A flow pressure control method and system for flow battery based on fuzzy control

Abstract

The application relates to a flow pressure control method and system for a flow battery based on fuzzy control. The method part mainly comprises the following steps: obtaining current parameters and operation instructions of a flow battery system, and determining a current target flow value according to the current parameters and the operation instructions; collecting actual flow and outlet pressure of positive and negative circulating pumps, generating a frequency adjustment amount of the positive and negative circulating pumps through a fuzzy controller based on an error between the target flow value and the actual flow and a difference between outlet pressures of the positive and negative circulating pumps; adjusting rotating speeds of the positive and negative circulating pumps according to the frequency adjustment amount, and tracking the actual flow and the outlet pressure of the positive and negative circulating pumps to form a closed-loop feedback. The rotating speeds of the positive and negative circulating pumps are controlled through fuzzy logic to realize dynamic flow control and effectively improve system energy efficiency; meanwhile, accurate regulation of outlet pressure differences of the positive and negative circulating pumps is realized, liquid level deviation and value state deviation problems caused by the positive and negative pressure differences are reduced, and the service life of the system is effectively prolonged.

Description

Technical Field

[0001] This application relates to the field of flow battery technology, and in particular to a flow battery flow and pressure control method and system based on fuzzy control. Background Technology

[0002] Flow batteries, as a crucial solution for large-scale, long-term energy storage, have received widespread attention and research in recent years. They achieve energy conversion through electrolyte circulation between the battery stack and an external storage tank, featuring a decoupled power-capacity design and intrinsic safety. These characteristics give flow batteries unique advantages in areas such as grid peak shaving and renewable energy integration. In today's society, with the increasing demand for renewable energy, the role of flow batteries in energy storage is becoming increasingly important. They can effectively store excess electricity generated by renewable energy sources and release it when needed, improving energy utilization efficiency and promoting sustainable energy development. Simultaneously, the large-scale application of flow batteries also helps stabilize grid operation and reduce dependence on traditional fossil fuels. In flow battery systems, energy efficiency is one of the key performance indicators, directly related to the practicality and economy of the flow battery.

[0003] In traditional flow battery systems, a circulation pump is typically used to control the electrolyte flow. There are two common methods for flow control. One is a high-flow-rate, fixed-frequency setting, which is simple and direct, maintaining a high electrolyte flow rate by fixing the pump's operating frequency. The other method is to adjust the system flow rate based on the current, dynamically changing the pump's operating state according to the battery's current operating current to adjust the electrolyte flow rate. However, both methods have limitations in practical applications. With a high-flow-rate, fixed-frequency setting, the pump operates at a high flow rate regardless of the battery's actual operating state, leading to excessive energy consumption, pump wear and tear, and reduced system energy efficiency. The current-based flow rate adjustment method only considers the current factor and doesn't adequately account for changes in parameters such as temperature, density, and dynamic viscosity of the electrolyte due to valence state changes, resulting in a single adjustment reference factor. Furthermore, this adjustment method has a certain lag, failing to respond promptly to system changes and affecting the system's response speed. Meanwhile, existing methods cannot adjust the pressure of the positive and negative electrodes of the fuel cell stack in real time, which can easily lead to liquid level and valence state shifts, which have an adverse effect on the cycle life of the fuel cell stack.

[0004] Therefore, how to overcome the problems of using large flow rate fixed frequency settings and adjusting system flow rate according to current current in the existing technology is a problem to be solved in this technical field. Summary of the Invention

[0005] To address the aforementioned deficiencies or improvement needs of existing technologies, and to resolve the problems associated with current methods that rely on large-flow fixed-frequency settings and adjustments to system flow based on current, this application provides a flow and pressure control method and system for a flow battery based on fuzzy control. By using a dynamically updatable target flow value and a fuzzy logic closed-loop control of the positive and negative electrode circulating pump speeds, dynamic flow control is achieved, effectively improving system energy efficiency. Simultaneously, precise adjustment of the pressure difference at the outlets of the positive and negative electrode circulating pumps is realized, mitigating liquid level and valence state shifts caused by the pressure difference and effectively extending system lifespan.

[0006] The embodiments of this application adopt the following technical solutions:

[0007] In a first aspect, this application provides a flow and pressure control method for a flow battery based on fuzzy control, comprising:

[0008] Obtain the current parameters and operating instructions of the flow battery system, and determine the current target flow rate value based on the current parameters and operating instructions;

[0009] The actual flow rate and outlet pressure of the positive and negative electrode circulation pumps are collected. Based on the error between the target flow rate and the actual flow rate, as well as the difference in outlet pressure of the positive and negative electrode circulation pumps, the frequency adjustment of the positive and negative electrode circulation pumps is generated by a fuzzy controller.

