Coupling control method and system for branch temperature and flow in thermal hydraulic experimental system

Abstract

The present invention discloses a method and system for coupling control of branch temperature and flow in a thermal hydraulic experiment system, and relates to the field of thermal hydraulic experiment research. The method for coupling control of branch temperature and flow in a thermal hydraulic experiment system includes collecting historical data of the thermal hydraulic experiment system; obtaining the constant-pressure specific heat capacity of the working fluid; calculating the heating power coefficient; training a heating power coefficient prediction model to be trained, and obtaining a trained heating power coefficient prediction model; predicting a heating power coefficient prediction value; calculating a heating power feedforward value; obtaining a heating power feedback adjustment value; and controlling the fluid temperature at the outlet of the experimental body according to the heating power feedforward value and the heating power feedback value. The present invention achieves efficient and precise control of the body outlet temperature, and solves the problems of poor experimental reliability and efficiency.

Description

Technical Field

[0001] The present invention relates to the field of thermal hydraulic experiment research, and in particular to a method and system for coupling control of branch temperature and flow in a thermal hydraulic experiment system. Background Art

[0002] Thermal-hydraulic experimental systems are essential platforms for studying thermal energy transfer and fluid dynamics, and are widely used in fields such as energy, chemical engineering, and HVAC. These systems typically feature a complex main circuit and experimental branch circuit structure. The main circuit ensures relatively constant fluid flow and temperature, providing relatively stable boundaries for the experimental branch circuit. The experimental branch circuit serves as the research object, and its core focus is on observing and analyzing specific thermal phenomena or equipment performance within the experimental unit through precise control of flow and temperature.

[0003] The experimental body, that is, the research object on the experimental branch, the stability of its outlet temperature is crucial to the consistency, repeatability and safety of the experiment. However, a wide range of stable experimental data points need to be obtained during the experiment. Therefore, it is necessary to obtain stable experimental data points for the flow rates of different experimental branches and the outlet fluid temperatures of different experimental bodies. During the working condition switching process, it is necessary to adjust the flow rate of the experimental branch and the outlet fluid temperature of the experimental body. The experimental body is a heating structure. When the heating power is fixed, a slight change in the flow rate will be directly reflected in the outlet temperature. This is because the heat capacity and heat transfer coefficient of the fluid will change with the flow rate, forming a nonlinear response relationship. Therefore, this nonlinear characteristic brings difficulties to the controller when adjusting the flow rate of the experimental branch and synchronously adjusting the heating power of the body to achieve coupled adjustment of the outlet fluid temperature of the experimental body, especially in situations where fast response and high-precision control are required.

[0004] The heat dissipation effect further exacerbates the control challenge, as the system must not only withstand heat exchange with the external environment but also maintain internal thermal equilibrium. This requires the controller to compensate for temperature fluctuations caused by heat dissipation in real time. Traditional control methods often struggle to accurately predict and compensate for these dynamic changes, making it difficult to stabilize experimental conditions at set values, limiting experimental accuracy and efficiency.

[0005] Given these challenges, existing technologies are limited in achieving coupled temperature and flow control in thermal-hydraulic experimental systems. Therefore, there is an urgent need to develop a method for coupled temperature and flow control in branches of thermal-hydraulic experimental systems. This method can achieve efficient and precise control of the main body outlet temperature when adjusting the flow in the experimental branches, thereby overcoming the shortcomings of traditional methods and improving the reliability and efficiency of experimental research. Summary of the Invention

[0006] The technical problem to be solved by the present invention is the lack of a method that can efficiently and accurately control the outlet temperature of the main body when adjusting the flow of the experimental branch, resulting in poor experimental reliability and efficiency. The purpose is to provide a coupled control method and system for the branch temperature and flow of a thermal hydraulic experimental system, which solves the problem of poor experimental reliability and efficiency.

