Rocket carrying capacity optimization method and device, electronic equipment and storage medium

Abstract

The application provides a rocket carrying capacity optimization method and device, electronic equipment and storage medium, relates to the technical field of carrying rocket, and includes the following steps: determining a plurality of target design parameters and the corresponding deviation of each target design parameter in the design parameters of a rocket to be optimized; taking each target design parameter as an optimization variable, determining a plurality of candidate design values corresponding to each target design parameter based on the corresponding deviation of each target design parameter; determining the optimal value of the carrying capacity parameter of the rocket to be optimized under each candidate design value corresponding to each target design parameter; and determining the influence function of each target design parameter on the carrying capacity parameter of the rocket to be optimized based on the optimal value of the carrying capacity parameter under each candidate design value corresponding to each target design parameter and the corresponding deviation of each target design parameter. The method and device provided by the application improve the optimization efficiency of the rocket carrying capacity design scheme.

Description

Technical Field

[0001] The present application relates to the field of launch vehicle technology, and in particular to a method, device, electronic equipment and storage medium for optimizing rocket carrying capacity. Background Art

[0002] Launch vehicle performance is widely used in space transportation, and its carrying capacity is a key indicator for evaluating its performance. For rockets with numerous subsystems and complex structures, especially multi-stage rockets, carrying capacity is not solely influenced by factors. When optimizing and upgrading launch vehicle designs to achieve greater carrying capacity, selecting optimization targets or design parameters has attracted considerable attention from designers.

[0003] Related technologies involve developing a trajectory optimization program and performing trajectory optimization design based on different states of parameters related to payload capacity. This method calculates the change in payload capacity before and after each parameter change, compares and processes the results, and ultimately determines the degree of impact of each design parameter on payload capacity. This method requires optimizing different states, is computationally intensive and time-consuming, and also requires consideration of the convergence of the calculation process.

[0004] Therefore, how to quickly determine the impact of various design parameters on the rocket's carrying capacity and improve the optimization efficiency of the rocket's carrying capacity design scheme has become a technical problem that the industry urgently needs to solve. Summary of the Invention

[0005] The present application provides a rocket carrying capacity optimization method, device, electronic equipment and storage medium, which are used to solve the technical problem of how to quickly determine the influence of various design parameters on the rocket carrying capacity and improve the optimization efficiency of the rocket carrying capacity design scheme.

[0006] This application provides a method for optimizing rocket carrying capacity, comprising:

[0007] Determining multiple target design parameters and deviations corresponding to the target design parameters among the design parameters of the rocket to be optimized;

[0008] Taking each target design parameter as an optimization variable and based on the deviation corresponding to each target design parameter, determining a plurality of candidate design values ​​corresponding to each target design parameter;

[0009] Determining the optimal value of the carrying capacity parameter of the rocket to be optimized under each candidate design value corresponding to each target design parameter;

[0010] Based on the optimal value of the carrying capacity parameter under each candidate design value corresponding to each target design parameter, and the deviation corresponding to each target design parameter, the influence function of each target design parameter on the carrying capacity parameter of the rocket to be optimized is determined.

[0011] In some embodiments, determining a plurality of target design parameters and deviations corresponding to the target design parameters in the design parameters of the rocket to be optimized includes:

[0012] Determining the degree of influence of various design parameters on the rocket to be optimized;

[0013] Screening each design parameter based on the degree of influence to determine the multiple target design parameters;

[0014] Based on the design performance requirements of the rocket to be optimized, the deviations corresponding to the various target design parameters are determined.

[0015] In some embodiments, determining the optimal value of the carrying capacity parameter of the rocket to be optimized under each candidate design value corresponding to each target design parameter includes:

[0016] Determining an orbital entry velocity corresponding to a target orbit of the rocket to be optimized;

[0017] Based on any candidate design value corresponding to any target design parameter, updating the design parameters of the rocket to be optimized;

[0018] Determining the flight speed of the rocket to be optimized when entering the target orbit based on the updated design parameters;

[0019] When the flight speed is greater than or equal to the orbital entry speed, recording a calculated value of the carrying capacity parameter under any candidate design value corresponding to any target design parameter;

[0020] The maximum value of the calculated values ​​of the carrying capacity parameter under each candidate design value corresponding to any target design parameter is determined as the optimal value of the carrying capacity parameter under each candidate design value corresponding to any target design parameter.

[0021] In some embodiments, recording the calculated value of the carrying capacity parameter under any candidate design value corresponding to any target design parameter includes:

[0022] Determining a numerical optimization range of the carrying capacity parameter;

[0023] Traversing each candidate design value corresponding to any target design parameter, and determining a calculated value of the carrying capacity parameter under each candidate design value corresponding to any target design parameter;

[0024] In the case that the flight speed is greater than or equal to the entry orbit speed and the calculated value of the carrying capacity parameter is within the numerical optimization range, the calculated value of the carrying capacity parameter at each candidate design value corresponding to each target design parameter is recorded.

[0025] In some embodiments, the design parameters of the rocket to be optimized include a mass parameter and a power parameter.

[0026] The mass parameter includes structural mass, equipment mass, and propellant mass of the rocket to be optimized, and the power parameter includes engine thrust and engine specific impulse.

[0027] In some embodiments, determining the influence function of each target design parameter on the carrying capacity parameter of the rocket to be optimized based on the optimal value of the carrying capacity parameter at each candidate design value corresponding to each target design parameter and the deviation corresponding to each target design parameter comprises:

[0028] determining the optimal value of the carrying capacity parameter corresponding to the upper limit of the deviation of each target design parameter;

[0029] determining the optimal value of the carrying capacity parameter corresponding to the lower limit of the deviation of each target design parameter;

[0030] determining the influence function of each target design parameter on the carrying capacity parameter of the rocket to be optimized based on the optimal value of the carrying capacity parameter corresponding to the upper limit of the deviation and the optimal value of the carrying capacity parameter corresponding to the lower limit of the deviation.

