Integrated system of aircraft thermal protection and power generation and optimization method thereof

Abstract

The application discloses an aircraft thermal protection and power generation integrated system and an optimization method thereof, and relates to the field of hypersonic aircrafts.The system comprises a compressor, an output end of the compressor being connected with a cooling channel of an aircraft engine combustion chamber, the cooling channel being connected with an input end of a first expander, and an output end of the first expander being connected with an input end of the compressor through a first heat exchange channel of a first heat exchanger; further comprising an oil supply assembly, the oil supply assembly being connected with the aircraft engine combustion chamber through a second heat exchange channel of the first heat exchanger; further comprising a second expander, an input end of the second expander being connected with a first intermediate position of the cooling channel through a first valve, and an output end of the second expander being connected with a second intermediate position of the cooling channel.The present application can solve the problem that the prior art cannot meet the system performance requirements under different flight conditions, and improve the applicability of the integrated system to different flight conditions.

Description

Technical Field

[0001] This application relates to the field of hypersonic vehicle technology, and in particular to an integrated thermal protection and power generation system for a vehicle and its optimization method. Background Technology

[0002] With the development of technology, the flight speed of aircraft is constantly increasing, and the heat load of aircraft is rising sharply. The thermal protection of aircraft has become one of the key factors restricting the development of hypersonic aircraft. At the same time, due to the increasing number of electronic devices carried by aircraft, the demand for electricity is growing. Therefore, integrated thermal protection and power generation systems for aircraft have emerged to improve the thermal protection performance of aircraft while using the heat load to generate electricity to power electronic devices.

[0003] However, current integrated systems (i.e., integrated systems for aircraft thermal protection and power generation) are limited to a single flight condition and cannot meet the system performance requirements of aircraft at low and high Mach numbers.

[0004] Therefore, there is a need for an integrated thermal protection and power generation system for aircraft that can meet different operating conditions, as well as its optimization method. Summary of the Invention

[0005] This application provides an integrated system for aircraft thermal protection and power generation, and its optimization method, which solves the problem that the existing technology cannot meet the system performance requirements under different flight conditions, and improves the applicability of the integrated system to different flight conditions.

[0006] In a first aspect, embodiments of this application provide an integrated thermal protection and power generation system for an aircraft, comprising:

[0007] The compressor's output end is connected to the cooling channel of the aircraft engine combustion chamber, the cooling channel is connected to the input end of the first expansion member, and the output end of the first expansion member is connected to the input end of the compressor through the first heat exchange channel of the first heat exchanger; it also includes an oil supply assembly, which is connected to the aircraft engine combustion chamber through the second heat exchange channel of the first heat exchanger; and it also includes a second expansion member, the input end of which is connected to the first intermediate position of the cooling channel through a first valve, and the output end of which is connected to the second intermediate position of the cooling channel.

[0008] Furthermore, the system also includes:

[0009] The second heat exchanger connects the compressor to the cooling channel via the third heat exchange channel of the second heat exchanger; it also includes a second valve and a third valve, and the first expansion member connects to the first heat exchange channel via the second valve. The first expansion member is also connected to the first heat exchange channel via the third valve and the fourth heat exchange channel of the second heat exchanger.

[0010] Furthermore, both the first and second expansion components are turbines.

[0011] Furthermore, both the first and second heat exchangers are TPMS (Triply Periodic Minimum Surface) heat exchangers.

[0012] Furthermore, the first valve, the second valve, and the third valve are all solenoid valves.

[0013] Secondly, embodiments of this application provide an optimization method for an integrated thermal protection and power generation system for aircraft. Based on the system of the first aspect, the method includes:

[0014] Sensitivity analysis was performed on multiple component parameters and corresponding system indicators of the integrated system under different system operating conditions to obtain the influence trends of multiple component parameters on the corresponding system indicators. The system operating conditions included low Mach number and high Mach number conditions. Under low Mach number conditions, multiple component parameters included the compressor inlet temperature, the inlet pressure of the first expander, the inlet pressure of the second expander, and the outlet position of the first expander; the corresponding system indicators included system cycle efficiency and fuel consumption rate. Under high Mach number conditions, multiple component parameters included the compressor inlet temperature, the fuel outlet temperature, and the inlet pressure of the first expander; the corresponding system indicators included system cycle efficiency, system cycle net work, and system total mass. Based on the influence trends, multiple target fitting intervals were determined for each component parameter. An error determination step was performed, which included: Based on multiple component parameters, multiple system indicators, and multiple target fitting intervals, an orthogonal experimental table is constructed to determine multiple first-variable high-order polynomials, each corresponding one-to-one with a system indicator. Based on these first-variable high-order polynomials and the corresponding computational model of the integrated system, a first error is determined, which is the average of the relative errors between the fitted result and the actual result. When the first error does not meet preset requirements, the target fitting interval is updated, and the error determination step is executed until the first error meets the preset requirements. When the first error meets the preset requirements, the multiple first-variable high-order polynomials are determined as the objective function of the target evolution algorithm. Based on the objective function and the target evolution algorithm, using multiple component parameters as optimization variables and the expected targets of multiple system indicators as optimization objectives, the optimal values ​​of the multiple component parameters are obtained. Based on the optimal values ​​of the multiple component parameters, the component parameters of the integrated system are set.