[0007] The present invention is achieved through the following technical solutions:

[0008] The coupling control method of branch temperature and flow in thermal hydraulic experimental system includes

[0009] Collecting historical data of the thermal hydraulic experiment system, wherein the historical data includes ambient temperature, heating power, experiment body inlet flow, experiment body inlet fluid temperature, experiment body outlet fluid temperature and experiment body inlet and outlet fluid average pressure;

[0010] According to the average pressure of the fluid inlet and outlet of the experimental body, the constant pressure specific heat capacity of the working fluid is obtained through the working fluid physical property function;

[0011] The heating power coefficient is calculated based on the heating power, the experimental body inlet flow rate, the experimental body inlet fluid temperature, the experimental body outlet fluid temperature and the working fluid constant pressure specific heat capacity;

[0012] The heating power coefficient prediction model to be trained is trained using the ambient temperature, the experimental body inlet flow rate, the experimental body inlet fluid temperature, the experimental body outlet fluid temperature, and the heating power coefficient to obtain a trained heating power coefficient prediction model;

[0013] The real-time ambient temperature, the experimental body inlet flow rate, the experimental body inlet fluid temperature and the experimental body outlet fluid temperature target value are used as the input parameters of the heating power coefficient prediction model to predict the heating power coefficient prediction value;

[0014] The heating power feedforward value is calculated based on the predicted heating power coefficient, the target value of the experimental body outlet fluid temperature, the real-time experimental body inlet flow, the experimental body inlet fluid temperature and the constant pressure specific heat capacity of the working fluid;

[0015] According to the deviation between the target temperature value of the fluid outlet of the main body and the temperature of the fluid outlet of the main body, the PID control algorithm is used to obtain the heating power feedback adjustment value;

[0016] The heating power feedforward value and the heating power feedback value are added to obtain the body heating power value. The body heating power value is used as the target value to adjust the experimental body heating power to achieve control of the fluid temperature at the experimental body outlet.

[0017] As a possible design, in the above heating power coefficient prediction model, ambient temperature, experimental body inlet flow, experimental body inlet fluid temperature, and experimental body outlet fluid temperature are used as input parameters, and the heating power coefficient is the output result.

[0018] As a possible design, the above heating power coefficient prediction model adopts an artificial neural network algorithm or a convolutional neural algorithm.

[0019] As a possible design, the above heating power coefficient is calculated by the following formula:

[0020] α=P / (F in ·(T out -T in )·c p )

[0021] Where,

[0022] α: heating power coefficient;

[0023] P: heating power;

[0024] F in : Experimental body inlet flow;

[0025] T in : Temperature of fluid at the inlet of the experimental body;

[0026] T out : The outlet fluid temperature of the experimental body;

[0027] c p : Specific heat capacity of working fluid at constant pressure.

[0028] As a possible design, the above heating power feedforward value is calculated by the following formula:

[0029] P ff =α ff ·F in ·(T out,s -T in )·c p

[0030] Where,

[0031] P ff : Heating power feedforward value;

[0032] α ff : predicted value of heating power coefficient;

[0033] F in : Experimental body inlet flow;

[0034] T out,s : Target value of the main body outlet temperature;

[0035] T in : Temperature of fluid at the inlet of the experimental body;

[0036] c p : Specific heat capacity of working fluid at constant pressure.

[0037] As a possible design, the above-mentioned control of the outlet fluid temperature of the experimental body is achieved by adjusting the experimental body heating power by taking the body heating power value as the target value. Specifically, it means adjusting the voltage and current of the experimental body so that the actual heating power value is consistent with the body heating power value.

[0038] The present invention also provides a coupling control system for branch temperature and flow of a thermal hydraulic experiment system, which is applied to the thermal hydraulic experiment system and includes:

[0039] The first parameter acquisition module is used to obtain historical data of the thermal hydraulic experiment system, the historical data including ambient temperature, heating power, experiment body inlet flow, experiment body inlet fluid temperature, experiment body outlet fluid temperature and experiment body inlet and outlet fluid average pressure;

[0040] The first calculation module is used to obtain the constant-pressure specific heat capacity of the working fluid through the working fluid physical property function according to the average pressure of the fluid inlet and outlet of the experimental body;

