A digital modeling method and device for a fuel system of a turboshaft engine test stand

Abstract

This application discloses a digital modeling method and apparatus for a turboshaft engine test bench fuel system, belonging to the field of aero-engine fuel system technology. The method includes: establishing a physical digital model of the test bench fuel system based on its structural composition and dividing its operating modes; measuring and processing input and output parameters for use in the physical digital model; establishing a mechanism model based on the physical digital model according to the physical formulas of the input and output parameters, and optimizing the mechanism model based on historical data collected on key characteristic relationships; constructing a simulation model of the fuel system using a hybrid C++ and Simulink programming approach based on the physical digital model and the optimized mechanism model; and performing real-time monitoring and processing of the measurement data, integrating the test bench physical mechanism model with the measurement data to compensate for the insufficient accuracy caused by simplified assumptions in traditional mechanism models, significantly improving modeling and simulation speed without sacrificing accuracy.

Description

Technical Field

[0001] This application belongs to the field of aero-engine fuel system technology, and specifically relates to a digital modeling method and device for the fuel system of a turboshaft engine test bench. Background Technology

[0002] The performance of the fuel system directly affects the reliability of test data. High-precision fuel flow measurement and stable fuel supply ensure that test data accurately reflects the actual performance of the engine. In traditional turboshaft engine test bench fuel system modeling, mathematical modeling methods based on physical principles, such as the characteristic line method, are typically used. The core of the characteristic line method lies in the in-depth analysis and precise description of the working characteristics of each component of the fuel system. Through a large amount of experimental data and theoretical derivation, a set of mathematical equations is constructed to simulate the operating state of the entire fuel system.

[0003] However, in practical applications, obtaining accurate component characteristic data often faces numerous difficulties. On the one hand, the engine and its fuel system are themselves highly complex mechanical and fluid coupled systems, making it extremely difficult to obtain accurate characteristic data for a particular component under such complex interactions. On the other hand, the equations to be solved in real-time simulation and multiphysics coupling analysis become enormous and complex, the solution process is extremely cumbersome, and the computation time increases significantly, resulting in insufficient speed and real-time performance during testing, which restricts the speed of engine testing and the progress of research and development. Summary of the Invention

[0004] To address the aforementioned problems, this application provides a digital modeling method for the fuel system of a turboshaft engine test bench, the improvement of which includes:

[0005] Based on the composition structure of the test bench fuel system, a physical digital model of the test bench fuel system is established and the working modes are divided. Input and output parameters are measured and processed for use in the physical digital model.

[0006] Based on the physical formulas of the physical model of the entity, a mechanism model is established and optimized based on historical data collected on the relationship between key characteristics.

[0007] Based on the physical digital model and the optimized mechanism model, a simulation model of the fuel system was constructed using a hybrid programming approach of C++ and Simulink.

[0008] Optionally, the input parameters of the entity digital model include at least one or more of the following: model control variables, boundary condition variables, or control command variables; the boundary condition variables include, but are not limited to, oil pressure at the oil depot, oil temperature at the oil depot, atmospheric temperature, atmospheric pressure, and fuel supply volume flow rate.

[0009] The output parameters of the physical digital model include at least one or more of the following: pressure at the pressure sensor, liquid level in the negative pressure tank, liquid level in the oil storage tank, fuel supply pressure, fuel supply temperature, or fuel supply mass flow rate.

[0010] Optionally, the measurement of input and output parameters, after processing, for use in the entity digitization model includes:

[0011] High-precision pressure sensors are installed at key locations in the fuel system to measure fuel supply pressure in real time. Flow meters are installed in the fuel delivery pipelines, and high-precision measuring equipment is used to measure the fuel supply volume flow rate in real time. Temperature sensors are installed in the fuel tanks, pipelines, and fuel supply outlets, and measuring elements such as resistance temperature detectors (RTDs) or thermocouples are used to monitor the fuel supply temperature, fuel depot inlet temperature, and atmospheric temperature in real time. Liquid level sensors are installed in the fuel tanks, and ultrasonic or pressure level gauges are used to monitor the liquid level height in the negative pressure fuel tank and the liquid level height in the storage tank in real time.

[0012] Based on the test mode, the measured input and output parameters are segmented. The segmented data is cleaned using an adaptive Kalman filter algorithm combined with multiple wavelet basis functions to eliminate noise. Key characteristic parameters are extracted from the cleaned data using a MATLAB program. Finally, the key characteristic parameters determined through regression analysis are input into the entity digitization model to complete the parameter assignment of the entity digitization model.

[0013] Optionally, establishing the mechanism model based on the physical formulas of the input and output parameters includes:

[0014] The heat loss of fuel in the pipeline is calculated using a steady-state heat transfer formula;

[0015] Establish a differential equation for the liquid level with respect to time, and calculate the liquid level in the oil tank in real time based on the simulated time.

