Optimization method for warm-up process of aero-engine

Abstract

The invention discloses an optimization method of an aero-engine warm-up process, which comprises the following steps of: firstly, acquiring corresponding samples of a high-pressure turbine blade tip clearance delta 1, a high-pressure compressor blade tip clearance delta 2, a minimum thrust Fm in a take-off process, a total oil consumption TFC in the whole process, warm-up time delta t and a warm-up rotating speed NH in the engine process; then, on the basis of the samples, a prediction model for delta 1, delta 2, Fm and TFC by delta t and NH is established through an artificial neural network; and finally, by taking the minimum values of delta 1, delta 2 and Fm required by actual use as constraints, selecting a combination of the lowest required machine warming time and machine warming rotating speed by utilizing an epsilon-constraint method, and if the combination is not unique, selecting a combination corresponding to the minimum TFC from a result to finish optimization of the machine warming process. According to the method, the artificial neural network is used for establishing the relation of the related variables along with the engine warming time and the engine warming rotating speed, the epsilon-constraint method is used for selecting the minimum required engine warming time under multiple constraints, and the engine warming process is scientifically optimized.

Description

Technical Field

[0001] The invention relates to a method for optimizing an aircraft engine warm-up process, and belongs to the technical field of aircraft engine warm-up process optimization. Background Art

[0002] Many aircraft engine manuals stipulate that when used in low-temperature environments, the engine needs to be kept at a certain speed for a period of time to warm up after successful start. In actual use, if the engine is not warmed up during a cold start, it may cause a decrease in thrust during takeoff, which in turn affects the load that can be carried during takeoff and even affects the safety of the takeoff process. The existence of the warm-up process directly increases the time the aircraft stays on the ground or on the deck, restricting the aircraft's dispatch efficiency.

[0003] my country's current warm-up regulations are based on the warm-up regulations of foreign series engines. Currently, there is no standardized and process-based method for determining the warm-up process of aircraft engines. Therefore, optimizing the warm-up procedure and shortening the warm-up time are of great practical significance. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide an optimization method for an aircraft engine warm-up process, and to scientifically formulate the aircraft engine warm-up process by using an artificial neural network and an ε-constraint method.

[0005] The present invention adopts the following technical solutions to solve the above technical problems:

[0006] A method for optimizing an aircraft engine warm-up process comprises the following steps:

[0007] Step 1: Taking the aircraft engine warm-up time and warm-up speed as a combination, obtaining the minimum blade tip clearance of the high-pressure turbine, the minimum blade tip clearance of the high-pressure compressor, the minimum thrust during takeoff, and the total fuel consumption of the engine during the entire process under different combinations, i.e., different warm-up times and warm-up speeds, as training samples;

[0008] Step 2, setting constraints during the warm-up process;

[0009] Step 3, using the warm-up time and the warm-up speed as independent variables, the minimum blade tip clearance of the high-pressure turbine, the minimum blade tip clearance of the high-pressure compressor, the minimum thrust during takeoff, and the total fuel consumption during the entire engine history as dependent variables, using an artificial neural network to establish a prediction model of the dependent variables with respect to the independent variables, and using the training samples of step 1 for training to obtain a trained prediction model;

[0010] Step 4, taking the minimum warm-up time as the optimization goal and the constraint conditions set in step 2 as the constraints, the prediction model trained in step 3 is solved by using the ε-constraint method to obtain several combination solutions of warm-up time and warm-up speed;

[0011] Step 5: If the warm-up time and warm-up speed combination solution obtained in step 4 exists, proceed to step 6; otherwise, return to step 2 to modify the constraint conditions;

[0012] Step 6: If the warm-up time and warm-up speed combination solution obtained in step 4 is unique, proceed to step 7; otherwise, select the warm-up time and warm-up speed combination solution corresponding to the minimum total fuel consumption in the entire engine history, and proceed to step 7;

[0013] Step 7, use the warm-up time and warm-up speed obtained in step 6 for verification, and obtain the verification results of the minimum tip clearance of the high-pressure turbine, the minimum tip clearance of the high-pressure compressor, and the minimum thrust during takeoff, and determine whether the verification result is within the constraints set in step 2. If so, use the warm-up time and warm-up speed obtained in step 6 as the final optimization result; otherwise, put the verification result into the training sample of step 1, and return to step 3 to continue training.

[0014] As a preferred embodiment of the present invention, in step 1, the full engine journey refers to the entire process from the start of the engine to the end of the flight.

[0015] As a preferred solution of the present invention, in step 2, the constraints include the minimum tip clearance of the high-pressure turbine, the minimum tip clearance of the high-pressure compressor, and the minimum acceptable value of the minimum thrust during takeoff.