[0041] The second calculation module is used to calculate the heating power coefficient according to the heating power, the experimental body inlet flow rate, the experimental body inlet temperature, the experimental body outlet temperature and the constant pressure specific heat capacity of the working fluid;

[0042] A model training module is used to use the ambient temperature, the experimental body inlet flow rate, the experimental body inlet fluid temperature, and the experimental body outlet fluid temperature as inputs and the heating power coefficient as output to train a heating power coefficient prediction model and obtain a trained heating power coefficient prediction model;

[0043] The second parameter acquisition module is used to obtain the real-time ambient temperature of the thermal hydraulic experiment system, the experiment body inlet flow, the experiment body inlet fluid temperature, the experiment body outlet fluid temperature and the experiment body inlet and outlet fluid average pressure;

[0044] The prediction module inputs the real-time ambient temperature, the experimental body inlet flow rate, the experimental body inlet fluid temperature and the experimental body outlet fluid temperature target value into the heating power coefficient prediction model to predict the heating power coefficient;

[0045] The third calculation module calculates the heating power feedforward value through the predicted value of the heating power coefficient, the target value of the experimental body outlet fluid temperature, and the experimental body inlet flow rate, experimental body inlet fluid temperature, and constant pressure specific heat capacity of the working fluid in the predicted sample;

[0046] The third parameter acquisition module obtains the outlet fluid temperature of the experimental body in real time;

[0047] A fourth calculation module calculates a target difference value by using the temperature of the fluid at the outlet of the experimental body and the target value of the fluid at the outlet of the experimental body, and inputs the target difference value into a PID controller to obtain a heating power feedback adjustment value;

[0048] A fifth calculation module obtains a main body heating power value by adding the heating power feedforward value and the heating power feedback value;

[0049] The control module is connected to the thermal hydraulic experiment system and adjusts the outlet fluid temperature of the experiment body according to the heating power value of the body.

[0050] The present invention also provides a host device, comprising

[0051] memory for storing computer programs;

[0052] The processor is used to implement a coupled control method of branch temperature and flow in a thermal hydraulic experiment system when executing the computer program.

[0053] The present invention also provides a computer program product, comprising a computer program / instruction, which, when executed by a processor, implements the steps of a method for coupling control of branch temperature and flow in a thermal hydraulic experimental system.

[0054] The present invention also provides a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are loaded and executed by a processor, a method for coupling control of branch temperature and flow in a thermal hydraulic experiment system is implemented.

[0055] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0056] The present invention obtains the constant-pressure specific heat capacity of the working fluid through the average pressure of the inlet and outlet fluids of the experimental body and the working fluid physical property function, obtains the heating power coefficient through the heating power, the experimental body inlet flow, the experimental body inlet fluid temperature, the experimental body outlet fluid temperature and the constant-pressure specific heat capacity of the working fluid, and trains the heating power coefficient prediction model with the ambient temperature, the experimental body inlet flow, the experimental body inlet fluid temperature, the experimental body outlet fluid temperature and the heating power coefficient, and then combines the real-time data to predict the heating power coefficient prediction value, and calculates the heating power feedforward value based on the predicted heating power coefficient prediction value, the experimental body outlet fluid temperature target value, the real-time experimental body inlet flow, the experimental body inlet fluid temperature and the constant-pressure specific heat capacity of the working fluid, and uses an ordinary PID controller according to the deviation between the body outlet fluid temperature target value and the body outlet fluid temperature to obtain the heating power feedback adjustment value, adds the heating power feedforward value and the heating power feedback value to obtain the body heating power value, and adjusts the heating power through the body heating power feedforward value to achieve control of the experimental body outlet fluid temperature. It solves the problem that during thermal hydraulic experiments, the outlet fluid temperature of the experimental body changes with the change of the body inlet flow, the adjustment of the experimental branch flow or the environment, as well as the complex problem of automatic adjustment of the outlet fluid temperature of the experimental body. It can efficiently and accurately control the outlet fluid temperature of the experimental body and improve the reliability and efficiency of experimental research.

