Performance evaluation method of self-adaptive variable cycle engine and electronic equipment

Abstract

The invention relates to a performance evaluation method for an ACE (Adaptive Cycle Engine) and electronic equipment. The method comprises the following steps: acquiring a to-be-evaluated ACE complete machine zero-dimensional simulation model, an adaptive fan high-fidelity simulation model, and working conditions and control rules of the to-be-evaluated ACE complete machine zero-dimensional simulation model; coupling the obtained models to obtain an ACE multi-dimensional coupling simulation model, and operating under the obtained working condition and control rule to obtain the ACE performance to be evaluated and the performance of each component in the ACE performance; according to the ACE multi-dimensional coupling simulation model, characteristic curves in an ACE complete machine zero-dimensional simulation model are adopted to represent characteristics of different ducts of a self-adaptive fan in the ACE complete machine zero-dimensional simulation model, and based on the difference of simulation results between the ACE complete machine zero-dimensional simulation model and the self-adaptive fan high-fidelity simulation model, the self-adaptive fan high-fidelity simulation model is obtained. The method is obtained after coupling is realized by continuously iteratively adjusting the scaling factor of the characteristic curve, so that the simulation precision of the self-adaptive fan is improved, and the overall performance evaluation accuracy is improved.

Description

Technical Field

[0001] This article relates to aero-engine technology, particularly to a performance evaluation method and electronic equipment for an adaptive cycle engine (ACE). Background Art

[0002] A comprehensive and accurate evaluation of aircraft engine performance is crucial for ensuring flight safety. Establishing a zero-dimensional simulation model of an engine is an important means of evaluating its performance. However, with the development of the aviation industry, ACE has emerged. Therefore, it is also necessary to establish a suitable model for ACE to evaluate its performance.

[0003] In related technologies, a zero-dimensional simulation model of the ACE engine is often established to obtain a zero-dimensional simulation model of the entire ACE for evaluating ACE performance. The established zero-dimensional simulation model of the entire ACE is established by characterizing the adaptive fan using two independent characteristic diagrams.

[0004] However, in reality, the aerodynamic coupling between the first fan and the second fan is very obvious, and the model construction method of the relevant technology cannot accurately characterize the adaptive fan, which makes the ACE overall performance simulation accuracy low, greatly affecting the accuracy of performance evaluation. Summary of the Invention

[0005] The embodiments of the present application provide a performance evaluation method and electronic device for ACE, which can improve the performance simulation accuracy of the entire machine and improve the accuracy of performance evaluation.

[0006] The present application provides a method for evaluating the performance of an ACE, the method comprising: Obtain the zero-dimensional simulation model of the ACE system to be evaluated and the high-fidelity simulation model of the adaptive fan therein, as well as the operating conditions and control laws of the ACE to be evaluated; The zero-dimensional simulation model of the ACE system to be evaluated and the high-fidelity simulation model of the adaptive fan are coupled to obtain the ACE multi-dimensional coupled simulation model; The obtained ACE multi-dimensional coupled simulation model is run according to the obtained ACE working conditions and control laws to obtain the performance of the ACE to be evaluated and the performance of each component therein; Among them, the ACE multi-dimensional coupling simulation model adopts the characteristic curves in the ACE whole machine zero-dimensional simulation model to be evaluated to respectively characterize the characteristics of different ducts of the adaptive fan, and based on the difference between the ACE whole machine zero-dimensional simulation model to be evaluated and the adaptive fan high-fidelity simulation model, continuously iteratively adjusts the scaling factor of the characteristic curve to achieve coupling between the ACE whole machine zero-dimensional simulation model and the adaptive fan high-fidelity simulation model.

[0007] An embodiment of the present application further provides an electronic device, comprising: a memory and a processor; The memory is connected to the processor and is used to store programs; The processor is used to implement the ACE performance evaluation method described above by running the program in the memory.

[0008] An embodiment of the present application includes obtaining a zero-dimensional simulation model of the ACE whole machine to be evaluated and a high-fidelity simulation model of the adaptive fan therein, as well as the working conditions and control laws of the ACE to be evaluated; coupling the zero-dimensional simulation model of the ACE whole machine to be evaluated and the high-fidelity simulation model of the adaptive fan therein to obtain an ACE multi-dimensional coupled simulation model; running the obtained ACE multi-dimensional coupled simulation model according to the obtained working conditions and control laws of the ACE to obtain the performance of the ACE to be evaluated and the performance of each component therein; wherein, the ACE multi-dimensional coupled simulation model adopts the characteristic curves in the zero-dimensional simulation model of the ACE whole machine to be evaluated to respectively characterize the characteristics of different ducts of the adaptive fan therein, and based on the difference between the zero-dimensional simulation model of the ACE whole machine to be evaluated and the high-fidelity simulation model of the adaptive fan therein, continuously iteratively adjusts the scaling factor of the characteristic curve to achieve the coupling between the zero-dimensional simulation model of the ACE whole machine and the high-fidelity simulation model of the adaptive fan. Therefore, by coupling the ACE zero-dimensional simulation model for the entire machine and the adaptive fan high-fidelity simulation model specifically for the adaptive fan, bidirectional data transmission between the two models is achieved, so that after convergence, the actual aerodynamic conditions in different ducts are reflected in the ACE zero-dimensional simulation model of the entire machine. Therefore, the adaptive fan flow field can be directly analyzed under the boundary conditions of the final ACE zero-dimensional simulation model of the entire machine, thereby improving the simulation accuracy of the ACE entire machine performance and the accuracy of the performance evaluation.

[0009] Other features and advantages of the present application will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present application. Other advantages of the present application can be realized and obtained by the solutions described in the description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The accompanying drawings are used to provide an understanding of the technical solution of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the technical solution of the present application and do not constitute a limitation on the technical solution of the present application.

[0011] Figure 1 Schematic diagram of a typical configuration of an adaptive fan in related art; Figure 2 This is a flow chart of a performance evaluation method of ACE according to an embodiment of the present application; Figure 3 This is a schematic diagram of a process for obtaining an ACE multi-dimensional coupling simulation model according to an embodiment of the present application; Figure 4 This is a flow chart of a model iteration operation according to an embodiment of the present application; Figure 5 It is a schematic diagram of the structure of a double-external ACE in the related art; Figure 6a It is a structural diagram of the zero-dimensional simulation model of the ACE whole machine in the related art; Figure 6b This is a structural diagram of a zero-dimensional simulation model of an ACE whole machine based on two streams characterizing an adaptive fan according to an embodiment of the present application; Figure 7 This is a flow chart of another ACE performance evaluation method according to an embodiment of the present application; Figure 8a A schematic diagram of a correction process for an adaptive fan intrinsic characteristic according to an embodiment of the present application; Figure 8b A schematic diagram of a correction process for an adaptive fan duct characteristic according to an embodiment of the present application; Figure 9a This is a schematic structural diagram of the ACE zero-dimensional simulation model of the adaptive fan based on two streams characterization in an embodiment of the present application; Figure 9b This is a schematic structural diagram of the ACE zero-dimensional simulation model of the adaptive fan based on three stream characterizations according to an embodiment of the present application; Figure 10 This is a schematic structural diagram of an ACE performance evaluation device according to an embodiment of the present application; Figure 11 This is a structural diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0012] This application describes multiple embodiments, but this description is exemplary rather than restrictive, and it is obvious to those skilled in the art that there may be more embodiments and implementations within the scope of the embodiments described in this application. Although many possible feature combinations are shown in the drawings and discussed in the detailed description, many other combinations of the disclosed features are also possible. Unless specifically limited, any feature or element of any embodiment may be used in combination with any other feature or element in any other embodiment, or may replace any other feature or element in any other embodiment.

[0013] The present application includes and contemplates combinations of features and elements known to those of ordinary skill in the art. The embodiments, features, and elements disclosed in this application may also be combined with any conventional features or elements to form a unique inventive solution. Any features or elements of any embodiment may also be combined with features or elements from other inventive solutions to form another unique inventive solution. Therefore, it should be understood that any feature shown and / or discussed in this application may be implemented individually or in any appropriate combination. Therefore, except for the limitations made according to the appended claims and their equivalents, the embodiments are not subject to other limitations. In addition, various modifications and changes may be made within the scope of protection of the appended claims.

[0014] In addition, when describing representative embodiments, the specification may have presented the method and / or process as a specific sequence of steps. However, to the extent that the method or process does not rely on the specific order of the steps described herein, the method or process should not be limited to the steps in the specific order described. As will be understood by those skilled in the art, other orders of steps are also possible. Therefore, the specific order of the steps set forth in the specification should not be interpreted as a limitation to the claims. In addition, the claims for the method and / or process should not be limited to performing their steps in the order written, and those skilled in the art can readily understand that these orders can be changed and still remain within the spirit and scope of the embodiments of the present application.