[0016] The heat lost by the fuel in the pipeline Q m Determine using the following formula:

[0017]

[0018] In the formula, This indicates the specific heat capacity of fuel. Indicates the oil temperature coming into the oil depot. Indicates the fuel supply temperature. Indicates atmospheric temperature. This indicates the thermal resistance of heat exchange between the fuel and the environment inside the pipeline.

[0019] In the oil replenishment operation mode of the oil storage tank, the oil tank level Determine by the following formula:

[0020]

[0021] Indicates the initial liquid level height of the oil storage tank. This represents the change in fuel quantity in the oil storage tank, where t represents time. This indicates the bottom area of ​​the oil storage tank.

[0022] Optionally, the key characteristic relationships of the fuel system mechanism model include at least one or more of the following: the characteristic relationship between pressure drop characteristics and volumetric flow rate, the characteristic relationship between pump boosting characteristics and volumetric flow rate, and the characteristic relationship between pressure drop characteristics and fuel change per unit time.

[0023] Optionally, in the oil storage tank supply mode, the characteristic relationship between the pump pressurization characteristics and the volumetric flow rate of the first section of the pipeline is defined. f 3. The characteristic relationship between the pressure drop characteristics and the volumetric flow rate of the second pipeline section. f 2. There are:

[0024]

[0025] in, Indicates atmospheric pressure. This indicates the pressure at pressure sensor #2. Indicates fuel supply pressure. Indicates the fuel supply volumetric flow rate;

[0026] Under the oil storage tank supply mode, the characteristic relationship between the pressure drop characteristics of the pipeline from the system inlet to the oil storage tank and the fuel change per unit time is investigated. f 8. There are:

[0027]

[0028] in, This indicates that the oil pressure at the oil depot is high. Indicates atmospheric pressure. This indicates the change in fuel quantity in the oil storage tank.

[0029] Optionally, the construction of the digital model of the fuel system, based on the physical digital model and the optimized mechanism model, using a hybrid programming approach of C++ and Simulink, includes:

[0030] A digital model of the fuel system is obtained by using C++ code to program the entity digital model and the optimized mechanism model.

[0031] The digital model of the fuel system is encapsulated using Simulink.

[0032] Optionally, the operating mode includes at least one or more of the following:

[0033] Oil depot direct oil supply mode, oil storage tank normal oil supply mode, negative pressure oil supply mode, negative pressure oil tank replenishment mode, or oil storage tank replenishment mode.

[0034] Based on the same inventive concept, this application also provides a digital modeling device for the fuel system of a turboshaft engine test bench, the improvement of which includes:

[0035] The digital abstraction unit is used to establish a physical digital model of the test bench fuel system based on the composition structure of the test bench fuel system, divide the working modes, measure and process the input and output parameters, and then use them for the physical digital model.

[0036] The mechanism model unit is used to establish a mechanism model based on the physical formulas of the input and output parameters of the entity digital model, and to optimize the mechanism model based on historical data collected on key characteristic relationships.

[0037] The simulation unit is used to construct a simulation model of the fuel system based on the physical digital model and the optimized mechanism model, using a hybrid programming approach of C++ and Simulink.

[0038] Optionally, the input parameters of the entity digital model include at least one or more of the following: model control variables, boundary condition variables, or control command variables; the boundary condition variables include, but are not limited to, oil pressure at the oil depot, oil temperature at the oil depot, atmospheric temperature, atmospheric pressure, and fuel supply volume flow rate.

[0039] The output parameters of the physical digital model include at least one or more of the following: pressure at the pressure sensor, liquid level in the negative pressure tank, liquid level in the oil storage tank, fuel supply pressure, fuel supply temperature, or fuel supply mass flow rate.

[0040] Optionally, the measurement of input and output parameters, after processing, for use in the entity digitization model includes:

[0041] High-precision pressure sensors are installed at key locations in the fuel system to measure fuel supply pressure in real time. Flow meters are installed in the fuel delivery pipelines, and high-precision measuring equipment is used to measure the fuel supply volume flow rate in real time. Temperature sensors are installed in the fuel tanks, pipelines, and fuel supply outlets, and measuring elements such as resistance temperature detectors (RTDs) or thermocouples are used to monitor the fuel supply temperature, fuel depot inlet temperature, and atmospheric temperature in real time. Liquid level sensors are installed in the fuel tanks, and ultrasonic or pressure level gauges are used to monitor the liquid level height in the negative pressure fuel tank and the liquid level height in the storage tank in real time.

[0042] Based on the test mode, the measured input and output parameters are segmented. The segmented data is cleaned using an adaptive Kalman filter algorithm combined with multiple wavelet basis functions to eliminate noise. Key characteristic parameters are extracted from the cleaned data using a MATLAB program. Finally, the key characteristic parameters determined through regression analysis are input into the entity digitization model to complete the parameter assignment of the entity digitization model.