[0057] This invention addresses the need for regulating flow and temperature in branch circuits of a thermal-hydraulic experimental system under different operating conditions during thermal-hydraulic experimental research. The control method of the invention enables automatic control of the outlet fluid temperature of the experimental body by coupling flow adjustment under different flow rates and different outlet fluid temperatures of the experimental body during the experiment. The invention has the advantages of simple structure and easy operation, and can fully meet the requirements for coupled control of temperature and flow in branch circuits of a thermal-hydraulic experimental system during thermal-hydraulic experiments.

[0058] In the calculation of the heating power feedforward value, the present invention takes into account environmental changes and other nonlinear influencing factors that are not directly considered in the heating power coefficient obtained through training. By obtaining the predicted value of the heating power coefficient, combined with the target value of the experimental body outlet fluid temperature, the real-time experimental body inlet flow, the experimental body inlet fluid temperature, and the constant-pressure specific heat capacity of the working fluid, a more accurate heating power feedforward value can be obtained. At the same time, in the calculation of the heating power feedforward value, the linear influence of the experimental body inlet flow on the heating power feedforward value is taken into account, which can realize the coupled regulation of the experimental body outlet temperature when the experimental body inlet flow changes rapidly. The heating power feedback value realizes the precise control of the small deviation between the experimental body outlet temperature value and the experimental body outlet temperature target value. Overall, the precise coupled control of the experimental body outlet fluid temperature and the experimental body inlet flow can be realized. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the following briefly introduces the drawings required for use in the examples. It should be understood that the following drawings only illustrate certain embodiments of the present invention and should not be considered as limiting the scope. A person of ordinary skill in the art can also derive other relevant drawings based on these drawings without inventive effort. In the drawings:

[0060] Figure 1 A schematic diagram of a thermal hydraulic experiment system circuit adapted to the method for coupling control of branch temperature and flow of the thermal hydraulic experiment system of the present invention;

[0061] Figure 2 A schematic diagram of the coupling control principle of the coupling control method for branch temperature and flow in a thermal hydraulic experimental system of the present invention;

[0062] Figure 3 This is the training diagram of the heating power coefficient prediction model of the present invention.

[0063] Markings and corresponding parts names in the accompanying drawings:

[0064] 1-pressure regulator; 2-main circulation pump; 3-experimental branch flow control valve; 4-experimental body; 5-experimental main circuit flow control valve; 6-mixer; 7-heat exchanger. DETAILED DESCRIPTION

[0065] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with Examples and accompanying drawings. The illustrative embodiments of the present invention and their description are only used to explain the present invention and are not intended to limit the present invention. In the examples, if specific conditions are not specified, the conditions according to conventional conditions or manufacturer's recommendations are used. If the manufacturer of the reagents or instruments is not specified, they are all conventional products that can be purchased commercially.

[0066] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0067] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0068] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0069] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0070] Those skilled in the art will understand that all or part of the steps in implementing the above facts and methods can be completed by instructing relevant hardware through a program, and the program involved or the program can be stored in a computer-readable storage medium. When the program is executed, it includes the following steps: the corresponding method steps are then brought out, and the storage medium can be ROM / RAM, a disk, an optical disk, etc.

[0071] Because changes in branch flow and environment in thermal hydraulic experimental systems can cause variations in the outlet temperature of the experimental body, achieving high-precision control and rapid response to the test body's outlet temperature is difficult, limiting the accuracy and efficiency of the experiment. This invention provides a method for coupled control of branch temperature and flow in a thermal hydraulic experimental system to address this issue. This method enables efficient and precise control of the outlet temperature of the experimental body, improving the reliability and efficiency of experimental research.

[0072] Reference Figure 1 , Figure 1The thermal hydraulic experimental system is only an example, and the coupling control method of the present invention is applicable to any thermal hydraulic experimental system.