[0031] In some embodiments, after determining the influence function of each target design parameter on the carrying capacity parameter of the rocket to be optimized based on the optimal value of the carrying capacity parameter at each candidate design value corresponding to each target design parameter and the deviation corresponding to each target design parameter, the method further comprises:

[0032] determining the target design parameter for optimizing the carrying capacity parameter of the rocket to be optimized based on the influence function of each target design parameter on the carrying capacity parameter of the rocket to be optimized.

[0033] The present application provides a rocket carrying capacity optimization device, comprising:

[0034] a parameter setting module configured to determine a plurality of target design parameters and a deviation corresponding to each target design parameter among design parameters of a rocket to be optimized;

[0035] a variable determination module configured to determine a plurality of candidate design values corresponding to each target design parameter based on the deviation corresponding to each target design parameter, with each target design parameter as an optimization variable;

[0036] An optimization calculation module is used to determine the optimal value of the carrying capacity parameter of the rocket to be optimized under each candidate design value corresponding to each target design parameter;

[0037] The function determination module is used to determine the influence function of each target design parameter on the carrying capacity parameter of the rocket to be optimized based on the optimal value of the carrying capacity parameter under each candidate design value corresponding to each target design parameter, and the deviation corresponding to each target design parameter.

[0038] The present application provides an electronic device, comprising 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 method for optimizing the rocket's carrying capacity is implemented.

[0039] The present application provides a non-transitory computer-readable storage medium having a computer program stored thereon, which implements the rocket carrying capacity optimization method when the computer program is executed by a processor.

[0040] The rocket carrying capacity optimization method, device, electronic device and storage medium provided in the present application determine multiple target design parameters and the deviations corresponding to each target design parameter in the design parameters of the rocket to be optimized; use each target design parameter as an optimization variable and, based on the deviations corresponding to each target design parameter, determine multiple candidate design values ​​corresponding to each target design parameter; determine the optimal value of the carrying capacity parameter of the rocket to be optimized under each candidate design value corresponding to each target design parameter; determine the influence function of each target design parameter on the carrying capacity parameter of the rocket to be optimized based on the optimal value of the carrying capacity parameter under each candidate design value corresponding to each target design parameter and the deviations corresponding to each target design parameter; since a numerical solution is used instead of an analytical solution, the calculation speed is greatly improved and the result error is small, and the degree of influence of each design parameter on the rocket carrying capacity can be quickly determined, and the optimization and upgrading of the rocket scheme can be effectively guided in the early design stage, the rapid iteration of the rocket scheme can be achieved, and the optimization efficiency of the rocket carrying capacity design scheme can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0042] In order to more clearly illustrate the technical solutions in the present application or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0043] Figure 1 This is one of the flow charts of the rocket carrying capacity optimization method provided in this application.

[0044] Figure 2 This is the second flow chart of the rocket carrying capacity optimization method provided in this application.

[0045] Figure 3 It is a structural schematic diagram of the rocket carrying capacity optimization device provided in this application.

[0046] Figure 4 It is a structural diagram of the electronic device provided in this application. DETAILED DESCRIPTION

[0047] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0048] It should be noted that the terms "first", "second" etc. in this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the application described herein can be implemented in a sequence other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, the process, method, system, product or equipment comprising a series of steps or units or modules is not necessarily limited to those steps or units or modules clearly listed, but may include other steps or units or modules that are not clearly listed or that are intrinsic to these processes, methods, products or equipment.

[0049] For launch vehicles of the same takeoff mass, a greater payload capacity indicates a better rocket design, resulting in greater efficiency and value. However, the payload capacity of a launch vehicle is influenced by multiple factors. Design parameters alone can be broadly categorized into mass and power parameters, such as structural mass, propellant mass, engine thrust, and engine specific impulse. Multi-stage rockets involve even more design parameters.

[0050] Related technologies use the partial derivatives of design parameters to determine the optimization direction for a rocket's payload capacity. The intuitive meaning of partial derivatives is the increase in payload capacity achieved by adjusting the design parameter by one unit (if the parameter has no units, it can be quantified as a percentage). This can be used to analyze the impact of deviations from the design parameter on payload capacity, indicate which design values ​​require strict control during the design and production process, and provide guidance for subsequent upgrades and optimizations of the rocket. Furthermore, the effects of these parameters are relatively independent within a certain range, so the partial derivatives of a single parameter can be used to algebraically analyze the impact of multiple parameters on payload capacity.

[0051] For example, for a four-stage rocket, the partial derivative of the propellant mass of the first-stage engine is 0.03kg / kg (kilogram / kilogram), which means that adding 100kg of propellant to the first-stage engine can only increase the carrying capacity by 3kg, while the partial derivative of the propellant mass of the fourth-stage engine is 0.5kg / kg, which means that adding 100kg of propellant to the fourth-stage engine can increase the carrying capacity by 50kg. Obviously, the carrying capacity improvement effect of adding propellant to the fourth stage is more obvious. Therefore, in production, the propellant dosage of the fourth stage must be strictly controlled to be no less than a certain value, or when the subsequent rocket plan is optimized, the propellant dosage design value of the fourth-stage engine can be changed to the existing value by increasing 100kg or even more to obtain a higher carrying capacity.

[0052] For launch vehicles, without considering the impact of flight plans, the carrying capacity can be written as a function of various design parameters, which can be expressed as:

[0053]

[0054] Where, is the carrying capacity parameter, is the carrying capacity calculation function, For the design parameters, .

