CN116522680A - Thermal constraint analysis method for constellation satellite on-orbit mission planning - Google Patents
Thermal constraint analysis method for constellation satellite on-orbit mission planning Download PDFInfo
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Abstract
The application discloses a thermal constraint analysis method for constellation satellite on-orbit mission planning, which belongs to the field of aerospace and comprises the following steps: under the condition that only a heat conduction heat exchange mode and a heat radiation heat exchange mode exist in a task single machine, establishing a heat balance equation of any node i on the task single machine at tau moment; taking the task single machine as a simplified model with consistent shell temperature, and integrating and simplifying a heat balance equation to obtain a simplified heat balance equation; analyzing the cooling process after the task single machine works by simplifying a heat balance equation and obtaining a temperature change rule; and acquiring the first heat dissipation capacity and the second heat dissipation capacity, obtaining a thermal constraint analysis formula by combining a temperature change rule, and performing thermal constraint calculation through the thermal constraint analysis formula so as to perform on-orbit task planning comprising thermal constraint analysis on the task single machine. The method provided by the application has the advantages of small use scene limit, short calculation time consumption, no need of periodically updating calculation parameters, and particular suitability for large-quantity constellation satellite task planning.
Description
Technical Field
The application relates to a thermal constraint analysis method for constellation satellite on-orbit mission planning, and belongs to the field of aerospace.
Background
With the improvement of the space remote sensing information industry on the time resolution requirement of satellite images, the establishment of a commercial microsatellite constellation becomes a necessary trend, and a reasonable on-orbit task planning strategy can furthest improve the use value of the constellation, wherein accurate and simple thermal constraint analysis is an indispensable one.
Taking a remote sensing satellite as an example, at the beginning of satellite design, the maximum imaging duration, the maximum data transmission duration, the task interval and the like are generally taken as the maximum envelope, and the satellite design is developed on the basis of the maximum envelope; when the actual satellite runs in orbit, the satellite is limited by energy constraint and ground constraint (limit of data transmission circle number and cross border arc length), the service arrangement is not obvious, and the satellite has larger access to working conditions in conventional thermal simulation analysis and vacuum thermal test, thereby introducing the necessity of in-orbit thermal constraint analysis. In the heat constraint, the task planning is most influenced by 1-2 groups of task single machines, and the single machines have higher heat consumption in the working state and are the main targets of research.
In the art, there are currently a patent of "satellite component layout temperature field prediction method based on physical prior" and a patent of "satellite component layout temperature field prediction method based on uncertainty" (patent No. 202210098085.6), etc. (patent No. 202110850313.6), and the main objective of such a patent is to simplify the layout iteration process in the design process, and not to predict the satellite on-orbit state. Another patent is "an imaging task planning method of remote sensing video satellite" (patent number: 202210998756.4), and when planning the satellite on-orbit task, the patent does not consider the problem of thermal constraint, and the problem is that: the actual task duration of the satellite can not meet the planning requirement, or the satellite needs more thermal control compensation resources in the design process. Other existing simple on-orbit temperature prediction methods mainly use on-orbit test data to fit up and down Wen Gongshi, and the main problems of the method are as follows: the on-orbit telemetry data refreshing frequency is low, the fitting data error is larger, the error can be iterated continuously, and the initial value is required to be updated irregularly; the temperature fluctuation of part of single machines is large, and the statistical formula is inconvenient.
Disclosure of Invention
The thermal constraint analysis method for the on-orbit task planning of the constellation satellites is provided, and aims at the characteristics of huge number of constellation satellites and high task planning complexity, the thermal constraint analysis method with only two characteristic parameters is obtained through simplified calculation, so that the temperature trend of the on-orbit satellite task single machine is predicted, and meanwhile, the method has higher accuracy.
To achieve the above object, a first aspect of the present application provides a thermal constraint analysis method for constellation satellite on-orbit mission planning, including:
under the condition that only a heat conduction heat exchange mode and a heat radiation heat exchange mode exist in a task single machine, establishing a heat balance equation of any node i on the task single machine at tau moment;
taking the task single machine as a simplified model with consistent shell temperature, and integrating and simplifying the heat balance equation to obtain a simplified heat balance equation;
analyzing the cooling process after the task single machine works through the simplified heat balance equation, and obtaining a temperature change rule, wherein the temperature change rule is that the heat dissipation capacity of the task single machine is reduced in an equal ratio in any period;
and obtaining a heat constraint analysis formula by combining the temperature change rule, and performing heat constraint calculation through the heat constraint analysis formula to perform on-orbit task planning comprising heat constraint analysis on the task single machine, wherein the task single machine has the same working rule of each orbit, when the temperature peak value of the task single machine is equal to the upper limit of the allowable temperature in an equilibrium state, obtaining the heat production or the heat dissipation of the task single machine in each orbit period as the first heat dissipation, and when the initial temperature of the task single machine is the equilibrium temperature under the condition that the task single machine does not work, continuously working until the temperature of the task single machine reaches the upper limit of the allowable temperature, and obtaining the maximum heat production of a single task or the maximum heat dissipation of each orbit period as the second heat dissipation.