[0073] First, refer to Figure 2-3 The present invention provides a coupling control method for branch temperature and flow of a thermal hydraulic experimental system, comprising:

[0074] S1. Collect historical data of the thermal hydraulic experiment system, wherein the historical data includes ambient temperature, heating power, experiment body inlet flow, experiment body inlet fluid temperature, experiment body outlet fluid temperature and experiment body inlet and outlet fluid average pressure.

[0075] The inventors have discovered that in thermal hydraulic experiments, to obtain experimental data at a stable operating point, researchers often need to continuously adjust the flow rate and heating power of the experimental branch to achieve the target temperature at the outlet of the experimental body. Furthermore, a single experiment often involves studying different operating conditions, resulting in a wide range of heating power levels and nonlinear characteristics. However, using ambient temperature, heating power, experimental body inlet flow rate, experimental body inlet fluid temperature, experimental body outlet fluid temperature, and experimental body inlet and outlet fluid average pressure as basic data for artificial intelligence-based heating power coefficient prediction, and employing an artificial intelligence-based method to predict the heating power coefficient, a heating power coefficient with high accuracy compared to actual results can be obtained, enabling the prediction and adjustment of the experimental body outlet fluid temperature.

[0076] S2. According to the average pressure of the inlet and outlet fluids of the experimental body, the constant-pressure specific heat capacity of the working fluid is obtained through the working fluid physical property function.

[0077] Preferably, the above-mentioned working fluid physical property function adopts IAPWS-IF97 physical property function.

[0078] S3. Calculate the heating power coefficient based on the heating power, the experimental body inlet flow rate, the experimental body inlet fluid temperature, the experimental body outlet fluid temperature and the constant pressure specific heat capacity of the working fluid.

[0079] In some embodiments of the present invention, the heating power coefficient is calculated by the following formula:

[0080] α=P / (F in ·(T out -T in )·c p )

[0081] Where,

[0082] α: heating power coefficient;

[0083] P: heating power;

[0084] F in: Experimental body inlet flow;

[0085] T in : Temperature of fluid at the inlet of the experimental body;

[0086] T out : The outlet fluid temperature of the experimental body;

[0087] c p : Specific heat capacity of working fluid at constant pressure.

[0088] S4. Using the ambient temperature, the experimental body inlet flow rate, the experimental body inlet fluid temperature, the experimental body outlet fluid temperature and the heating power coefficient to train the heating power coefficient prediction model to be trained, and obtain a trained heating power coefficient prediction model.

[0089] In some embodiments of the present invention, the heating power coefficient prediction model adopts an artificial neural network algorithm or a convolutional neural algorithm.

[0090] Artificial neural network algorithms, or convolutional neural network algorithms, have significant advantages in processing nonlinear relationships and complex data patterns, making them suitable for the multivariable, nonlinear coupled control characteristics of thermal hydraulic experimental systems. First, artificial neural networks (ANNs) and convolutional neural networks (CNNs) can learn and simulate these complex nonlinear relationships through weighted connections across multiple layers of nodes and nonlinear activation functions. This enables them to more accurately predict the heating power coefficient under different input conditions, thereby improving control accuracy. Second, they can automatically adjust weights through training, achieving adaptive response to system changes. As historical data accumulates, the model can be continuously optimized through retraining to adapt to changes in system parameters or new operating conditions, ensuring continuous optimization of the control effect; third, convolutional neural networks perform well in processing image data. Although images are not directly processed here, their local connections and weight sharing mechanisms are also applicable to processing data with spatial or time series characteristics, such as changes in the inlet flow of the experimental body over time, which helps the model extract key features from the input data, reduce redundant information, and improve prediction efficiency; fourth, through sufficient training, the neural network model can generalize to unseen data, which means that even in the face of slight changes in experimental conditions, the model can provide reliable predictions, which is crucial for maintaining the stability and control accuracy of the experimental system; fifth, the structure of neural networks, especially CNNs, is suitable for parallel computing, which can significantly improve computing efficiency when processing large amounts of data. For real-time control systems, fast response is key.

[0091] In some embodiments of the present invention, in the above-mentioned heating power coefficient prediction model, ambient temperature, experimental body inlet flow, experimental body inlet fluid temperature, and experimental body outlet fluid temperature are used as input parameters, and the heating power coefficient is the output result.