[0010] The speed of the positive and negative circulating pumps is adjusted according to the frequency regulation, and the actual flow rate and outlet pressure of the positive and negative circulating pumps are tracked to form a closed-loop feedback.

[0011] By adopting the above technical solution, the speed of the positive and negative electrode circulation pumps can be dynamically controlled through fuzzy logic closed-loop control based on the target flow rate value of the electrolyte in the current system, thereby achieving dynamic flow control and effectively improving the system's energy efficiency. At the same time, it can achieve precise adjustment of the outlet pressure difference of the positive and negative electrode circulation pumps, reduce the problems of liquid level deviation and valence state deviation caused by the positive and negative electrode pressure difference, effectively improve the service life of the system, and has the advantages of strong adaptability, fast dynamic response, and high reliability.

[0012] In some embodiments, the current parameters include one or more of the current voltage, current, and SOC value, and the operating commands include one or more of charging, discharging, and load pulling.

[0013] By adopting the above technical solution, the current voltage, current and SOC value of the flow battery system can be obtained, as well as the current charging, discharging and load-bearing operating status of the flow battery system. Based on these parameters and status, the current target flow rate of the flow battery system can be determined, which facilitates the subsequent adjustment of the positive and negative electrode circulation pumps through fuzzy control, so that the actual flow rate of the positive and negative electrode circulation pumps matches the target flow rate.

[0014] In some embodiments, determining the current target flow value based on current parameters and operating instructions specifically includes:

[0015] Calculate the recommended flow rate under the current current based on the ratio of the current to the rated current and the reference flow rate under the rated current;

[0016] Based on the characteristic curve of the circulating pump, determine the upper and lower limits of the circulating pump's flow rate;

[0017] The recommended flow rate is adjusted based on the state of charge / discharge and the SOC value to obtain the target flow rate value.

[0018] By adopting the above technical solution, the target flow rate of the electrolyte in the current system can be dynamically updated, making the target flow rate more consistent with the actual operation of the flow battery system. This provides a more accurate basis for subsequent dynamic flow control through fuzzy logic closed-loop control of the circulating pump speed, effectively improving the system's energy efficiency.

[0019] In some embodiments, adjusting the recommended flow rate based on the state of charge / discharge and the SOC value to obtain the target flow rate specifically includes:

[0020] If it is in a suspended state, the target flow rate is Q. set =Q min ;

[0021] If it is in a charging state, the target flow rate is Q. set =max{min{Q0(1-k1(1-SOC)), Q max}, Q min};

[0022] If in a discharge state, the target flow rate is Q. set =max{min{Q0(1-k1SOC)k2,Q max}, Q min};

[0023] Where k1 and k2 are preset coefficients, Q0 is the recommended flow rate under the current current, and Q max Q is the upper limit of the flow rate of the circulating pump. min This is the lower limit of the flow rate of the circulating pump.

[0024] By adopting the above technical solution, the recommended flow rate can be adjusted according to the different charge / discharge states and SOC values ​​of the flow battery system to obtain the target flow rate value. This can accurately determine the electrolyte flow rate under different operating conditions, optimize pump power loss, and improve system energy efficiency. The system can adjust the flow rate in real time according to the actual operating conditions to avoid excessively high or low flow rates, ensure stable system operation, and reduce problems such as slow system response and high pump loss caused by inappropriate flow rates.

[0025] In some embodiments, the recommended flow rate Q0 = IQ under the current current e / I e , where Q e I is the reference flow rate under rated current. e I is the rated current, and I is the current.

[0026] By adopting the above technical solution, and combining the reference flow rate under rated current, rated current, and current, the recommended flow rate under the current can be accurately calculated. This provides a basis for adjusting the recommended flow rate according to the charge / discharge state and SOC value to obtain the target flow rate value. It helps to achieve precise control of the flow rate of the flow battery system, optimize pump power loss, and improve system energy efficiency.

[0027] In some embodiments, the step of acquiring the actual flow rate and outlet pressure of the positive and negative electrode circulation pumps, and generating the frequency adjustment amount of the positive and negative electrode circulation pumps through a fuzzy controller based on the error between the target flow rate value and the actual flow rate and the difference in outlet pressure of the positive and negative electrode circulation pumps specifically includes:

[0028] Collect the actual flow rate Q of the positive electrode circulation pump P The actual flow rate Q of the negative electrode circulation pump N The outlet pressure P of the positive circulation pump P and the outlet pressure P of the negative electrode circulation pump N ;

[0029] The input variable is defined as: flow error e Q =Q set -(Q P +Q N Pressure difference e P =P P -P N The output variable is determined to be: the frequency adjustment amount Δω of the positive electrode circulation pump. P Frequency adjustment amount Δω of the negative electrode circulation pump N ;

[0030] The input variables are fuzzified and fuzzy inference is performed to obtain a fuzzy set of output variables; the fuzzy set is then defuzzified to obtain the precise value of the output variables, which is the frequency adjustment amount Δω of the positive electrode circulation pump. P and the frequency adjustment amount Δω of the negative electrode circulation pump N The precise value.