[0055] Partial derivatives of design parameters, that is, carrying capacity calculation function First-order partial derivative with respect to the independent variable parameter Since the carrying capacity calculation function The specific functional relationship of is unclear, and it is difficult to find its analytical solution, especially in the early stage of launch vehicle design.

[0056] At the outset of a new rocket design demonstration, to guide overall design optimization and achieve rapid iteration, it's necessary to qualitatively and quantitatively reference the partial derivatives of key design parameters to iterate and optimize the overall design. In addition to referencing the plans and parameters of similar models and drawing on development experience from other models, it's crucial to be able to quickly and accurately calculate the partial derivatives of the payload capacity.

[0057] In order to solve the above technical problems, Figure 1 This is one of the flow charts of the rocket carrying capacity optimization method provided by this application, such as Figure 1 As shown, the method includes step 110 , step 120 , step 130 and step 140 .

[0058] Step 110: Determine multiple target design parameters and deviations corresponding to the target design parameters among the design parameters of the rocket to be optimized.

[0059] Specifically, the rocket carrying capacity optimization method provided in the embodiments of the present application is implemented by a rocket carrying capacity optimization device. This device can be implemented through software, such as a rocket carrying capacity optimization program running on a computer, or through hardware, such as a computer or server that executes the rocket carrying capacity optimization method.

[0060] The application scenario of the rocket carrying capacity optimization method provided in the embodiments of this application is to guide the optimization and upgrading of rocket design schemes in the early stages of launch vehicle design, thereby achieving rapid iteration of rocket design schemes. Launch vehicles are rockets that transport various manufactured spacecraft into space. The rocket to be optimized is the launch vehicle whose carrying capacity is being optimized.

[0061] Design parameters refer to the key indicators and characteristics determined during the rocket design and manufacturing process. They can include thrust, payload capacity, orbital parameters, launch weight, fuel type, thrust-to-weight ratio, structural characteristics, flight performance, etc. Design parameters are also called overall parameters.

[0062] Target design parameters are those that launch vehicle designers are most concerned about, or those that have a significant impact on launch capacity. Target design parameters can be determined by screening among the design parameters based on actual needs.

[0063] Deviation refers to the difference between the actual measured value and the designed value of a design parameter during the rocket design, manufacturing, or testing process. Design parameters are generally given within a range of ± the design value. For example, the engine structural mass requirement is 2000kg ± 50kg, where ±50kg is the allowable deviation from the design value. If the actual product exceeds this range, it will be deemed unqualified and rejected for use in rocket assembly. Within this range, the impact of the deviation can be determined using partial derivatives, allowing for impact assessment.

[0064] Step 120 : Taking each target design parameter as an optimization variable and based on the deviation corresponding to each target design parameter, determine a plurality of candidate design values ​​corresponding to each target design parameter.

[0065] Specifically, optimization variables are parameters or variables that need to be adjusted during the optimization process, with the goal of maximizing or minimizing the objective function within certain constraints. Optimization calculations can be performed using the target design parameters as optimization variables and the rocket's payload capacity parameters as the objective function. The payload capacity parameters characterize the rocket's carrying capacity and directly influence how much payload the rocket can deliver into a predetermined orbit or space target.

[0066] Based on the deviations corresponding to the target design parameters, multiple candidate design values ​​corresponding to the target design parameters can be determined. For example, the design values ​​of the target design parameters are taken as the median values, and the numerical fluctuation range of the target design parameters is determined based on the deviations. Each value within the numerical fluctuation range is determined as a candidate design value.

[0067] Step 130: Determine the optimal value of the carrying capacity parameter of the rocket to be optimized under each candidate design value corresponding to each target design parameter.

[0068] Specifically, under each candidate design value corresponding to each target design parameter, the calculated value of the carrying capacity parameter under each candidate design value corresponding to each target design parameter can be obtained through the calculation method in the relevant technology.

[0069] Since the carrying capacity parameter varies with different candidate design values ​​corresponding to the target design parameters and there is also a numerical optimization range, multiple calculations can be performed to obtain the optimal value of the carrying capacity parameter under each candidate design value corresponding to each target design parameter.

[0070] It is understandable that the larger the carrying capacity parameter is, the better the rocket's carrying capacity is. Therefore, the optimal value of the carrying capacity parameter is the maximum value of the carrying capacity parameter.

[0071] Step 140: Based on the optimal value of the carrying capacity parameter under each candidate design value corresponding to each target design parameter, and the deviation corresponding to each target design parameter, determine the influence function of each target design parameter on the carrying capacity parameter of the rocket to be optimized.

[0072] Specifically, the influence function of each target design parameter on the launch capacity parameter of the rocket to be optimized is used to represent the degree of influence of each target design parameter on the launch capacity parameter. The influence function can be determined by taking the change in the launch capacity parameter as the dividend and the change in the target design parameter as the divisor. It can be understood that the larger the value of the influence function, the greater the influence of the corresponding target design parameter on the launch capacity parameter.

[0073] Since the specific functional relationship of the carrying capacity calculation function is unclear and difficult to find its analytical solution, a numerical solution can be used instead of its analytical solution for analysis in engineering. According to the formula of the second-order central difference method, when the second-order truncation error is not considered, the function value of the partial derivative of the carrying capacity parameter with respect to the target design parameter can be simplified to the ratio of the deviation between the carrying capacity parameter and the target design parameter. In other words, the influence function of the target design parameter on the carrying capacity parameter can be used to approximate the partial derivative of the carrying capacity parameter with respect to the target design parameter, which can be expressed as follows:

[0074]

[0075] Where, is the partial derivative of the carrying capacity parameter with respect to the target design parameter, It is the influence function of target design parameters on carrying capacity parameters.