[0092] S5. Using the real-time ambient temperature, the experimental body inlet flow rate, the experimental body inlet fluid temperature and the experimental body outlet fluid temperature target value as input parameters of the heating power coefficient prediction model to predict the heating power coefficient prediction value.

[0093] S6. Calculate the heating power feedforward value based on the predicted heating power coefficient, the target value of the experimental body outlet fluid temperature, the real-time experimental body inlet flow rate, the experimental body inlet fluid temperature and the constant-pressure specific heat capacity of the working fluid.

[0094] In some embodiments of the present invention, the heating power feedforward value is calculated by the following formula:

[0095] P ff =α ff ·F in ·(T out,s -T in )·c p

[0096] Where,

[0097] P ff : Heating power feedforward value;

[0098] α ff : predicted value of heating power coefficient;

[0099] F in : Experimental body inlet flow;

[0100] T out,s : Target value of the main body outlet temperature;

[0101] T in : Temperature of fluid at the inlet of the experimental body;

[0102] c p : Specific heat capacity of working fluid at constant pressure.

[0103] S7. According to the deviation between the target temperature value of the fluid at the outlet of the main body and the temperature of the fluid at the outlet of the main body, a PID control algorithm is used to obtain a heating power feedback adjustment value.

[0104] S8. Add the heating power feedforward value and the heating power feedback value to obtain the body heating power value, and adjust the experimental body heating power by taking the body heating power value as the target value to achieve control of the fluid temperature at the outlet of the experimental body.

[0105] The present invention can realize automatic control of the outlet temperature of the experimental body under coupled flow adjustment by automatic control means according to different flow rates and different experimental body outlet fluid temperature working conditions.

[0106] In some embodiments of the present invention, the above-mentioned control of the outlet fluid temperature of the experimental body is achieved by adjusting the experimental body heating power by taking the body heating power value as the target value, specifically by adjusting the voltage and current of the experimental body so that the actual heating power value is consistent with the body heating power value.

[0107] In the second aspect, the present invention provides a coupling control system for branch temperature and flow of a thermal hydraulic experiment system, which is applied to the thermal hydraulic experiment system, including

[0108] The first parameter acquisition module is used to obtain historical data of the thermal hydraulic experiment system, the historical data including ambient temperature, heating power, experiment body inlet flow, experiment body inlet fluid temperature, experiment body outlet fluid temperature and experiment body inlet and outlet fluid average pressure;

[0109] The first calculation module is used to obtain the constant-pressure specific heat capacity of the working fluid through the working fluid physical property function according to the average pressure of the fluid inlet and outlet of the experimental body;

[0110] The second calculation module is used to calculate the heating power coefficient according to the heating power, the experimental body inlet flow rate, the experimental body inlet temperature, the experimental body outlet temperature and the constant pressure specific heat capacity of the working fluid;

[0111] A model training module is used to use the adopted ambient temperature, the experimental body inlet flow rate, the experimental body inlet fluid temperature, and the experimental body outlet fluid temperature as inputs, and use the heating power coefficient as output to train a heating power coefficient prediction model to obtain a trained heating power coefficient prediction model;

[0112] The second parameter acquisition module is used to obtain the real-time ambient temperature of the thermal hydraulic experiment system, the experiment body inlet flow, the experiment body inlet fluid temperature, the experiment body outlet fluid temperature and the experiment body inlet and outlet fluid average pressure;

[0113] The prediction module inputs the real-time ambient temperature, the experimental body inlet flow rate, the experimental body inlet fluid temperature and the experimental body outlet fluid temperature target value into the heating power coefficient prediction model to predict the heating power coefficient;

[0114] The third calculation module calculates the heating power feedforward value through the predicted value of the heating power coefficient, the target value of the experimental body outlet fluid temperature, and the experimental body inlet flow rate, experimental body inlet fluid temperature, and constant pressure specific heat capacity of the working fluid in the predicted sample;

[0115] The third parameter acquisition module obtains the outlet fluid temperature of the experimental body in real time;

[0116] A fourth calculation module calculates a target difference value by using the experimental body outlet fluid temperature and the experimental body outlet fluid temperature target value, and inputs the target difference value into the PID controller of the fourth calculation module to obtain a heating power feedback adjustment value;

[0117] A fifth calculation module obtains a main body heating power value by adding the heating power feedforward value and the heating power feedback value;

[0118] The control module is connected to the thermal hydraulic experiment system and adjusts the outlet fluid temperature of the experiment body according to the heating power value of the body.