[0043] Optionally, establishing the mechanism model based on the physical formulas of the input and output parameters includes:

[0044] The heat loss of fuel in the pipeline is calculated using a steady-state heat transfer formula;

[0045] Establish a differential equation for the liquid level with respect to time, and calculate the liquid level in the oil tank in real time based on the simulated time.

[0046] The heat lost by the fuel in the pipeline Q m Determine using the following formula:

[0047]

[0048] In the formula, This indicates the specific heat capacity of fuel. Indicates the oil temperature coming into the oil depot. Indicates the fuel supply temperature. Indicates atmospheric temperature. This indicates the thermal resistance of heat exchange between the fuel and the environment inside the pipeline.

[0049] In the oil replenishment operation mode of the oil storage tank, the oil tank level Determine by the following formula:

[0050]

[0051] Indicates the initial liquid level height of the oil storage tank. This represents the change in fuel quantity in the oil storage tank, where t represents time. This indicates the bottom area of ​​the oil storage tank.

[0052] Optionally, the key characteristic relationships of the fuel system mechanism model include at least one or more of the following: the characteristic relationship between pressure drop characteristics and volumetric flow rate, the characteristic relationship between pump boosting characteristics and volumetric flow rate, and the characteristic relationship between pressure drop characteristics and fuel change per unit time.

[0053] Optionally, in the oil storage tank supply mode, the characteristic relationship between the pump pressurization characteristics and the volumetric flow rate of the first section of the pipeline is defined. f 3. The characteristic relationship between the pressure drop characteristics and the volumetric flow rate of the second pipeline section.f 2. There are:

[0054]

[0055] in, Indicates atmospheric pressure. This indicates the pressure at pressure sensor #2. Indicates fuel supply pressure. Indicates the fuel supply volumetric flow rate;

[0056] Under the oil storage tank supply mode, the characteristic relationship between the pressure drop characteristics of the pipeline from the system inlet to the oil storage tank and the fuel change per unit time is investigated. f 8. There are:

[0057]

[0058] in, This indicates that the oil pressure at the oil depot is high. Indicates atmospheric pressure. This indicates the change in fuel quantity in the oil storage tank.

[0059] Optionally, the construction of the digital model of the fuel system, based on the physical digital model and the optimized mechanism model, using a hybrid programming approach of C++ and Simulink, includes:

[0060] A digital model of the fuel system is obtained by using C++ code to program the entity digital model and the optimized mechanism model.

[0061] The digital model of the fuel system is encapsulated using Simulink.

[0062] Optionally, the operating mode includes at least one or more of the following:

[0063] Oil depot direct oil supply mode, oil storage tank normal oil supply mode, negative pressure oil supply mode, negative pressure oil tank replenishment mode, or oil storage tank replenishment mode.

[0064] Furthermore, this application also provides a computing device, comprising: at least one processor and a memory;

[0065] The memory is used to store one or more programs;

[0066] When the one or more programs are executed by the one or more processors, a digital modeling method for the fuel system of a turboshaft engine test bench, as described above, is implemented.

[0067] In another aspect, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed, implements the digital modeling method for a turboshaft engine test bench fuel system as described above.

[0068] Compared with the prior art, this application has the following advantages:

[0069] This application provides a digital modeling method and apparatus for a turboshaft engine test bench fuel system, comprising: establishing a physical digital model of the test bench fuel system based on its composition and structure, dividing it into working modes, measuring and processing input and output parameters for use in the physical digital model; establishing a mechanism model based on the physical digital model according to the physical formulas of the input and output parameters, and optimizing the mechanism model based on historical data collected on key characteristic relationships; and constructing a simulation model of the fuel system using a hybrid programming approach of C++ and Simulink based on the physical digital model and the optimized mechanism model.

[0070] By integrating the physical mechanism model of the test bench with measurement data, the insufficient accuracy caused by the simplification assumptions in the traditional mechanism model is compensated for, thereby more accurately reflecting the real characteristics of each component of the fuel system. Without sacrificing accuracy, the modeling and simulation speed is significantly improved, enabling the fuel system model to respond to changes in engine status in real time and support real-time operation. This provides timely and accurate basis for adjusting the fuel supply strategy during the test run, improving test efficiency and the accuracy of engine performance testing.

[0071] To improve the level of precision, traditional mechanistic models often simplify complex systems for ease of derivation, resulting in insufficient prediction accuracy. In this application, a large amount of data can be used to identify the key details that have been "simplified" through statistical analysis and data mining, which can then be used to optimize the model structure and make it more closely resemble the real system.

[0072] The method described in this application has powerful real-time data acquisition, processing, and analysis capabilities, enabling real-time monitoring and diagnosis of key parameters such as fuel pressure, flow rate, and temperature. Once an anomaly is detected, it can react quickly and take timely measures to ensure the safety and stability of the test run.