[0031] By adopting the above technical solution, the actual flow rate and outlet pressure of the positive and negative electrode circulating pumps are collected. Using the error between the target flow rate and the actual flow rate, as well as the difference in outlet pressure of the positive and negative electrode circulating pumps, a fuzzy controller is used to generate the frequency adjustment amount of the positive and negative electrode circulating pumps. This enables precise adjustment of the outlet pressure difference of the positive and negative electrode circulating pumps, reducing liquid level and valence state deviations caused by the pressure difference and effectively extending the system's service life. Simultaneously, based on the dynamically updated target flow rate of the electrolyte in the current system, dynamic flow control can be achieved, effectively improving the system's energy efficiency. The fuzzy control method also features strong adaptability, automatically adapting to complex and changing working conditions, being insensitive to external interference and changes in internal parameters, and having a fast dynamic response, quickly responding to dynamic changes in the system, shortening adjustment time, and reducing flow fluctuations.

[0032] In some embodiments, the step of fuzzifying the input variables and performing fuzzy inference to obtain a fuzzy set of output variables specifically includes:

[0033] Precisely input variable e Q and e P Convert to fuzzy language values, set e Q and e P The universe of discourse and membership function, wherein the membership function is a triangular or Gaussian membership function;

[0034] Establish a fuzzy rule base, wherein the rules of the fuzzy rule base include: if e Q Belongs to the first fuzzy language value and e P If it belongs to the second fuzzy language value, then Δω P Belongs to the third fuzzy language value and Δω N It belongs to the fourth fuzzy language value; there are multiple predefined fuzzy language values, and the first fuzzy language value, the second fuzzy language value, the third fuzzy language value, and the fourth fuzzy language value all belong to one of the multiple predefined fuzzy language values;

[0035] Based on the current input variable e Q and e P The fuzzy linguistic values ​​are calculated using the Mamdani or Sugeno inference method, and each output variable Δω is calculated. P and Δω N A fuzzy set.

[0036] By adopting the above technical solutions, precise input variables are converted into fuzzy linguistic values, the universe of discourse and membership function are set, a fuzzy rule base is established, and the fuzzy set of output variables is calculated using inference methods. This enables the fuzzy controller to handle the uncertainty and nonlinear characteristics of the system, endows the system with the ability to perceive "degree", makes the system highly adaptive, can quickly respond to dynamic changes, shorten the adjustment time, reduce flow fluctuations, suppress flow fluctuations, and improve the system's energy efficiency.

[0037] In some embodiments, the process of defuzzifying the fuzzy set to obtain the precise value of the output variable specifically includes:

[0038] The output variable Δω is obtained using the centroid method or the average maximum membership method. P and Δω N The fuzzy set is converted back to the precise value.

[0039] By adopting the above technical solutions, the fuzzy set of output variables can be converted back to precise values ​​using the centroid method or the average maximum membership method. The results obtained from fuzzy inference can be transformed into precise frequency adjustment quantities that can be used to adjust the speed of the circulating pump, making the fuzzy control process complete. This helps to achieve dynamic flow control of the flow battery system and precise adjustment of the pressure difference at the outlet of the positive and negative electrode pumps, improves the system's adaptability and dynamic response speed, ensures the pressure difference between the positive and negative electrodes of the battery stack to reduce liquid level deviation and valence state deviation problems, and optimizes pump power loss to improve system energy efficiency.

[0040] Secondly, this application provides a flow battery flow and pressure control system based on fuzzy control, which applies the flow battery flow and pressure control method based on fuzzy control as described in the first aspect, including a signal acquisition unit, a fuzzy controller, and an execution unit, wherein:

[0041] The signal acquisition unit is connected to the battery management system of the flow battery system and is used to obtain the current parameters and operating instructions of the flow battery system through the battery management system.

[0042] The fuzzy controller is connected to the signal acquisition unit and the execution unit respectively, and is used to generate the frequency adjustment amount of the positive and negative circulating pump according to the data acquired by the signal acquisition unit, and output the frequency adjustment amount of the positive and negative circulating pump to the execution unit;

[0043] The execution unit is connected to the positive and negative circulating pumps and is used to adjust the speed of the positive and negative circulating pumps according to the frequency adjustment amount of the positive and negative circulating pumps, thereby realizing the flow and pressure regulation of the positive and negative circulating pumps.