[0076] The rocket carrying capacity optimization method provided in the embodiment of the present application determines multiple target design parameters and the deviations corresponding to each target design parameter in the design parameters of the rocket to be optimized; uses each target design parameter as an optimization variable and, based on the deviations corresponding to each target design parameter, determines multiple candidate design values ​​corresponding to each target design parameter; determines the optimal value of the carrying capacity parameter of the rocket to be optimized under each candidate design value corresponding to each target design parameter; determines the influence function of each target design parameter on the carrying capacity parameter of the rocket to be optimized based on the optimal value of the carrying capacity parameter under each candidate design value corresponding to each target design parameter and the deviations corresponding to each target design parameter; since a numerical solution is used instead of an analytical solution, the calculation speed is greatly improved and the result error is small, and the degree of influence of each design parameter on the rocket carrying capacity can be quickly determined, and the optimization and upgrading of the rocket scheme can be effectively guided in the early design stage, and the rapid iteration of the rocket scheme can be achieved, thereby improving the optimization efficiency of the rocket carrying capacity design scheme.

[0077] It should be noted that each embodiment of the present application can be freely combined, changed in order or executed alone, and does not need to rely on or depend on a fixed execution order.

[0078] In some embodiments, a plurality of target design parameters are determined among the design parameters of the rocket to be optimized, and a deviation corresponding to each target design parameter includes:

[0079] The influence degree of each design parameter on the rocket to be optimized is determined;

[0080] Each design parameter is screened based on the influence degree to determine a plurality of target design parameters;

[0081] The deviation corresponding to each target design parameter is determined based on the design performance requirement of the rocket to be optimized.

[0082] Among them, the design parameters of the rocket to be optimized include mass parameters and power parameters; the mass parameters include the structural mass, equipment mass and propellant mass of the rocket to be optimized; the power parameters include engine thrust and engine specific impulse.

[0083] Specifically, the design parameters of the rocket to be optimized can include at least two categories of parameters: mass parameters and power parameters.

[0084] The mass parameter refers to the parameter related to the mass of the rocket, which can include structural mass, equipment mass and propellant mass, etc. The structural mass refers to the mass of the structural components of the rocket itself, including the fuselage, cabin, support structure, tail nozzle, etc. The equipment mass refers to the mass of all equipment and systems on the rocket, including navigation systems, communication equipment, control systems, sensors, etc. The propellant mass refers to the mass of the fuel and oxidizer used in the rocket engine, including liquid fuel, solid fuel, etc.

[0085] The power parameter refers to the parameter related to the power of the rocket, which can include engine thrust and engine specific impulse, etc. The engine thrust refers to the upward force generated by the engine. The engine specific impulse refers to an index that measures the efficiency of the engine, usually in seconds, representing the thrust per unit of fuel.

[0086] The influence degree of each design parameter on the rocket to be optimized can be determined first, that is, the importance of each design parameter to the rocket or the degree of attention of the designer. For example, the influence of each design parameter (such as thrust, specific impulse, structural mass, equipment mass, etc.) on the performance of the rocket can be determined according to the dynamics and thermodynamics model of the rocket; or the importance of the design parameter is evaluated in combination with experience and expert knowledge to determine which parameter is more critical in a specific situation.

[0087] According to the influence degree, each design parameter is screened to determine a plurality of target design parameters. The target design parameters are usually main design parameters. According to the design performance requirements of the rocket to be optimized, the deviation corresponding to each target design parameter can be determined.

[0088] The design performance requirement is a performance index and capability required by the rocket to achieve a flight task, such as thrust, specific impulse, payload capacity, flight trajectory and precision, reliability, structural strength and mass, etc.

[0089] According to the design performance requirement, the deviation corresponding to each target design parameter can be determined. The target design parameter is generally given according to the design value ± the allowable deviation range. For example, the engine structure mass requirement is 2000kg ± 50kg, 2000kg is the design value, and ± 50kg is the allowable deviation.

[0090] The rocket carrying capacity optimization method provided by the embodiment of the application can effectively determine the main design parameters, effectively guide the optimization and upgrading of the rocket scheme in the early design stage, and realize the rapid iteration of the rocket scheme.

[0091] In some embodiments, determining the optimal value of the carrying capacity parameter of the rocket to be optimized under each candidate design value corresponding to each target design parameter comprises:

[0092] Determining the entry orbit speed corresponding to the target orbit of the rocket to be optimized;

[0093] Updating the design parameters of the rocket to be optimized based on any candidate design value corresponding to any target design parameter;

[0094] Determining the flight speed of the rocket to be optimized entering the target orbit based on the updated design parameters;

[0095] In the case where the flight speed is greater than or equal to the entry orbit speed, recording the calculated value of the carrying capacity parameter under any candidate design value corresponding to any target design parameter;

[0096] Determining the maximum value of the calculated value of the carrying capacity parameter under each candidate design value corresponding to any target design parameter as the optimal value of the carrying capacity parameter under each candidate design value corresponding to any target design parameter.

[0097] Specifically, the target orbit refers to the ideal or designed orbit for the rocket to be optimized to perform its mission. The orbital velocity refers to the speed the rocket needs to reach the predetermined orbit. Meeting the target orbit requirement means the rocket is able to operate within that orbit. Simply put, it requires the rocket to have a corresponding speed at the target orbital altitude. Altitude represents potential energy, while speed represents kinetic energy. Since different forms of energy are convertible, potential energy can be converted into corresponding kinetic energy, or speed. In this way, the orbital entry condition satisfies the total energy requirement (potential energy + kinetic energy), which can ultimately be converted into a speed requirement.