[0073] Other features and advantages of this application will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0074] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0075] Figure 1 A flowchart illustrating the implementation of a digital modeling method for a turboshaft engine test bench fuel system provided in this application is shown.

[0076] Figure 2 The flowchart of the digital modeling method for the fuel system of a turboshaft engine test bench provided in this application is shown.

[0077] Figure 3 This application shows a schematic diagram of the physical model of the fuel system of the turboshaft engine test bench.

[0078] Figure 4 This paper shows a schematic diagram of the digital model construction of the fuel system of the turboshaft engine test bench provided in this application;

[0079] Figure 5 The diagram shows the user interface of the Simulink simulation model of the fuel system on the turboshaft engine test bench provided in this application.

[0080] Figure 6 This application provides an organizational diagram of a digital modeling device for the fuel system of a turboshaft engine test bench. Detailed Implementation

[0081] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0082] Example 1

[0083] This application provides a digital modeling method for the fuel system of a turboshaft engine test bench, such as... Figure 1 ,include:

[0084] Based on the composition structure of the test bench fuel system, a physical digital model of the test bench fuel system is established and the working modes are divided. Input and output parameters are measured and processed for use in the physical digital model.

[0085] Based on the physical formulas of the physical model of the entity, a mechanism model is established and optimized based on historical data collected on the relationship between key characteristics.

[0086] Based on the physical digital model and the optimized mechanism model, a simulation model of the fuel system was constructed using a hybrid programming approach of C++ and Simulink.

[0087] The technical solution architecture diagram of this application is as follows: Figure 2 As shown;

[0088] S1: Analyze the modeling requirements of the fuel system of the turboshaft engine test bench, perform digital modeling and abstraction of the solid model, and divide the working modes.

[0089] S2: Integrate the physical mechanism model of the test bench with the test data;

[0090] S3: Digital model building through mixed programming of C++ and Simulink.

[0091] Further, step S1 includes the following steps:

[0092] S11: Clearly define the composition and structure of the fuel system on the test bench, understand the function and principle of each component, and based on this, perform digital modeling and abstraction of the fuel system's physical model. A schematic diagram of the abstracted digital model is shown below. Figure 3 As shown.

[0093] Furthermore, digital modeling abstraction involves simplifying and making assumptions about the schematic diagram.

[0094] The simplification assumptions are as follows:

[0095] (1) The electric regulating valve of the negative pressure oil tank and the oil replenishment solenoid valve of the oil storage tank are automatically controlled by the liquid level controller and the small closed loop, which can realize the automatic replenishment of the negative pressure oil tank and the oil storage tank. Therefore, these two valves can be simplified.

[0096] (2) The pressure at the outlet of the negative pressure tank is approximately equal to the pressure inside the negative pressure tank, i.e., the pressure at pressure sensor No. 1.

[0097] (3) The heating process can be ideally controlled, that is, the temperature response follows the target value in real time.

[0098] (4) The oil storage tank and the negative pressure oil tank are large containers, and the oil temperature inside the tank is approximately equal to the temperature of the test workshop.

[0099] (5) The oil storage tank is connected to the outside world, and the pressure inside the tank is approximately equal to the pressure in the test workshop.

[0100] (6) The negative pressure oil tank can achieve ideal control during the negative pressure test, that is, the pressure inside the tank responds to the target value immediately, and in other cases it is approximately equal to the pressure of the test workshop.

[0101] S12: Based on the functional principles of the fuel system, the working modes of the test bench fuel system are divided in detail.

[0102] The working modes are divided into 5 modes, including direct oil supply from the oil depot, normal oil supply from the oil storage tank, negative pressure oil supply, oil replenishment from the negative pressure oil tank, and oil replenishment from the oil storage tank.

[0103] S13: Review the measurable parameters and experimental data to determine the input and output parameters of the digital model.

[0104] The input parameters include 12 model control variables, 5 boundary condition variables, and 2 control command variables.

[0105] The model control variables include the on / off status of manual valve 1, manual valve 2, manual valve 5, manual valve 7, solenoid valve 1, solenoid valve 2, electric fire damper, vacuum pump, booster pump, and heater.

[0106] Boundary condition variables include oil pressure from the oil depot, oil temperature from the oil depot, atmospheric temperature, atmospheric pressure, and fuel supply volumetric flow rate.

[0107] Control command variables include negative pressure reference command and fuel heating target temperature command.

[0108] The output parameters include the pressure at pressure sensor 1, the pressure at pressure sensor 2, the liquid level in the negative pressure tank, the liquid level in the oil storage tank, the fuel supply pressure, the fuel supply temperature, and the fuel supply mass flow rate.