[0044] By adopting the above technical solution, the signal acquisition unit obtains the current parameters and operating instructions of the flow battery system, providing a data foundation for subsequent control. The fuzzy controller uses the data from the signal acquisition unit to generate the frequency adjustment of the positive and negative electrode circulating pumps. Based on fuzzy control, no precise mathematical model is required, and it can automatically adapt to complex and changing working conditions. It is insensitive to external interference and changes in internal parameters, and can quickly respond to dynamic changes in the system, shorten the adjustment time, reduce flow fluctuations, and achieve fast dynamic response and strong adaptability. The execution unit adjusts the speed of the positive and negative electrode circulating pumps according to the frequency adjustment, realizing precise adjustment of the pressure difference at the outlet of the positive and negative electrode pumps. This reduces the problems of liquid level deviation and valence state deviation caused by the pressure difference between the positive and negative electrodes, improves the reliability and service life of the system, and optimizes pump power loss, thereby improving the energy efficiency of the system.

[0045] In summary, this application includes at least the following beneficial technical effects:

[0046] 1. Based on the dynamically updated target flow rate of the electrolyte in the current system, the speed of the positive and negative electrode circulation pumps can be controlled by fuzzy logic closed loop to achieve dynamic flow control and effectively improve the energy efficiency of the system; at the same time, it can achieve precise adjustment of the outlet pressure difference of the positive and negative electrode circulation pumps, reduce the liquid level deviation and valence state deviation caused by the positive and negative electrode pressure difference, effectively improve the service life of the system, and has the advantages of strong adaptability, fast dynamic response and high reliability.

[0047] 2. The recommended flow rate is adjusted according to the different charge / discharge states and SOC values ​​of the flow battery system to obtain the target flow rate value. This can accurately determine the electrolyte flow rate under different operating conditions, optimize pump power loss, and improve system energy efficiency. The system can adjust the flow rate in real time according to the actual operating conditions to avoid excessively high or low flow rates, ensure stable system operation, and reduce problems such as slow system response and high pump loss caused by inappropriate flow rates.

[0048] 3. By collecting the actual flow rate and outlet pressure of the positive and negative electrode circulation pumps, and utilizing the error between the target flow rate and the actual flow rate, as well as the difference in outlet pressure of the positive and negative electrode circulation pumps, a fuzzy controller is used to generate the frequency adjustment of the positive and negative electrode circulation pumps. This enables precise adjustment of the outlet pressure difference of the positive and negative electrode circulation pumps, reducing liquid level and valence state deviations caused by the pressure difference and effectively extending the system's service life. Simultaneously, based on the dynamically updated target flow rate of the electrolyte in the current system, dynamic flow control can be achieved, effectively improving the system's energy efficiency. The fuzzy control method also features strong adaptability, automatically adapting to complex and changing working conditions, being insensitive to external interference and changes in internal parameters, and exhibiting fast dynamic response, quickly responding to dynamic changes in the system, shortening adjustment time, and reducing flow fluctuations. Attached Figure Description

[0049] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments of this application will be briefly described below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0050] Figure 1 A flowchart of a flow battery flow and pressure control method based on fuzzy control is provided for an embodiment of this application;

[0051] Figure 2 A diagram illustrating the architecture of a flow battery flow and pressure control system based on fuzzy control, provided in this application embodiment;

[0052] Figure 3 A fuzzy control flowchart provided for an embodiment of this application. Detailed Implementation

[0053] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application. Furthermore, the technical features involved in the various embodiments described below can be combined with each other as long as they do not conflict with each other.

[0054] This application aims to address the problems of slow system response, high pump loss, and low system energy efficiency in flow battery systems caused by insufficient precision in flow control and differential pressure control, as well as to solve the problems of liquid level deviation and valence state deviation caused by differential pressure.

[0055] The present application will now be described in detail with reference to the accompanying drawings and embodiments. Example 1

[0056] like Figure 1 As shown in the figure, Embodiment 1 of this application provides a flow and pressure control method for a flow battery based on fuzzy control, and the specific steps are as follows.

[0057] Step 101: Obtain the current parameters and operating instructions of the flow battery system, and determine the current target flow rate value based on the current parameters and operating instructions.

[0058] For this step, the current parameters and operating commands of the Battery Management System (BMS) in the flow battery system are first obtained, mainly including the current system voltage U, current I, and SOC value. When the BMS issues operating commands such as charging / discharging and load-applying, the command parameters are collected first. During operation, the sampling period is recommended to be 5-20 minutes, which is the dynamic update cycle of the system's target flow rate value. By obtaining the current voltage, current, and SOC value of the flow battery system, the current charging, discharging, and load-applying operating states of the flow battery system can be obtained. Based on these parameters and states, the current target flow rate value of the flow battery system can be determined, which facilitates the subsequent adjustment of the positive and negative electrode circulation pumps through fuzzy control to match the actual flow rate of the positive and negative electrode circulation pumps with the target flow rate value.

