Installation performance optimization method of aero-engine

Abstract

The invention discloses a mounting performance optimization method for an aero-engine, and belongs to the field of aero-engines. According to the method, the bypass deflation flow coefficient of the air inlet channel and the outlet area of the spray pipe are optimized in different optimization layers respectively. According to the hierarchical optimization method, the bypass deflation flow coefficient of the air inlet channel and the adjustable parameters of the engine are jointly taken as global optimization variables, and the outlet area of the spray pipe is optimized through a local univariate optimization process. Therefore, the coupling effect of the engine and the intake / exhaust system of the engine can be considered only by adding one global optimization variable, and the installation performance of the engine is optimal.

Description

Technical Field

[0001] The present invention belongs to the field of aero-engines, and in particular relates to a method for optimizing the installation performance of an aero-engine. Background Art

[0002] When a high-Mach-number aircraft engine is installed on an aircraft, its intake and exhaust systems experience significant installation losses, resulting in reduced thrust or, at the same thrust level, increased fuel consumption. Typically, adjustments to the adjustable mechanisms of the intake and exhaust systems focus solely on the installation losses of the intake and exhaust systems themselves, failing to consider the coupling effects between the engine and its intake and exhaust systems. This results in inadequate performance during installation.

[0003] In the "Simulation of the Installation Performance of a High-Speed ​​Single-Shaft Turbojet Engine with a Bypass Bleed Cycle" in the 40th issue of the 6th volume of the Propulsion Technology journal in 2019, Figure 6 (1) on page 1204 shows the default bypass bleed control law of the inlet. Given that the reduction of bypass bleed will lead to a reduction in bypass bleed resistance and an increase in overflow resistance, the bypass bleed control law is usually optimized with the goal of minimizing the sum of bypass bleed resistance and overflow resistance. However, the reduction of bypass bleed will also increase the total pressure recovery coefficient of the inlet. Generally, a 1% increase in the total pressure recovery coefficient of the inlet will increase the non-installed thrust of the engine by 1.5% to 2%. It can be seen that bypass bleed will affect both the installed resistance of the inlet and the non-installed thrust of the engine. The previous bypass bleed control law optimization method that only considers the installed resistance of the inlet cannot achieve the optimal control of the installed performance of the engine. In addition, Figure 8 on page 1205 of the document shows the characteristic diagram of the nozzle rear body drag coefficient. As can be seen from this characteristic diagram, a moderate increase in the nozzle exit area is beneficial for reducing the nozzle's rear body drag. However, the nozzle exit area is typically calculated based on the fully expanded nozzle exit airflow (the fully expanded, non-installed thrust is the largest), and this area is used directly to calculate the nozzle's rear body drag, thereby ignoring the gain in installed thrust from nozzle exit area adjustment. Clearly, the inlet bypass bleed flow coefficient and nozzle exit area can be included as optimization variables along with the other adjustable engine parameters, but the increase in optimization variables will lead to an increase in the optimization computational complexity. Therefore, it is necessary to develop an installed performance optimization method that considers the coupling effects of the engine and the intake / exhaust system without excessively increasing the optimization computational complexity. Summary of the Invention

[0004] Technical issues to be solved:

[0005] In order to avoid the shortcomings of the existing technology, the present invention provides a method for optimizing the installation performance of an aircraft engine. This method incorporates the bypass bleed flow coefficient of the inlet duct and the adjustable parameters of the engine as global optimization variables, and optimizes the nozzle outlet area through a local single-variable optimization process, thereby optimizing the engine's installation performance.

[0006] The technical solution of the present invention is: a method for optimizing the installation performance of an aircraft engine, characterized by the following specific steps:

[0007] The engine's adjustable parameters and the intake bypass air flow coefficient are selected as global optimization variables;

[0008] Set engine constraints;

[0009] A local optimization process for installed thrust is set up in the nozzle model of the engine model; after the calculations of the remaining engine components are completed, the nozzle outlet area is optimized using the ratio of the nozzle outlet area to the outlet area of ​​the fully expanded nozzle airflow as the local optimization variable to maximize the installed thrust of the engine;

[0010] An optimization algorithm is used to solve the global optimization variable to maximize the installed thrust of the engine or minimize the installed fuel consumption rate while satisfying the constraint conditions. When calling the engine model, the engine nozzle model must include the installed thrust local optimization process.