[0015] Furthermore, based on the objective function and using an evolutionary algorithm, with multiple component parameters as optimization variables and the expected targets of multiple system indicators as optimization objectives, the optimal values ​​of multiple component parameters are obtained. Based on these optimal values, the component parameters of the integrated system are set, including:

[0016] Based on the objective function and using the objective evolution algorithm, with multiple component parameters as optimization variables and the expected targets of multiple system indicators as optimization objectives, the Pareto optimal solution set corresponding to the optimization objective is obtained. Based on the Pareto optimal solution set, the optimal Pareto front is obtained. Based on the optimization objective and the optimal Pareto front, the ideal point is determined; the ideal point is the point in the solution space corresponding to the optimal Pareto front that satisfies the optimization objective. Based on the ideal point, the target point is determined from the optimal Pareto front; the target point is the point in the optimal Pareto front that is closest to the ideal point. Based on the target point, the optimal values ​​of multiple component parameters are determined. Based on the optimal values ​​of multiple component parameters, the component parameters of the integrated system are set.

[0017] Furthermore, the objective evolutionary algorithm is a multi-objective whale optimization algorithm.

[0018] Furthermore, based on the ideal point, the target point is determined from the optimal Pareto front, including:

[0019] The points in the optimal Pareto front are normalized; the target point is determined based on the Euclidean distance between the normalized points and the ideal point.

[0020] Furthermore, when the first error does not meet the preset requirements, the target fitting interval is updated, including:

[0021] If the first error does not meet the preset requirements, the target fitting interval is adjusted to half the range.

[0022] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0023] This application embodiment achieves thermal protection by setting up a cooling channel to cool the combustion chamber of the aircraft engine, and uses a first expansion member to expand the high-pressure refrigerant entering it to generate electricity. A first heat exchanger lowers the temperature of the refrigerant entering the compressor while raising the temperature of the fuel entering the combustion chamber of the aircraft engine to ensure complete combustion. A first valve and a second expansion member further cool the combustion chamber of the aircraft engine under high Mach number flight conditions to meet higher thermal protection performance and provide electrical energy to the aircraft. This can meet the needs of both low and high Mach number flight conditions, solve the problem that the existing technology cannot meet the system performance requirements under different flight conditions, and improve the applicability of the integrated system to different flight conditions. Attached Figure Description

[0024] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 This is a schematic diagram of the integrated thermal protection and power generation system for aircraft provided in an embodiment of this application;

[0026] Figure 2 Another structural schematic diagram of the integrated thermal protection and power generation system for aircraft provided in this application embodiment;

[0027] Figure 3 A flowchart illustrating the optimization method for an integrated thermal protection and power generation system for aircraft provided in this application embodiment.

[0028] Reference numerals: 1-Compressor; 2-Aircraft engine combustion chamber; 21-Cooling passage; 3-First expansion component; 4-First heat exchanger; 41-First heat exchange passage; 42-Second heat exchange passage; 5-Fuel supply assembly; 6-Second expansion component; 7-First valve; 8-Second heat exchanger; 81-Third heat exchange passage; 82-Fourth heat exchange passage; 9-Second valve; 10-Third valve. Detailed Implementation

[0029] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0030] The following description of some technologies involved in the embodiments of this application is provided to aid understanding and should be considered merely exemplary. Therefore, those skilled in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this application. Similarly, for clarity and brevity, some descriptions of well-known functions and structures are omitted in the following description.

[0031] With the development of technology, the flight speed of aircraft is constantly increasing, and the heat load of aircraft is rising sharply. The thermal protection of aircraft has become one of the key factors restricting the development of hypersonic aircraft. At the same time, due to the increasing number of electronic devices carried by aircraft, the demand for electricity is growing. Therefore, integrated thermal protection and power generation systems for aircraft have emerged to improve the thermal protection performance of aircraft while using the heat load to generate electricity to power electronic devices.