[0015] ACE utilizes a multi-duct structure and numerous variable geometry components, enabling flexible adjustment of the engine's operating mode and thermodynamic cycle parameters, breaking through the design constraints of traditional engines. During takeoff and air combat, ACE operates at high thrust, similar to a low-bypass-ratio turbofan engine, while during cruise flight, it maintains low fuel consumption, similar to a high-bypass-ratio turbofan engine. It is considered an ideal powerplant for next-generation aircraft.

[0016] The adaptive fan is a key component in ACE's variable cycle function. In addition to achieving the traditional fan boost function, the adaptive fan also realizes ACE's unique flow regulation, working mode conversion, reducing intake duct overflow resistance, thermal management and other functions. The coupling effect with the entire machine is very strong. The typical configuration diagram of the adaptive fan can be shown as follows: Figure 1 As shown, the adaptive fan is divided into two parts: the first fan (i.e., the fan closer to the air inlet and farther from the air outlet of the two fans, often called the front fan, denoted as FFan) and the second fan (i.e., the fan farther from the air inlet and closer to the air outlet of the two fans, often called the rear fan, denoted as RFan). A diverter ring and corresponding duct are located between the first and second fan outlets. By adjusting the fan guide vane angle, the stator blade angle, and the duct outlet flow area, the bypass ratio and fan pressure ratio of the ACE can be adjusted. The second fan outlet is also typically equipped with a diverter ring, resulting in three airflows exiting the adaptive fan. This configuration of the adaptive fan is also called a three-flow fan. As can be seen from the above analysis, adaptive fans differ significantly from traditional fans. Therefore, accurately characterizing the adaptive fan is crucial to improving the overall performance simulation accuracy of the ACE.

[0017] However, the ACE's complex structure, multiple geometrically variable components, and multiple operating modes—particularly the complex multi-duct adaptive fan—significantly impact the accuracy of overall ACE performance simulations. Furthermore, conventional characteristic curves struggle to accurately represent the complex characteristics of adaptive fans, making it difficult to reliably predict ACE steady-state performance using traditional simulation methods. Further improving ACE steady-state performance evaluation methods to enhance the simulation accuracy of both the ACE and the adaptive fan, while balancing solution speed, feasibility, solution stability, and ease of use, has become a key challenge in this field.

[0018] Currently, the most widely used aviation engine performance simulation method is the zero-dimensional (0D) simulation method. Based on a zero-dimensional model, this method uses the balance relationships between components, such as power, flow, and speed, and aerodynamic thermodynamic equations to calculate the gas parameters at the inlet and outlet sections of each engine component, as well as key performance parameters of the entire engine, including thrust and fuel consumption. Therefore, it has the advantages of a simple model architecture, high computational efficiency, and good versatility. Due to these advantages, the zero-dimensional simulation model is often used in related technologies for ACE engines to establish a zero-dimensional simulation model of the ACE engine, thereby obtaining a zero-dimensional simulation model of the entire ACE for ACE performance evaluation.

[0019] However, in the ACE full-scale zero-dimensional simulation model, the adaptive fan is represented using two separate characteristic maps: one for each of the first and second fans. This approach employs two assumptions: 1) the adaptive fan's outer duct characteristics are represented using the average characteristics of the first fan; and 2) the flow interactions between the first and second fans, and their impact on the adaptive fan, are ignored. In reality, the axial spacing between the first and second fans is small, resulting in significant aerodynamic coupling between them. Due to the presence of the splitter ring and the outer duct, the radial distribution of the aerodynamic parameters at the first fan outlet is highly non-uniform, resulting in a significant difference between the outer duct characteristics and the average characteristics of the first fan. Furthermore, at different split ratios (the ratio of the outer duct flow rate at the first fan outlet to the second fan inlet flow rate), the streamline shape and flow field structure near the splitter ring change, altering the radial distribution of the aerodynamic parameters at the first fan outlet. This, in turn, affects the characteristics of both the first and second fans. Consequently, the overall performance simulation accuracy is low, and numerous design iterations are required, negatively impacting the ACE development cycle, development costs, and R&D quality.

[0020] To this end, the present disclosure provides a performance evaluation method for ACE, such as Figure 2 Shown, including: Step 100: Obtain a zero-dimensional simulation model of the ACE to be evaluated, a high-fidelity simulation model of the adaptive fan therein, and the operating conditions and control laws of the ACE to be evaluated.

[0021] Step 110 : Couple the ACE whole machine zero-dimensional simulation model to be evaluated and the adaptive fan high-fidelity simulation model therein to obtain the ACE multi-dimensional coupled simulation model.

[0022] Step 120 : Run the obtained ACE multi-dimensional coupling simulation model according to the obtained ACE working conditions and control laws to obtain the performance of the ACE to be evaluated and the performance of each component therein.

[0023] Among them, the ACE multi-dimensional coupling simulation model adopts the characteristic curves in the ACE whole machine zero-dimensional simulation model to be evaluated to respectively characterize the characteristics of different ducts of the adaptive fan, and based on the difference between the ACE whole machine zero-dimensional simulation model to be evaluated and the adaptive fan high-fidelity simulation model, continuously iteratively adjusts the scaling factor of the characteristic curve to achieve coupling between the ACE whole machine zero-dimensional simulation model and the adaptive fan high-fidelity simulation model.

[0024] The ACE performance evaluation method provided in the embodiment of the present application realizes bidirectional data transmission between the two models by coupling the ACE zero-dimensional simulation model for the whole machine and the high-fidelity simulation model of the adaptive fan specifically for the adaptive fan, so that after convergence, the actual aerodynamic conditions in different ducts are reflected in the ACE zero-dimensional simulation model of the whole machine. Therefore, the adaptive fan flow field can be directly analyzed under the boundary conditions of the final ACE zero-dimensional simulation model of the whole machine, thereby improving the accuracy of the ACE whole machine performance simulation and the accuracy of the performance evaluation.

[0025] The method used in related art to separately characterize the first fan (front fan) and the second fan (rear fan) lacks a system-level perspective, and this localized characterization may lead to neglecting the collaborative working effect of the entire ACE. The ACE performance evaluation method provided in the embodiments of this application uses characteristic curves from the ACE's zero-dimensional simulation model to separately characterize the characteristics of different ducts of the adaptive fan in the ACE. Using the characteristics of different ducts as the characterization objects provides a more macro perspective, helps understand the response mechanism of the entire ACE, and thus facilitates understanding the aerodynamic characteristics of the ACE.

[0026] In an exemplary embodiment, Figure 3 As shown, each of the ACE multi-dimensional coupled simulation models is obtained by: Step 200: construct a simulation model for the ACE whole machine to obtain the zero-dimensional simulation model of the ACE whole machine, and construct an adaptive fan in the ACE to obtain a high-fidelity simulation model of the adaptive fan.

[0027] The constructed high-fidelity simulation model of the adaptive fan can be a one-dimensional model, a two-dimensional model, or a three-dimensional model. When the constructed high-fidelity simulation model of the adaptive fan is a three-dimensional model, the adaptive fan has a higher degree of simulation.

[0028] Step 210: Determine a representation method for the adaptive fan according to the external structure type of the ACE and the simulation accuracy requirement.

[0029] The external structure types of ACE include: single external structure ACE, double external structure ACE and triple external structure ACE. When the external structure type of ACE is double external structure ACE, ACE includes: inner duct and outer duct. According to the simulation accuracy requirements, the characteristics of one or more structures of the first fan, the second fan, the inner duct and the outer duct can be characterized. Each characterized characteristic can be a characteristic of one of these structures, or a joint characteristic of multiple structures. When the external structure type of ACE is double external structure ACE, ACE includes: inner duct, the first outer duct and the second outer duct (the first outer duct and the second outer duct refer to the first layer of outer duct airflow channel and the second layer of outer duct airflow channel, respectively, which are gradually farther away from the core engine). According to the simulation accuracy requirements, the characteristics of one or more structures of the first fan, the second fan, the inner duct, the first outer duct and the second outer duct can be characterized. The characteristics of the fan are characterized, and each characterized characteristic can be a characteristic of one of these structures, or a joint characteristic of multiple structures; when the outer containment type of ACE is a three-outer containment configuration ACE, ACE includes: an inner duct, a first outer duct, a second outer duct, and a third outer duct (the first outer duct, the second outer duct, and the third outer duct refer to the first layer of outer duct airflow channel, the second layer of outer duct airflow channel, and the third layer of outer duct airflow channel, which are gradually farther away from the core engine respectively). According to the simulation accuracy requirements, the characteristics of one or more structures of the first fan, the second fan, the inner duct, the first outer duct, the second outer duct, and the third outer duct can be characterized. Each characterized characteristic can be a characteristic of one of these structures, or a joint characteristic of multiple structures.