[0011] A further technical solution of the present invention is: the adjustable parameters of the engine include at least one of the fuel supply to the combustion chamber, the inlet guide vane angle of the compression component, the inlet guide vane angle of the turbine component, the mixing area ratio of the mixing chamber, and the nozzle throat area.

[0012] A further technical solution of the present invention is: the constraint conditions include at least one of the surge margin of the compression component, the stable combustion margin of the combustion chamber, the total outlet temperature of the compression component, the total outlet pressure of the compression component, the rotor speed, and the total outlet temperature of the combustion chamber.

[0013] A further technical solution of the present invention is: the local optimization process of the installation thrust is:

[0014] Select the exit area A that allows the nozzle airflow to fully expand 9,base As the optimization benchmark, define the nozzle outlet area A9 and the optimization benchmark A 9,base The ratio is the local optimization variable α A , the expression is as follows:

[0015]

[0016] The nozzle outlet area A9 is larger than the nozzle throat area A8, so α A The lower limit expression is:

[0017]

[0018] α A The upper limit is based on the maximum value of A9 / A8 (A9 / A8) max OK, the expression is:

[0019]

[0020] The nozzle throat area A8 is a given value or a global optimization variable.

[0021] A further technical solution of the present invention is: the local optimization variable α A The initial value of is set to 1.0.

[0022] A further technical solution of the present invention is: the maximum value of A9 / A8 (A9 / A8) max Constrained by the nozzle structure, not more than 2.0.

[0023] A further technical solution of the present invention is: the specific process of using the optimization algorithm to solve the global optimization variable is as follows:

[0024] Let the global optimization variable be X, and calculate the engine objective function f(X) according to the following formula:

[0025]

[0026] Where p(X) represents the performance parameters of the engine; p Limit represents the limiting value of the engine performance parameter. For the maximization problem, p Limit is the upper limit value. For the minimization problem, p Limit is the lower limit; for the minimization problem, f(X) decreases as p(X) decreases; for the maximization problem, f(X) decreases as p(X) increases, thus converting the maximization problem of p(X) into the minimization problem of f(X); where |p on the denominator is Limit | Make the order of magnitude of f(X) be 10 0 Level 1;

[0027] The comprehensive constraint function g(X) is calculated according to the following formula:

[0028]

[0029] Where, the subscript i represents the sequence number of the constraint parameter; I represents the total number of constraint parameters; c i (X) and c i,Limit Represent the calculated value and limit value of the i-th constraint parameter respectively; S iis the identifier of the upper and lower bound constraints. For the upper bound constraint problem S i =1, for the lower bound constraint problem S i =-1;

[0030] The comprehensive objective function h(X) is calculated according to the following formula:

[0031] h(X)=f(X)+σ×g(X)

[0032] Where σ represents the penalty factor of the comprehensive constraint function.

[0033] A further technical solution of the present invention is that the penalty factor σ is set to 10, so that the order of magnitude of σ×g(X) is 10 1 Level 1.

[0034] A further technical solution of the present invention is: the optimization algorithm selects a swarm intelligence optimization algorithm or a sequential quadratic programming algorithm according to the number of global optimization variables.

[0035] An electronic device, characterized in that it includes at least one processor and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the method for optimizing the installation performance of the aircraft engine.

