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

Abstract

The invention provides a rocket carrying capacity optimization method and device, electronic equipment and a storage medium, and relates to the technical field of carrier rockets, and the method comprises the steps: determining a plurality of target design parameters in the design parameters of a to-be-optimized rocket, and the deviation corresponding to each target design parameter; taking each target design parameter as an optimization variable, and determining a plurality of candidate design values corresponding to each target design parameter based on the deviation 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; and 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. According to the method and the device provided by the invention, the optimization efficiency of a rocket carrying capacity design scheme is improved.

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] As a widely used space transportation tool, launch vehicles have an important performance indicator including carrying capacity. For rockets with many subsystems and complex structures, especially multi-stage rockets, the factors that affect their carrying capacity are not unique. When optimizing and upgrading the design of launch vehicles in pursuit of greater carrying capacity, how to choose the optimization direction or design parameters has attracted great attention from designers.

[0003] Related technologies write trajectory optimization programs and perform trajectory optimization design according to different states of parameters related to carrying capacity, obtain the changes in carrying capacity before and after the changes in various parameters, and compare and process the results to ultimately determine the degree of influence of each design parameter on the carrying capacity. This method requires optimization of different states, has a large amount of calculations, is time-consuming, and also needs to consider 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 device 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] The present application provides a method for optimizing rocket carrying capacity, comprising: Determine a plurality of target design parameters and deviations corresponding to the respective target design parameters in 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; 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.

[0007] In some embodiments, the step of determining a plurality of target design parameters and deviations corresponding to the respective 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 influence degree 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.

[0008] 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: Determine the orbital velocity corresponding to the 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; Based on the updated design parameters, determining the flight speed of the rocket to be optimized when entering the target orbit; 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 among 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.

[0009] In some embodiments, recording 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 one of the target design parameters, and determining a calculated value of the carrying capacity parameter under each candidate design value corresponding to any one of the target design parameters; 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.

[0010] In some embodiments, 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.

[0011] 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 under each candidate design value corresponding to each target design parameter and the deviation corresponding to each target design parameter includes: Determine the optimal value of the carrying capacity parameter corresponding to the upper limit of the deviation corresponding to each target design parameter; Determine the optimal value of the carrying capacity parameter corresponding to the lower limit of the deviation corresponding to each target design parameter; 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.

[0012] 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 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 parameter for optimizing the carrying capacity parameter of the rocket to be optimized is determined.

[0013] The present application provides a rocket carrying capacity optimization device, comprising: A parameter setting module, used to determine a plurality of 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, used to determine a plurality of candidate design values ​​corresponding to each target design parameter based on the deviation corresponding to each target design parameter, taking each target design parameter as an optimization variable; An optimization calculation module, 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; 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.

[0014] The present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method for optimizing the rocket's carrying capacity when executing the computer program.

[0015] The present application provides a non-transitory computer-readable storage medium having a computer program stored thereon, and the computer program, when executed by a processor, implements the method for optimizing the rocket's carrying capacity.

[0016] The rocket carrying capacity optimization method, device, electronic device and storage medium provided in the present application determine multiple target design parameters and 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 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; 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; because a numerical solution is used instead of an analytical solution, the calculation speed is greatly improved and the result error is small, so the influence degree of each design parameter on the rocket carrying capacity can be quickly determined, and the optimization and upgrading of the rocket plan can be effectively guided in the early design stage, and the rapid iteration of the rocket plan can be realized, thereby improving the optimization efficiency of the rocket carrying capacity design plan. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] 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.

[0018] In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 paying any creative work.

[0019] Figure 1 This is one of the flow charts of the rocket carrying capacity optimization method provided in this application.

[0020] Figure 2 This is the second flow chart of the rocket carrying capacity optimization method provided in this application.

[0021] Figure 3 It is a structural schematic diagram of the rocket carrying capacity optimization device provided in this application.

[0022] Figure 4 It is a structural schematic diagram of the electronic device provided by this application. DETAILED DESCRIPTION

[0023] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0024] It should be noted that the terms "first", "second" etc. in the present application are used to distinguish similar objects, and need not be used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable in appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order 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 need not be 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 inherent to these processes, methods, products or equipment.

[0025] For launch vehicles with the same takeoff mass, the greater the carrying capacity, the better the rocket design, the more efficient and valuable it is. However, for a launch vehicle, the carrying capacity is affected by many factors. In terms of design parameters alone, they can be divided into mass parameters and power parameters, such as structural mass, propellant mass, engine thrust, engine specific impulse, etc. If it is a multi-stage rocket, there will be more design parameters involved.