In one embodiment, the thermal equilibrium equation includes:
wherein C is p m is heat capacity, T is temperature, P is internal heat source and space external heat flow, the heat flow items of the internal heat source and the space external heat flow are constant or the rules of each track are the same, and then the heat flow items are nodes P at the same moment of each track i Is a constant, D is a thermal conductivity coefficient, R is a thermal emissivity coefficient, sigma is a Stefan-Boltzmann constant, and subscript j represents other nodes on the satellite.
In one embodiment, before the integrating the thermal equilibrium equation is simplified, the method further comprises:
in the heat balance equation, the radiation heat exchange amount of the task single machine is in direct proportion to the four-time variance of the temperature, and the heat conduction item and the heat radiation item are combined into one item to obtain the heat balance equation, wherein the assumption is that the radiation heat exchange amount of the task single machine is in direct proportion to the one-time variance of the temperature:
wherein A is the comprehensive heat exchange coefficient.
In one embodiment, the simplified thermal equilibrium equation is:
τ＝-Bln(T-T ∞ )+
wherein T is the temperature of the task single machine at tau moment, T ∞ B, C is a characteristic constant for the temperature of the task unit at equilibrium.
In one embodiment, the integrating the thermal balance equation further comprises:
changing the form of the simplified heat balance equation to:
wherein D, E is a characteristic constant, the positive and negative of the D value depend on the equilibrium process being a temperature decreasing process or a temperature increasing process, when τ is 0, the temperature initial value is obtained by solving, and when τ approaches infinity, T approaches the equilibrium temperature.
In one embodiment, the analyzing the cooling process after the task stand-alone operation by the simplified heat balance equation and obtaining the temperature change rule includes:
taking the cooling process after the task single machine works for analysis, and setting the initial temperature as T 0 Taking the fixed time interval as delta T to obtain the temperature T of a plurality of time nodes 1 、T 2 、T 3 、T 4 ……T ∞ The following rules apply:
the temperature change rule is obtained through the formula.
In one embodiment, the thermal constraint analysis formula is:
wherein, the liquid crystal display device comprises a liquid crystal display device,for balance ratio, Q is the second heat dissipation capacity, Q 0 For the first heat dissipation capacity。
In one embodiment, the performing the thermal constraint calculation by the thermal constraint analysis formula includes:
calculating the single-rail minimum heat generation or heat dissipation capacity of the task single machine through a thermal simulation model, and taking the single-rail minimum heat generation or heat dissipation capacity as the first heat dissipation capacity;
calculating balance proportion of the task single machine through a thermal simulation model;
calculating the second heat dissipation capacity through the thermal constraint analysis formula to obtain the maximum heat dissipation capacity or the maximum allowable heat generation capacity of the task single machine;
and performing on-orbit task planning comprising task single machine thermal constraint analysis based on the maximum heat dissipation capacity or the maximum allowable heat generation.
A second aspect of 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, the processor implementing the steps of the first aspect or any implementation of the first aspect as described above when the computer program is executed.
A third aspect of the present application provides a computer readable storage medium storing a computer program which when executed by a processor performs the steps of the first aspect or any implementation of the first aspect.