[0036] Beneficial effects

[0037] The beneficial effects of the present invention lie in: applying the method for optimizing aircraft engine installation performance, the bypass bleed flow coefficient of the inlet duct and the engine's adjustable parameters are incorporated into global optimization variables, and the nozzle exit area is optimized through a local single-variable optimization process. This addition of a single global optimization variable allows the coupling effect between the engine and its intake / exhaust system to be considered, resulting in optimal engine installation performance without significantly increasing the computational complexity of engine performance optimization. A detailed analysis is as follows:

[0038] 1. Balance between computational efficiency and optimization effect. The inlet bypass air flow coefficient and nozzle outlet area are optimized separately at different optimization layers. This hierarchical optimization method incorporates the inlet bypass air flow coefficient and the engine adjustable parameters into the global optimization variables, and uses a local single-variable optimization process to optimize the nozzle outlet area separately, avoiding the inclusion of the nozzle outlet area in the global optimization variables and reducing the total number of global optimization variables. Only one global variable is added (the bypass air flow coefficient), avoiding the exponential growth in computational complexity caused by too many global optimization variables. At the same time, the local optimization process uses efficient algorithms such as the Newton method, and provides the algorithm with optimization initial values ​​and reasonable upper and lower limits that are close to the optimal solution, further reducing time complexity.

[0039] 2. Comprehensive consideration of coupling effects. Traditional methods focus solely on the installation losses of the intake / exhaust system itself. However, this invention incorporates the bypass bleed flow coefficient as an optimization variable, simultaneously balancing the coupling relationship between the inlet total pressure recovery coefficient (which affects non-installed thrust), the bypass bleed drag coefficient, and the overflow drag coefficient. This global collaborative optimization more comprehensively reflects the interaction between the engine and the intake / exhaust system, thereby unlocking the potential of installed performance.

[0040] 3. Nozzle aft body drag optimization gain. A local optimization process is implemented within the nozzle model, using the baseline area of ​​the fully expanded nozzle airflow as the optimization starting point. The outlet area is dynamically adjusted to maximize installed thrust. While conventional methods fix the nozzle outlet area (pursuing only the optimal fully expanded, non-installed thrust), this invention reduces the nozzle aft body drag by allowing for a moderate expansion of the outlet area, thereby achieving higher net thrust in the installed state.

[0041] 4. Intelligent Prioritization of Constraints. A penalty factor (set to 10) is introduced into the comprehensive objective function, making the penalty for constraint violations orders of magnitude higher than the performance objective. This design prioritizes safety constraints (such as surge margin and temperature limits) during the optimization process, avoiding sacrificing engine reliability and safety in pursuit of performance.

[0042] It has been verified that when optimizing the installed thrust of a hybrid exhaust turbofan engine, the installation performance optimization method of the present invention increases the installed thrust by 2.98% compared to the conventional installation performance optimization method, and increases the optimization time by only 2.42%; compared to directly incorporating the nozzle throat area into the global optimization variable, incorporating the nozzle throat area into the local optimization variable not only does not affect the optimization result of the installed thrust, but also reduces the number of global optimization variables and reduces the optimization time by 9.48%. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 The present invention is a flowchart of an optional method for optimizing the installation performance of an aircraft engine according to an embodiment of the present invention.

[0044] Figure 2 It is a schematic diagram of the global optimization process of engine installation performance and the local optimization process in the nozzle model. DETAILED DESCRIPTION

[0045] The embodiments described below with reference to the accompanying drawings are exemplary and are intended to explain the present invention, but should not be construed as limiting the present invention.

[0046] Based on traditional methods, the inlet bypass bleed flow coefficient and the nozzle outlet area can be included together with other adjustable parameters of the engine as optimization variables. However, the increase in optimization variables will lead to problems such as an increase in the optimization calculation amount. The present invention provides a method for optimizing the installation performance of an aircraft engine. The specific steps are as follows:

[0047] Step 1: Select the engine's adjustable parameters and the intake bypass air flow coefficient as global optimization variables;

[0048] Step 2: Set the constraints of the engine;

[0049] Step 3: Set up a local optimization process for installed thrust in the nozzle model of the engine model. After the calculations for the remaining engine components are completed, the nozzle outlet area is optimized using the ratio of the nozzle outlet area to the outlet area of ​​the fully expanded nozzle airflow as the local optimization variable to maximize the installed thrust of the engine.