[0026] Related technologies can determine the optimization direction of the rocket's carrying capacity through the partial derivatives of the design parameters. The intuitive meaning of the partial derivatives of the design parameters is how much the carrying capacity can be improved by adjusting the design parameters by one unit (if the parameters have no units, they can be quantified as percentages). It can be used to analyze the impact of design parameters deviating from the design values ​​on the carrying capacity, and it can also indicate which design values ​​need to be strictly controlled during the design and production process. It can also indicate the direction for subsequent upgrades and optimizations of the rocket. Moreover, the impact of these parameters is relatively independent within a certain range, so the partial derivatives of a single parameter can be used to perform algebraic analysis of the impact of multiple parameters on the carrying capacity.

[0027] 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 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 not 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 to increase 100kg or even more to obtain a higher carrying capacity.

[0028] 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: In the formula, is the carrying capacity parameter, is the carrying capacity calculation function, For the design parameters, .

[0029] Partial derivatives of design parameters, i.e., 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 cannot be clearly defined, and it is difficult to find its analytical solution, especially in the early stage of launch vehicle design.

[0030] At the beginning of the demonstration of a new rocket program, in order to guide the optimization of the overall program and achieve rapid iteration of the program, it is necessary to refer to the partial derivatives of the main design parameters both qualitatively and quantitatively to iterate the overall program and optimize the overall parameters. In addition to referring to the programs and parameters of other similar models and drawing on the development experience of other models, it is necessary to be able to provide the calculation results of the partial derivatives of the carrying capacity quickly and accurately.

[0031] 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 .

[0032] Step 110: Determine a plurality of target design parameters and deviations corresponding to the respective target design parameters in the design parameters of the rocket to be optimized.

[0033] Specifically, the execution subject of the rocket carrying capacity optimization method provided in the embodiment of the present application is a rocket carrying capacity optimization device. The device can be implemented by software, such as a rocket carrying capacity optimization program running in a computer; it can also be implemented by hardware, such as a computer or server that executes the rocket carrying capacity optimization method.

[0034] The application scenario of the rocket carrying capacity optimization method provided in the embodiment of the present application is to guide the optimization and upgrading of the rocket design scheme in the early stage of the design of the launch vehicle, and realize the rapid iteration of the rocket design scheme. The launch vehicle refers to the rocket that transports various manufactured spacecraft into space. The rocket to be optimized refers to the launch vehicle whose carrying capacity is optimized.

[0035] Design parameters refer to the key indicators and characteristics determined during the rocket design and manufacturing process, which 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.

[0036] Target design parameters refer to the design parameters that the designers of the launch vehicle are more concerned about, or the design parameters that have a greater impact on the carrying capacity. The target design parameters can be screened according to actual needs to determine the target design parameters.

[0037] Deviation refers to the difference between the actual measured value and the designed value of the design parameter during the rocket design, manufacturing or testing process. For design parameters, it is generally given in the range of design value ± allowable deviation. For example, the engine structure quality requirement is 2000kg ± 50kg, where ± 50kg is the allowable deviation of the design value. If the actual product exceeds this range, it is a substandard product and will be rejected and not used for rocket assembly; within this range, the impact of the deviation can be given based on the partial derivative to carry out impact assessment.

[0038] 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.

[0039] Specifically, the optimization variables are the parameters or variables that need to be adjusted during the optimization process, with the goal of maximizing or minimizing the objective function under certain constraints. The optimization calculation can be performed with each target design parameter as the optimization variable and the rocket's carrying capacity parameter as the objective function. The carrying capacity parameter refers to the parameter that characterizes the rocket's carrying capacity, which directly affects how much payload the rocket can deliver into the predetermined orbit or space target.

[0040] 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 value of each target design parameter is taken as the intermediate value, the numerical fluctuation range of the target design parameter is determined according to the deviation, and each value within the numerical fluctuation range is determined as the candidate design value.

[0041] 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.

[0042] 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.

[0043] 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.

[0044] It is understandable that the larger the carrying capacity parameter is, the better the carrying capacity of the rocket is. Therefore, the optimal value of the carrying capacity parameter is the maximum value of the carrying capacity parameter.

[0045] 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.