[0030] For example, when the configuration of the ACE is a double-external configuration ACE, the characterization method of the adaptive fan can be a two-stream characterization method, and the two-stream characterization method can be a characterization method for characterizing the internal characteristics and the external characteristics; when the configuration of the ACE is a double-external configuration ACE, the characterization method of the adaptive fan can also be a three-stream characterization method, and the three-stream characterization method can be a characterization method for characterizing the internal characteristics, the first external characteristics, and the second external characteristics.

[0031] Step 220: Characterize the adaptive fan according to the determined characterization method and using the characteristic curve in the ACE whole machine zero-dimensional simulation model.

[0032] When the configuration of the ACE is a double-external configuration ACE and it is determined to adopt a two-stream characterization method, the converted flow characteristic curve, pressure ratio characteristic curve and isentropic efficiency characteristic curve in the ACE whole machine zero-dimensional simulation model can be used to characterize the internal characteristics and the external characteristics respectively; when the configuration of the ACE is a double-external configuration ACE and it is determined to adopt a three-stream characterization method, the converted flow characteristic curve, pressure ratio characteristic curve and isentropic efficiency characteristic curve in the ACE whole machine zero-dimensional simulation model can be used to characterize the internal characteristics, the first external characteristics and the second external characteristics respectively.

[0033] Step 230: Based on the characterized adaptive fan, obtain the difference between the ACE whole machine zero-dimensional simulation model and the adaptive fan high-fidelity simulation model, and continuously iterate the scaling factor of the characteristic curve used to characterize the adaptive fan in the ACE whole machine zero-dimensional simulation model based on the obtained difference until the obtained difference is less than the preset requirement, thereby obtaining the ACE multi-dimensional coupling simulation model.

[0034] In an exemplary embodiment, based on the characterized adaptive fan, obtaining a difference between the ACE whole-machine zero-dimensional simulation model and the adaptive fan high-fidelity simulation model, and continuously iterating the scaling factor of the characteristic curve used to characterize the adaptive fan in the ACE whole-machine zero-dimensional simulation model based on the obtained difference until the obtained difference is less than a preset requirement, thereby obtaining the ACE multi-dimensional coupled simulation model, including: The constructed ACE whole machine zero-dimensional simulation model is used as the current ACE whole machine zero-dimensional simulation model, and the constructed adaptive fan high-fidelity simulation model is used as the current adaptive fan high-fidelity simulation model. The following model iteration operation is performed cyclically until the difference between the adaptive fan performance under the obtained adaptive fan high-fidelity simulation model and the adaptive fan performance under the obtained ACE whole machine zero-dimensional simulation model is less than a preset threshold. The finally obtained ACE whole machine zero-dimensional simulation model is used as the ACE multi-dimensional coupled simulation model. The model iteration operation is as follows: Figure 4 As shown, including: Step 300: Run the current ACE whole machine zero-dimensional simulation model to obtain a high-fidelity simulation model result of the adaptive fan under the current ACE whole machine zero-dimensional simulation model.

[0035] In addition, running the current ACE whole-machine zero-dimensional simulation model can also obtain the whole-machine performance, among which the whole-machine performance includes: engine thrust, fuel consumption and turbine inlet temperature.

[0036] Step 310: Use the adaptive fan high-fidelity simulation model results under the current ACE whole machine zero-dimensional simulation model to update the adaptive fan boundary conditions under the current adaptive fan high-fidelity simulation model, obtain an updated adaptive fan high-fidelity simulation model, and replace the updated current adaptive fan high-fidelity simulation model with it as the current adaptive fan high-fidelity simulation model.

[0037] Step 320: Obtain the adaptive fan performance under the current adaptive fan high-fidelity simulation model according to the current adaptive fan high-fidelity simulation model.

[0038] Step 330: When the difference between the adaptive fan high-fidelity simulation model result obtained under the current adaptive fan high-fidelity simulation model and the adaptive fan performance obtained under the current ACE whole machine zero-dimensional simulation model is not less than a preset threshold, the intrinsic characteristic diagram scaling factor and the extrinsic characteristic diagram scaling factor in the current ACE whole machine zero-dimensional simulation model are updated according to the adaptive fan performance obtained under the current adaptive fan high-fidelity simulation model to obtain an updated ACE whole machine zero-dimensional simulation model, and the updated current ACE whole machine zero-dimensional simulation model is replaced by the updated one as the current ACE whole machine zero-dimensional simulation model.

[0039] The difference between the adaptive fan performance obtained under the current adaptive fan high-fidelity simulation model and the adaptive fan performance obtained under the current ACE whole machine zero-dimensional simulation model can be obtained through the residual between the two.

[0040] In an exemplary embodiment, when the configuration of the ACE is a double-external configuration ACE, the characterization mode of the adaptive fan includes: a two-stream characterization mode and a three-stream characterization mode; Among them, the characterization method of the two flows is a joint characterization method of the outer duct characteristics and the inner duct characteristics, the outer duct characteristics are the comprehensive characteristics of the first fan blade tip part and the second outer duct, and the inner duct characteristics are the comprehensive characteristics of the first fan blade root part and the second fan.

[0041] The three-stream characterization method is a joint characterization method of the characteristics of the second outer duct, the characteristics of the first outer duct and the characteristics of the inner duct. The second outer duct characteristic is the comprehensive characteristic of the first fan blade tip part and the second outer duct, the first outer duct characteristic is the comprehensive characteristic of the first fan blade root part and the second fan blade tip, and the inner duct characteristic is the comprehensive characteristic of the first fan blade root part and the second fan blade heel.

[0042] In an exemplary instance, the adaptive fan high-fidelity simulation model results include: adaptive fan inlet simulation results and adaptive fan outlet simulation results, the adaptive fan inlet simulation results include: adaptive fan inlet total pressure simulation results and adaptive fan inlet total temperature simulation results; the adaptive fan outlet simulation results include: adaptive fan duct outlet flow simulation results and adaptive fan duct outlet total pressure simulation results; the adaptive fan boundary conditions include: physical speed, guide vane variable geometric angle, adaptive fan inlet boundary conditions, and adaptive fan duct outlet boundary conditions.

[0043] In an exemplary embodiment, when a two-stream representation method is adopted, updating the adaptive fan boundary conditions under the current adaptive fan high-fidelity simulation model using the adaptive fan high-fidelity simulation model results under the current ACE whole machine zero-dimensional simulation model includes: The adaptive fan inlet simulation results under the current ACE whole machine zero-dimensional simulation model are used as the adaptive fan inlet boundary conditions under the current adaptive fan high-fidelity simulation model; The total pressure simulation result of the inner duct outlet is selected from the adaptive fan outlet simulation results under the current ACE whole machine zero-dimensional simulation model as the adaptive fan inner duct outlet boundary condition under the current adaptive fan high-fidelity simulation model, and the outer duct outlet flow simulation result is selected from the adaptive fan outlet simulation results under the current ACE whole machine zero-dimensional simulation model as the adaptive fan outer duct outlet boundary condition under the current adaptive fan high-fidelity simulation model.

[0044] In an exemplary embodiment, when a three-stream representation method is adopted, updating the adaptive fan boundary conditions under the current adaptive fan high-fidelity simulation model using the adaptive fan high-fidelity simulation model results under the current ACE whole machine zero-dimensional simulation model includes: The adaptive fan inlet simulation results under the current ACE whole machine zero-dimensional simulation model are used as the adaptive fan inlet boundary conditions under the current adaptive fan high-fidelity simulation model; The total pressure simulation result of the inner duct outlet is selected from the adaptive fan outlet simulation results under the current ACE whole machine zero-dimensional simulation model as the adaptive fan inner duct outlet boundary condition under the current adaptive fan high-fidelity simulation model, and the first outer duct outlet flow simulation result is selected from the adaptive fan outlet simulation results under the current ACE whole machine zero-dimensional simulation model as the adaptive fan first outer duct outlet boundary condition under the current adaptive fan high-fidelity simulation model, and the second outer duct outlet flow simulation result is selected from the adaptive fan outlet simulation results under the current ACE whole machine zero-dimensional simulation model as the adaptive fan second outer duct outlet boundary condition under the current adaptive fan high-fidelity simulation model.

[0045] The combination of boundary conditions in the above embodiments of the present application helps to improve the stability and convergence of iterative coupling simulation in practical applications.