[0050] Step 4: Use the optimization algorithm to solve the global optimization variable to maximize the installed thrust of the engine or minimize the installed fuel consumption rate while satisfying the constraints; when calling the engine model, the engine nozzle model must include the installed thrust local optimization process.

[0051] This invention significantly improves the installation performance of aircraft engines through a global-local stepwise optimization strategy, while limiting the increase in computational effort. It systematically addresses the coupling effects between the engine and the intake and exhaust systems, balancing computational efficiency, safety constraints, and performance optimization, providing an effective solution for the design of powertrains for high-Mach number aircraft.

[0052] The above technical solution is further explained below with reference to examples:

[0053] In one embodiment, taking the optimization problem of maximizing the installed thrust of a hybrid exhaust turbofan engine at the apex of a subsonic climb as an example, this embodiment includes the following steps:

[0054] Step one, select the engine's adjustable parameters and the intake duct bypass bleed flow coefficient as global optimization variables. The engine's adjustable parameters include but are not limited to: combustion chamber fuel supply, compression component inlet guide vane angle, turbine component inlet guide vane angle, mixing chamber mixing area ratio, nozzle throat area, etc. In this step, the introduction of the intake duct bypass bleed flow coefficient as an optimization variable can balance the relationship between the total pressure recovery coefficient of the intake duct (this coefficient affects the non-installed thrust of the engine), the bypass bleed resistance coefficient and the overflow resistance coefficient, thereby optimizing the engine's installed performance. Only adding one global optimization variable can effectively control the increment of the optimization calculation amount.

[0055] The global optimization variables and their upper and lower limits selected in this embodiment are shown in Table 1.

[0056] Table 1 Global optimization variables and their upper and lower limits for engine installation performance

[0057]

[0058] Step 2: Set engine constraints, including but not limited to: the surge margin of the compression component is not lower than a certain value, the stable combustion margin of the combustion chamber is not lower than a certain value, the total temperature at the outlet of the compression component is not higher than a certain value, the total pressure at the outlet of the compression component is not higher than a certain value, the rotor speed is not higher than a certain value, the total temperature at the outlet of the combustion chamber is not higher than a certain value, etc.

[0059] The constraint parameters and their upper and lower limits selected in this embodiment are shown in Table 2.

[0060] Table 2 Constraint parameters and upper and lower limits for engine installation performance optimization

[0061]

[0062]

[0063] Step 3: Set up a local optimization process for installed thrust in the nozzle model of the engine model. The specific process is as follows:

[0064] After the calculation of the remaining engine components is completed, the nozzle outlet area is locally optimized in the nozzle model, with the goal of maximizing the installed thrust of the engine, such as Figure 2 As shown. For this local optimization problem, the Newton method is selected as the optimization algorithm, so as not to increase the time complexity of the engine model. In the local optimization process, the outlet area A that makes the nozzle airflow fully expanded is selected. 9,base As the optimization benchmark, define the nozzle outlet area A9 and the optimization benchmark A 9,base The ratio is the local optimization variable α A :

[0065]

[0066] Optimization variable α A The initial value of is 1.0, which can provide the Newton method with an initial value close to the optimal solution, thereby improving the optimization efficiency of the nozzle outlet area. Since the nozzle outlet area A9 needs to be larger than the nozzle throat area A8, α A The lower limit of is:

[0067]

[0068] α A The upper limit is based on the maximum value of A9 / A8 (A9 / A8) max Sure:

[0069]

[0070] In this embodiment, A8 in formula (2) and formula (3) belongs to the global optimization variable in step 1. (A9 / A8) in formula (2) max Constrained by the structure of the nozzle, it is set to 2.0 in this embodiment.

