battery and the system perception characteristics according to claim 1 is characterized in that: Methods for building parameter-based models include: Determine the electrochemical characteristics corresponding to the liquid flow battery system according to the intrinsic physical model of the liquid flow battery system, the intrinsic physical model includes the second-order equivalent circuit model corresponding to the liquid flow battery unit in the liquid flow battery system during the charging and discharging process and the bypass current model corresponding to the liquid flow battery unit, and obtain the intrinsic physical model of the liquid flow battery stack composed of multiple liquid flow battery units in the liquid flow battery system according to the second-order equivalent circuit model corresponding to the liquid flow battery unit during the charging and discharging process and the bypass current model corresponding to the liquid flow battery unit; Determining physical characteristics of the flow battery system during the charging and discharging process according to a physical perception model of the flow battery system; The analysis results of the liquid flow battery system are determined based on the electrochemical characteristics and the physical characteristics, and compared with the actual measured data.

4. The system fault judgment method based on the intrinsic characteristics of the flow battery and the system perception characteristics according to claim 3 is characterized in that: For each liquid flow battery unit in the liquid flow battery system, a second-order equivalent circuit model is established; According to Kirchhoff's circuit law, the circuit dynamic model of the second-order differential network is obtained: According to the definition of SOC: Where Δt is the sampling period, Q n is the rated capacity of the battery, ξ is the charge and discharge efficiency; The parameter matrix composed of parameters SOC, U1, and U2 [SOC U1 U2] T As the state variable, the state space equation of the battery cell can be obtained through equations (1) and (2), and the calculation process is: Get parameter U L The observation equation K(*): U L =K(f(SOC),U1,U2)=f(SOC)-U1-U2-I L R o (4), The parameters R of the equivalent circuit model are obtained by analyzing the electrochemical impedance test experimental data of the battery cell. o , R1, R2, C1 and C2 and their changes with the state of charge during the charging and discharging process; The closed-circuit voltage frequency domain representation is: Composition voltage difference (U L -U oc ) is constantly changing during the charge and discharge process. L -U oc ) as the output of the dynamic system, and the current parameter I L As the input of the dynamic system, the dynamic system transfer function G(s) is obtained as: Among them, U oc is the open circuit voltage, R o is the ohmic internal resistance, R1 is the polarization internal resistance of the battery cell, C1 is the polarization capacitance, R2 is the surface equivalent resistance of the battery cell, C2 is the surface equivalent capacitance, I(t) is the circuit current, U L It is the closed circuit voltage when external load is connected.

5. The system fault judgment method based on the intrinsic characteristics of the flow battery and the system perception characteristics according to claim 3 is characterized in that: Based on the electrochemical impedance spectroscopy experimental data of liquid flow battery cells, the dynamic system characteristics of the liquid flow battery cells are established, and the second-order equivalent circuit model and the bypass current model are combined to form the intrinsic physical model of the liquid flow battery cells. The intrinsic physical model is combined with the physical perception model of the liquid flow battery system to determine the characteristics of the liquid flow battery system during the charging and discharging process.

6. The system fault judgment method based on the intrinsic characteristics of the flow battery and the system perception characteristics according to claim 3 is characterized in that: The equivalent impedance Z of each flow battery unit i =Z i (R Ωi , R cti , R di , C dli , C di ), i=1~n+1; Among them, Z i It is the impedance value converted from the second-order equivalent circuit model and electrochemical impedance spectroscopy parameters.

7. The system fault judgment method based on the intrinsic characteristics of the flow battery and the system perception characteristics according to claim 3 is characterized in that: The electrochemical impedance spectroscopy parameters R of the flow battery cell are obtained by Ω , R ct , R d , C dl and C d And the bypass current model is used to obtain the circuit model of the flow battery unit.