[0046] To uniquely determine the operating state of the adaptive fan, in addition to the adaptive fan inlet boundary conditions, the adaptive fan outlet boundary conditions must also be specified, typically in the form of outlet static pressure or flow rate. Considering that the ACE complete machine zero-dimensional simulation model primarily involves total parameters (or stagnation parameters), when using the outlet static pressure boundary condition, a custom function is used during the simulation to adjust the outlet static pressure in real time to achieve a given outlet total pressure or a given total pressure ratio. Therefore, the above process can be understood as specifying a given outlet total pressure boundary condition. For a high-fidelity adaptive fan simulation model with two outlets, there are four possible combinations of outlet boundary conditions. When flow rate boundary conditions are used for both the external and internal outlets, the flow rate obtained by the ACE complete machine zero-dimensional simulation model may exceed the flow rate range of the adaptive fan high-fidelity simulation model, resulting in an inability to obtain a converged solution. When the total pressure boundary condition is used for the outer duct outlet, since the outer duct pressure ratio in the ACE whole machine zero-dimensional simulation model is equal to the average pressure ratio of the front fan, the difference in the front fan blade tip characteristics and the total pressure loss in the outer duct are not taken into account. The outer duct pressure ratio may be overestimated, resulting in the adaptive fan high-fidelity simulation model outlet back pressure being too high and the outer duct flow rate being close to zero, and the convergence solution cannot be obtained. Therefore, in the embodiment of the present application, the outer duct outlet adopts the flow boundary condition and the inner duct outlet adopts the total pressure boundary condition. Such a combination of boundary conditions helps to improve the stability and convergence of the iterative coupling simulation. The boundary condition setting can be as follows, where the adaptive fan high-fidelity simulation model takes the adaptive fan three-dimensional simulation model as an example: (1) in, represents the total pressure at the inlet of the adaptive fan under the three-dimensional simulation model of the adaptive fan, represents the total pressure of the adaptive fan inlet under the ACE zero-dimensional simulation model, represents the total inlet temperature under the adaptive fan 3D simulation model, represents the total inlet temperature under the ACE zero-dimensional simulation model, represents the physical speed of the adaptive fan under the three-dimensional simulation model, Indicates the physical speed of the ACE machine under the zero-dimensional simulation model, Indicates the variable geometric angle of the rear fan guide blade under the adaptive fan 3D simulation model, Indicates the variable geometric angle of the rear fan guide vane under the ACE whole machine zero-dimensional simulation model, It represents the external conversion flow rate under the three-dimensional simulation model of the adaptive fan. It represents the external conversion flow under the ACE whole machine zero-dimensional simulation model, represents the intrinsic outlet static pressure under the three-dimensional simulation model of the adaptive fan, represents the intrinsic total pressure ratio under the three-dimensional simulation model of the adaptive fan, It represents the intrinsic total pressure ratio under the zero-dimensional simulation model of the ACE whole machine.

[0047] In an exemplary embodiment, obtaining the adaptive fan performance under the current adaptive fan high-fidelity simulation model according to the current adaptive fan high-fidelity simulation model includes: The current adaptive fan high-fidelity simulation model is run to obtain the current adaptive fan high-fidelity simulation results. Based on the obtained current adaptive fan high-fidelity simulation results, the adaptive fan performance under the current adaptive fan high-fidelity simulation model is calculated using the mass flow averaging method.

[0048] In an exemplary embodiment, when the determined representation method is a two-stream representation method, updating the intrinsic characteristic map scaling factor and the extrinsic characteristic map scaling factor in the current ACE whole machine zero-dimensional simulation model based on the obtained adaptive fan performance under the current adaptive fan high-fidelity simulation model includes: A relaxation factor is introduced, and the intrinsic characteristic map scaling factor and the extrinsic characteristic map scaling factor in the current ACE whole machine zero-dimensional simulation model are updated respectively according to the adaptive fan performance obtained under the current adaptive fan high-fidelity simulation model.

[0049] In an exemplary embodiment, when the determined representation method is a three-stream representation method, the extrinsic characteristic map scaling factor includes: a first extrinsic characteristic map scaling factor and a second extrinsic characteristic map scaling factor; and updating the intrinsic characteristic map scaling factor and the extrinsic characteristic map scaling factor in the current ACE whole machine zero-dimensional simulation model based on the obtained adaptive fan performance under the current adaptive fan high-fidelity simulation model includes: A relaxation factor is introduced, and the intrinsic characteristic map scaling factor, the first extrinsic characteristic map scaling factor and the second extrinsic characteristic map scaling factor in the current ACE whole machine zero-dimensional simulation model are updated respectively according to the adaptive fan performance obtained under the current adaptive fan high-fidelity simulation model.

[0050] The introduction of the relaxation factor can suppress parameter oscillation during the iteration process. Usually, the relaxation factor can be set to 0.5. The update of the intrinsic characteristic map scaling factor and the extrinsic characteristic map scaling factor in the ACE whole machine zero-dimensional simulation model can be expressed as follows: (2) in, 、 and They represent the converted flow scaling factor, pressure ratio scaling factor and isentropic efficiency scaling factor under the ACE whole machine zero-dimensional simulation model respectively. i and i +1 represents the current unupdated step and the next updated step respectively.

[0051] Since the boundary condition setting formula ensures and Therefore, it is only necessary to correct the flow scaling factor and efficiency scaling factor of the intrinsic characteristic diagram, and the pressure ratio scaling factor and efficiency scaling factor of the extrinsic characteristic diagram.

[0052] In an exemplary embodiment, the operating conditions include: flight altitude, flight Mach number; The control law includes: low-pressure physical speed, or the control law includes: low-pressure physical speed and variable geometry law, and the variable geometry law includes: guide vane variable geometry guide vane angle.

[0053] In an exemplary embodiment, when the determined characterization method is a two-stream characterization method, the adaptive fan performance includes: internal converted flow rate, internal total pressure ratio, internal efficiency, external converted flow rate, external total pressure ratio, and external efficiency; When the determined characterization method is the three-stream characterization method, the adaptive fan performance includes: internal converted flow, internal total pressure ratio, internal efficiency, first external converted flow, first external total pressure ratio, first external efficiency, second external converted flow, second external total pressure ratio, and second external efficiency.

[0054] The present application also provides a method for evaluating the performance of ACE. Figure 5 Take the double-external duct configuration ACE shown as an example. In the related art, the adaptive fan is characterized in series using the FFan characteristic and the RFan characteristic. In the performance evaluation method of ACE provided in the embodiment of the present application, the adaptive fan is characterized in parallel using different duct characteristics. Therefore, before performing iterative coupling simulation, the ACE whole machine zero-dimensional model needs to be adaptively modified. Taking the two-stream characterization of the adaptive fan as an example, the ACE whole machine zero-dimensional simulation model in the related art and the ACE whole machine zero-dimensional simulation model of the adaptive fan based on the two-stream characterization in the embodiment of the present application can be as follows Figure 6a 、 6b As shown. Figure 6a It can be seen that the representation of the adaptive fan in the ACE whole machine zero-dimensional simulation model in the related art is represented by the series connection of FFan and RFan. Figure 6bIt can be seen that the characterization method of the adaptive fan in the embodiment of the present application is modified to a parallel representation of the front and rear separated fan core (Split Fan Core) and the front and rear separated fan bypass (Split FanBypass), wherein the Split Fan Bypass characteristic is a comprehensive characteristic considering the near-tip part of the first fan and the second bypass, and the Split Fan Core characteristic is a comprehensive characteristic considering the near-root part of the first fan and the second fan.

[0055] Still taking the adaptive fan high-fidelity simulation model as an adaptive fan three-dimensional simulation model as an example, the performance evaluation method of ACE provided in the embodiment of the present application is as follows: Figure 7 Shown, including: Step 400: Set the working conditions (also called working conditions) and control laws of the ACE.

[0056] Among them, the working conditions of ACE include: flight altitude, flight Mach number, and the control laws of ACE include: low-pressure physical speed, variable geometry law, etc.

[0057] Step 410: Run the ACE whole machine zero-dimensional simulation model to obtain the whole machine performance, adaptive fan performance, and adaptive fan boundary conditions.

[0058] Among them, the overall performance includes: engine thrust, fuel consumption and turbine inlet temperature. Adaptive fan performance includes internal conversion flow, internal total pressure ratio, internal efficiency, external conversion flow, external total pressure ratio, and external efficiency. Adaptive fan boundary conditions include: adaptive fan inlet total pressure , total inlet temperature , physical speed , the rear fan guide vane changes the geometric angle dVG.

[0059] Step 420: Update the adaptive fan boundary conditions of the adaptive fan three-dimensional simulation model.

[0060] The adaptive fan boundary conditions of the adaptive fan 3D simulation model are set to the corresponding values ​​of the ACE full-machine zero-dimensional simulation model. The adaptive fan boundary conditions of the adaptive fan 3D simulation model can be set as follows.