[0071] Step 4: Use the optimization algorithm to solve the optimization variables set in step 1, so that the engine's installed thrust is maximized or the installed fuel consumption rate is minimized while satisfying the constraints set in step 2. It should be noted that when calling the engine model in this step, the engine's nozzle model must include the installed thrust local optimization process in step 3. This step includes the following sub-steps:

[0072] Sub-step 1: Let the global optimization variable set in step 1 be X, and calculate the engine objective function f(X) according to the following formula:

[0073]

[0074] Where p(X) represents the performance parameters of the engine; p Limit represents the limiting value of the engine performance parameter (for the maximization problem, p Limit is the upper limit; for the minimization problem, p Limit is the lower limit). It can be seen that for the minimization problem, f(X) decreases as p(X) decreases; for the maximization problem, f(X) decreases as p(X) increases, so the maximization problem of p(X) can be converted into the minimization problem of f(X). Limit | can make the order of magnitude of f(X) be 10 0 The optimization goal selected in this embodiment is to maximize the installed thrust of the engine, so p(X) represents the installed thrust of the engine, p Limit It can be set to the upper limit of the installation thrust, i.e. 100kN.

[0075] Sub-step 2: Calculate the comprehensive constraint function g(X) according to the following formula:

[0076]

[0077] Where, the subscript i represents the sequence number of the constraint parameter; I represents the total number of constraint parameters; c i (X) and c i,Limit Represent the calculated value and limit value of the i-th constraint parameter respectively; S i is the identifier of the upper and lower bound constraints. For the upper bound constraint problem S i =1, for the lower bound constraint problem S i =-1.

[0078] Sub-step 3: Calculate the comprehensive objective function h(X) according to the following formula:

[0079] h(X)=f(X)+σ×g(X)(6)

[0080] Where σ represents the penalty factor of the comprehensive constraint function. Usually σ is set to 10, so that the order of magnitude of σ×g(X) is 10 1 Level 1. Since the order of magnitude of f(X) is 10 0 Level 1, so in the process of minimizing h(X), g(X) will be minimized first, that is, the optimization constraints will be satisfied first.

[0081] Sub-step 4: Call an optimization algorithm to solve the optimization variable X, minimizing h(X). In this step, for a large number of optimization variables (approximately greater than 6), a swarm intelligence optimization algorithm such as a genetic algorithm or a differential evolution algorithm can be used. For a smaller number of optimization variables, a classic optimization algorithm such as a sequential quadratic programming algorithm can be used. In this embodiment, due to the large number of optimization variables, a differential evolution algorithm is selected as the algorithm for solving the optimization variables.

[0082] In one embodiment, the optimization time and thrust of a conventional installation performance optimization method and the method of the present invention are compared in the table below. As can be seen, the addition of the inlet bypass bleed flow coefficient to the global optimization variable of the present invention increases the optimization time by 2.42%. However, compared to the conventional installation performance optimization method, the installation performance optimization method of the present invention can increase the installed thrust by 2.98%.

[0083] Table 3 Optimization time and installation thrust of different optimization methods

[0084]

[0085] In one embodiment, the optimization time and thrust performance comparisons for incorporating nozzle throat area into both the global optimization variable in step 1 and the local optimization variable in step 3 are shown in the table below. This shows that the inclusion of the local optimization process in step 3 not only does not affect the installed thrust optimization results, but also reduces the number of global optimization variables and reduces optimization time by 9.48%.

[0086] Table 4 Effect of nozzle throat area optimization method on optimization time and installed thrust

[0087]

[0088]

[0089] Although the embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and are not to be construed as limitations on the present invention. A person skilled in the art may change, modify, replace and modify the above embodiments within the scope of the present invention without departing from the principles and purpose of the present invention.