[0119] Preferably, temperature measuring points and flow measuring points are set on the inlet pipe of the experimental body of the thermal hydraulic experimental system, temperature measuring points are set on the outlet pipe of the experimental body, and heating power measuring points are set on the experimental body to accumulate historical data and real-time data.

[0120] Preferably, the above-mentioned control module includes a heating power controller to realize the control of the heating power.

[0121] In a third aspect, the present invention provides a host device, comprising

[0122] memory for storing computer programs;

[0123] The processor is used to implement the above-mentioned method for coupling control of branch temperature and flow in the thermal hydraulic experimental system when executing the computer program.

[0124] In a fourth aspect, the present invention provides a computer program product, comprising a computer program / instruction, which, when executed by a processor, implements the steps of the above-mentioned method for coupling control of branch temperature and flow in a thermal hydraulic experimental system.

[0125] In a fifth aspect, the present invention provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are loaded and executed by a processor, the coupling control method of the branch temperature and flow of the above-mentioned thermal-hydraulic experimental system is implemented.

[0126] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A coupling control method for branch temperature and flow in a thermal hydraulic experiment system, characterized in that: include Collecting historical data of the thermal hydraulic experiment system, wherein the historical data includes ambient temperature, heating power, experiment body inlet flow, experiment body inlet fluid temperature, experiment body outlet fluid temperature and experiment body inlet and outlet fluid average pressure; According to the average pressure of the fluid inlet and outlet of the experimental body, the constant pressure specific heat capacity of the working fluid is obtained through the working fluid physical property function; The heating power coefficient is calculated based on the heating power, the experimental body inlet flow rate, the experimental body inlet fluid temperature, the experimental body outlet fluid temperature and the working fluid constant pressure specific heat capacity; The heating power coefficient prediction model to be trained is trained using the ambient temperature, the experimental body inlet flow rate, the experimental body inlet fluid temperature, the experimental body outlet fluid temperature, and the heating power coefficient to obtain a trained heating power coefficient prediction model; The real-time ambient temperature, the experimental body inlet flow rate, the experimental body inlet fluid temperature and the experimental body outlet fluid temperature are used as input parameters of the heating power coefficient prediction model to predict the heating power coefficient. The heating power feedforward value is calculated based on the predicted heating power coefficient, the target value of the experimental body outlet fluid temperature, the real-time experimental body inlet flow, the experimental body inlet fluid temperature and the constant pressure specific heat capacity of the working fluid; According to the deviation between the target temperature value of the fluid outlet of the main body and the temperature of the fluid outlet of the main body, the PID control algorithm is used to obtain the heating power feedback adjustment value; The heating power feedforward value and the heating power feedback value are added to obtain the body heating power value. The body heating power value is used as the target value to adjust the experimental body heating power to achieve control of the fluid temperature at the experimental body outlet.

2. The coupled control method of branch temperature and flow of a thermal hydraulic experimental system according to claim 1 is characterized in that: In the heating power coefficient prediction model, ambient temperature, experimental body inlet flow, experimental body inlet fluid temperature, and experimental body outlet fluid temperature are used as input parameters, and the heating power coefficient is the output result.

3. The method for coupling control of branch temperature and flow in a thermal hydraulic experiment system according to claim 1, characterized in that: The heating power coefficient prediction model adopts an artificial neural network algorithm or a convolutional neural algorithm.