[0016] As a preferred solution of the present invention, the training samples in step 1 are obtained by:

[0017] 1) Determine the ground slow speed N idle And the maximum speed N allowed during the warm-up process max ;

[0018] 2) Determine the maximum allowable warm-up time t max ;

[0019] 3) Reduce the warm-up speed from N idle To N max Divide into a number of equal parts;

[0020] 4) Change the warm-up time from 0-t max Divide into 5 equal parts;

[0021] 5) Select any warm-up speed in 3) and any warm-up time in 4) as a combination, conduct tests or calculations, and obtain the corresponding high-pressure turbine minimum tip clearance, high-pressure compressor minimum tip clearance, minimum thrust during takeoff, and total fuel consumption during the entire engine history under different combinations.

[0022] A computer device comprises a memory, a processor, and a computer program stored in the memory and capable of running on the processor. When the processor executes the computer program, the steps of the method for optimizing the aircraft engine warm-up process are implemented.

[0023] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for optimizing the aircraft engine warm-up process are implemented.

[0024] Compared with the prior art, the present invention adopts the above technical solution and has the following technical effects:

[0025] According to the actual use requirements of the engine, the present invention uses artificial neural network (ANN) to establish the relationship between relevant parameters and warm-up time and warm-up speed, and uses ε-constraint method to perform multi-objective optimization to obtain the combination of the minimum required warm-up time and warm-up speed. If the combination is not unique, the warm-up process with the lowest total fuel consumption is selected to scientifically formulate or optimize the engine warm-up process. A standardized and process-based warm-up method is provided for aircraft engines. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flow chart of an optimization method for an aircraft engine warm-up process of the present invention;

[0027] Figure 2 It is a sample of the relationship between warm-up speed, warm-up time and minimum compressor tip clearance;

[0028] Figure 3 It is a sample of the relationship between warm-up speed, warm-up time and minimum blade tip clearance of high-pressure turbine;

[0029] Figure 4 It is a sample of the relationship between warm-up time, warm-up speed and minimum thrust during take-off;

[0030] Figure 5 It is a sample of the relationship between warm-up time, warm-up speed and total fuel consumption. DETAILED DESCRIPTION

[0031] The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be interpreted as limiting the present invention.

[0032] During the cold start of an aircraft engine, if the engine is not warmed up, the thrust may drop during takeoff. Currently, there is no standardized and process-based method for determining the warm-up process of an aircraft engine. Based on the test results or calculation results, the present invention optimizes the warm-up process of an aircraft engine and formulates the optimal warm-up process of the engine, such as Figure 1 As shown, the specific process is as follows:

[0033] 1) Obtain the minimum tip clearance δ of the high-pressure turbine in different processes 1 、High pressure compressor minimum tip clearance δ 2 , minimum thrust F during takeoff m And the total fuel consumption TFC test results or calculation results in the whole process, set the constraints in the optimization process: δ 1 , δ 2 The minimum acceptable value, F m The minimum acceptable value.

[0034] 2) Based on the existing engine test results or calculation results, the high pressure delta 1 , δ 2 , F m The total fuel consumption TFC during the whole process is the same as the warm-up time Δt and the warm-up speed N H The details are as follows:

[0035] a. Determine the ground slow speed N idle And the maximum speed N allowed during the warm-up process max ;

[0036] b. Determine the maximum allowable warm-up time t max ;

[0037] c. Change the warm-up time from 0 to t max Divide into 5 equal parts;

[0038] d. Reduce the warm-up speed from N idle To N max Divide into equal parts;

[0039] e. Combine the warm-up speed and warm-up time in c and d into a warm-up history, and perform tests or calculations to obtain F m ,δ 1 , δ 2 and TFC in different N H The result of the combination of and Δt;

[0040] f. N H and Δt are independent variables, F m , δ 1 , δ 2 and TFC as dependent variables, and F is obtained through artificial intelligence neural network training.m , δ 1 , δ 2 About N H and prediction models for Δt.

[0041] 3) Taking the shortest Δt as the optimization goal and the constraints established in step 1) as constraints, use the ε-constraint method to find the optimal solution that meets Δt and N H combination.

[0042] 4) If Δt and N obtained in 3) H If the combination exists, go to step 5), otherwise return to step 1) to modify the constraints.

[0043] 5) If the obtained Δt and N H If the combination is unique, go to step 7); if the combination is not unique, go to step 6).

[0044] 6) Select the result with the smallest TFC among the results given in 5), and then go to step 7).

[0045] 7) Re-use calculation or test to verify the current Δt and N H Whether the warm-up effect under the above conditions is within the constraint range, if so, input the optimization result and end the process; if not, return to step 1) and use the current calculation result or test result as the training sample of the artificial neural network again.

[0046] Example

[0047] First, the minimum tip clearance δ of different high-pressure turbines is obtained by calculation or experimental method. 1 、Minimum tip clearance δ of different high pressure compressors 2 , minimum thrust F during different takeoff processes m With different total fuel consumption TFC, same warm-up time Δt and warm-up speed N H The corresponding sample points of Figure 2-Figure 5 shown.

[0048] Optimize the warm-up process using the current sample:

[0049] 1) Using artificial neural network (ANN), with Δt and N H As the independent variable, fitting δ 1 , δ 2 、F m and TFC prediction models.