[0109] High-precision pressure sensors are installed at key locations in the fuel system to measure fuel supply pressure in real time. Flow meters are installed in the fuel delivery pipeline, using high-precision measuring equipment to measure the fuel supply volumetric flow rate in real time. Temperature sensors are installed in the fuel tank, pipelines, and fuel supply outlet, using measuring elements such as resistance temperature detectors (RTDs) or thermocouples to monitor the fuel supply temperature, fuel depot inlet temperature, and atmospheric temperature in real time. Level sensors are installed in the fuel tank, using ultrasonic level gauges or pressure level gauges to monitor the liquid level in the negative pressure fuel tank and the liquid level in the storage tank in real time.

[0110] Based on the test mode, the measured input and output parameters are segmented. The segmented data is cleaned using an adaptive Kalman filter algorithm combined with multiple wavelet basis functions to eliminate noise. Key characteristic parameters are extracted from the cleaned data using a MATLAB program. Finally, the key characteristic parameters determined through regression analysis are input into the entity digitization model to complete the parameter assignment of the entity digitization model.

[0111] Further, step S2 includes the following steps:

[0112] S21: Construct the underlying architecture of the fuel system mechanism model on the test bench through physical formulas;

[0113] Furthermore, valves and components that require switching (including pumps, heaters, etc.) are digitized, with 0 representing closed and 1 representing open.

[0114] For calculating fuel volumetric flow rate and pipeline pressure, taking the fuel tank supply mode as an example, the pipeline involved is divided into two sections: the first section is from the fuel tank to pressure sensor No. 2; the second section is from pressure sensor No. 2 to the system outlet. The pressure at pressure sensor No. 2 and the fuel supply volumetric flow rate can both be calculated based on the inlet and outlet pressures and pressure drop characteristics of both pipeline sections.

[0115] Furthermore, for the calculation of fuel temperature, taking the direct supply mode from the fuel depot as an example, heat exchange is considered for the second pipeline section, and the transient effect in the heat transfer process is ignored. That is, the heat lost by the fuel in the pipeline is equal to the heat transferred to the environment. The steady-state heat transfer formula is used for calculation.

[0116]

[0117] in, This indicates the specific heat capacity of fuel. Indicates the oil temperature coming into the oil depot. Indicates the fuel supply temperature. Indicates atmospheric temperature. This indicates the thermal resistance between the fuel and the environment inside the pipeline.

[0118] Furthermore, for the calculation of oil tank level, taking the oil replenishment working mode of oil storage tank as an example, a differential equation of liquid level with respect to time is established, and the real-time calculation of oil tank level is performed based on the simulated time.

[0119]

[0120] in, Indicates the liquid level height in the oil storage tank. Indicates the initial liquid level height of the oil storage tank. This indicates the change in fuel quantity in the oil storage tank. Indicates time, This indicates the bottom area of ​​the oil storage tank.

[0121] S22: By mining experimental data, drive the key characteristics of the fuel system mechanism model on the test bench.

[0122] Furthermore, for the calculation of fuel volumetric flow rate, a characteristic relationship between pressure drop characteristics and volumetric flow rate is established;

[0123] Furthermore, for the calculation of pipeline pressure, the characteristic relationship between pump pressurization characteristics and volumetric flow rate is established;

[0124] For the calculation of fuel volume flow rate and pipeline pressure, taking the fuel tank supply mode as an example, given the pressure boosting characteristics and pressure drop characteristics of the two pipeline pumps, atmospheric pressure, and fuel supply pressure, the pressure at pressure sensor No. 2 can be obtained by solving the equation set.

[0125]

[0126] in, Indicates atmospheric pressure. This indicates the pressure at pressure sensor #2. Indicates fuel supply pressure. This indicates the volumetric flow rate of fuel supply.

[0127] Furthermore, for the calculation of fuel change per unit time in the oil tank, a characteristic relationship between pressure drop characteristics and fuel change per unit time is established.

[0128] For calculating the oil tank level, taking the oil replenishment operation mode of the oil storage tank as an example, the following model is constructed for the pipeline from the system inlet to the oil storage tank:

[0129]

[0130] in, This indicates that the oil pressure at the oil depot is high. Indicates atmospheric pressure. This indicates the change in fuel quantity in the oil storage tank.

[0131] function The function represents the pressurization-flow characteristics of the pump in the first section of the pipeline. The function represents the pressure drop-flow characteristic of the second pipeline section. This indicates the pressure drop-flow characteristic of this pipeline section. The characteristics of the three pipeline sections can be obtained through regression analysis of existing experimental data.

[0132] Furthermore, the pressure drop-flow characteristics of each pipeline section have their own specific numerical characteristic table.

[0133] Furthermore, each pump has its own specific numerical characteristic table for pressure drop-flow rate.

[0134] Furthermore, each oil tank has a specific numerical characteristic table for its pressure drop-fuel change per unit time characteristic.