From the above, the application provides a thermal constraint analysis method for constellation satellite on-orbit mission planning, a new thermal constraint analysis formula is constructed by adopting a theoretical calculation mode, thermal constraint is carried out on the single-machine temperature of a satellite mission, satellite on-orbit service planning is assisted, and the single-machine temperature of a high-heat-consumption mission is ensured to be lower than the upper limit of the allowable temperature. The calculation process only needs to calculate two characteristic parameters by the thermal simulation model, the planning process is simple, and the accuracy is high. The method has the advantages of small use scene limit, short calculation time consumption, no need of periodically updating calculation parameters, and particular suitability for constellation satellite mission planning with huge quantity. The method can be applied to predicting the temperature trend of an on-orbit satellite task single machine, and can ensure that task planning meets the task quantity (a plurality of satellite orbit periods) within the minimum task envelope duration on the premise that the temperature of the task single machine does not exceed the allowable temperature, thereby providing a reliable basis for flexibly and rapidly planning the service.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following description will briefly introduce the drawings that are needed in the embodiments or the description of the prior art, it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a thermal constraint analysis method according to an embodiment of the present application;
FIG. 2 is a schematic flow chart of performing thermal constraint calculation according to a thermal constraint analysis formula according to an embodiment of the present application;
fig. 3 is a graph of measured temperature of a single satellite task provided in an embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system configurations, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. However, it will be apparent to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It should be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
The following description of the embodiments of the present application, taken in conjunction with the accompanying drawings, clearly and fully describes the technical solutions of the embodiments of the present application, and it is evident that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application, but the present application may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present application is not limited to the specific embodiments disclosed below.
Example 1
The embodiment of the application provides a thermal constraint analysis method for constellation satellite on-orbit mission planning, as shown in fig. 1, the method comprises the following steps:
s100, under the condition that a task single machine only has a heat conduction heat exchange mode and a heat radiation heat exchange mode, establishing a heat balance equation of any node i on the task single machine at tau moment;
in one embodiment, when in-orbit thermal constraint analysis is performed, task single machines with the largest influence on task planning are usually 1-2 groups, and the single machines have higher heat consumption in the working state, so that the single machines are taken as main analysis objects, and the task quantity in the minimum task envelope duration (a plurality of satellite orbit periods) can be met by task planning on the premise that the temperature of the task single machines does not exceed the allowable temperature through analysis of the method disclosed by the embodiment of the application. Wherein the task unit should generally meet the condition that the difference between the peak value and the valley value of the temperature in the on-orbit state is less than 40 ℃.
Alternatively, in a cosmic environment, on-board single units usually only have two heat exchange modes of heat conduction and heat radiation, so that a heat balance equation of any node i on the task single unit at the time τ is as follows:
wherein C is p m is heat capacity, T is temperature, P is internal heat source and space external heat flow, the heat flow items of the internal heat source and the space external heat flow are constant or the rules of each track are the same, and then the heat flow items are nodes P at the same moment of each track i Is a constant, D is a thermal conductivity coefficient, R is a thermal emissivity coefficient, sigma is a Stefan-Boltzmann constant, and subscript j represents other nodes on the satellite.
Optionally, in the heat balance equation, the heat exchange amount of the task single machine radiation is proportional to the fourth variance of the temperature, and it is assumed here that the heat exchange amount is proportional to the first variance of the temperature, and the heat conduction term and the heat radiation term are combined into one term, that is, sigma j A ij (T j -T i ) The thermal equilibrium equation is obtained as follows:
wherein A is the comprehensive heat exchange coefficient, the radiation item is approximately linear in the interval range due to the narrow temperature fluctuation interval of the task single machine, for example, the error brought by the assumption is 2.8% at maximum in the interval of 0-40 ℃ and can be approximately ignored.
S200, regarding the task single machine as a simplified model with consistent shell temperature, and integrating and simplifying the heat balance equation to obtain a simplified heat balance equation;
alternatively, considering the task stand-alone as a simplified model of shell temperature agreement, the thermal equilibrium equation can be simplified as an integral:
τ＝-Bln(T-T ∞ )+C
wherein T is the temperature of the task single machine at tau moment, T ∞ B, C is a characteristic constant for the temperature of the task unit at equilibrium.
Further, to facilitate understanding of the physical meaning of this formula, the form is changed as follows:
where D, E is a characteristic constant, the positive and negative of the D value depends on whether the equilibrium process is a temperature decreasing process or a temperature increasing process, when τ is 0, the initial temperature value can be solved, and when τ approaches infinity, t approaches the equilibrium temperature.
S300, analyzing a cooling process after the task single machine works through the simplified heat balance equation and obtaining a temperature change rule, wherein the temperature change rule is that the heat dissipation capacity of the task single machine is reduced in an equal ratio in any period;
optionally, taking the cooling process after the task single machine works for analysis, and setting the initial temperature as t 0 Taking the fixed time interval as delta T to obtain the temperature T of a plurality of time nodes 1 、T 2 、T 3 、T 4 ……T ∞ The following rules apply:
it is known from the assumption that the heat dissipation capacity in unit time is proportional to the primary temperature difference, and the physical meaning of the law is that the heat dissipation capacity of the task single machine in any period is reduced in an equal ratio.