[0061] ( ) in, represents the total pressure at the inlet of the adaptive fan under the three-dimensional simulation model of the adaptive fan, represents the total pressure of the adaptive fan inlet under the ACE zero-dimensional simulation model, represents the total inlet temperature under the adaptive fan 3D simulation model, represents the total inlet temperature under the ACE zero-dimensional simulation model, represents the physical speed of the adaptive fan under the three-dimensional simulation model, Indicates the physical speed of the ACE machine under the zero-dimensional simulation model, Indicates the variable geometric angle of the rear fan guide blade under the adaptive fan 3D simulation model, Indicates the variable geometric angle of the rear fan guide vane under the ACE whole machine zero-dimensional simulation model, It represents the external conversion flow rate under the three-dimensional simulation model of the adaptive fan. It represents the external conversion flow under the ACE whole machine zero-dimensional simulation model, represents the intrinsic outlet static pressure under the three-dimensional simulation model of the adaptive fan, represents the intrinsic total pressure ratio under the three-dimensional simulation model of the adaptive fan, It represents the intrinsic total pressure ratio under the zero-dimensional simulation model of the ACE whole machine.

[0062] Step 430: Run the adaptive fan three-dimensional simulation model under the set boundary conditions to obtain the adaptive fan performance.

[0063] In practical applications, the mass flow averaging method can be used to calculate the adaptive fan performance.

[0064] Step 440: Calculate the characteristic residual between the adaptive fan three-dimensional simulation model and the ACE whole machine zero-dimensional simulation model.

[0065] The residual calculation method can be shown as follows.

[0066] (3) Where Z represents the characteristic parameter in step 410. The convergence criterion can be set to 1×10 -3 .

[0067] Step 450: Determine whether the residuals of all characteristic parameters meet the convergence criteria. If any characteristic parameter does not meet the convergence criteria, execute step 460. If the residuals of all characteristic parameters meet the convergence criteria, exit the iteration and output the performance of each component and the performance of the entire machine.

[0068] Step 460: Based on the characteristic differences between the adaptive fan three-dimensional simulation model and the ACE whole machine zero-dimensional simulation model, update the intrinsic characteristic map scaling factor and the extrinsic characteristic map scaling factor in the ACE whole machine zero-dimensional simulation model.

[0069] Steps 410 to 460 are executed in a loop until the residuals of the characteristic parameters meet the convergence criteria.

[0070] The intrinsic characteristic diagram scaling factor and the extrinsic characteristic diagram scaling factor each include a converted flow scaling factor, a pressure ratio scaling factor and an isentropic efficiency scaling factor, wherein the flow scaling factor, the pressure ratio scaling factor and the isentropic efficiency scaling factor are updated as shown below.

[0071] ( ) in, 、 and They represent the converted flow scaling factor, pressure ratio scaling factor and isentropic efficiency scaling factor under the ACE whole machine zero-dimensional simulation model respectively. i and i +1 represents the current unupdated step and the next updated step respectively.

[0072] Since step 420 ensures and Therefore, only the flow scaling factor and efficiency scaling factor of the intrinsic characteristic diagram, and the pressure ratio scaling factor and efficiency scaling factor of the extrinsic characteristic diagram need to be corrected. The correction process diagram of the intrinsic characteristic and extrinsic characteristic of the adaptive fan can be shown as follows: Figure 8a 、 8b shown.

[0073] Compared with the above embodiment using two stream characterization as an example, the comparison between the ACE whole machine zero-dimensional simulation model based on two stream characterization adaptive fan and the ACE whole machine zero-dimensional simulation model based on three stream characterization adaptive fan can be as follows: Figure 9a 、 9b As shown, compared to the ACE zero-dimensional simulation model based on a two-stream representation of the adaptive fan (i.e., the two-stream representation of the adaptive fan), the three-stream representation of the adaptive fan adds a bypass at the second fan outlet. This further considers the impact of aerodynamic parameter non-uniformity at the second fan outlet on ACE performance, thereby further improving the computational accuracy of the coupled simulation method. The iterative coupled simulation process based on the three-stream representation of the adaptive fan is the same as above, except that the number of bypasses required for coupling increases from two to three. Simultaneously, the adaptive fan's performance parameters and boundary condition parameters increase from two to three, making the coupling more complex than the two-stream representation. Before performing the iterative coupled simulation, the ACE zero-dimensional model must be adaptively modified. The adaptively modified three-stream representation is shown in Figure 9(b). The adaptive fan representation is modified to a comprehensive representation using the second outer bypass (Split Fan Bypass 2) characteristic, the first outer bypass (Split Fan Bypass 1) characteristic, and the inner bypass characteristic.

[0074] The performance evaluation method of ACE based on three-stream characterization adaptive fans is basically the same as that based on two-stream characterization adaptive fans. It will not be repeated here. However, since the three-stream characterization adaptive fan involves an additional duct, the following adaptive changes are made: 1. The adaptive fan performance includes different contents. The adaptive fan performance in the ACE performance evaluation method based on three-stream characterization of the adaptive fan includes: internal converted flow rate, internal total pressure ratio, internal efficiency, first external converted flow rate, first external total pressure ratio, first external efficiency, second external converted flow rate, second external total pressure ratio, and second external efficiency.

[0075] 2. The boundary conditions of the adaptive fan in the three-dimensional simulation model of the adaptive fan are slightly different. The boundary conditions of the adaptive fan in the three-dimensional simulation model of the adaptive fan based on the three-stream representation are set as follows: (4) in, It represents the first external conversion flow rate under the three-dimensional simulation model of the adaptive fan. It represents the first external conversion flow under the ACE whole machine zero-dimensional simulation model, It represents the second external conversion flow rate under the three-dimensional simulation model of the adaptive fan. It represents the second external conversion flow under the ACE whole machine zero-dimensional simulation model.

[0076] 3. The updated scaling factors are different. The three-dimensional simulation model of the adaptive fan based on the three-stream representation needs to update the intrinsic characteristic diagram scaling factor, the first extrinsic characteristic diagram scaling factor, and the second extrinsic characteristic diagram scaling factor. However, the intrinsic characteristic diagram scaling factor, the first extrinsic characteristic diagram scaling factor, and the second extrinsic characteristic diagram scaling factor each include a flow scaling factor, a pressure ratio scaling factor, and an isentropic efficiency scaling factor. The update method of the flow scaling factor, the pressure ratio scaling factor, and the isentropic efficiency scaling factor can also be shown as in formula (2).

[0077] 4. The characteristic parameters for judging convergence are partially different. Compared with some parameter characteristics of the adaptive fan performance in the performance evaluation method of ACE based on two-stream characterization of the adaptive fan: external duct converted flow rate, external duct total pressure ratio, and external duct efficiency, some parameter characteristics of the adaptive fan performance in the performance evaluation method of ACE based on three-stream characterization of the adaptive fan are correspondingly modified to: first external duct converted flow rate, first external duct total pressure ratio, first external duct efficiency, second external duct converted flow rate, second external duct total pressure ratio, and second external duct efficiency.

[0078] 5. The characteristics of the correction are different. Since the adaptive fan boundary conditions of the three-dimensional simulation model of the adaptive fan based on the three-stream representation are guaranteed 、 and Therefore, it is only necessary to modify the flow scaling factor and efficiency scaling factor of the intrinsic characteristic diagram, and the pressure ratio scaling factor and efficiency scaling factor of the first and second extrinsic characteristic diagrams.

[0079] The ACE performance evaluation method provided in the embodiments of the present application has the following characteristics: 1. The adaptive fan configuration can be other multi-duct configurations.

[0080] 2. The engine configuration is not limited to a double-bypass configuration, but may also be other multi-bypass configurations, or other types of aircraft engines.

[0081] 3. The dimension of the high-fidelity simulation model of the adaptive fan can be three-dimensional, two-dimensional or one-dimensional.

[0082] 4. Adaptive fans can use fixed geometry or variable geometry.

[0083] 5. The convergence accuracy threshold is not limited to 0.001. The selection of the convergence accuracy threshold depends on the performance simulation accuracy of the ACE whole machine zero-dimensional model (whole machine 0D model) and the adaptive fan high-fidelity simulation model, as well as the acceptable coupled simulation time. Generally speaking, the smaller the convergence accuracy threshold, the longer the coupled simulation time.

[0084] 6. The engine operating conditions and control laws are not limited to a single one. Coupling can be achieved by changing any non-design point operating parameters, but the entire coupling simulation process needs to be repeated.

[0085] 7. The expression of the characteristic curve scaling factor updated in each loop iteration is not limited to equation (2) and can also be other expressions.