[0046] Specifically, the influence function of each target design parameter on the carrying capacity parameter of the rocket to be optimized is used to express the influence degree of each target design parameter on the carrying capacity parameter. The influence function can be determined by taking the change of the carrying capacity parameter as the dividend and the change of 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 carrying capacity parameter.

[0047] Since the specific functional relationship of the carrying capacity calculation function cannot be clearly defined, it is difficult to find its analytical solution. Therefore, numerical solutions can be used instead of analytical solutions 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: In the formula, 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.

[0048] The rocket carrying capacity optimization method provided in the embodiment of the present application determines multiple target design parameters and deviations corresponding to each target design parameter in the design parameters of the rocket to be optimized; takes 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; because 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 plan can be effectively guided in the early design stage, and the rapid iteration of the rocket plan can be achieved, thereby improving the optimization efficiency of the rocket carrying capacity design plan.

[0049] It should be noted that each implementation method of the present application can be freely combined, the order can be changed, or it can be executed separately, and does not need to rely on or depend on a fixed execution order.

[0050] In some embodiments, determining a plurality of target design parameters and deviations corresponding to the respective target design parameters in the design parameters of the rocket to be optimized includes: Determine the degree of influence of each design parameter on the rocket to be optimized; Screen each design parameter based on the degree of influence and determine multiple target design parameters; Based on the design performance requirements of the rocket to be optimized, determine the deviations corresponding to each target design parameter.

[0051] 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.

[0052] Specifically, the design parameters of the rocket to be optimized may include at least two categories of parameters: mass parameters and power parameters.

[0053] Mass parameters refer to parameters related to the mass of the rocket, which can include structural mass, equipment mass, and propellant mass. Structural mass refers to the mass of the structural components of the rocket itself, including the fuselage, cabin, support structure, tail nozzle, etc. Equipment mass refers to the mass of all equipment and systems on the rocket, including navigation systems, communication equipment, control systems, sensors, etc. Propellant mass refers to the mass of the fuel and oxidizer used in the rocket engine, including liquid fuel, solid fuel, etc.

[0054] Power parameters refer to parameters related to the power of a rocket, which can include engine thrust and engine specific impulse. Engine thrust refers to the upward force generated by the engine. Engine specific impulse refers to an indicator of engine efficiency, usually expressed in seconds, indicating the thrust that can be generated per unit of fuel.

[0055] We can first determine the degree of influence of each design parameter on the optimized rocket, that is, the importance of each design parameter to the rocket or the degree of attention paid by the designer. For example, we can determine the influence of each design parameter (such as thrust, specific impulse, structural mass, equipment mass, etc.) on the rocket performance based on the dynamic and thermodynamic models of the rocket; or we can combine experience and expert knowledge to evaluate the importance of design parameters to determine which parameters are more critical in specific situations.

[0056] The various design parameters are screened according to the degree of influence, and multiple target design parameters are determined. The target design parameters are usually the main design parameters. The deviations corresponding to the various target design parameters can be determined according to the design performance requirements of the rocket to be optimized.

[0057] The design performance requirements are the performance indicators and capabilities that the rocket needs to achieve under flight mission conditions, such as thrust, specific impulse, payload capacity, flight trajectory and accuracy, reliability, structural strength and quality, etc.

[0058] According to the design performance requirements, the deviations corresponding to each target design parameter can be determined. The target design parameters are generally given in the range of design value ± allowable deviation. For example, the engine structure mass requirement is 2000kg ± 50kg, 2000kg is the design value, and ± 50kg is the allowable deviation.

[0059] 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, which can effectively determine the main design parameters, and can effectively guide the optimization and upgrading of the rocket plan in the early stage of design, and realize the rapid iteration of the rocket plan.

[0060] 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: Determine the orbital velocity corresponding to the target orbit of the rocket to be optimized; Based on any candidate design value corresponding to any target design parameter, the design parameters of the rocket to be optimized are updated; Based on the updated design parameters, determine the flight speed of the rocket to be optimized when entering the target orbit; When the flight speed is greater than or equal to the orbital velocity, the calculated value of the carrying capacity parameter under any candidate design value corresponding to any target design parameter is recorded; The maximum value among 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.