[0135] Furthermore, step S3 includes the following steps:

[0136] S31: Algorithm kernel for developing a digital model of the fuel system on a test bench based on C++;

[0137] Furthermore, using C++ code, we developed the algorithm kernel for the digital model of the fuel system on the test bench. The algorithm enables functions such as real-time simulation, working mode recognition, and automatic fuel replenishment.

[0138] S32: Using Simulink to encapsulate the digital model of the fuel system on the test bench.

[0139] Furthermore, the digital model of the fuel system on the test bench is encapsulated on the Simulink platform to build a simulation model and perform real-time simulation. The specific operation interface is as follows: Figure 4 The specific simulation results are as follows: Figure 5 .

[0140] The digital modeling method for the fuel system of a turboshaft engine test bench presented in this application addresses the shortcomings of traditional fuel system modeling methods in terms of accuracy and real-time performance, significantly improving modeling and simulation speed without sacrificing accuracy. This enables the fuel system model to respond in real-time to changes in engine status, supporting real-time operation and providing timely and accurate data for adjusting fuel supply strategies during testing, thereby improving testing efficiency and the accuracy of engine performance testing.

[0141] The digital modeling method for the fuel system of the turboshaft engine test bench disclosed in this application possesses powerful real-time data acquisition, processing, and analysis capabilities. It enables real-time monitoring and diagnosis of key parameters such as fuel pressure, flow rate, and temperature. Upon detecting anomalies, it can react rapidly and take timely measures to ensure the safety and stability of the test process. This invention lays the foundation for Digital Prototype 3.0, which emphasizes the integration of model-based design, development, and verification, requiring each subsystem model to possess high precision, high real-time performance, and excellent collaborative capabilities.

[0142] Example 2

[0143] Based on the same inventive concept, this application also provides a digital modeling device for the fuel system of a turboshaft engine test bench, such as... Figure 6 ,include:

[0144] The digital abstraction unit is used to establish a physical digital model of the test bench fuel system based on the composition structure of the test bench fuel system, divide the working modes, measure and process the input and output parameters, and then use them for the physical digital model.

[0145] The mechanism model unit is used to establish a mechanism model based on the physical formulas of the input and output parameters of the entity digital model, and to optimize the mechanism model based on historical data collected on key characteristic relationships.

[0146] The simulation unit is used to construct a simulation model of the fuel system based on the physical digital model and the optimized mechanism model, using a hybrid programming approach of C++ and Simulink.

[0147] Optionally, the input parameters of the entity digital model include at least one or more of the following: model control variables, boundary condition variables, or control command variables; the boundary condition variables include, but are not limited to, oil pressure at the oil depot, oil temperature at the oil depot, atmospheric temperature, atmospheric pressure, and fuel supply volume flow rate.

[0148] The output parameters of the physical digital model include at least one or more of the following: pressure at the pressure sensor, liquid level in the negative pressure tank, liquid level in the oil storage tank, fuel supply pressure, fuel supply temperature, or fuel supply mass flow rate.

[0149] Optionally, the measurement of input and output parameters, after processing, for use in the entity digitization model includes:

[0150] High-precision pressure sensors are installed at key locations in the fuel system to measure fuel supply pressure in real time. Flow meters are installed in the fuel delivery pipelines, and high-precision measuring equipment is used to measure the fuel supply volume flow rate in real time. Temperature sensors are installed in the fuel tanks, pipelines, and fuel supply outlets, and measuring elements such as resistance temperature detectors (RTDs) or thermocouples are used to monitor the fuel supply temperature, fuel depot inlet temperature, and atmospheric temperature in real time. Liquid level sensors are installed in the fuel tanks, and ultrasonic or pressure level gauges are used to monitor the liquid level height in the negative pressure fuel tank and the liquid level height in the storage tank in real time.

[0151] Based on the test mode, the measured input and output parameters are segmented. The segmented data is cleaned using an adaptive Kalman filter algorithm combined with multiple wavelet basis functions to eliminate noise. Key characteristic parameters are extracted from the cleaned data using a MATLAB program. Finally, the key characteristic parameters determined through regression analysis are input into the entity digitization model to complete the parameter assignment of the entity digitization model.

[0152] Optionally, establishing the mechanism model based on the physical formulas of the input and output parameters includes:

[0153] The heat loss of fuel in the pipeline is calculated using a steady-state heat transfer formula;

[0154] Establish a differential equation for the liquid level with respect to time, and calculate the liquid level in the oil tank in real time based on the simulated time.

[0155] The heat lost by the fuel in the pipeline Q m Determine using the following formula:

[0156]

[0157] In the formula, This indicates the specific heat capacity of fuel. Indicates the oil temperature coming into the oil depot. Indicates the fuel supply temperature. Indicates atmospheric temperature. This indicates the thermal resistance between the fuel and the environment inside the pipeline.