[0086] The adaptive fan high-fidelity simulation model in the ACE performance evaluation method provided in the embodiments of this application can also be referred to as an adaptive fan high-fidelity simulation model. Compared to the ACE full-machine zero-dimensional model in related art, the ACE performance evaluation method provided in the embodiments of this application does not involve solving the problem of solving the adaptive fan high-fidelity simulation characteristic curve. The adaptive fan characteristics are complex and have many boundary condition independent variables, making it difficult to simply describe them using high-fidelity simulation characteristic curves. Therefore, the embodiments of this application use a universal characteristic curve in the ACE full-machine zero-dimensional simulation model to describe the characteristics of different ducts of the adaptive fan. Based on the differences between the ACE full-machine zero-dimensional simulation model and the adaptive fan high-fidelity simulation model, the universal characteristic curve scaling factor is continuously iterated to achieve coupling between the ACE full-machine zero-dimensional simulation model and the adaptive fan high-fidelity simulation model. This method enables bidirectional data transfer between component models and the full-machine model, with good convergence and high accuracy. After the iterative coupling simulation converges, the adaptive fan flow field can be directly analyzed under the full-machine boundary conditions. At the same time, the adaptive fan model in this method is relatively independent of the whole machine model, and only minor modifications are required to the whole machine model architecture, so it has good operability and strong scalability.

[0087] The ACE performance evaluation method provided in the embodiments of the present application allows the adaptive fan to select its own characterization method based on the simulation accuracy requirements, including a two-stream characterization method and a three-stream characterization method. Compared with the adaptive fan series characterization method in the related art, it can further consider the non-uniformity of the aerodynamic parameters of different ducts at the fan outlet, so the simulation results have higher accuracy. In the method of the present invention, a 0D-3D iterative coupling simulation method based on the three-stream characterization method of the adaptive fan is proposed for the first time. This method can consider the differences in aerodynamic parameters of the adaptive fan along three different flow channels and has higher accuracy.

[0088] The ACE performance evaluation method provided in the embodiments of this application provides boundary condition selection principles for the two-stream and three-stream characterization methods for front and rear separated fans. When the two-stream characterization method is selected for an adaptive fan, the outer duct outlet uses the flow boundary condition, and the inner duct outlet uses the total pressure boundary condition. Similarly, when the three-stream characterization method is selected for an adaptive fan, the second and first outer duct outlets both use the flow boundary condition, and the inner duct outlet uses the total pressure boundary condition. This combination of boundary conditions helps improve the stability and convergence of iterative coupled simulations.

[0089] Corresponding to the above-mentioned ACE performance evaluation method, an embodiment of the present application also provides an ACE performance evaluation device. Figure 10 This is a schematic diagram of the structure of an ACE performance evaluation device provided in an embodiment of the present application. Figure 10 As shown, the ACE performance evaluation device provided in the embodiment of the present application includes: An acquisition unit 500 is configured to acquire a zero-dimensional simulation model of the ACE system to be evaluated, a high-fidelity simulation model of the adaptive fan therein, and operating conditions and control laws of the ACE to be evaluated; A coupling unit 510 is configured to couple the ACE zero-dimensional simulation model to be evaluated and the adaptive fan high-fidelity simulation model therein to obtain an ACE multi-dimensional coupled simulation model; The processing unit 520 is configured to run the obtained ACE multi-dimensional coupled simulation model according to the obtained ACE operating conditions and control laws to obtain the performance of the ACE to be evaluated and the performance of each component thereof; Among them, the ACE multi-dimensional coupling simulation model adopts the characteristic curves in the ACE whole machine zero-dimensional simulation model to be evaluated to respectively characterize the characteristics of different ducts of the adaptive fan, and based on the difference between the ACE whole machine zero-dimensional simulation model to be evaluated and the adaptive fan high-fidelity simulation model, continuously iteratively adjusts the scaling factor of the characteristic curve to achieve the coupling between the ACE whole machine zero-dimensional simulation model and the adaptive fan high-fidelity simulation model.

[0090] In an exemplary embodiment, the coupling unit 510 is further configured to obtain each of the ACE multi-dimensional coupling simulation models in the following manner: Constructing a simulation model for the ACE whole machine to obtain a zero-dimensional simulation model of the ACE whole machine, and constructing a high-fidelity simulation model for the adaptive fan in the ACE; Determine a characterization method for the adaptive fan according to the external structure type and simulation accuracy requirements of the ACE; Characterizing the adaptive fan according to the determined characterization method and using a characteristic curve in the ACE whole machine zero-dimensional simulation model; Based on the characterized adaptive fan, the difference between the ACE whole machine zero-dimensional simulation model and the adaptive fan high-fidelity simulation model is obtained, and based on the obtained difference, the scaling factor of the characteristic curve used to characterize the adaptive fan in the ACE whole machine zero-dimensional simulation model is continuously iterated until the obtained difference is less than the preset requirement, thereby obtaining the ACE multi-dimensional coupling simulation model.

[0091] In an exemplary embodiment, the coupling unit 510 is further configured to: The constructed ACE whole machine zero-dimensional simulation model is used as the current ACE whole machine zero-dimensional simulation model, and the constructed adaptive fan high-fidelity simulation model is used as the current adaptive fan high-fidelity simulation model. The following model iteration operation is performed cyclically until the difference between the adaptive fan performance under the obtained adaptive fan high-fidelity simulation model and the adaptive fan performance under the obtained ACE whole machine zero-dimensional simulation model is less than a preset threshold. The finally obtained ACE whole machine zero-dimensional simulation model is used as the ACE multi-dimensional coupled simulation model. The model iteration operation includes: Run the current ACE whole machine zero-dimensional simulation model to obtain the adaptive fan high-fidelity simulation model results under the current ACE whole machine zero-dimensional simulation model; Using the adaptive fan high-fidelity simulation model results under the current ACE whole machine zero-dimensional simulation model to update the adaptive fan boundary conditions under the current adaptive fan high-fidelity simulation model, an updated adaptive fan high-fidelity simulation model is obtained, and the updated current adaptive fan high-fidelity simulation model is replaced with the updated adaptive fan high-fidelity simulation model as the current adaptive fan high-fidelity simulation model; Obtaining adaptive fan performance under the current adaptive fan high-fidelity simulation model according to the current adaptive fan high-fidelity simulation model; When the difference between the adaptive fan high-fidelity simulation model result obtained under the current adaptive fan high-fidelity simulation model and the adaptive fan performance obtained under the current ACE whole machine zero-dimensional simulation model is not less than a preset threshold, the intrinsic characteristic diagram scaling factor and the extrinsic characteristic diagram scaling factor in the current ACE whole machine zero-dimensional simulation model are updated according to the adaptive fan performance obtained under the current adaptive fan high-fidelity simulation model to obtain an updated ACE whole machine zero-dimensional simulation model, and the updated current ACE whole machine zero-dimensional simulation model is replaced by this as the current ACE whole machine zero-dimensional simulation model.

[0092] In an exemplary embodiment, when the configuration of the ACE is a double-external configuration ACE, the characterization mode of the adaptive fan includes: a two-stream characterization mode and a three-stream characterization mode; Among them, the characterization method of the two flows is a joint characterization method of the outer duct characteristics and the inner duct characteristics, the outer duct characteristics are the comprehensive characteristics of the first fan blade tip part and the second outer duct, and the inner duct characteristics are the comprehensive characteristics of the first fan blade root part and the second fan.

[0093] The three-stream characterization method is a joint characterization method of the characteristics of the second outer duct, the characteristics of the first outer duct and the characteristics of the inner duct. The second outer duct characteristic is the comprehensive characteristic of the first fan blade tip part and the second outer duct, the first outer duct characteristic is the comprehensive characteristic of the first fan blade root part and the second fan blade tip, and the inner duct characteristic is the comprehensive characteristic of the first fan blade root part and the second fan blade heel.

[0094] In an exemplary instance, the adaptive fan high-fidelity simulation model results include: adaptive fan inlet simulation results and adaptive fan outlet simulation results, the adaptive fan inlet simulation results include: adaptive fan inlet total pressure simulation results and adaptive fan inlet total temperature simulation results; the adaptive fan outlet simulation results include: adaptive fan duct outlet flow simulation results and adaptive fan duct outlet total pressure simulation results; the adaptive fan boundary conditions include: physical speed, guide vane variable geometric angle, adaptive fan inlet boundary conditions, and adaptive fan duct outlet boundary conditions.

[0095] In an exemplary embodiment, when the determined characterization method is a two-flow characterization method, the coupling unit 510 is further configured to: The adaptive fan inlet simulation results under the current ACE whole machine zero-dimensional simulation model are used as the adaptive fan inlet boundary conditions under the current adaptive fan high-fidelity simulation model; The total pressure simulation result of the inner duct outlet is selected from the adaptive fan outlet simulation results under the current ACE whole machine zero-dimensional simulation model as the adaptive fan inner duct outlet boundary condition under the current adaptive fan high-fidelity simulation model, and the outer duct outlet flow simulation result is selected from the adaptive fan outlet simulation results under the current ACE whole machine zero-dimensional simulation model as the adaptive fan outer duct outlet boundary condition under the current adaptive fan high-fidelity simulation model.