[0098] The required speed for different orbits may vary, and the orbital insertion speed is affected by the orbital altitude and mission type. The orbital parameters of the target orbit can be used to determine the corresponding orbital insertion speed of the rocket to be optimized.

[0099] Any target design parameter is selected from multiple target design parameters as an optimization variable in the current optimization calculation, and any candidate design value is selected within a numerical fluctuation range determined by the target design parameter and its deviation.

[0100] Based on any candidate design value corresponding to any target design parameter, the design parameters of the rocket to be optimized are updated. This step is performed mainly because the various design parameters are interdependent or mutually influential. When the value of any target design parameter is determined to be any candidate design value, the related design parameters need to be updated simultaneously.

[0101] According to the updated design parameters, the flight speed of the rocket to be optimized when entering the target orbit can be calculated based on relevant theories, such as the Tsiolkovsky formula, combined with engineering experience, when the design parameters are updated.

[0102] For example, the Tsiolkovsky formula is:

[0103]

[0104] in, For consumption ( ) is the maximum speed increase that a rocket can theoretically achieve, or the theoretical speed increase; is the engine specific impulse; is the total mass of the rocket when the engine is ignited; is the total mass of the rocket when the engine is shut down.

[0105] This formula gives the theoretical growth rate, but in actual flight, the rocket is negatively affected by atmospheric resistance, the earth's gravity, etc. (the above forces all do negative work), and the actual growth rate cannot reach the theoretical growth rate, which is called speed loss. The proportion of this speed loss to the theoretical growth rate is Although it varies depending on the design of the rocket, a reasonable range can be given based on the analysis results of mathematical simulation or actual flight data (a specific value can be taken during calculation), so that a rocket growth rate that is closer to the actual value can be obtained. , or actual growth rate, .

[0106] When the flight speed is greater than or equal to the orbital insertion speed, it means that after optimizing the design parameters by any candidate design value corresponding to any target design parameter, the designed flight speed meets the speed requirement for orbital insertion, and the carrying capacity parameter can be calculated, and the calculated value of the carrying capacity parameter under any candidate design value corresponding to any target design parameter is recorded; if it does not meet the requirement, it may not be recorded.

[0107] There may be multiple calculated values ​​of the carrying capacity parameter under each candidate design value corresponding to any target design parameter. The maximum value of these calculated values ​​can be determined as the optimal value of the carrying capacity parameter under each candidate design value corresponding to any target design parameter.

[0108] The rocket carrying capacity optimization method provided in the embodiment of the present application updates the design parameters and compares the flight speed of the rocket to be optimized when entering the target orbit with the orbital insertion speed. From the energy perspective, the calculation results meet the rocket orbit insertion requirements. Compared with the partial derivative calculation in the related technology, it does not need to consider the convergence of the optimization, greatly improves the calculation speed and has a small result error, and can quickly determine the degree of influence of each design parameter on the rocket carrying capacity.

[0109] In some embodiments, recording a calculated value of a carrying capacity parameter under any candidate design value corresponding to any target design parameter includes:

[0110] Determine the numerical optimization range of the carrying capacity parameters;

[0111] Traversing each candidate design value corresponding to any target design parameter, and determining a calculated value of the carrying capacity parameter under each candidate design value corresponding to any target design parameter;

[0112] When the flight speed is greater than or equal to the orbital insertion speed and the calculated value of the carrying capacity parameter is within the numerical optimization range, the calculated value of the carrying capacity parameter under each candidate design value corresponding to any target design parameter is recorded.

[0113] Specifically, in the design scheme of the rocket to be optimized, the carrying capacity parameters may also have a numerical optimization range.

[0114] Each candidate design value corresponding to any target design parameter is traversed, and the calculated value corresponding to the carrying capacity parameter when each candidate design value is selected for any target design parameter is calculated.

[0115] If the flight speed is greater than or equal to the orbital entry speed and the calculated value of the carrying capacity parameter is within the numerical optimization range, the calculated value of the carrying capacity parameter under each candidate design value corresponding to any target design parameter can be recorded.

[0116] The rocket carrying capacity optimization method provided in the embodiment of the present application, from the energy perspective, the calculation results meet the requirements for rocket orbit entry. Compared with the partial derivative calculation in the related technology, it does not need to consider the convergence of the optimization, greatly improves the calculation speed and has a smaller result error.

[0117] In some embodiments, based on the optimal value of the carrying capacity parameter under each candidate design value corresponding to each target design parameter and the deviation corresponding to each target design parameter, determining the influence function of each target design parameter on the carrying capacity parameter of the rocket to be optimized includes:

[0118] Determine the optimal value of the carrying capacity parameter corresponding to the upper limit of the deviation corresponding to each target design parameter;

[0119] Determine the optimal value of the carrying capacity parameter corresponding to the lower limit of the deviation corresponding to each target design parameter;

[0120] Based on the optimal value of the carrying capacity parameter corresponding to the upper limit of the deviation and the optimal value of the carrying capacity parameter corresponding to the lower limit of the deviation, the influence function of each target design parameter on the carrying capacity parameter of the rocket to be optimized is determined.

[0121] Specifically, taking any target design parameter as an example, the method in the above embodiment can be used to determine the optimal value of the carrying capacity parameter corresponding to the upper limit of the deviation corresponding to the target design parameter, as well as the optimal value of the carrying capacity parameter corresponding to the lower limit of the deviation corresponding to the target design parameter.