[0032] However, current integrated systems (i.e., integrated systems for aircraft thermal protection and power generation) are limited to a single flight condition and cannot simultaneously meet the thermal protection requirements of aircraft at both low and high Mach numbers.

[0033] For example, at high Mach numbers, aircraft engines operate under harsh thermal conditions and experience further fuel shortages, requiring stringent thermal protection capabilities and prioritizing thermal protection. Conversely, at low Mach numbers, thermal conditions are better and the cooling supply is relatively abundant, resulting in lower thermal protection requirements and a lower likelihood of thermal protection issues. Therefore, prioritizing the complete combustion of fuel is crucial. However, current integrated systems cannot meet the needs of both flight conditions.

[0034] Therefore, there is a need for an integrated thermal protection and power generation system for aircraft that can meet different operating conditions, as well as its optimization method.

[0035] Against this background, this disclosure provides an integrated system for aircraft thermal protection and power generation, which can improve the applicability of the integrated system to different flight conditions.

[0036] like Figure 1 As shown, this application embodiment provides an integrated thermal protection and power generation system for aircraft. The system includes:

[0037] The compressor's output end is connected to the cooling channel of the aircraft engine combustion chamber, and the cooling channel is connected to the input end of the first expansion member. The output end of the first expansion member is connected to the input end of the compressor through the first heat exchange channel of the first heat exchanger.

[0038] It also includes a fuel supply assembly, which is connected to the aircraft engine combustion chamber through the second heat exchange channel of the first heat exchanger.

[0039] It also includes a second expansion member, the input end of which is connected to the first intermediate position of the cooling channel via the first valve, and the output end of which is connected to the second intermediate position of the cooling channel.

[0040] For example, supercritical carbon dioxide (S-CO2) can be used as a refrigerant.

[0041] Specifically, both the first and second expansion components are turbines, which use high-pressure refrigerant to expand and do work, driving the turbine to rotate, and then generate electricity through the connected power generation components.

[0042] Specifically, the first heat exchanger can be a TPMS heat exchanger, thereby improving the heat exchange capacity.

[0043] Specifically, the first valve can be a solenoid valve.

[0044] like Figure 1As shown, the solid line represents the refrigerant circulation path, the dashed line represents the fuel path, and the arrow indicates the direction of movement of the refrigerant or fuel.

[0045] refer to Figure 1 Under low Mach number flight conditions, the first valve is closed. The refrigerant, after being compressed and cooled by the compressor, enters the cooling channel of the aircraft engine combustion chamber, absorbing heat from the combustion chamber and cooling it to protect it (i.e., the aircraft's thermal protection function). After passing through the cooling channel, the refrigerant is in a high-temperature, high-pressure state and then enters the first expansion component to expand and do work, providing electrical energy for the aircraft (i.e., the power generation function). After passing through the first expansion component, the refrigerant is still at a high temperature and then passes through the first heat exchange channel of the first heat exchanger, exchanging heat with the ambient-temperature fuel in the second heat exchange channel of the first heat exchanger. This increases the fuel temperature, thereby improving the combustion efficiency in the aircraft engine combustion chamber and increasing fuel utilization. After passing through the first heat exchanger, the refrigerant enters the compressor for compression and cooling again, completing one cycle.

[0046] Under high Mach number flight conditions, the refrigerant circulation path is similar to that under low Mach number flight conditions. The difference is that under high Mach number flight conditions, the temperature of the aircraft engine combustion chamber is higher. Therefore, the first valve can be opened, allowing the refrigerant to pass through the first half of the cooling pipe to cool the aircraft engine combustion chamber and become high temperature and high pressure. Then, it enters the second expansion component to expand and do work (generating electricity). After passing through the second expansion component, the refrigerant will be cooled and depressurized, and can then enter the second half of the cooling pipe to cool the aircraft engine combustion chamber again, further reducing the temperature of the aircraft engine combustion chamber to meet the higher thermal protection requirements of high Mach number flight conditions.

[0047] This embodiment of the invention achieves thermal protection by setting up a cooling channel to cool the combustion chamber of the aircraft engine, and uses a first expansion member to expand the high-pressure refrigerant entering the chamber to generate electricity. A first heat exchanger lowers the temperature of the refrigerant entering the compressor while raising the temperature of the fuel entering the combustion chamber of the aircraft engine to ensure complete combustion of the fuel. A first valve and a second expansion member further cool the combustion chamber of the aircraft engine under high Mach number flight conditions to meet higher thermal protection performance and provide electrical energy to the aircraft, thereby meeting the needs of both low and high Mach number flight conditions.