[0096] In an exemplary embodiment, when the determined characterization method is a three-stream characterization method, the coupling unit 510 is further configured to: The adaptive fan inlet simulation results under the current ACE whole machine zero-dimensional simulation model are used as the adaptive fan inlet boundary conditions under the current adaptive fan high-fidelity simulation model; The total pressure simulation result of the inner duct outlet is selected from the adaptive fan outlet simulation results under the current ACE whole machine zero-dimensional simulation model as the adaptive fan inner duct outlet boundary condition under the current adaptive fan high-fidelity simulation model, and the first outer duct outlet flow simulation result is selected from the adaptive fan outlet simulation results under the current ACE whole machine zero-dimensional simulation model as the adaptive fan first outer duct outlet boundary condition under the current adaptive fan high-fidelity simulation model, and the second outer duct outlet flow simulation result is selected from the adaptive fan outlet simulation results under the current ACE whole machine zero-dimensional simulation model as the adaptive fan second outer duct outlet boundary condition under the current adaptive fan high-fidelity simulation model.

[0097] In an exemplary embodiment, the coupling unit 510 is further configured to: Run the current adaptive fan high-fidelity simulation model diagram to obtain the current adaptive fan high-fidelity simulation results. Based on the obtained current adaptive fan high-fidelity simulation results, the mass flow averaging method is used to calculate the adaptive fan performance under the current adaptive fan high-fidelity simulation model.

[0098] In an exemplary instance, when the determined representation method of the adaptive fan is a two-stream representation method, the coupling unit 510 is also used to introduce a relaxation factor, and update the intrinsic characteristic diagram scaling factor and the extrinsic characteristic diagram scaling factor in the current ACE whole machine zero-dimensional simulation model according to the adaptive fan performance obtained under the current adaptive fan high-fidelity simulation model.

[0099] In an exemplary instance, when the determined representation method of the adaptive fan is a three-stream representation method, the extrinsic characteristic diagram scaling factor includes: a first extrinsic characteristic diagram scaling factor and a second extrinsic characteristic diagram scaling factor; the coupling unit 510 is also used to introduce a relaxation factor, and update the intrinsic characteristic diagram scaling factor, the first extrinsic characteristic diagram scaling factor and the second extrinsic characteristic diagram scaling factor in the current ACE whole machine zero-dimensional simulation model according to the adaptive fan performance obtained under the current adaptive fan high-fidelity simulation model.

[0100] In an exemplary embodiment, the operating conditions include: flight altitude, flight Mach number; The control law includes: low-pressure physical speed, or the control law includes: low-pressure physical speed and variable geometry law, and the variable geometry law includes: guide vane variable geometry guide vane angle.

[0101] In an exemplary embodiment, when the characterization method is a two-stream characterization method, the adaptive fan performance includes: internal converted flow rate, internal total pressure ratio, internal efficiency, external converted flow rate, external total pressure ratio, and external efficiency; When the characterization method is a three-stream characterization method, the adaptive fan performance includes: internal converted flow, internal total pressure ratio, internal efficiency, first external converted flow, first external total pressure ratio, first external efficiency, second external converted flow, second external total pressure ratio, and second external efficiency.

[0102] The ACE performance evaluation device provided in this embodiment and the ACE performance evaluation method provided in the above embodiments of this application are based on the same application concept and can execute the ACE performance evaluation method provided in any of the above embodiments of this application, and has the corresponding functional modules and beneficial effects of executing the ACE performance evaluation method. For technical details not fully described in this embodiment, please refer to the specific processing content of the ACE performance evaluation method provided in the above embodiments of this application, and will not be repeated here.

[0103] The present application also provides an electronic device, such as Figure 11 As shown, it includes: a memory 600 and a processor 610; The memory 600 is connected to the processor 610 and is used to store programs; The processor 610 is configured to implement the ACE performance evaluation method described in any of the above embodiments by running the program in the memory 600 .

[0104] Specifically, the electronic device may further include: a bus, a communication interface 620 , an input device 630 and an output device 640 .

[0105] The processor 610, the memory 600, the communication interface 620, the input device 630 and the output device 640 are interconnected via a bus. A bus may include a pathway that transfers information between components of a computer system.

[0106] Processor 610 can be a general-purpose processor, such as a general-purpose central processing unit (CPU), a microprocessor, or the like. It can also be an application-specific integrated circuit (ASIC), or one or more integrated circuits used to control the execution of programs in the solution of the present invention. It can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic device, or discrete hardware components.

[0107] The processor 610 may include a main processor, and may also include a baseband chip, a modem, and the like.

[0108] Memory 600 stores a program for executing the technical solution of the present invention and may also store an operating system and other key services. Specifically, the program may include program code, which includes computer operating instructions. More specifically, memory 600 may include read-only memory (ROM), other types of static storage devices capable of storing static information and instructions, random access memory (RAM), other types of dynamic storage devices capable of storing information and instructions, disk storage, flash memory, and the like.

[0109] The input device 630 may include a device for receiving data and information input by a user, such as a keyboard, a mouse, a camera, a scanner, a light pen, a voice input device, a touch screen, a pedometer, or a gravity sensor.

[0110] Output device 640 may include a device that allows information to be output to a user, such as a display screen, printer, speaker, etc.

[0111] The communication interface 620 may include any transceiver or similar device for communicating with other devices or communication networks, such as Ethernet, Radio Access Network (RAN), Wireless Local Area Network (WLAN), etc.

[0112] The processor 610 executes the program stored in the memory 600 and calls other devices, which can be used to implement the various steps of the performance evaluation method of any ACE provided in the above embodiments of the present application.

[0113] In addition to the above-mentioned methods and devices, an embodiment of the present application may also be a computer program product, which includes computer program instructions, which, when executed by a processor, enable the processor to execute the steps of the performance evaluation method of ACE according to various embodiments of the present application described in any of the above embodiments of this specification.

[0114] The computer program product may be written in any combination of one or more programming languages ​​to implement the program code for performing the operations of the embodiments of the present application, including object-oriented programming languages ​​such as Java, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0115] In addition, an embodiment of the present application further provides a storage medium on which a computer program is stored. When the computer program is executed by a processor, the performance evaluation method of ACE described in any of the above embodiments is implemented.

[0116] Those skilled in the art will appreciate that all or some of the steps, systems, and functional modules / units in the methods, systems, and devices disclosed above may be implemented as software, firmware, hardware, or any combination thereof. In hardware implementations, the division between functional modules / units described above does not necessarily correspond to the division between physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all components may be implemented as software executed by a processor, such as a digital signal processor or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software may be distributed on computer-readable media, which may include computer storage media (or non-transitory media) and communication media (or transient media). As is well known to those skilled in the art, the term "computer storage media" encompasses volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information, such as computer-readable instructions, data structures, program modules, or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer. In addition, as is well known to those skilled in the art, communication media typically embodies computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

Claims

1. A performance evaluation method for an adaptive variable cycle engine, characterized in that: include: Obtain the zero-dimensional simulation model of the ACE system to be evaluated and the high-fidelity simulation model of the adaptive fan therein, as well as the operating conditions and control laws of the ACE to be evaluated; The zero-dimensional simulation model of the ACE system to be evaluated and the high-fidelity simulation model of the adaptive fan are coupled to obtain the ACE multi-dimensional coupled simulation model; The obtained ACE multi-dimensional coupled simulation model is run according to the obtained ACE working conditions and control laws to obtain the performance of the ACE to be evaluated and the performance of each component therein; Among them, the ACE multi-dimensional coupling simulation model adopts the characteristic curves in the ACE whole machine zero-dimensional simulation model to be evaluated to respectively characterize the characteristics of different ducts of the adaptive fan, and based on the difference between the ACE whole machine zero-dimensional simulation model to be evaluated and the adaptive fan high-fidelity simulation model, continuously iteratively adjusts the scaling factor of the characteristic curve to achieve coupling between the ACE whole machine zero-dimensional simulation model and the adaptive fan high-fidelity simulation model.

2. The method according to claim 1, characterized in that The ACE multi-dimensional coupled simulation model is obtained in the following way: Constructing a simulation model for the ACE whole machine to obtain a zero-dimensional simulation model of the ACE whole machine, and constructing a high-fidelity simulation model for the adaptive fan in the ACE; Determine the representation method of the adaptive fan based on the external structure type of ACE and the simulation accuracy requirements; Characterizing the adaptive fan according to the determined characterization method and using a characteristic curve in the ACE whole machine zero-dimensional simulation model; Based on the characterized adaptive fan, the difference between the ACE whole machine zero-dimensional simulation model and the adaptive fan high-fidelity simulation model is obtained, and based on the obtained difference, the scaling factor of the characteristic curve used to characterize the adaptive fan in the ACE whole machine zero-dimensional simulation model is continuously iterated until the obtained difference is less than the preset requirement, thereby obtaining the ACE multi-dimensional coupling simulation model.