S400, obtaining a first heat dissipation capacity and a second heat dissipation capacity, obtaining a heat constraint analysis formula by combining the temperature change rule, carrying out heat constraint calculation through the heat constraint analysis formula, and carrying out on-orbit task planning comprising heat constraint analysis on the task single machine, wherein the task single machine has the same working rule in each orbit, when the temperature peak value of the task single machine is equal to the upper allowable temperature limit in an equilibrium state, obtaining the heat generation capacity or the heat dissipation capacity of the task single machine in each orbit period as the first heat dissipation capacity, and when the initial temperature of the task single machine is the equilibrium temperature under the condition that the task single machine does not work, continuously working until the temperature of the task single machine reaches the upper allowable temperature limit, and obtaining the maximum heat generation capacity of a single task or the maximum heat dissipation capacity in each orbit period as the second heat dissipation capacity.
In one application scenario, two conditions may be defined: working condition I, in which the working rule of each track of the task single machine is the same, in the equilibrium state, the single machine temperature peak value is just equal to the allowable temperature upper limit, and the heat generation/dissipation capacity of each track period task single machine under the working condition is recorded as Q 0 (i.e., a first heat dissipation capacity); and under the second working condition, the initial temperature of the single task is the equilibrium temperature under the condition that the single task does not work, and then the single task continuously works until the single task temperature reaches the upper limit of the allowable temperature, and the maximum heat generation/maximum heat dissipation capacity per track period of the single task is recorded as Q (namely, the second heat dissipation capacity).
Alternatively, when the time interval Δt is an orbital period, there are:
the writing form of the thermal constraint analysis formula is changed to obtain the thermal constraint analysis formula:
when the thermal constraint calculation is performed through the method, the thermal constraint analysis of the constellation satellite on-orbit task planning can be performed according to the fact that Q has the maximum heat dissipation capacity/maximum allowable heat generation of a task single machine.
In one embodiment, as shown in fig. 2, performing the thermal constraint calculation by the thermal constraint analysis formula includes:
s410, before task planning, ensuring that the difference between the peak value and the valley value of the on-orbit predicted temperature of a task single machine is less than 40 ℃;
s420, performing trial calculation in a thermal simulation model corrected by a vacuum thermal test to obtain the minimum heat generation/dissipation Q of the single-unit task monorail 0 As the first heat dissipation amount;
s430, calculating balance proportion through a cooling curve of the task single machine in the thermal simulation model due to the fact that primary temperature difference of the task single machine is reduced in an equal ratio at fixed time intervalsIs a numerical value of (2);
s440 will Q 0 And (3) withCarrying out the heat constraint analysis on the task unit, and carrying out heat constraint analysis on the task unit to obtain a heat constraint analysis formula;
s450, in a low-temperature balance state, the maximum heat dissipation capacity of the first circle is Q; the heat generation in the circle of the task single machine is the product of the heat consumption of the single machine and the working time; when the balance heat of the ring is(maximum heat dissipation in turns-heat generation in turns), the maximum heat dissipation in turns of the rest turns being (Q) 0 + the balance heat of the previous round), and performing on-orbit task planning comprising task single machine thermal constraint analysis.
The maximum heat dissipation capacity, the heat generation capacity and the balance heat capacity in the circle can be calculated in the above mode during task planning, so that on-orbit task planning comprising task single machine thermal constraint analysis is realized, namely, on the premise that the temperature of the task single machine does not exceed the allowable temperature, the task planning is enabled to meet the task capacity in the minimum task envelope duration (a plurality of satellite orbit periods). When the balance heat is not negative, theoretically, the maximum temperature of the circle of the task single machine is lower than the upper limit of the allowable temperature.
From the above, the embodiment of the application provides a thermal constraint analysis method for constellation satellite on-orbit task planning, a new thermal constraint analysis formula is constructed by adopting a theoretical calculation mode, thermal constraint is carried out on the single-machine temperature of a satellite task, on-orbit service planning of the satellite is assisted, and the single-machine temperature of a high-heat-consumption task is ensured to be lower than the upper limit of the allowable temperature. The calculation process only needs to calculate two characteristic parameters by the thermal simulation model, the planning process is simple, and the accuracy is high. The method has the advantages of small use scene limit, short calculation time consumption, no need of periodically updating calculation parameters, and particular suitability for constellation satellite mission planning with huge quantity. The method can be applied to predicting the temperature trend of an on-orbit satellite task single machine, and can ensure that task planning meets the task quantity (a plurality of satellite orbit periods) within the minimum task envelope duration on the premise that the temperature of the task single machine does not exceed the allowable temperature, thereby providing a reliable basis for flexibly and rapidly planning the service.