[0048] Furthermore, such as Figure 2 As shown, the system may also include:

[0049] The compressor is connected to the cooling channel through the third heat exchange channel of the second heat exchanger;

[0050] It also includes a second valve and a third valve. The first expansion member is connected to the first heat exchange channel through the second valve. The first expansion member is also connected to the first heat exchange channel through the third valve and the fourth heat exchange channel of the second heat exchanger.

[0051] Specifically, the second heat exchanger can also be a TPMS heat exchanger.

[0052] Specifically, the second and third valves can also be solenoid valves.

[0053] refer to Figure 2 Under low Mach number flight conditions, the third valve opens, while the first and second valves close. After passing through the first expansion member, the refrigerant can exchange heat with the refrigerant in the fourth heat exchange channel of the second heat exchanger via the third heat exchange channel, increasing the temperature of the subsequent refrigerant and further increasing the temperature of the fuel entering the engine combustion chamber. This results in faster fuel combustion compared to... Figure 1 The integrated system shown in the diagram achieves more complete combustion (this configuration is due to the favorable thermal environment at low Mach numbers and the relatively sufficient supply of cold source, which reduces the requirements for thermal protection and makes thermal protection problems less likely to occur).

[0054] Under high Mach number flight conditions, the third valve is closed, and the first and second valves are open, opening the refrigerant circulation path. Figure 1 The refrigerant circulation path under high Mach number flight conditions is the same, and will not be described again here.

[0055] This embodiment, by setting a second valve, a third valve, and a second heat exchanger, can further increase the temperature of the fuel entering the combustion chamber of the aircraft engine, thereby making the fuel combustion more complete.

[0056] This application also provides an optimization method for an integrated thermal protection and power generation system for aircraft. The execution entity of this optimization method can be a computer or server, or other electronic devices with data processing capabilities; alternatively, the execution entity can be a processor (e.g., a central processing unit (CPU)) within the aforementioned electronic device; furthermore, the execution entity can be an application (APP) installed on the aforementioned electronic device capable of implementing the method's function; or, the execution entity can be a functional module or unit within the aforementioned electronic device that performs the method's function. No limitation is placed on the execution entity of this method.

[0057] The following description, in conjunction with the accompanying drawings, provides an exemplary illustration of the optimization method for the integrated thermal protection and power generation system of this aircraft.

[0058] Figure 3 This is a flowchart illustrating the optimization method for the integrated thermal protection and power generation system for aircraft provided in this application embodiment. Wherein, Figure 3 This is merely one execution order shown in the embodiments of this application and does not represent the only execution order of the optimization method for the integrated thermal protection and power generation system of an aircraft. Where the final result can be achieved, Figure 3 The steps shown can be performed in parallel or in reverse order. For example... Figure 1 As shown, the method may include:

[0059] S301. Perform sensitivity analysis on multiple component parameters and corresponding system indicators of an integrated system under different system operating conditions to obtain the influence trend of multiple component parameters on the corresponding system indicators.

[0060] The system operating conditions include low Mach number and high Mach number conditions. Under low Mach number conditions, multiple component parameters include the compressor inlet temperature, the inlet pressure of the first expander, the inlet pressure of the second expander, and the outlet position of the first expander. The corresponding system indicators include system cycle efficiency and fuel consumption rate. Under high Mach number conditions, multiple component parameters include the compressor inlet temperature, the fuel outlet temperature, and the inlet pressure of the first expander. The corresponding system indicators include system cycle efficiency, system cycle net work, and system total mass.

[0061] Sensitivity analysis is a method used to assess the impact of changes in variables on the results in a model or decision. It can determine the research scope of parameters for each component based on the specific parameters of the heat source and fuel cold source of the integrated system.

[0062] For example, under high Mach number conditions, the research range for the compressor inlet temperature can be determined to be 333K (Kelvin temperature) to 373K based on the parameters of the cold source and the heat source, the research range for the fuel outlet temperature can be 623K to 723K, and the research range for the inlet pressure of the first expansion component can be 25MPa to 35MPa.

[0063] After obtaining the study range of each component's parameters, sampling can be performed according to a pre-set step size. For example, the step size can be one-tenth of the study range.

[0064] Continuing with the example above, for the compressor inlet temperature with a step size of 4K, a total of eleven samples can be obtained: 333K, 337K, ..., 373K. For the fuel outlet temperature with a step size of 10K, a total of eleven samples can be obtained: 623K, 633K, ..., 723K. For the inlet pressure of the first expansion component with a step size of 1MPa, a total of eleven samples can be obtained: 25MPa, 26MPa, ..., 35MPa.