[0059] Furthermore, according to the rated current I specified for the fuel cell stack e The reference flow Q below e Determine the recommended flow rate Q0=IQ under the current current of the flow battery system. e / I e By combining the reference flow rate at rated current, rated current, and current current, the recommended flow rate at the current current can be accurately calculated. This provides a basis for adjusting the recommended flow rate according to the charge / discharge state and SOC value to obtain the target flow rate value, which helps to achieve precise control of the flow rate of the flow battery system, optimize pump power loss, and improve system energy efficiency.

[0060] Furthermore, based on the characteristic curve of the circulating pump, the usable flow range of the circulating pump, i.e., the upper limit of the flow rate Q, is determined. max Traffic limit Q min .

[0061] Furthermore, based on the state of charge / discharge and the state of charge (SOC), the current and recommended flow rate at the current and SOC of the flow battery system are adjusted to obtain the target flow rate value; where:

[0062] If it is in a suspended state, the target flow rate is Q. set =Q min ;

[0063] If it is in a charging state, the target flow rate is Q. set =max{min{Q0(1-k1(1-SOC)), Q max}, Q min};

[0064] If in a discharge state, the target flow rate is Q. set =max{min{Q0(1-k1SOC)k2,Q max}, Q min};

[0065] Wherein, k1 and k2 are preset coefficients, with recommended values ​​for k1 ranging from 0.8 to 0.9 and for k2 ranging from 0.80 to 0.95.

[0066] By using the scheme in step 101 above, the recommended flow rate is adjusted according to the different charge / discharge states and SOC values ​​of the flow battery system to obtain the target flow rate value. This can accurately determine the electrolyte flow rate under different operating conditions, optimize pump power loss, and improve system energy efficiency. It also allows the system to adjust the flow rate in real time according to the actual operating conditions, avoiding excessively high or low flow rates, ensuring stable system operation, and reducing problems such as slow system response and high pump loss caused by unsuitable flow rates.

[0067] Step 102: Collect the actual flow rate and outlet pressure of the positive and negative electrode circulation pumps. Based on the error between the target flow rate and the actual flow rate, as well as the difference in outlet pressure of the positive and negative electrode circulation pumps, generate the frequency adjustment amount of the positive and negative electrode circulation pumps through a fuzzy controller.

[0068] This step begins with data collection and processing, including setting the target flow value Q. set Collect the actual flow rate Q of the positive electrode circulation pump. P The actual flow rate Q of the negative electrode circulation pump N The outlet pressure P of the positive circulation pump P and the outlet pressure P of the negative electrode circulation pump N .

[0069] Furthermore, define the input and output, and determine the input variable as: flow error e. Q =Q set -(Q P +Q N Pressure difference e P =P P -P N The output variable is determined to be: the frequency ω of the positive electrode circulation pump. P Frequency adjustment amount Δω P , negative electrode circulation pump frequency ω N Frequency adjustment amount Δω N .

[0070] Furthermore, fuzzing is performed to blur the precise input value e. Q and e P Convert to fuzzy language values, for e Q and e P Fuzzy linguistic values ​​include negative large (NB), negative small (NS), zero (ZO), positive small (PS), and positive large (PB); for Δω P and Δω N Similarly, it can be defined as NB, NS, ZO, PS, PB.

[0071] Furthermore, define the universe of discourse and membership function: define e Q The domain of discourse is [-50, 50]; let e P The domain of discourse is [-10, 10], and triangular or Gaussian membership functions are used.

[0072] Furthermore, a fuzzy rule base is established, which serves as the "brain" of the fuzzy controller. This base is built based on expert experience or experimental data. The rule format is: IF (e Q is ...) AND (e P is ...) THEN (Δω P is ...,Δω N is ...), that is, if e Q Belongs to the first fuzzy language value and e P If it belongs to the second fuzzy language value, then Δω P Belongs to the third fuzzy language value and Δω N It belongs to the fourth fuzzy language value; there are multiple predefined fuzzy language values, such as NB, NS, ZO, PS, and PB mentioned above. The first fuzzy language value, the second fuzzy language value, the third fuzzy language value, and the fourth fuzzy language value all belong to one of the multiple predefined fuzzy language values.

[0073] Below is a simplified example of a rule representation:

[0074]

[0075] Rule description (example):

[0076] Rule 1: IF e Q is NB (average flow rate of positive and negative electrodes is much higher than the set value) AND e P is NB (positive electrode pressure is much lower than negative electrode) THEN Δω P =NS (Slightly reduce the positive electrode circulation pump frequency) AND Δω N =NB (significantly reduces the frequency of the negative electrode circulation pump);

[0077] Rule 2: IF e Q is ZO (average flow rate of positive and negative electrodes equals set value) AND e P is NB (positive electrode pressure is much lower than negative electrode) THEN Δω P =PS (Slightly increase the positive electrode circulation pump frequency) AND Δω N =NS (Slightly reduce the frequency of the negative electrode circulation pump)...