[0050] 2) Set the constraints during the warm-up process: δ 1 Not less than 0.19mm, δ 2 Not less than 0.19mm.

[0051] 3) Set F m The minimum values ​​are 120kN, 120.5kN, 121kN, 121.5kN and 122kN respectively.

[0052] 4) With δ 1 , δ 2 、F m As the constraint condition, the optimization objective is to minimize Δt and the ε-constraint method is used for optimization.

[0053] The optimization results are shown in the following table:

[0054] Table 1 Optimization results

[0055] <![CDATA[F m / kN]]> <![CDATA[N H / %]]> Δt / min 120 86.94 2.33 120.5 87.26 2.85 121 87.15 3.45 121.5 89.03 3.64 122 87.98 4.54

[0056] In summary, the warm-up process optimized by the warm-up process optimization method of the present invention can formulate the warm-up process in a systematic and process-based manner. The optimized warm-up time is reduced by more than 20% and the fuel consumption is reduced by more than 20% compared with the traditional warm-up process, which has important engineering reference value for the formulation of the aircraft engine warm-up process.

[0057] Based on the same inventive concept, an embodiment of the present application provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the aforementioned method for optimizing the aircraft engine warm-up process are implemented.

[0058] Based on the same inventive concept, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of the aforementioned method for optimizing the aircraft engine warm-up process are implemented.

[0059] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0060] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0061] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0062] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0063] The above embodiments are only for illustrating the technical idea of ​​the present invention, and cannot be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution in accordance with the technical idea proposed by the present invention shall fall within the protection scope of the present invention.

Claims

1. A method for optimizing an aircraft engine warm-up process, characterized in that: The steps include: Step 1: Taking the aircraft engine warm-up time and warm-up speed as a combination, obtaining the minimum blade tip clearance of the high-pressure turbine, the minimum blade tip clearance of the high-pressure compressor, the minimum thrust during takeoff, and the total fuel consumption of the engine during the entire process under different combinations, i.e., different warm-up times and warm-up speeds, as training samples; Step 2, setting constraints during the warm-up process; Step 3, using the warm-up time and the warm-up speed as independent variables, the minimum blade tip clearance of the high-pressure turbine, the minimum blade tip clearance of the high-pressure compressor, the minimum thrust during takeoff, and the total fuel consumption during the entire engine history as dependent variables, using an artificial neural network to establish a prediction model of the dependent variables with respect to the independent variables, and using the training samples of step 1 for training to obtain a trained prediction model; Step 4, taking the minimum warm-up time as the optimization goal and the constraint conditions set in step 2 as the constraints, the prediction model trained in step 3 is solved by using the ε-constraint method to obtain several combination solutions of warm-up time and warm-up speed; Step 5: If the warm-up time and warm-up speed combination solution obtained in step 4 exists, proceed to step 6; otherwise, return to step 2 to modify the constraint conditions; Step 6: If the warm-up time and warm-up speed combination solution obtained in step 4 is unique, proceed to step 7; otherwise, select the warm-up time and warm-up speed combination solution corresponding to the minimum total fuel consumption in the entire engine history, and proceed to step 7; Step 7, use the warm-up time and warm-up speed obtained in step 6 for verification, and obtain the verification results of the minimum tip clearance of the high-pressure turbine, the minimum tip clearance of the high-pressure compressor, and the minimum thrust during takeoff, and determine whether the verification result is within the constraints set in step 2. If so, use the warm-up time and warm-up speed obtained in step 6 as the final optimization result; otherwise, put the verification result into the training sample of step 1, and return to step 3 to continue training.

2. The method for optimizing the aircraft engine warm-up process according to claim 1, characterized in that: In step 1, the full engine journey refers to the entire process from the start of the engine to the end of the flight.

3. The method for optimizing the aircraft engine warm-up process according to claim 1, characterized in that: In step 2, the constraints include the minimum tip clearance of the high-pressure turbine, the minimum tip clearance of the high-pressure compressor, and the minimum acceptable value of the minimum thrust during takeoff.

4. The method for optimizing the aircraft engine warm-up process according to claim 1, characterized in that: The training samples in step 1 are obtained in the following way: 1) Determine the ground slow speed N idle And the maximum speed N allowed during the warm-up process max ; 2) Determine the maximum allowable warm-up time t max ; 3) Reduce the warm-up speed from N idle To N max Divide into a number of equal parts; 4) Change the warm-up time from 0-t max Divide into 5 equal parts; 5) Select any warm-up speed in 3) and any warm-up time in 4) as a combination, conduct tests or calculations, and obtain the corresponding high-pressure turbine minimum tip clearance, high-pressure compressor minimum tip clearance, minimum thrust during takeoff, and total fuel consumption during the entire engine history under different combinations.

5. A computer device comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that: When the processor executes the computer program, the steps of the method for optimizing the aircraft engine warm-up process as described in any one of claims 1 to 4 are implemented.

6. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for optimizing the aircraft engine warm-up process as claimed in any one of claims 1 to 4 are implemented.

Images