[0158] In the oil replenishment operation mode of the oil storage tank, the oil tank level Determine by the following formula:

[0159]

[0160] Indicates the initial liquid level height of the oil storage tank. This represents the change in fuel quantity in the oil storage tank, where t represents time. This indicates the bottom area of ​​the oil storage tank.

[0161] Optionally, the key characteristic relationships of the fuel system mechanism model include at least one or more of the following: the characteristic relationship between pressure drop characteristics and volumetric flow rate, the characteristic relationship between pump boosting characteristics and volumetric flow rate, and the characteristic relationship between pressure drop characteristics and fuel change per unit time.

[0162] Optionally, in the oil storage tank supply mode, the characteristic relationship between the pump pressurization characteristics and the volumetric flow rate of the first section of the pipeline is defined. f 3. The characteristic relationship between the pressure drop characteristics and the volumetric flow rate of the second pipeline section. f 2. There are:

[0163]

[0164] in, Indicates atmospheric pressure. This indicates the pressure at pressure sensor #2. Indicates fuel supply pressure. Indicates the fuel supply volumetric flow rate;

[0165] Under the oil storage tank supply mode, the characteristic relationship between the pressure drop characteristics of the pipeline from the system inlet to the oil storage tank and the fuel change per unit time is investigated. f 8. There are:

[0166]

[0167] in, This indicates that the oil pressure at the oil depot is high. Indicates atmospheric pressure. This indicates the change in fuel quantity in the oil storage tank.

[0168] Optionally, the construction of the digital model of the fuel system, based on the physical digital model and the optimized mechanism model, using a hybrid programming approach of C++ and Simulink, includes:

[0169] A digital model of the fuel system is obtained by using C++ code to program the entity digital model and the optimized mechanism model.

[0170] The digital model of the fuel system is encapsulated using Simulink.

[0171] Optionally, the operating mode includes at least one or more of the following:

[0172] Oil depot direct oil supply mode, oil storage tank normal oil supply mode, negative pressure oil supply mode, negative pressure oil tank replenishment mode, or oil storage tank replenishment mode.

[0173] Example 3

[0174] Based on the same inventive concept, this application also provides an electronic device. The electronic device of this application includes at least one processor and at least one storage medium electrically connected to the processor. The storage medium is electrically connected to the processor, wherein the storage medium stores instructions executable by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform the method described above.

[0175] Example 4

[0176] Based on the same inventive concept, this application also provides a storage medium storing instructions executable by at least one processor, the instructions being executed by at least one processor to enable at least one processor to perform the method described above.

[0177] Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A digital modeling method for a turboshaft engine test cell fuel system, characterized in that, include: Based on the composition structure of the test bench fuel system, a physical digital model of the test bench fuel system is established and the working modes are divided. Input and output parameters are measured and processed for use in the physical digital model. Based on the physical formulas of the physical model of the entity, a mechanism model is established and optimized based on historical data collected on the relationship between key characteristics. Based on the physical digital model and the optimized mechanism model, a simulation model of the fuel system was constructed using a hybrid programming approach of C++ and Simulink. The input parameters of the entity digital model include at least one or more of the following: model control variables, boundary condition variables, or control command variables; the boundary condition variables include, but are not limited to, oil depot inlet pressure, oil depot inlet temperature, atmospheric temperature, atmospheric pressure, and fuel supply volume flow rate; the output parameters of the entity digital model include at least one or more of the following: pressure at the pressure sensor, liquid level in the negative pressure oil tank, liquid level in the oil storage tank, fuel supply pressure, fuel supply temperature, or fuel supply mass flow rate. The physical formulas for the input and output parameters are established by the following mechanism models: The heat loss of fuel in the pipeline is calculated using a steady-state heat transfer formula; Establish a differential equation for the liquid level with respect to time, and calculate the liquid level in the oil tank in real time based on the simulated time. wherein the heat lost by the fuel in the pipe Q m is determined by the formula: In the formula, This indicates the specific heat capacity of fuel. Indicates the oil temperature coming into the oil depot. Indicates the fuel supply temperature. Indicates atmospheric temperature. This indicates the thermal resistance of heat exchange between the fuel and the environment inside the pipeline. In the oil replenishment operation mode of the oil storage tank, the oil tank level Determine using the following formula: Indicates the initial liquid level height of the oil storage tank. This represents the change in fuel quantity in the oil storage tank, where t represents time. This indicates the bottom area of ​​the oil storage tank.