[0065] After obtaining the research samples of each component parameter, the influence of each component parameter on different system indicators can be investigated by controlling variables. By substituting the sample values ​​of each component parameter into the calculation model corresponding to the integrated system, the influence trend of each component parameter on each system indicator can be obtained, and a dot-line graph can be drawn. Finally, the influence trend of multiple component parameters on multiple system indicators can be obtained.

[0066] The computational model corresponding to the integrated system is a mathematical model in which each component of the integrated system calculates and then transmits inlet and outlet parameters to achieve system closed-loop operation. It includes the calculation equations for each component. The compressor and the first and second expansion components use isentropic efficiency to calculate the actual enthalpy value, and the calculation equations are linear equations. In the first and second heat exchangers, the heat transfer equations are discretized. After discretization, the differential heat transfer equations are transformed into a system of linear algebraic equations. All enthalpy value transmission processes in the system are linear equations.

[0067] S302. Based on the influence trend, determine multiple target fitting intervals corresponding to each of the multiple component parameters.

[0068] For example, the fitting range of component parameters on each system index can be determined based on the expected and influencing trends of the system index.

[0069] For system cycle efficiency, first find its maximum point in the influence trend (i.e., dotted line graph). If there is a maximum point, take the two sample values ​​adjacent to the sample value of the component parameter corresponding to the maximum point as the two endpoints of the fitting interval of the component parameter on the system cycle efficiency. If there is no maximum point, take the sample values ​​of the component parameter corresponding to the two largest system cycle efficiency values ​​as the two endpoints of the fitting interval of the component parameter on the system cycle efficiency.

[0070] For fuel consumption rate, first find its minimum point in the influence trend. If there is a minimum point, take the two sample values ​​adjacent to the sample value of the component parameter corresponding to the minimum point as the two endpoints of the fitting interval of the component parameter on the fuel consumption rate. If there is no minimum point, take the sample values ​​of the component parameter corresponding to the two smallest fuel consumption rate values ​​as the two endpoints of the fitting interval of the component parameter on the fuel consumption rate.

[0071] For the system's cyclic net power, first find its maximum point in the influence trend. If there is a maximum point, take the two adjacent sample values ​​of the component parameter corresponding to the maximum point as the two endpoints of the fitting interval of the component parameter on the system's cyclic net power. If there is no maximum point, take the sample values ​​of the component parameter corresponding to the two largest system cyclic net power values ​​as the two endpoints of the fitting interval of the component parameter on the system's cyclic net power.

[0072] For the total mass of the system, first find its minimum point in the influence trend. If there is a minimum point, take the two adjacent sample values ​​of the component parameter corresponding to the minimum point as the two endpoints of the fitting interval of the component parameter on the total mass of the system. If there is no minimum point, take the sample values ​​of the component parameter corresponding to the two smallest total mass values ​​of the system as the two endpoints of the fitting interval of the component parameter on the total mass of the system.

[0073] For example, after obtaining the fitting intervals of the component parameters on various system indicators, the union of multiple fitting intervals can be taken as the target fitting interval corresponding to the component parameter.

[0074] Continuing with the previous example, we can obtain the influence trends (i.e., dotted-line graphs) of the compressor inlet temperature on the system cycle efficiency, system net cycle work, and system total mass under high Mach number conditions. When a maximum value exists in the dotted-line graph corresponding to the system cycle efficiency, the two adjacent sample values ​​of the compressor inlet temperature corresponding to that maximum value are used as the two endpoints of the fitting interval for the compressor inlet temperature on the system cycle efficiency. When a maximum value exists in the dotted-line graph corresponding to the system net cycle work, the two adjacent sample values ​​of the compressor inlet temperature corresponding to that maximum value are used as the two endpoints of the fitting interval for the compressor inlet temperature on the system net cycle work. When no minimum value exists in the dotted-line graph corresponding to the system total mass, the sample values ​​of the compressor inlet temperature corresponding to the two minimum system total mass values ​​are used as the two endpoints of the fitting interval for the compressor inlet temperature on the system total mass. By performing a union operation on the three fitting intervals, we obtain the target fitting interval for the compressor inlet temperature.

[0075] S303, Perform the error determination steps.

[0076] The error determination steps include: constructing an orthogonal experimental table based on multiple component parameters, multiple system indicators, and multiple target fitting intervals; determining multiple first-variable high-order polynomials, with each first-variable high-order polynomial corresponding to one of the multiple system indicators; and determining the first error based on the multiple first-variable high-order polynomials and the calculation model corresponding to the integrated system, where the first error is the average of the relative errors between the fitting results and the actual results.