[0078] Furthermore, fuzzy reasoning is performed based on the current input e. Q and eP The fuzzy value is used to activate all relevant rules. The Mamdani or Sugeno inference methods can be used to calculate the Δω of each output variable. P and Δω N The fuzzy set. The Mamdani or Sugeno inference methods are existing technologies and will not be elaborated here.

[0079] By converting precise input variables into fuzzy linguistic values, setting the domain and membership function, establishing a fuzzy rule base, and using inference methods to calculate the fuzzy set of output variables, the fuzzy controller can handle the uncertainty and nonlinear characteristics of the system, giving the system the ability to perceive "degrees," making the system highly adaptive, able to respond quickly to dynamic changes, shorten adjustment time, reduce flow fluctuations, suppress flow fluctuations, and improve system energy efficiency.

[0080] Furthermore, defuzzification can be performed using the centroid method or the average maximum membership method to defuzzify the fuzzy output set (Δω) obtained from the inference. P and Δω N The fuzzy set of the output variable is then converted back to its precise value. The centroid method or average maximum membership method are existing technologies and will not be elaborated upon here. Using the centroid method or average maximum membership method to convert the fuzzy set of the output variable back to its precise value allows the results obtained from fuzzy inference to be transformed into precise frequency adjustment quantities that can be used to regulate the speed of the circulating pump. This makes the fuzzy control process complete, helps to achieve dynamic flow control of the flow battery system and precise adjustment of the outlet pressure difference of the positive and negative electrode pumps, and improves the system's adaptability and dynamic response speed.

[0081] Through the scheme in step 102 above, the actual flow rate and outlet pressure of the positive and negative electrode circulation pumps are collected. By utilizing the error between the target flow rate and the actual flow rate, as well as the difference in outlet pressure of the positive and negative electrode circulation pumps, a fuzzy controller is used to generate the frequency adjustment amount of the positive and negative electrode circulation pumps. This enables precise adjustment of the outlet pressure difference of the positive and negative electrode circulation pumps, reducing liquid level and valence state deviations caused by the positive and negative electrode pressure difference, and effectively improving the service life of the system. At the same time, based on the dynamically updated target flow rate of the electrolyte in the current system, dynamic flow control can be achieved, effectively improving the system's energy efficiency. The fuzzy control method also has the characteristics of strong adaptability, which can automatically adapt to complex and changing working conditions, is not sensitive to external interference and changes in internal parameters, and has a fast dynamic response, which can quickly respond to the dynamic changes of the system, shorten the adjustment time, and reduce flow fluctuations.

[0082] Step 103: Adjust the speed of the positive and negative electrode circulation pumps according to the frequency adjustment amount, and track the actual flow rate and outlet pressure of the positive and negative electrode circulation pumps to form a closed-loop feedback. For this step, firstly, the positive and negative electrode circulation pumps are driven by frequency converter according to the frequency adjustment amount to achieve flow and pressure regulation. At the same time, flow and pressure are continuously tracked to form a closed-loop feedback. Through the scheme in Step 103, the speed of the positive and negative electrode circulation pumps can be controlled by fuzzy logic closed loop based on the dynamically updated target flow rate value of the current system electrolyte, achieving dynamic flow control and effectively improving the system energy efficiency; at the same time, it can achieve precise adjustment of the outlet pressure difference of the positive and negative electrode circulation pumps, reducing the liquid level deviation and valence state deviation problems caused by the positive and negative electrode pressure difference, effectively extending the service life of the system, and has the advantages of strong adaptability, fast dynamic response, and high reliability. Example 2

[0083] Based on the fuzzy control-based flow battery flow and pressure control method provided in Example 1, this Example 2 provides a fuzzy control-based flow battery flow and pressure control system, which applies the fuzzy control-based flow battery flow and pressure control method as described in Example 1.

[0084] refer to Figure 2 As shown, the flow battery system includes a flow battery power unit (i.e., a stack) and positive and negative electrode storage tanks connected to the power unit. Positive and negative electrode circulation pumps are installed on the channels connecting the power unit to the positive and negative electrode storage tanks, respectively. In addition to piping and electrical auxiliary components, the flow battery system also includes a battery management system (BMS) for acquiring relevant parameters. The power unit is the core of the flow battery system, serving as the site for the conversion between electrical and chemical energy. The positive and negative electrode storage tanks are the "energy warehouses" of the flow battery system, directly determining its energy storage capacity. The positive and negative electrode circulation pumps are the "power heart" of the flow battery system, responsible for driving the electrolyte circulation within the system. Piping and auxiliary components form the "vascular network" connecting the entire flow battery system. The electrical connections and the battery management system are the "brain and nerves" of the system, responsible for managing energy and information flow.