8. The system fault judgment method based on the intrinsic characteristics of the flow battery and the system perception characteristics according to claim 3 is characterized in that: Based on the stack composed of n flow battery units in series, the bypass current model in the stack is established: the equivalent impedance Z of each flow battery unit i =Z i (R Ωi , R cti , R di , C dli , C di ), i=1~n+1; According to Kirchhoff's circuit laws, the following relationship exists: are the positive electrode common flow channel and the branch channel current, are the negative electrode common flow channel and branch channel current, I t is the input and output current of the battery stack, i n is the internal current through the nth flow battery cell, R MP is the equivalent resistance of the positive electrode common flow channel, R P is the equivalent resistance of the positive electrode branch channel, R MN is the equivalent resistance of the negative electrode common flow channel, R N is the equivalent resistance of the negative electrode branch channel, Z i (i=1~n+1) is the equivalent impedance of each flow battery unit; By matching the bypass current model with the second-order equivalent circuit model, a dynamic simulation model based on the intrinsic electrochemical characteristics of the flow battery unit is established, and the dynamic system transfer function based on the flow battery unit is obtained; The parameters R of the flow battery cell are obtained by analyzing the electrochemical impedance test experimental data of the flow battery cell. Ω , R ct , R d , C dl and C d , and transmit it to the simulation model of the flow battery unit in real time to reflect the intrinsic electrochemical characteristics of the flow battery unit at each stage of the charge and discharge process; Among them, R Ω is the ohmic polarization resistance of the flow battery cell, R ct is the electrochemical polarization resistance, R d is the concentration polarization resistance, C dl is the double layer capacitance, C d is the concentration capacitance; Parameter R Ω , R ct , R d , C dl , C d With parameter R o , R1, R2, C1, and C2 correspond one to one.

9. The method for determining system faults based on intrinsic characteristics of a flow battery and system sensing characteristics according to claim 8, characterized in that: Taking the liquid flow battery unit or liquid flow battery stack and its battery system as the dynamic system of the research object, a liquid flow battery simulation training module is established; At different current parameters I L When used as input to a dynamic system, the voltage parameter (U L -U oc ) as the output of the dynamic system, and add the structural characteristic comprehensive factor set M(*) related to the liquid flow battery unit or battery stack, the environmental coupling factor set T(*) and the system parameter set S(*) characterizing the operation of the liquid flow battery system, which is used to comprehensively describe the digital model of a certain actual liquid flow battery system, and obtain the dynamic system transfer function correction value based on the liquid flow battery unit or battery stack: G(s)+ξ(*), where ξ(*) represents the correction factor; Thus, an equivalent circuit model of the flow battery based on electrode processes and bypass current and a parameterized description of the flow battery system can be obtained.

10. The method for determining system faults based on intrinsic characteristics of a flow battery and system sensing characteristics according to claim 3, characterized in that: The flow battery system includes a battery stack, a flow circulation system, a battery support system, and a battery management system; The auxiliary equipment includes circulating pumps, valves, pressure transmitters, flow meters, electrolyte heaters, thermocouple thermometers, liquid level gauges, liquid leakage sensors, heat exchangers in the state-of-charge battery and battery support system, ventilation systems, safety systems, hydrogen concentration analysis devices, hydrogen exhaust fans, water-gas separators, cabin temperature and humidity sensors, and pH detectors in the liquid circulation system; The circulation pump, valve, pressure transmitter, flow meter, electrolyte heater, thermocouple thermometer, liquid level gauge, liquid leakage sensor and hydrogen concentration analyzer, hydrogen exhaust fan, water-gas separator, cabin temperature and humidity sensor and pH detector in the liquid flow circulation system are used to sense and meet the needs of the liquid flow battery system for active substances participating in the redox reaction in the electrolyte during the charging and discharging process, and collect, diagnose and monitor the operating status and health status of the liquid flow circulation system; The heat exchangers, ventilation systems, and safety systems in the battery support system are used to respond to emergencies in the flow battery system; A physical perception model of the liquid flow battery system is obtained according to the auxiliary equipment.

11. The system fault judgment method based on the intrinsic characteristics of the flow battery and the system perception characteristics according to claim 10, characterized in that: Establish standard parameter operation maps and fault parameter operation maps of various auxiliary equipment of the flow battery system, determine the correlation coefficients and weight coefficients between various auxiliary equipment, and build a fault diagnosis model for the flow battery system; According to the fault diagnosis model, the operating status, health status and similarity of the standard status of the flow battery system are judged in real time; By setting similarity thresholds, alarm thresholds, and energy-saving thresholds, the flow battery system can be guided to operate in a reasonable state in a timely manner, and possible faults can be predicted, and guidance on troubleshooting, repair, and maintenance can be provided for possible faults; The fault diagnosis model can perform machine learning by comparing fault diagnosis guidance with actual fault repair information feedback, and continuously iterate through real-time comparison and optimization of various graphs, continuously adjusting the association probability value between the physical model and digital model of the flow battery system, and the correlation coefficient and weight coefficient between various auxiliary equipment.

12. A digital system of a liquid flow battery, using the system fault judgment method based on the intrinsic characteristics of the liquid flow battery and the system perception characteristics according to any one of claims 1 to 11, characterized in that: include: The flow battery includes a sensing device and an actuator that performs corresponding actions in linkage; Acquire the perception information of the perception device, the perception information is used to characterize the battery intrinsic characteristics and system perception characteristics of the flow battery, and transmit the battery intrinsic characteristics and system perception characteristics information to the terminal module, and the terminal module controls the actuator to perform corresponding actions.