Example two
In order to verify the effect of the thermal constraint analysis method for constellation satellite on-orbit mission planning in the first embodiment, the embodiment of the application performs mission planning and actual measurement verification by using a typical mission stand-alone machine (imaging processing box) of a remote sensing constellation satellite.
The star was imaged 20W square kilometers per day and downloaded as a mission requirement with a track period of 5720s, i.e. 15 flights around the ground per day. To accomplish this task, 1800s, 3300s for data compression, 3420s for data transmission are required daily, and the number of imaging and data transmission cycles is limited by other constraints, which are not described in detail herein.
The temperature fluctuation level of the star task single machine is a main index of satellite service thermal constraint. The heat consumption of the task single machine is 22W in satellite imaging, 34W in data compression and 23W in data transmission.
Between the satellite constellations of the model, the on-orbit low-temperature equilibrium temperature of a task single machine of each satellite is 20+/-2 ℃, and the average value is 20 ℃; the upper limit of the on-orbit temperature alarm of the single machine is 43 ℃, the maximum allowable temperature of task planning is 35 ℃, and a certain margin is reserved.
The thermal constraint process for calculating the star traffic is as follows:
the single task machine meets the requirement that the difference between the on-orbit predicted temperature peaks/valleys is 15 ℃ and is smaller than 40 ℃;
as can be seen from trial calculation in a thermal simulation model corrected by a vacuum thermal test, when the temperature peak value reaches 35 ℃ which is the maximum allowable temperature due to the periodic operation of each track of the single task machine, the single track machine has 23000J of heat consumption, namely the single track is the most practicalSmall heat generation/dissipation Q 0 。
The balance proportion is calculated through the cooling curve of the task single machine in the thermal simulation model due to the fact that the primary temperature difference of the task single machine is reduced in an equal ratio at fixed time intervalsAbout 33%.
Through Q 0 And (3) withThe maximum heat dissipation capacity/maximum allowable heat generation Q of the available task unit was calculated to be 34328J.
In a low-temperature balance state, the maximum heat dissipation capacity of the first circle is Q; the heat generation in the circle of the task single machine is the product of the heat consumption of the single machine and the working time; when the balance heat of the ring is(maximum heat dissipation in turns-heat generation in turns); the maximum heat dissipation capacity in the other circles is (Q) 0 + the balance heat of the previous round).
The maximum heat dissipation, the heat generation amount in the circle and the balance heat of the task single machine are calculated in the mode, and the single-day task planning of arrangement is shown in a table 1. When the balance heat is not negative, the maximum temperature of the circle of the task single machine is theoretically lower than the upper limit of the allowable temperature.
Table 1 single day mission planning for 20w square kilometer service
Description
The satellite of a certain model performs task implementation according to the task plan of table 1, and the temperature curve of a task single machine is shown in fig. 3, so that the balance heat in table 1 is closer to zero, and the temperature peak value of the task single machine is approximately close to the maximum allowable temperature of 35 ℃. The thermal constraint of task planning can better predict the in-orbit temperature state of a satellite task single machine.
Example III
The embodiment of the application provides an electronic device, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the memory is used for storing the software program and a module, and the processor executes various functional applications and data processing by running the software program and the module stored in the memory. The memory and the processor are connected by a bus. In particular, the processor implements any of the steps of the above-described embodiment by running the above-described computer program stored in the memory.
It should be appreciated that in embodiments of the present application, the processor may be a central processing unit (Central Processing Unit, CPU), which may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory may include read-only memory, flash memory, and random access memory, and provides instructions and data to the processor. Some or all of the memory may also include non-volatile random access memory.
From the above, the electronic device provided in the embodiment of the present application implements the method described in embodiment one by running a computer program, and adopts a theoretical calculation mode to construct a new thermal constraint analysis formula, so as to perform thermal constraint on the task single machine temperature of the satellite, assist in satellite on-orbit service planning, and ensure that the high heat consumption task single machine temperature is lower than the allowable upper limit. The calculation process only needs to calculate two characteristic parameters by the thermal simulation model, the planning process is simple, and the accuracy is high. The method has the advantages of small use scene limit, short calculation time consumption, no need of periodically updating calculation parameters, and particular suitability for constellation satellite mission planning with huge quantity. The method can be applied to predicting the temperature trend of an on-orbit satellite task single machine, and can ensure that task planning meets the task quantity (a plurality of satellite orbit periods) within the minimum task envelope duration on the premise that the temperature of the task single machine does not exceed the allowable temperature, thereby providing a reliable basis for flexibly and rapidly planning the service.