[0085] In addition to the modules inherent in the flow battery system itself, refer to Figure 2 As shown, the flow battery flow and pressure control system based on fuzzy control provided in this embodiment 2 also includes a signal acquisition unit, a fuzzy controller, and an execution unit.

[0086] The signal acquisition unit is connected to the battery management system of the flow battery system and is used to obtain the current parameters and operating instructions of the flow battery system through the battery management system. The signal acquisition unit is mainly used to acquire the acquisition data of the BMS and the operating data of the positive and negative electrode circulation pumps, such as current, voltage, SOC, temperature, and the speed, flow rate, and pressure data of the circulation pumps. Based on the acquired data, the target flow rate value that the flow battery system needs to adjust is output.

[0087] The fuzzy controller is connected to both the signal acquisition unit and the execution unit. It generates frequency adjustment values ​​for the positive and negative circulating pumps based on data acquired by the signal acquisition unit and outputs these values ​​to the execution unit. The fuzzy controller is the core of the flow and pressure control system. Unlike traditional PID controllers that rely on precise mathematical models, it mimics the thinking of experienced operators, using an advanced "if...then..." fuzzy rule base to handle the system's uncertainty and nonlinear characteristics. Its workflow is a sophisticated "fuzzification-inference-defuzzification" process: First, it converts precise pressure errors and error change rates from sensors into fuzzy language values ​​such as "positive large," "negative small," and "zero," giving the system the ability to perceive "degree." Then, the inference engine makes intelligent decisions based on preset expert rules, generating a fuzzy control output. Finally, the defuzzifier converts this fuzzy output back into precise, executable control commands to drive the actuator.

[0088] The execution unit is connected to the positive and negative circulating pumps and is used to adjust the speed of the positive and negative circulating pumps according to the frequency adjustment of the circulating pumps, thereby realizing the flow and pressure regulation of the positive and negative circulating pumps. The core of the execution unit is a frequency converter, which receives frequency adjustment commands from the fuzzy controller and precisely changes the power frequency and voltage output to the circulating pump motor through its internal inverter circuit. According to the principles of motor theory, the speed of the motor is directly proportional to the power frequency. Therefore, the frequency converter directly and linearly controls the speed of the circulating pump motor by smoothly and steplessly adjusting the frequency.

[0089] refer to Figure 3As shown, the overall control process of fuzzy control implemented by the signal acquisition unit, fuzzy controller, and execution unit includes: acquiring BMS operating parameters; collecting and processing data; obtaining the target flow rate value; defining inputs and outputs based on the target flow rate value and performing fuzzification processing; setting the universe of discourse and membership function; establishing a fuzzy rule base; performing fuzzy decision-making; performing defuzzification to obtain the final precise output value; transmitting the precise output value to the execution unit; the execution unit controlling the positive and negative circulating pumps to perform precise frequency adjustment according to the precise output value; and the signal acquisition unit continuously acquiring various parameters and performing cyclic feedback adjustment of the fuzzification process. A more detailed process is described in Example 1 and will not be repeated here.

[0090] Through the above technical solution, the signal acquisition unit obtains the current parameters and operating instructions of the flow battery system, providing a data foundation for subsequent control; the fuzzy controller uses the data from the signal acquisition unit to generate the frequency adjustment of the positive and negative electrode circulating pumps. Based on fuzzy control, no precise mathematical model is required, and it can automatically adapt to complex and changing working conditions. It is insensitive to external interference and changes in internal parameters, and can quickly respond to dynamic changes in the system, shorten the adjustment time, reduce flow fluctuations, and achieve fast dynamic response and strong adaptability; the execution unit adjusts the speed of the positive and negative electrode circulating pumps according to the frequency adjustment, realizing precise adjustment of the pressure difference at the outlet of the positive and negative electrode pumps, reducing the liquid level deviation and valence state deviation caused by the pressure difference between the positive and negative electrodes, improving the system reliability and service life, while optimizing pump power loss and improving system energy efficiency.

[0091] In summary, this application has the following advantages:

[0092] (1) Strong adaptability: The temperature and viscosity of the electrolyte change with the charging and discharging valence state, which is ultimately reflected in the changes in flow rate and pressure. Fuzzy control does not need to know the precise mathematical model and can automatically adapt to complex and ever-changing working conditions. It is not sensitive to external disturbances and changes in internal parameters.

[0093] (2) Fast dynamic response: It can quickly respond to the dynamic changes of the system, shorten the adjustment time, reduce flow fluctuations, and quickly suppress flow fluctuations;

[0094] (3) High reliability: The positive and negative electrode circulating pumps are coordinated to ensure the pressure difference between the positive and negative electrodes of the stack in real time, thereby reducing the electrolyte valence state shift and liquid level shift;

[0095] (4) Energy efficiency improvement: Optimize pump power loss and improve system energy efficiency.