[0122] Based on the optimal value of the payload capacity parameter corresponding to the upper deviation limit and the optimal value of the payload capacity parameter corresponding to the lower deviation limit, the influence function of the target design parameter on the payload capacity parameter of the rocket to be optimized is calculated. For example, the ratio of the difference between the optimal value and the difference between the upper and lower deviation limits is determined as the influence coefficient. The change in the payload capacity parameter can be obtained by multiplying this influence coefficient by the change in the target design parameter. By expressing the change in the payload capacity parameter, the change in the target design parameter, and the influence coefficient through a functional relationship, the influence function can be obtained.

[0123] According to the above method, the influence function of each target design parameter on the carrying capacity parameter of the rocket to be optimized can be obtained.

[0124] The rocket carrying capacity optimization method provided in the embodiment of the present application determines the influence function of each target design parameter on the carrying capacity parameter of the rocket to be optimized based on the optimal value of the carrying capacity parameter under each candidate design value corresponding to each target design parameter, and the deviation corresponding to each target design parameter. It can quickly determine the degree of influence of each design parameter on the rocket carrying capacity, realize rapid iteration of the rocket plan, and improve the optimization efficiency of the rocket carrying capacity design plan.

[0125] In some embodiments, after determining the influence function of each target design parameter on the launch capacity parameter of the rocket to be optimized based on the optimal value of the launch capacity parameter under each candidate design value corresponding to each target design parameter and the deviation corresponding to each target design parameter, the method further includes:

[0126] Based on the influence function of each target design parameter on the carrying capacity parameter of the rocket to be optimized, the target design parameter for optimizing the carrying capacity parameter of the rocket to be optimized is determined.

[0127] Specifically, the target design parameters to be optimized can be determined from the influence functions of the target design parameters on the rocket's carrying capacity parameters. For example, the target design parameters that have a greater impact on the carrying capacity parameters can be determined based on the influence functions, and these target design parameters can be used as optimization directions.

[0128] The rocket carrying capacity optimization method provided in the embodiment of the present application determines the target design parameters for optimizing the carrying capacity parameters of the rocket to be optimized based on the influence function, can quickly determine the degree of influence of each design parameter on the rocket carrying capacity, realize rapid iteration of the rocket plan, and improve the optimization efficiency of the rocket carrying capacity design plan.

[0129] Figure 2 This is the second flow chart of the rocket carrying capacity optimization method provided by this application, such as Figure 2 As shown, the method includes:

[0130] Step 210: Parameter status setting

[0131] Determine the design parameters of the rocket (including the design load) and the deviation of the main design parameters, and update the design parameters taking the given value of any main design parameter as an example.

[0132] Step 220: Optimize carrying capacity

[0133] According to the Tsiolkovsky formula and combined with engineering experience, the flight speed of the rocket at the moment of entering orbit under the new design parameters is estimated.

[0134] Compare the rocket's flight speed with the speed requirement of the target orbit: if the speed requirement for orbital entry is met, record the value of the optimized variable at this time; if the speed requirement for orbital entry is not met, do not record the value.

[0135] According to the optimization range of the carrying capacity, the values ​​of the optimization variables are gradually updated, and the above calculation steps are repeated. When the values ​​of the optimization variables exceed the optimization range, the calculation is stopped.

[0136] The maximum value of all recorded values ​​is selected as the optimal carrying capacity under the influence of this deviation.

[0137] Step 230: Calculate the numerical solution of partial derivatives

[0138] According to the optimal carrying capacity value corresponding to the upper (lower) deviation, the numerical solution of the partial derivative of the carrying capacity of this main design parameter is calculated.

[0139] If you need to calculate the partial derivatives of the carrying capacity of other design parameters, just repeat all the above steps.

[0140] Taking a certain four-stage rocket as an example, calculating the partial derivatives of the carrying capacity of the mass of each stage of the launch vehicle structure requires calculating a total of eight states (upper and lower deviations). Using the ballistic program optimization method for calculation, the calculation time for each optimized state is measured in minutes. Using the method provided in this application, the total calculation time for the entire process is less than 2 seconds, greatly improving the calculation speed. Comparing the calculation results with the ballistic program optimization calculation results (which are assumed to be the true values), the maximum calculation error of the partial derivatives of the mass carrying capacity of each stage of the rocket structure does not exceed 22%. The accuracy of this result is fully sufficient for use in engineering applications and the early stages of scheme design.

[0141] The device provided in the embodiment of the present application is described below. The device described below and the method described above can be referenced to each other.

[0142] Figure 3 This is a schematic diagram of the structure of the rocket carrying capacity optimization device provided by this application. Figure 3 As shown, the device includes:

[0143] A parameter setting module 310 is used to determine a plurality of target design parameters and deviations corresponding to the target design parameters in the design parameters of the rocket to be optimized;

[0144] A variable determination module 320 is configured to use each target design parameter as an optimization variable and determine a plurality of candidate design values ​​corresponding to each target design parameter based on the deviation corresponding to each target design parameter;

[0145] The optimization calculation module 330 is configured to determine an optimal value of the payload capacity parameter of the rocket to be optimized at each candidate design value corresponding to each target design parameter;

[0146] The function determination module 340 is configured to determine an influence function of each target design parameter on the payload capacity parameter of the rocket to be optimized based on the optimal value of the payload capacity parameter of the rocket to be optimized at each candidate design value corresponding to each target design parameter and the deviation corresponding to each target design parameter.