4. The method for coupling control of branch temperature and flow in a thermal hydraulic experiment system according to claim 1, characterized in that: The heating power coefficient is calculated by the following formula: α=P / (F in ·(T out -T in )·c p ) Where, α: heating power coefficient; P: heating power; F in : Experimental body inlet flow; T in : Temperature of fluid at the inlet of the experimental body; T out : The outlet fluid temperature of the experimental body; c p : Specific heat capacity of working fluid at constant pressure.

5. The method for coupling control of branch temperature and flow in a thermal hydraulic experiment system according to claim 1, characterized in that: The heating power feedforward value is calculated by the following formula: P ff =α ff ·F in ·(T out,s -T in )·c p Where, P ff : Heating power feedforward value; α ff : predicted value of heating power coefficient; F in : Experimental body inlet flow; T out,s : Target value of the main body outlet temperature; T in : Temperature of fluid at the inlet of the experimental body; c p : Specific heat capacity of working fluid at constant pressure.

6. The method for coupling control of branch temperature and flow in a thermal hydraulic experiment system according to claim 1, characterized in that: The adjusting the heating power of the experimental body specifically refers to adjusting the voltage and current of the experimental body so that the actual heating power value is consistent with the body heating power value.

7. A coupled control system for branch temperature and flow in a thermal hydraulic experiment system, characterized in that: Applied to thermal hydraulic experimental system, including The first parameter acquisition module is used to obtain historical data of the thermal hydraulic experiment system, the historical data including ambient temperature, heating power, experiment body inlet flow, experiment body inlet fluid temperature, experiment body outlet fluid temperature and experiment body inlet and outlet fluid average pressure; The first calculation module is used to obtain the constant-pressure specific heat capacity of the working fluid through the working fluid physical property function according to the average pressure of the fluid inlet and outlet of the experimental body; The second calculation module is used to calculate the heating power coefficient according to the heating power, the experimental body inlet flow rate, the experimental body inlet temperature, the experimental body outlet temperature and the constant pressure specific heat capacity of the working fluid; A model training module is used to use the ambient temperature, the experimental body inlet flow rate, the experimental body inlet fluid temperature, and the experimental body outlet fluid temperature as inputs and the heating power coefficient as output to train a heating power coefficient prediction model and obtain a trained heating power coefficient prediction model; The second parameter acquisition module is used to obtain the real-time ambient temperature of the thermal hydraulic experiment system, the experiment body inlet flow, the experiment body inlet fluid temperature, the experiment body outlet fluid temperature and the experiment body inlet and outlet fluid average pressure; The prediction module inputs the real-time ambient temperature, the experimental body inlet flow rate, the experimental body inlet fluid temperature and the experimental body outlet fluid temperature target value into the heating power coefficient prediction model to predict the heating power coefficient; The third calculation module calculates the heating power feedforward value through the predicted value of the heating power coefficient, the target value of the experimental body outlet fluid temperature, and the experimental body inlet flow rate, experimental body inlet fluid temperature, and constant pressure specific heat capacity of the working fluid in the predicted sample; The third parameter acquisition module obtains the outlet fluid temperature of the experimental body in real time; A fourth calculation module calculates a target difference value by using the temperature of the fluid at the outlet of the experimental body and the standard value of the temperature of the fluid at the outlet of the experimental body, and inputs the target difference value into a PID controller to obtain a heating power feedback adjustment value; A fifth calculation module obtains a main body heating power value by adding the heating power feedforward value and the heating power feedback value; The control module is connected to the thermal hydraulic experiment system and adjusts the outlet fluid temperature of the experiment body according to the heating power value of the body.

8. A host device, characterized in that: include memory for storing computer programs; A processor is used to implement the coupled control method of branch temperature and flow of a thermal hydraulic experimental system as described in any one of claims 1 to 6 when executing the computer program.

9. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the steps of the method for coupling control of branch temperature and flow in a thermal hydraulic experimental system according to any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions. When the computer-executable instructions are loaded and executed by the processor, the method for coupling control of branch temperature and flow in a thermal-hydraulic experimental system according to any one of claims 1 to 6 is implemented.

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