[0061] Specifically, the target orbit refers to the ideal orbit or designed orbit for the rocket to be optimized to perform its flight mission. The orbital velocity refers to the flight speed required for the rocket to reach the predetermined orbit. Meeting the target orbit requirements means that the rocket can operate on this orbit. In simple terms, it means that the rocket must have a corresponding speed at the target orbit altitude. Altitude represents potential energy, speed represents kinetic energy, and different forms of energy can be converted, so potential energy can be converted into corresponding kinetic energy, that is, speed. In this way, the orbital entry condition satisfies the total energy requirement (potential energy + kinetic energy), which can eventually be converted into a speed requirement.

[0062] The speed required for different orbits may be different, and the orbital velocity is affected by the orbital altitude and the mission type. The orbital velocity corresponding to the rocket to be optimized can be determined based on the orbital parameters of the target orbit.

[0063] 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.

[0064] According to any candidate design value corresponding to any target design parameter, the design parameters of the rocket to be optimized are updated. This step is mainly performed 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 relevant design parameters need to be updated synchronously.

[0065] 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.

[0066] For example, the Tsiolkovsky formula is: 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.

[0067] 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 results of mathematical simulation or analysis of 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, .

[0068] When the flight speed is greater than or equal to the orbital 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 entry, 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 is not satisfied, it may not be recorded.

[0069] There may be multiple calculated values ​​of the carrying capacity parameter under each candidate design value corresponding to any target design parameter, and 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.

[0070] 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 entry speed. From the energy perspective, the calculation result meets the rocket orbit entry 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.

[0071] In some embodiments, recording a calculated value of a carrying capacity parameter under any candidate design value corresponding to any target design parameter includes: Determine the numerical optimization range of the carrying capacity parameters; 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 velocity 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.

[0072] Specifically, in the design of the rocket to be optimized, the carrying capacity parameter may also have a numerical optimization range.

[0073] Each candidate design value corresponding to any target design parameter is traversed, and the calculated value corresponding to the carrying capacity parameter when any target design parameter selects each candidate design value is calculated.

[0074] If the flight speed is greater than or equal to the orbital velocity 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.

[0075] 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 the rocket to enter orbit. Compared with the partial derivative calculation in the related technology, it does not need to consider the convergence of the optimization, which greatly improves the calculation speed and has a smaller result error.

[0076] 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: Determine the optimal value of the carrying capacity parameter corresponding to the upper limit of the deviation corresponding to each target design parameter; Determine the optimal value of the carrying capacity parameter corresponding to the lower limit of the deviation corresponding to each target design parameter; 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.

[0077] 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, and the optimal value of the carrying capacity parameter corresponding to the lower limit of the deviation corresponding to the target design parameter.

[0078] According to 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 the target design parameter on the carrying 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 limits of the deviation is determined as the influence coefficient, and the change of the carrying capacity parameter can be obtained by multiplying the influence coefficient with the change of the target design parameter. The change of the carrying capacity parameter, the change of the target design parameter and the influence coefficient are expressed by a functional relationship to obtain the influence function.

[0079] 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.

[0080] 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 according to 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 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.

[0081] 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: 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.

[0082] Specifically, the value of the influence function of the carrying capacity parameter of the rocket to be optimized can be determined from each target design parameter, and the target design parameters that need to be optimized can be determined from each target design parameter. For example, the target design parameters that have a greater impact on the carrying capacity parameter can be determined based on the influence function, and these target design parameters can be used as the direction of optimization.

[0083] 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 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.

[0084] 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: Step 210: Parameter status setting Determine the design parameters of the rocket (including the design load) and the deviations of the main design parameters, and update the design parameters taking a given value of any main design parameter as an example.

[0085] Step 220: Optimize the carrying capacity 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.

[0086] Compare the rocket 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.

[0087] 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.

[0088] The maximum value of all recorded values ​​is selected as the optimal carrying capacity under the influence of this deviation.

[0089] Step 230: Calculation of partial derivative numerical solution 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.

[0090] If you need to calculate the partial derivatives of the carrying capacity of other design parameters, just repeat all the above steps.

[0091] Taking a certain type of four-stage rocket as an example, to calculate the partial derivatives of the carrying capacity of the mass of the structure of each stage of the launch vehicle, a total of 8 states (upper and lower deviations) need to be calculated. The calculation time of an optimized state needs to be measured in minutes when the ballistic program optimization method is used for calculation. If the method provided in this application is used for calculation, the total time for the entire calculation process is less than 2 seconds, and the calculation speed is greatly improved. Comparing the calculation results with the calculation results of the ballistic program optimization (the results are considered to be true values), the maximum calculation error of the partial derivatives of the mass carrying capacity of the rocket structure at each stage does not exceed 22%. In the early stages of engineering application and scheme design, the accuracy of this result can fully meet the use requirements.