[0077] For example, an orthogonal experimental design can be used, with multiple component parameters as independent variables and multiple system indices as dependent variables. An orthogonal experimental table is constructed based on the target fitting interval for each independent variable (i.e., component parameter). A high-order polynomial is then established for each dependent variable (i.e., system indices), resulting in multiple high-order polynomials. High-order polynomials can be used for fitting to achieve a coefficient of determination R0. 2 And the corrected coefficient of determination is greater than a preset value (e.g., 0.98, which can be understood as the coefficient of determination R). 2And the closer the coefficient of determination is to 1, the better the fit. The fitted high-order polynomial is then determined as the first multivariate high-order polynomial.

[0078] For example, after obtaining multiple first multivariate high-order polynomials corresponding to multiple system indicators, multiple sets of random sample values ​​can be randomly generated. Each set of random sample values ​​includes a value of multiple component parameters randomly selected from their respective target fitting intervals.

[0079] Continuing with the previous example, under high Mach number conditions, each set of sample values ​​includes the compressor inlet temperature, the fuel outlet temperature, and the inlet pressure of the first expander. The compressor inlet temperature is a random value in its corresponding target fitting interval, the fuel outlet temperature is a random value in its corresponding target fitting interval, and the inlet pressure of the first expander is a random value in its corresponding target fitting interval.

[0080] For example, multiple sets of random sample values ​​can be substituted into multiple first-variable high-order polynomials to obtain multiple sets of fitted values ​​(i.e., fitting results) of the corresponding system indicators; multiple sets of random sample values ​​can be substituted into the calculation model corresponding to the integrated system to obtain multiple sets of actual values ​​(i.e., actual results) of the system indicators.

[0081] Continuing with the example above, both the fitted values ​​and the actual values ​​include the system cycle efficiency, the system cycle net work, and the total mass of the system.

[0082] S304. When the first error does not meet the preset requirements, update the target fitting interval and execute the error determination step until the first error meets the preset requirements. When the first error meets the preset requirements, determine multiple first multivariate high-order polynomials as the objective function of the target evolution algorithm.

[0083] For example, the preset requirement can be that the first error is less than a preset threshold (e.g., 2%), or that the first error is less than or equal to a preset threshold. There are no restrictions on the preset requirement or the preset threshold.

[0084] Specifically, when the first error does not meet the preset requirements, the target fitting interval is updated, including:

[0085] If the first error does not meet the preset requirements, the target fitting interval is adjusted to half the range.

[0086] For example, when the target fitting interval is [10, 20], the updated target fitting interval can be...

[0087] [12.5, 17.5].

[0088] For example, after updating the target fitting intervals corresponding to the parameters of each component, S303 and S304 can be re-executed until the first error meets the preset requirements.

[0089] For example, after the first error meets the preset requirements, the objective function can be determined by multiple first multivariate high-order polynomials corresponding to multiple system indicators, and S305 can be executed again.

[0090] For example, the objective evolutionary algorithm can be a multi-objective whale optimization algorithm.

[0091] S305. Based on the objective function and the objective evolution algorithm, using multiple component parameters as optimization variables and the expected targets of multiple system indicators as optimization objectives, the optimal values ​​of multiple component parameters are obtained. Based on the optimal values ​​of multiple component parameters, the component parameters of the integrated system are set.

[0092] Specifically, based on the objective function and using an evolutionary algorithm, with multiple component parameters as optimization variables and the expected targets of multiple system indicators as optimization objectives, the optimal values ​​of multiple component parameters are obtained. Based on these optimal values, the component parameters of the integrated system are set, including:

[0093] S401. Based on the objective function and the objective evolution algorithm, using multiple component parameters as optimization variables and the expected targets of multiple system indicators as optimization objectives, the Pareto optimal solution set corresponding to the optimization objective is obtained.

[0094] For example, the expected target can be the optimal target corresponding to the system index. For instance, the expected target for system cycle efficiency is to maximize system cycle efficiency, the expected target for fuel consumption rate is to minimize fuel consumption rate, the expected target for system cycle net work is to maximize system cycle net work, and the expected target for system total mass is to minimize system total mass.

[0095] For example, continuing with the previous example, the optimization problem under high Mach number conditions can be expressed as follows:

[0096] maxf1(x1,x2,…,x i ),f2(x1,x2,…,x i );

[0097] minf3(x1,x2,…,x i );

[0098] stg(x1,x2,…,x i ≥5;

[0099] x iLB ≤x i ≤x iUB ;

[0100] Where f1(*) represents the objective function corresponding to the system cycle efficiency, f2(*) represents the objective function corresponding to the system cycle net work, f3(*) represents the objective function corresponding to the system total mass, and g(*) represents the constraint condition. Taking the heat exchanger pinch temperature as an example, g(*) can be expressed as the function for calculating the heat exchanger pinch temperature, x i Let x represent the i-th independent variable. iUB Let x represent the upper limit of the i-th independent variable (i.e., the maximum value of the research scope of the i-th independent variable). iLB This represents the lower limit of the i-th independent variable (i.e., the minimum value of the research range of the i-th independent variable); it can be understood that i = 1, 2, 3, and x1, x2, x3 can be the inlet temperature of the compressor, the outlet temperature of the fuel, and the inlet pressure of the first expansion component, respectively.