2. The method as described in claim 1, characterized in that, The measured input and output parameters, after processing, are used for the entity digitization model, including: High-precision pressure sensors are installed at key locations in the fuel system to measure fuel supply pressure in real time. Flow meters are installed in the fuel delivery pipelines, and high-precision measuring equipment is used to measure the fuel supply volume flow rate in real time. Temperature sensors are installed in the fuel tanks, pipelines, and fuel supply outlets, and resistance temperature detectors or thermocouples are used to monitor the fuel supply temperature, fuel depot inlet temperature, and atmospheric temperature in real time. Liquid level sensors are installed in the fuel tanks, and ultrasonic or pressure level gauges are used to monitor the liquid level height in the negative pressure fuel tank and the liquid level height in the storage tank in real time. Based on the test mode, the measured input and output parameters are segmented. The segmented data is cleaned using an adaptive Kalman filter algorithm combined with multiple wavelet basis functions to eliminate noise. Key characteristic parameters are extracted from the cleaned data using a MATLAB program. Finally, the key characteristic parameters determined through regression analysis are input into the entity digitization model to complete the parameter assignment of the entity digitization model.

3. The method as described in claim 1, characterized in that, The key characteristic relationships of the fuel system mechanism model include at least one or more of the following: the characteristic relationship between pressure drop characteristics and volumetric flow rate, the characteristic relationship between pump boosting characteristics and volumetric flow rate, and the characteristic relationship between pressure drop characteristics and fuel change per unit time.

4. A method as described in claim 3, characterized in that, Under the oil storage tank supply mode, the characteristic relationship between the pump pressurization characteristics and the volumetric flow rate of the first section of the pipeline. f 3. The characteristic relationship between the pressure drop characteristics and the volumetric flow rate of the second pipeline section. f 2. There are: in, Indicates atmospheric pressure. This indicates the pressure at pressure sensor #2. Indicates fuel supply pressure. Indicates the fuel supply volumetric flow rate; Under the oil storage tank supply mode, the characteristic relationship between the pressure drop characteristics of the pipeline from the system inlet to the oil storage tank and the fuel change per unit time is investigated. f 8. There are: in, This indicates that the oil pressure at the oil depot is high. Indicates atmospheric pressure. This indicates the change in fuel quantity in the oil storage tank.

5. A method according to claim 1, characterized in that, The process involves constructing a digital model of the fuel system using a hybrid C++ and Simulink programming approach, based on the physical digital model and the optimized mechanistic model. This includes: A digital model of the fuel system is obtained by using C++ code to program the entity digital model and the optimized mechanism model. The digital model of the fuel system is encapsulated using Simulink.

6. The method according to claim 1, characterized in that, The operating modes include at least one or more of the following: Oil depot direct oil supply mode, oil storage tank normal oil supply mode, negative pressure oil supply mode, negative pressure oil tank replenishment mode, or oil storage tank replenishment mode.

7. A digital modeling device for the fuel system of a turboshaft engine test bench, characterized in that, include: The digital abstraction unit is used to establish a physical digital model of the test bench fuel system based on the composition structure of the test bench fuel system, divide the working modes, measure and process the input and output parameters, and then use them for the physical digital model. The mechanism model unit is used to establish a mechanism model based on the physical formulas of the input and output parameters of the entity digital model, and to optimize the mechanism model based on historical data collected on key characteristic relationships. The simulation unit is used to construct a simulation model of the fuel system based on the physical digital model and the optimized mechanism model, using a hybrid programming approach of C++ and Simulink. The input parameters of the entity digital model include at least one or more of the following: model control variables, boundary condition variables, or control command variables; the boundary condition variables include, but are not limited to, oil depot inlet pressure, oil depot inlet temperature, atmospheric temperature, atmospheric pressure, and fuel supply volume flow rate; the output parameters of the entity digital model include at least one or more of the following: pressure at the pressure sensor, liquid level in the negative pressure oil tank, liquid level in the oil storage tank, fuel supply pressure, fuel supply temperature, or fuel supply mass flow rate. The physical formulas for the input and output parameters are established by the following mechanism models: The heat loss of fuel in the pipeline is calculated using a steady-state heat transfer formula; Establish a differential equation for the liquid level with respect to time, and calculate the liquid level in the oil tank in real time based on the simulated time. The heat lost by the fuel in the pipeline Q m Determine using the following formula: In the formula, This indicates the specific heat capacity of fuel. Indicates the oil temperature coming into the oil depot. Indicates the fuel supply temperature. Indicates atmospheric temperature. This indicates the thermal resistance of heat exchange between the fuel and the environment inside the pipeline. In the oil replenishment operation mode of the oil storage tank, the oil tank level Determine using the following formula: Indicates the initial liquid level height of the oil storage tank. This represents the change in fuel quantity in the oil storage tank, where t represents time. This indicates the bottom area of ​​the oil storage tank.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the digital modeling method for the fuel system of a turboshaft engine test bench as described in any one of claims 1-6.

9. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; When a processor executes a program stored in a memory, it implements the steps of the digital modeling method for the fuel system of a turboshaft engine test bench as described in any one of claims 1-6.

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