[0092] 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.

[0093] Figure 3 is a schematic diagram of the structure of the rocket carrying capacity optimization device provided by this application, such as Figure 3 As shown, the device comprises: 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; A variable determination module 320 is used to determine a plurality of candidate design values ​​corresponding to each target design parameter based on the deviation corresponding to each target design parameter, taking each target design parameter as an optimization variable; An optimization calculation module 330 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; The function determination module 340 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.

[0094] The rocket carrying capacity optimization device provided in the embodiment of the present application determines multiple target design parameters and deviations corresponding to each target design parameter in the design parameters of the rocket to be optimized; takes 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; because 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 plan can be effectively guided in the early design stage, and the rapid iteration of the rocket plan can be achieved, thereby improving the optimization efficiency of the rocket carrying capacity design plan.

[0095] In some embodiments, the parameter setting module is used to: Determine the degree of influence of each design parameter on the rocket to be optimized; Screen each design parameter based on the degree of influence and determine multiple target design parameters; Based on the design performance requirements of the rocket to be optimized, determine the deviations corresponding to each target design parameter.

[0096] In some embodiments, the optimization calculation module is used to: Determine the orbital velocity corresponding to the target orbit of the rocket to be optimized; Based on any candidate design value corresponding to any target design parameter, the design parameters of the rocket to be optimized are updated; Based on the updated design parameters, determine the flight speed of the rocket to be optimized when entering the target orbit; When the flight speed is greater than or equal to the orbital velocity, the calculated value of the carrying capacity parameter under any candidate design value corresponding to any target design parameter is recorded; The maximum value among 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.

[0097] In some embodiments, the optimization calculation module is used to: Determine the numerical optimization range of the carrying capacity parameters; 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 velocity 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.

[0098] In some embodiments, 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.

[0099] In some embodiments, the function determination module is used to: Determine the optimal value of the carrying capacity parameter corresponding to the upper limit of the deviation corresponding to each target design parameter; Determine the optimal value of the carrying capacity parameter corresponding to the lower limit of the deviation corresponding to each target design parameter; 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.

[0100] In some embodiments, the device is also used to: 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.

[0101] Figure 4 is a schematic diagram of the structure of the electronic device provided by this application, such as 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 through the communication bus 440. The processor 410 may call the logic command in the memory 430 to execute the method described in the above embodiment, for example: 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; 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.

[0102] 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 can be essentially or partly embodied in the form of a software product that contributes to the prior art. 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, etc., which can store program code.

[0103] 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.

[0104] An embodiment of the present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the methods provided in the above embodiments are implemented.

[0105] Its specific implementation is consistent with the aforementioned method implementation and can achieve the same beneficial effects, so it will not be repeated here.

[0106] An embodiment of the present application provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0107] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0108] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0109] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for optimizing rocket carrying capacity, characterized in that: include: Determine a plurality of target design parameters and deviations corresponding to the respective target design parameters in 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; 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.

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 influence degree 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, characterized in that: The step of 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: Determine the orbital velocity corresponding to the 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; Based on the updated design parameters, determining the flight speed of the rocket to be optimized when entering the target orbit; 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 among 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 one of the target design parameters, and determining a calculated value of the carrying capacity parameter under each candidate design value corresponding to any one of the target design parameters; 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 claim 1, characterized in that: 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.

6. The method for optimizing rocket carrying capacity according to claim 1, characterized in that: 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, the influence function of each target design parameter on the carrying capacity parameter of the rocket to be optimized comprises: Determine the optimal value of the carrying capacity parameter corresponding to the upper limit of the deviation corresponding to each target design parameter; Determine the optimal value of the carrying capacity parameter corresponding to the lower limit of the deviation corresponding to each target design parameter; 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.

7. The method for optimizing rocket carrying capacity according to any one of claims 1 to 6, 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 parameter for optimizing the carrying capacity parameter of the rocket to be optimized is determined.

8. A rocket carrying capacity optimization device, characterized in that: include: A parameter setting module, used to determine a plurality of 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, used to determine a plurality of candidate design values ​​corresponding to each target design parameter based on the deviation corresponding to each target design parameter, taking each target design parameter as an optimization variable; An optimization calculation module, 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; 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.

9. 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 7 is implemented.

10. 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 7 is implemented.

Images