[0147] The rocket payload capacity optimization device provided by the embodiments of the present application determines a plurality of target design parameters and a deviation corresponding to each target design parameter among the design parameters of the rocket to be optimized; determines a plurality of candidate design values corresponding to each target design parameter based on the deviation corresponding to each target design parameter, with each target design parameter as an optimization variable; determines an optimal value of the payload capacity parameter of the rocket to be optimized at each candidate design value corresponding to each target design parameter; and determines an influence function of each target design parameter on the payload capacity parameter of the rocket to be optimized based on the optimal value of the payload capacity parameter of the rocket to be optimized at each candidate design value corresponding to each target design parameter and the deviation corresponding to each target design parameter. Since the numerical solution is used instead of the analytical solution, the calculation speed is greatly improved and the result error is small, the influence degree of each design parameter on the rocket payload capacity can be quickly determined, the optimization and upgrading of the rocket scheme can be effectively guided in the early design stage, the rapid iteration of the rocket scheme is realized, and the optimization efficiency of the rocket payload capacity design scheme is improved.

[0148] In some embodiments, the parameter setting module is configured to:

[0149] determine the influence degree of each design parameter on the rocket to be optimized;

[0150] screen each design parameter based on the influence degree to determine a plurality of target design parameters;

[0151] determine the deviation corresponding to each target design parameter based on the design performance requirement of the rocket to be optimized.

[0152] In some embodiments, the optimization calculation module is configured to:

[0153] determine an entry orbit speed corresponding to a target orbit of the rocket to be optimized;

[0154] update the design parameters of the rocket to be optimized based on any candidate design value corresponding to any target design parameter;

[0155] determine a flight speed of the rocket to be optimized for entering the target orbit based on the updated design parameters;

[0156] When the flight speed is greater than or equal to the orbital insertion speed, record the calculated value of the carrying capacity parameter under any candidate design value corresponding to any target design parameter;

[0157] The maximum value of the calculated values ​​of the carrying capacity parameter under each candidate design value corresponding to any target design parameter is determined as the optimal value of the carrying capacity parameter under each candidate design value corresponding to any target design parameter.

[0158] In some embodiments, the optimization calculation module is used to:

[0159] Determine the numerical optimization range of the carrying capacity parameters;

[0160] Traversing each candidate design value corresponding to any target design parameter, and determining a calculated value of the carrying capacity parameter under each candidate design value corresponding to any target design parameter;

[0161] When the flight speed is greater than or equal to the orbital insertion speed and the calculated value of the carrying capacity parameter is within the numerical optimization range, the calculated value of the carrying capacity parameter under each candidate design value corresponding to any target design parameter is recorded.

[0162] In some embodiments, the design parameters of the rocket to be optimized include mass parameters and power parameters;

[0163] The mass parameters include the structural mass, equipment mass and propellant mass of the rocket to be optimized; the power parameters include engine thrust and engine specific impulse.

[0164] In some embodiments, the function determination module is configured to:

[0165] Determine the optimal value of the carrying capacity parameter corresponding to the upper limit of the deviation corresponding to each target design parameter;

[0166] Determine the optimal value of the carrying capacity parameter corresponding to the lower limit of the deviation corresponding to each target design parameter;

[0167] Based on the optimal value of the carrying capacity parameter corresponding to the upper limit of the deviation and the optimal value of the carrying capacity parameter corresponding to the lower limit of the deviation, the influence function of each target design parameter on the carrying capacity parameter of the rocket to be optimized is determined.

[0168] In some embodiments, the device is further configured to:

[0169] Based on the influence function of each target design parameter on the carrying capacity parameter of the rocket to be optimized, the target design parameter for optimizing the carrying capacity parameter of the rocket to be optimized is determined.

[0170] Figure 4 This is a schematic diagram of the structure of the electronic device provided by this application. Figure 4As shown, the electronic device may include: a processor (Processor) 410, a communication interface (Communications Interface) 420, a memory (Memory) 430 and a communication bus (Communications Bus) 440, wherein the processor 410, the communication interface 420, and the memory 430 communicate with each other via the communication bus 440. The processor 410 may call the logic commands in the memory 430 to execute the method described in the above embodiments, for example:

[0171] Determine multiple target design parameters and deviations corresponding to each target design parameter in the design parameters of the rocket to be optimized; take each target design parameter as an optimization variable, and determine multiple candidate design values ​​corresponding to each target design parameter based on the deviations corresponding to each target design parameter; determine the optimal value of the carrying capacity parameter of the rocket to be optimized under each candidate design value corresponding to each target design parameter; based on the optimal value of the carrying capacity parameter under each candidate design value corresponding to each target design parameter, and the deviations corresponding to each target design parameter, determine the influence function of each target design parameter on the carrying capacity parameter of the rocket to be optimized.

[0172] In addition, the logical commands in the above-mentioned memory can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present application, or the part that contributes to the existing technology, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several commands to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program code.

[0173] The processor in the electronic device provided in the embodiment of the present application can call the logic instructions in the memory to implement the above method. Its specific implementation method is consistent with the implementation method of the aforementioned method and can achieve the same beneficial effects, which will not be repeated here.

[0174] An embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method provided in the above embodiments is executed.

[0175] The specific implementation is consistent with the foregoing method implementation, and the same beneficial effects can be achieved, which will not be repeated here.

[0176] The embodiment of the application provides a computer program product, comprising a computer program, and the computer program is executed by a processor to realize the method.

[0177] The device embodiments described above are only schematic, wherein the units described as separated components can or can not be physically separated, and the components displayed as units can or can not be physical units, that is, they can be located in one place, or can be distributed on a plurality of network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiment scheme. Those skilled in the art can understand and implement without creative labor.

[0178] Through the description of the foregoing embodiments, those skilled in the art can clearly understand that each embodiment can be realized by means of software and the necessary general hardware platform, and of course, can also be realized by hardware. Based on such understanding, the foregoing technical solutions can be embodied in the form of a software product in essence or in the form of a contribution to the prior art. The computer software product can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, and the like, and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the method described in each embodiment or some parts of the embodiment.