[0101] For example, taking the multi-objective whale optimization algorithm as the objective evolutionary algorithm, we can choose a population size of 100, an iteration count of 200, use crowding distance and non-dominated sorting as the determination method, and solve the optimization problem with the goal of maximizing cycle efficiency and cycle net work and minimizing the total weight of the system, to obtain the Pareto optimal solution set.

[0102] S402. Based on the Pareto optimal solution set, obtain the optimal Pareto front.

[0103] It can be understood that the optimal Pareto front is the geometric representation of the Pareto optimal solution set in the target space. It is the set of target vectors corresponding to all Pareto optimal solutions, and it is represented as a continuous curve, surface or hypersurface in the target space.

[0104] S403. Based on the optimization objective and the optimal Pareto front, determine the ideal point, which is the point in the solution space corresponding to the optimal Pareto front that satisfies the optimization objective.

[0105] For example, in the target space corresponding to the optimal Pareto front, the preference multidimensional analysis linear programming technique (LINMAP) can be used as the decision method to find the ideal point that satisfies the optimization objective. The ideal point can be a hypothetical point (i.e. a point that is not in the optimal Pareto front).

[0106] S404. Based on the ideal point, determine the target point from the optimal Pareto front. The target point is the point in the optimal Pareto front that is closest to the ideal point.

[0107] Specifically, based on the ideal point, the target point is determined from the optimal Pareto front, including:

[0108] The points in the optimal Pareto front are normalized; the target point is determined based on the Euclidean distance between the normalized points and the ideal point.

[0109] S405. Determine the optimal values ​​of multiple component parameters based on the target point.

[0110] It can be understood that the value of the component parameter corresponding to the target point is the optimal value of the component parameter.

[0111] S406. Set the component parameters of the integrated system according to the optimal values ​​of multiple component parameters.

[0112] For example, the specific values ​​of the component parameters of the integrated system can be set to the optimal values ​​of the corresponding component parameters, thereby achieving optimal system indicators and improving the overall performance of the integrated system.

[0113] For example, the hardware structure parameters of the integrated system can also be adjusted according to the optimal values ​​of multiple component parameters, so that the component parameters of the integrated system can achieve optimal values.

[0114] This embodiment performs sensitivity analysis on multiple component parameters and corresponding system indicators of an integrated system under different system operating conditions to obtain the influence trends of multiple component parameters on the corresponding system indicators. Based on the influence trends, multiple target fitting intervals are determined for each component parameter. An error determination step is then performed, which includes: constructing an orthogonal experimental table based on multiple component parameters, multiple system indicators, and multiple target fitting intervals to determine multiple first-variable high-order polynomials; determining a first error based on the multiple first-variable high-order polynomials and the corresponding calculation model of the integrated system; updating the target fitting intervals when the first error does not meet the preset requirements, and performing the error determination step again until the first error meets the preset requirements; when the first error meets the preset requirements, the multiple first-variable high-order polynomials are determined as the objective function of the target evolution algorithm; based on the objective function, using the target evolution algorithm with multiple component parameters as optimization variables and the expected targets of multiple system indicators as optimization objectives, the optimal values ​​of multiple component parameters are obtained. By setting the component parameters of the integrated system based on the optimal values ​​of multiple component parameters, the computational complexity can be reduced while ensuring the calculation accuracy of the optimal values, thereby achieving more accurate optimization of the integrated system and improving the optimization efficiency of the integrated system.

[0115] While this application provides the method operation steps as described in the embodiments or flowcharts, more or fewer operation steps may be included based on conventional or non-inventive labor. The order of steps listed in this embodiment is merely one possible execution order among many and does not represent the only possible execution order. In actual device or client product execution, the methods shown in this embodiment or the accompanying drawings can be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment).

[0116] The various embodiments described in this specification are presented in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on its differences from other embodiments. All or part of this application can be used in numerous general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, mobile communication terminals, multiprocessor systems, microprocessor-based systems, programmable electronic devices, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices, etc.

[0117] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of this application.