Claims

1. A method for optimizing the installation performance of an aircraft engine, characterized in that The specific steps are as follows: Selecting the adjustable parameters of the engine and the intake bypass bleed air flow coefficient as global optimization variables; Set engine constraints; A local optimization process of installed thrust is set in the nozzle model of the engine model; after the calculation of other engine components is completed, the ratio of the nozzle outlet area to the outlet area of ​​the nozzle airflow fully expanded is used as a local optimization variable to optimize the nozzle outlet area so as to maximize the installed thrust of the engine; The global optimization variable is solved by using an optimization algorithm to maximize the installed thrust of the engine or minimize the installed fuel consumption rate while satisfying the constraint conditions; when calling the engine model, the engine nozzle model needs to include the installed thrust local optimization process.

2. The method for optimizing the installation performance of an aircraft engine according to claim 1, characterized in that: The adjustable parameters of the engine include at least one of a fuel supply to a combustion chamber, an inlet guide vane angle of a compression component, an inlet guide vane angle of a turbine component, a mixing area ratio of a mixing chamber, and a nozzle throat area.

3. The method for optimizing the installation performance of an aircraft engine according to claim 1, characterized in that: The constraint conditions include at least one of a surge margin of a compression component, a stable combustion margin of a combustion chamber, an outlet total temperature of a compression component, an outlet total pressure of a compression component, a rotor speed, and an outlet total temperature of a combustion chamber.

4. The method for optimizing the installation performance of an aircraft engine according to claim 1, characterized in that: The local optimization process of the installation thrust is: Choose the exit area A that allows the nozzle airflow to fully expand 9,base As the optimization benchmark, define the nozzle outlet area A9 and the optimization benchmark A 9,base The ratio is the local optimization variable α A , the expression is as follows: The nozzle outlet area A9 is larger than the nozzle throat area A8, so α A The lower limit expression is: α A The upper limit is based on the maximum value of A9 / A8 (A9 / A8) max OK, the expression is: The nozzle throat area A8 is a given value or a global optimization variable.

5. The method for optimizing the installation performance of an aircraft engine according to claim 4, characterized in that: The local optimization variable α A The initial value of is set to 1.

0.

6. The method for optimizing the installation performance of an aircraft engine according to claim 5, characterized in that: The maximum value of A9 / A8 (A9 / A8) max Constrained by the nozzle structure, not more than 2.

0.

7. The method for optimizing the installation performance of an aircraft engine according to claim 4, characterized in that: The specific process of using the optimization algorithm to solve the global optimization variable is as follows: Let the global optimization variable be X, and calculate the engine objective function f(X) according to the following formula: Where p(X) represents the performance parameter of the engine; p Limit represents the limiting value of the engine performance parameter. For the maximization problem, p Limit is the upper limit value. For the minimization problem, p Limit is the lower limit; for the minimization problem, f(X) decreases as p(X) decreases; for the maximization problem, f(X) decreases as p(X) increases, thus converting the p(X) maximization problem into the f(X) minimization problem; where |p on the denominator is Limit | Make the magnitude of f(X) to be 10 0 Level 1; The comprehensive constraint function g(X) is calculated according to the following formula: In the formula, the subscript i represents the sequence number of the constraint parameter; I represents the total number of constraint parameters; c i (X) and c i,Limit Respectively represent the calculated value and limit value of the i-th constraint parameter; S i is the identifier of the upper and lower constraints. For the upper limit constraint problem S i =1, for the lower bound constraint problem S i = -1; The comprehensive objective function h(X) is calculated according to the following formula: h(X)=f(X)+σ×g(X) Where σ represents the penalty factor of the comprehensive constraint function.

8. The method for optimizing the installation performance of an aircraft engine according to claim 7, characterized in that: The penalty factor σ is set to 10, so that the order of magnitude of σ×g(X) is 10 1 Level 1.

9. The method for optimizing the installation performance of an aircraft engine according to claim 7, characterized in that: The optimization algorithm selects a swarm intelligence optimization algorithm or a sequential quadratic programming algorithm according to the number of global optimization variables.

10. An electronic device, characterized in that: It comprises at least one processor and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for optimizing the installation performance of an aircraft engine as described in any one of claims 1 to 9.

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