[0096] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A flow rate and pressure control method for a flow battery based on fuzzy control, characterized in that, include: The system acquires the current parameters and operating instructions of the flow battery system. The current parameters include one or more of the current voltage, current, and SOC value, and the operating instructions include one or more of charging, discharging, and load loading. The system then determines the current target flow rate value based on the current parameters and operating instructions. Specifically, based on the ratio of the current to the rated current and the reference flow rate at the rated current, the recommended flow rate at the current current is calculated, wherein the recommended flow rate at the current current is Q0=IQ. e / I e , where Q e I is the reference flow rate under rated current. e I is the rated current, and I is the current. Based on the circulation pump characteristic curve, determine the upper and lower flow limits of the circulation pump. Adjust the recommended flow rate according to the charge / discharge state and SOC value to obtain the target flow rate value. If the pump is idle, the target flow rate value is Q. set =Q min If it is in charging state, the target flow rate is Q. set =max{min{Q0(1-k1(1-SOC)), Q max }, Q min If in a discharge state, the target flow rate is Q. set =max{min{Q0(1-k1SOC)k2,Q max }, Q min }; where k1 and k2 are preset coefficients, Q0 is the recommended flow rate under the current current, and Q max Q is the upper limit of the flow rate of the circulating pump. min This is the lower limit of the flow rate of the circulating pump; The actual flow rate and outlet pressure of the positive and negative electrode circulation pumps are collected. Based on the error between the target flow rate and the actual flow rate, as well as the difference in outlet pressure between the positive and negative electrode circulation pumps, a fuzzy controller is used to generate the frequency adjustment of the positive and negative electrode circulation pumps. Specifically, the actual flow rate Q of the positive electrode circulation pump is collected. P The actual flow rate Q of the negative electrode circulation pump N The outlet pressure P of the positive circulation pump P and the outlet pressure P of the negative electrode circulation pump N The input variable is defined as: flow error e. Q =Q set -(Q P +Q N Pressure difference e P =P P -P N The output variable is determined to be: the frequency adjustment amount Δω of the positive electrode circulation pump. P Frequency adjustment amount Δω of the negative electrode circulation pump N ; to accurately input the variable e Q and e P Convert to fuzzy language values, set e Q and e P The universe of discourse and membership function, wherein the membership function is a triangular or Gaussian membership function; a fuzzy rule base is established, wherein the rules of the fuzzy rule base include: if e Q Belongs to the first fuzzy language value and e P If it belongs to the second fuzzy language value, then Δω P Belongs to the third fuzzy language value and Δω N This belongs to the fourth fuzzy language value; there are multiple predefined fuzzy language values, and the first, second, third, and fourth fuzzy language values ​​are all one of the predefined multiple fuzzy language values; based on the current input variable e Q and e P The fuzzy linguistic values ​​are calculated using the Mamdani or Sugeno inference method, and each output variable Δω is calculated. P and Δω N The fuzzy set is used to defuzzify the fuzzy set, obtaining the precise value of the output variable, which is the frequency adjustment amount Δω of the positive electrode circulation pump. P and the frequency adjustment amount Δω of the negative electrode circulation pump N The precise value; The speed of the positive and negative circulating pumps is adjusted according to the frequency regulation, and the actual flow rate and outlet pressure of the positive and negative circulating pumps are tracked to form a closed-loop feedback.

2. The flow rate and pressure control method for a flow battery based on fuzzy control according to claim 1, characterized in that, The process of defuzzifying the fuzzy set to obtain the precise value of the output variable specifically includes: The output variable Δω is obtained using the centroid method or the average maximum membership method. P and Δω N The fuzzy set is converted back to the precise value.

3. A flow battery flow and pressure control system based on fuzzy control, employing the flow battery flow and pressure control method based on fuzzy control as described in any one of claims 1-2, characterized in that, It includes a signal acquisition unit, a fuzzy controller, and an execution unit, wherein: The signal acquisition unit is connected to the battery management system of the flow battery system and is used to obtain the current parameters and operating instructions of the flow battery system through the battery management system. The fuzzy controller is connected to the signal acquisition unit and the execution unit respectively, and is used to generate the frequency adjustment amount of the positive and negative circulating pump according to the data acquired by the signal acquisition unit, and output the frequency adjustment amount of the positive and negative circulating pump to the execution unit; The execution unit is connected to the positive and negative circulating pumps and is used to adjust the speed of the positive and negative circulating pumps according to the frequency adjustment amount of the positive and negative circulating pumps, thereby realizing the flow and pressure regulation of the positive and negative circulating pumps.

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