3. The method according to claim 2, characterized in that The method of obtaining a difference between the ACE whole machine zero-dimensional simulation model and the adaptive fan high-fidelity simulation model based on the characterized adaptive fan, and continuously iterating a scaling factor of a characteristic curve used to characterize the adaptive fan in the ACE whole machine zero-dimensional simulation model based on the obtained difference until the obtained difference is less than a preset requirement, thereby obtaining the ACE multi-dimensional coupled simulation model, including: The constructed ACE whole machine zero-dimensional simulation model is used as the current ACE whole machine zero-dimensional simulation model, and the constructed adaptive fan high-fidelity simulation model is used as the current adaptive fan high-fidelity simulation model. The following model iteration operation is performed cyclically until the difference between the adaptive fan performance under the obtained adaptive fan high-fidelity simulation model and the adaptive fan performance under the obtained ACE whole machine zero-dimensional simulation model is less than a preset threshold. The finally obtained ACE whole machine zero-dimensional simulation model is used as the ACE multi-dimensional coupled simulation model. The model iteration operation includes: Run the current ACE whole machine zero-dimensional simulation model to obtain the adaptive fan high-fidelity simulation model results under the current ACE whole machine zero-dimensional simulation model; Using the adaptive fan high-fidelity simulation model results under the current ACE whole machine zero-dimensional simulation model to update the adaptive fan boundary conditions under the current adaptive fan high-fidelity simulation model, an updated adaptive fan high-fidelity simulation model is obtained, and the updated current adaptive fan high-fidelity simulation model is replaced with the updated adaptive fan high-fidelity simulation model as the current adaptive fan high-fidelity simulation model; Obtaining adaptive fan performance under the current adaptive fan high-fidelity simulation model according to the current adaptive fan high-fidelity simulation model; When the difference between the adaptive fan high-fidelity simulation model result obtained under the current adaptive fan high-fidelity simulation model and the adaptive fan performance obtained under the current ACE whole machine zero-dimensional simulation model is not less than a preset threshold, the intrinsic characteristic diagram scaling factor and the extrinsic characteristic diagram scaling factor in the current ACE whole machine zero-dimensional simulation model are updated according to the adaptive fan performance obtained under the current adaptive fan high-fidelity simulation model to obtain an updated ACE whole machine zero-dimensional simulation model, and the updated current ACE whole machine zero-dimensional simulation model is replaced by this as the current ACE whole machine zero-dimensional simulation model.

4. The method according to claim 3, characterized in that When the configuration of the ACE is a double-external configuration ACE, the characterization methods of the adaptive fan include: a two-stream characterization method and a three-stream characterization method; The two flows are characterized by a combined characteristic of an outer duct and an inner duct, wherein the outer duct characteristic is a comprehensive characteristic of a blade tip of the first fan and a second outer duct, and the inner duct characteristic is a comprehensive characteristic of a blade root of the first fan and a second fan. The three-stream characterization method is a joint characterization method of the characteristics of the second outer duct, the characteristics of the first outer duct and the characteristics of the inner duct. The second outer duct characteristic is the comprehensive characteristic of the first fan blade tip part and the second outer duct, the first outer duct characteristic is the comprehensive characteristic of the first fan blade root part and the second fan blade tip, and the inner duct characteristic is the comprehensive characteristic of the first fan blade root part and the second fan blade heel.

5. The method according to claim 4, characterized in that The results of the adaptive fan high-fidelity simulation model include: adaptive fan inlet simulation results and adaptive fan outlet simulation results. The adaptive fan inlet simulation results include: adaptive fan inlet total pressure simulation results and adaptive fan inlet total temperature simulation results; the adaptive fan outlet simulation results include: adaptive fan duct outlet flow simulation results and adaptive fan duct outlet total pressure simulation results; the adaptive fan boundary conditions include: physical speed, guide vane variable geometric angle, adaptive fan inlet boundary conditions, and adaptive fan duct outlet boundary conditions.

6. The method according to claim 5, characterized in that When the determined characterization method is a two-stream characterization method, the method of updating the adaptive fan boundary conditions under the current adaptive fan high-fidelity simulation model using the adaptive fan high-fidelity simulation results under the current ACE whole machine zero-dimensional simulation model includes: The adaptive fan inlet simulation results under the current ACE whole machine zero-dimensional simulation model are used as the adaptive fan inlet boundary conditions under the current adaptive fan high-fidelity simulation model; The total pressure simulation result of the inner duct outlet is selected from the adaptive fan outlet simulation results under the current ACE whole machine zero-dimensional simulation model as the adaptive fan inner duct outlet boundary condition under the current adaptive fan high-fidelity simulation model, and the outer duct outlet flow simulation result is selected from the adaptive fan outlet simulation results under the current ACE whole machine zero-dimensional simulation model as the adaptive fan outer duct outlet boundary condition under the current adaptive fan high-fidelity simulation model; When the determined characterization method is the three-stream characterization method, the method of updating the adaptive fan boundary conditions under the current adaptive fan high-fidelity simulation model using the adaptive fan high-fidelity simulation results under the current ACE whole machine zero-dimensional simulation model includes: The adaptive fan inlet simulation results under the current ACE whole machine zero-dimensional simulation model are used as the adaptive fan inlet boundary conditions under the current adaptive fan high-fidelity simulation model; The total pressure simulation result of the inner duct outlet is selected from the adaptive fan outlet simulation results under the current ACE whole machine zero-dimensional simulation model as the adaptive fan inner duct outlet boundary condition under the current adaptive fan high-fidelity simulation model, and the first outer duct outlet flow simulation result is selected from the adaptive fan outlet simulation results under the current ACE whole machine zero-dimensional simulation model as the adaptive fan first outer duct outlet boundary condition under the current adaptive fan high-fidelity simulation model, and the second outer duct outlet flow simulation result is selected from the adaptive fan outlet simulation results under the current ACE whole machine zero-dimensional simulation model as the adaptive fan second outer duct outlet boundary condition under the current adaptive fan high-fidelity simulation model.

7. The method according to claim 3, characterized in that The obtaining, according to the current adaptive fan high-fidelity simulation model, the adaptive fan performance under the current adaptive fan high-fidelity simulation model includes: The current adaptive fan high-fidelity simulation model is run to obtain the current adaptive fan high-fidelity simulation results. Based on the obtained current adaptive fan high-fidelity simulation results, the adaptive fan performance under the current adaptive fan high-fidelity simulation model is calculated using the mass flow averaging method.

8. The method according to claim 4, characterized in that When the determined characterization method is a two-stream characterization method, updating the intrinsic characteristic diagram scaling factor and the extrinsic characteristic diagram scaling factor in the current ACE whole machine zero-dimensional simulation model according to the obtained adaptive fan performance under the current adaptive fan high-fidelity simulation model includes: Introducing a relaxation factor, and updating the intrinsic characteristic map scaling factor and extrinsic characteristic map scaling factor in the current ACE whole machine zero-dimensional simulation model respectively according to the adaptive fan performance obtained under the current adaptive fan high-fidelity simulation model; When the determined representation method is a three-stream representation method, the extrinsic characteristic map scaling factor includes: a first extrinsic characteristic map scaling factor and a second extrinsic characteristic map scaling factor; and updating the intrinsic characteristic map scaling factor and the extrinsic characteristic map scaling factor in the current ACE whole machine zero-dimensional simulation model according to the obtained adaptive fan performance under the current adaptive fan high-fidelity simulation model includes: A relaxation factor is introduced, and the intrinsic characteristic map scaling factor, the first extrinsic characteristic map scaling factor and the second extrinsic characteristic map scaling factor in the current ACE whole machine zero-dimensional simulation model are updated respectively according to the adaptive fan performance obtained under the current adaptive fan high-fidelity simulation model.

9. The method according to claim 3, characterized in that The working conditions include: flight altitude, flight Mach number; The control law includes: low-pressure physical speed, or the control law includes: low-pressure physical speed and variable geometry law, and the variable geometry law includes: guide vane variable geometry guide vane angle; When the determined characterization method is a two-stream characterization method, the adaptive fan performance includes: internal converted flow rate, internal total pressure ratio, internal efficiency, external converted flow rate, external total pressure ratio, and external efficiency; When the determined characterization method is the three-stream characterization method, the adaptive fan performance includes: internal converted flow, internal total pressure ratio, internal efficiency, first external converted flow, first external total pressure ratio, first external efficiency, second external converted flow, second external total pressure ratio, and second external efficiency.

10. An electronic device, characterized in that: include: memory and processor; The memory is connected to the processor and is used to store programs; The processor is used to implement the ACE performance evaluation method according to any one of claims 1 to 9 by running the program in the memory.

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