Claims

1. An integrated thermal protection and power generation system for aircraft, characterized in that, The system includes: The compressor has its output end connected to the cooling channel of the aircraft engine combustion chamber, and the cooling channel is connected to the input end of the first expansion member. The output end of the first expansion member is connected to the input end of the compressor through the first heat exchange channel of the first heat exchanger. It also includes a fuel supply assembly, which is connected to the combustion chamber of the aircraft engine through a second heat exchange channel of the first heat exchanger; It also includes a second expansion member, the input end of which is connected to the first intermediate position of the cooling channel via a first valve, and the output end of which is connected to the second intermediate position of the cooling channel.

2. The system according to claim 1, characterized in that, The system also includes: The compressor is connected to the cooling channel through the third heat exchange channel of the second heat exchanger; It also includes a second valve and a third valve. The first expansion member is connected to the first heat exchange channel through the second valve. The first expansion member is also connected to the first heat exchange channel through the third valve and the fourth heat exchange channel of the second heat exchanger.

3. The system according to claim 1, characterized in that, Both the first expansion member and the second expansion member are turbines.

4. The system according to claim 2, characterized in that, Both the first heat exchanger and the second heat exchanger are TPMS heat exchangers.

5. The system according to claim 2, characterized in that, The first valve, the second valve, and the third valve are all solenoid valves.

6. An optimization method for an integrated thermal protection and power generation system for aircraft, based on the system according to any one of claims 1 to 5, characterized in that, The method includes: Sensitivity analysis was performed on multiple component parameters and corresponding system indicators of an integrated system under different system operating conditions to obtain the influence trend of multiple component parameters on the corresponding system indicators. The system operating conditions include low Mach number conditions and high Mach number conditions. Under the low Mach number conditions, multiple component parameters include the compressor inlet temperature, the inlet pressure of the first expander, the inlet pressure of the second expander, and the outlet position of the first expander. Corresponding system indicators include system cycle efficiency and fuel consumption rate. Under the high Mach number conditions, multiple component parameters include the compressor inlet temperature, the fuel outlet temperature, and the inlet pressure of the first expander. Corresponding system indicators include system cycle efficiency, system cycle net work, and system total mass. Based on the aforementioned influence trend, multiple target fitting intervals are determined, each corresponding to one of the parameters of the multiple components. The error determination step includes: constructing an orthogonal experimental table based on multiple component parameters, multiple system indicators, and multiple target fitting intervals; determining multiple first multivariate high-order polynomials, which correspond one-to-one with multiple system indicators; and determining a first error based on the multiple first multivariate high-order polynomials and the calculation model corresponding to the integrated system, wherein the first error is the average value of the relative error between the fitting result and the actual result. When the first error does not meet the preset requirements, the target fitting interval is updated, and the error determination step is executed until the first error meets the preset requirements; when the first error meets the preset requirements, the plurality of first multivariate high-order polynomials are determined as the objective function of the target evolution algorithm. Based on the objective function and the objective evolution algorithm, using multiple component parameters as optimization variables and the expected targets of multiple system indicators as optimization objectives, the optimal values ​​of multiple component parameters are obtained. Based on the optimal values ​​of multiple component parameters, the component parameters of the integrated system are set.

7. The method according to claim 6, characterized in that, The process involves obtaining optimal values ​​for multiple component parameters based on the objective function and the objective evolution algorithm, using multiple component parameters as optimization variables and the expected targets of multiple system indicators as optimization objectives. Based on these optimal values, the component parameters of the integrated system are then set, including: Based on the objective function and the objective evolution algorithm, using multiple component parameters as optimization variables and the expected targets of multiple system indicators as optimization objectives, the Pareto optimal solution set corresponding to the optimization objective is obtained. Based on the Pareto optimal solution set, the optimal Pareto front is obtained; Based on the optimization objective and the optimal Pareto front, an ideal point is determined, wherein the ideal point is a point in the solution space corresponding to the optimal Pareto front that satisfies the optimization objective; Based on the ideal point, a target point is determined from the optimal Pareto front, wherein the target point is the point in the optimal Pareto front that is closest to the ideal point; Based on the target point, determine the optimal values ​​of multiple component parameters; Set the component parameters of the integrated system according to the optimal values ​​of multiple component parameters.

8. The method according to claim 6, characterized in that, The target evolution algorithm is a multi-objective whale optimization algorithm.

9. The method according to claim 7, characterized in that, The step of determining the target point from the optimal Pareto front based on the ideal point includes: The points in the optimal Pareto front are normalized. The target point is determined based on the Euclidean distance between the normalized point and the ideal point.

10. The method according to claim 6, characterized in that, The step of updating the target fitting interval when the first error does not meet the preset requirements includes: If the first error does not meet the preset requirements, the target fitting interval is adjusted to 1 / 2 range.

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