13. The digital system of flow battery according to claim 12, characterized in that: It also includes management servers and control systems; The management server is used for the management and backup of task management servers, operation management servers, data management servers, application management servers and service management servers; The control system includes a data input terminal and a data processing platform. The data input terminal is used to obtain control data input by a user and transmit it to the data processing platform. The data processing platform can process and process the control data and generate corresponding control commands. The control commands are transmitted to the controller via the control command communication module. The controller is connected to the corresponding actuator through the control circuit.

14. The digital system of flow battery according to claim 13, characterized in that: The task management server is used to manage battery charging and discharging efficiency tasks, battery system perception tasks, computing and operation and maintenance tasks, battery safe operation tasks, and battery intelligent scheduling tasks; The computing management server is used for battery stack polarization process computing, battery stack system optimization computing, battery system perception computing, battery system operation and maintenance index computing, battery intelligent scheduling computing, battery maintenance cycle prediction computing, battery life prediction computing, battery overall performance prediction computing, and artificial intelligence computing and training; The data management server is used for basic data cleaning and integration analysis, derivative data generation and analysis, virtual data training and simulation, and virtual and real data fusion; The application management server is used for battery performance calculation and application, battery life prediction and application, battery simulation training and application, and battery intelligent scheduling and application; The service management server is used to provide services to defined user groups according to a plan.

15. The digital system of flow battery according to claim 13, characterized in that: The data input terminal is used for data level division, data source division, data function division and data module division; The data hierarchy includes component level, functional module level, factory test level, laboratory test level, equipment commissioning level, project site operation and maintenance level, and cloud level; The data sources include localized device data, cloud upload data, laboratory test data, factory production test data, component and module test data, and component and module design data; The data function division includes normal operation of functional modules, system debugging, normal system operation, and abnormal and fault collection; The data modules are divided into those for collecting system scheduling information, real-time collection of system operating status, optimization of system operating process, electrical balance within the fuel cell stack and / or between fuel cell stack groups, equipment safety and debugging, overall equipment performance evaluation, equipment abnormality and fault analysis, equipment troubleshooting and bypass, and regular equipment maintenance.

16. The digital system of flow battery according to claim 13, characterized in that: The data input terminal is used for data processing and processing; The data processing and processing include: Sampling data storage and reorganization; Data identification, cleaning and management; Add additional attributes including historical time and climate, geography and meteorology, equipment type and version, project type and data collection point, historical restoration of charging and discharging demand, historical data of equipment and power grid dispatching, and historical data of equipment operation and maintenance; Data processing includes the association and integration of basic data, and the generation and application of derived data.

17. The digital system of flow battery according to claim 12, characterized in that: It also includes a data acquisition module, which is used to collect: The intrinsic characteristic quantities of the flow battery unit include ohmic resistance, double layer capacitance, charge transfer resistance, concentration polarization resistance and concentration capacitance, leakage characteristic quantities such as flow channel leakage resistance, flow channel leakage current, positive / negative electrode side potential and current, and electrode and electrolyte reaction interface temperature; The charging and discharging voltage, charging and discharging current, equivalent resistance, charging and discharging time, ambient temperature, pressure loss and internal / external leakage of the battery stack; Pipeline pressure, pipeline flow, temperature and leakage of flow battery systems; The existence and changes of physical quantities such as combustible and toxic gases, smoke, temperature, humidity, light, insulation, lightning protection, electromagnetic interference resistance, noise resistance, and heating and heat preservation of the battery support system; Power conversion efficiency of flow battery system and operating parameters of auxiliary equipment.

18. The digital system of flow battery according to claim 12, characterized in that: It also includes a terminal computing module for a battery management system; The terminal computing modules of the battery management system include: Fault handling includes fault detection, fault warning, fault protection and fault isolation; The charge and discharge process includes scanning of electrode polarization process, tracking of electrolyte composition and concentration, detection of accumulated by-products, detection of gas evolution rate and optimization of charge and discharge process efficiency; The overall performance includes the flow battery system status indicator set (SOX) such as state of charge (SOC), state of health (SOH), state of power (SOP), state of life (SOL), state of energy (SOE), remaining life (RUL), end of life (EOL) and other indicators to predict battery life, auxiliary power loss and optimization, and energy regeneration; Battery balancing includes intra-stack balancing and / or electrical balancing between stack groups; regular maintenance such as maintenance trigger logic, maintenance mechanism and effect verification.

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