[0179] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the application, and not to limit them; although the application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for some technical features; and these modifications or replacements do not make the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the application.

Claims

1. A method for optimizing rocket carrying capacity, characterized in that: include: Determining multiple target design parameters and deviations corresponding to the target design parameters among the design parameters of the rocket to be optimized; Taking each target design parameter as an optimization variable and based on the deviation corresponding to each target design parameter, determining a plurality of candidate design values ​​corresponding to each target design parameter; Determining the optimal value of the carrying capacity parameter of the rocket to be optimized under each candidate design value corresponding to each target design parameter; Determining, based on the optimal value of the carrying capacity parameter under each candidate design value corresponding to each target design parameter, and the deviation corresponding to each target design parameter, an influence function of each target design parameter on the carrying capacity parameter of the rocket to be optimized; The determining, based on the optimal value of the carrying capacity parameter under each candidate design value corresponding to each target design parameter and the deviation corresponding to each target design parameter, an influence function of each target design parameter on the carrying capacity parameter of the rocket to be optimized includes: Determining the optimal value of the carrying capacity parameter corresponding to the upper limit of the deviation corresponding to each target design parameter; Determining the optimal value of the carrying capacity parameter corresponding to the lower limit of the deviation corresponding to each target design parameter; Determining the influence function of each target design parameter on the carrying capacity parameter of the rocket to be optimized based on the optimal value of the carrying capacity parameter corresponding to the upper deviation limit and the optimal value of the carrying capacity parameter corresponding to the lower deviation limit; The design parameters of the rocket to be optimized include mass parameters and power parameters; The mass parameters include the structural mass, equipment mass and propellant mass of the rocket to be optimized; the power parameters include engine thrust and engine specific impulse.

2. The method for optimizing rocket carrying capacity according to claim 1, characterized in that: Determining a plurality of target design parameters and deviations corresponding to the target design parameters in the design parameters of the rocket to be optimized includes: Determining the degree of influence of various design parameters on the rocket to be optimized; Screening each design parameter based on the degree of influence to determine the multiple target design parameters; Based on the design performance requirements of the rocket to be optimized, the deviations corresponding to the various target design parameters are determined.

3. The method for optimizing rocket carrying capacity according to claim 1, wherein: Determining the optimal value of the carrying capacity parameter of the rocket to be optimized under each candidate design value corresponding to each target design parameter includes: Determining an orbital entry velocity corresponding to a target orbit of the rocket to be optimized; Based on any candidate design value corresponding to any target design parameter, updating the design parameters of the rocket to be optimized; Determining the flight speed of the rocket to be optimized when entering the target orbit based on the updated design parameters; When the flight speed is greater than or equal to the orbital entry speed, recording a calculated value of the carrying capacity parameter under any candidate design value corresponding to any target design parameter; The maximum value of the calculated values ​​of the carrying capacity parameter under each candidate design value corresponding to any target design parameter is determined as the optimal value of the carrying capacity parameter under each candidate design value corresponding to any target design parameter.

4. The method for optimizing rocket carrying capacity according to claim 3, characterized in that: The recording of the calculated value of the carrying capacity parameter under any candidate design value corresponding to any target design parameter includes: Determining a numerical optimization range of the carrying capacity parameter; Traversing each candidate design value corresponding to any target design parameter, and determining a calculated value of the carrying capacity parameter under each candidate design value corresponding to any target design parameter; When the flight speed is greater than or equal to the orbital entry speed and the calculated value of the carrying capacity parameter is within the numerical optimization range, the calculated value of the carrying capacity parameter under each candidate design value corresponding to any target design parameter is recorded.

5. The method for optimizing rocket carrying capacity according to any one of claims 1 to 4, characterized in that: After determining the influence function of each target design parameter on the carrying capacity parameter of the rocket to be optimized based on the optimal value of the carrying capacity parameter under each candidate design value corresponding to each target design parameter and the deviation corresponding to each target design parameter, the method further includes: Based on the influence function of each target design parameter on the carrying capacity parameter of the rocket to be optimized, the target design parameters for optimizing the carrying capacity parameter of the rocket to be optimized are determined.

6. A rocket carrying capacity optimization device, characterized in that: include: A parameter setting module is used to determine multiple target design parameters and deviations corresponding to each target design parameter in the design parameters of the rocket to be optimized; a variable determination module, configured to use each target design parameter as an optimization variable and determine a plurality of candidate design values ​​corresponding to each target design parameter based on deviations corresponding to each target design parameter; An optimization calculation module is used to determine the optimal value of the carrying capacity parameter of the rocket to be optimized under each candidate design value corresponding to each target design parameter; a function determination module for determining an influence function of each target design parameter on the carrying capacity parameter of the rocket to be optimized based on the optimal value of the carrying capacity parameter under each candidate design value corresponding to each target design parameter and the deviation corresponding to each target design parameter; The function determination module is used to: Determining the optimal value of the carrying capacity parameter corresponding to the upper limit of the deviation corresponding to each target design parameter; Determining the optimal value of the carrying capacity parameter corresponding to the lower limit of the deviation corresponding to each target design parameter; Determining the influence function of each target design parameter on the carrying capacity parameter of the rocket to be optimized based on the optimal value of the carrying capacity parameter corresponding to the upper deviation limit and the optimal value of the carrying capacity parameter corresponding to the lower deviation limit; The design parameters of the rocket to be optimized include mass parameters and power parameters; The mass parameters include the structural mass, equipment mass and propellant mass of the rocket to be optimized; the power parameters include engine thrust and engine specific impulse.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the rocket carrying capacity optimization method described in any one of claims 1 to 5 is implemented.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the rocket carrying capacity optimization method described in any one of claims 1 to 5 is implemented.

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