It should be appreciated that the above-described integrated modules/units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer-readable storage medium. Based on such understanding, the present application may implement all or part of the flow of the method of the above embodiment, or may be implemented by instructing related hardware by a computer program, where the computer program may be stored in a computer readable storage medium, and the computer program may implement the steps of each method embodiment described above when executed by a processor. The computer program comprises computer program code, and the computer program code can be in a source code form, an object code form, an executable file or some intermediate form and the like. The computer readable medium may include: any entity or device capable of carrying the computer program code described above, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. The content of the computer readable storage medium can be appropriately increased or decreased according to the requirements of the legislation and the patent practice in the jurisdiction.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
It should be noted that, the method and the details thereof provided in the foregoing embodiments may be combined into the apparatus and the device provided in the embodiments, and are referred to each other and are not described in detail.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other manners. For example, the apparatus/device embodiments described above are merely illustrative, e.g., the division of modules or elements described above is merely a logical functional division, and may be implemented in other ways, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed.
The above embodiments are only for illustrating the technical solution of the present application, and are not limiting; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.
Claims (10)
1. A thermal constraint analysis method for constellation satellite on-orbit mission planning, comprising:
under the condition that only a heat conduction heat exchange mode and a heat radiation heat exchange mode exist in a task single machine, establishing a heat balance equation of any node i on the task single machine at tau moment;
taking the task single machine as a simplified model with consistent shell temperature, and integrating and simplifying the heat balance equation to obtain a simplified heat balance equation;
analyzing the cooling process after the task single machine works through the simplified heat balance equation, and obtaining a temperature change rule, wherein the temperature change rule is that the heat dissipation capacity of the task single machine is reduced in an equal ratio in any period;
and obtaining a heat constraint analysis formula by combining the temperature change rule, and performing heat constraint calculation through the heat constraint analysis formula to perform on-orbit task planning comprising heat constraint analysis on the task single machine, wherein the task single machine has the same working rule of each orbit, when the temperature peak value of the task single machine is equal to the upper limit of the allowable temperature in an equilibrium state, obtaining the heat production or the heat dissipation of the task single machine in each orbit period as the first heat dissipation, and when the initial temperature of the task single machine is the equilibrium temperature under the condition that the task single machine does not work, continuously working until the temperature of the task single machine reaches the upper limit of the allowable temperature, and obtaining the maximum heat production of a single task or the maximum heat dissipation of each orbit period as the second heat dissipation.
2. The thermal constraint analysis method of claim 1, wherein the thermal equilibrium equation comprises:
wherein C is p m is heat capacity, T is temperature, P is internal heat source and space external heat flow, the heat flow items of the internal heat source and the space external heat flow are constant or the rules of each track are the same, and then the heat flow items are nodes P at the same moment of each track i Is a constant, D is a thermal conductivity coefficient, R is a thermal emissivity coefficient, sigma is a Stefan-Boltzmann constant, and subscript j represents other nodes on the satellite.
3. The thermal constraint analysis method of claim 2, wherein the integrating the thermal equilibrium equation further comprises, prior to:
in the heat balance equation, the radiation heat exchange amount of the task single machine is in direct proportion to the four-time variance of the temperature, and the heat conduction item and the heat radiation item are combined into one item to obtain the heat balance equation, wherein the assumption is that the radiation heat exchange amount of the task single machine is in direct proportion to the one-time variance of the temperature:
wherein A is the comprehensive heat exchange coefficient.
4. A thermal constraint analysis method according to claim 3, wherein the simplified thermal equilibrium equation is:
τ＝-Bln(T-T ∞ )+
wherein T is the temperature of the task single machine at tau moment, T ∞ B, C is a characteristic constant for the temperature of the task unit at equilibrium.
5. The thermal constraint analysis method of claim 4, wherein said integrating the thermal equilibrium equation further comprises:
changing the form of the simplified heat balance equation to:
wherein D, E is a characteristic constant, the positive and negative of the D value depend on the equilibrium process being a temperature decreasing process or a temperature increasing process, when τ is 0, the temperature initial value is obtained by solving, and when τ approaches infinity, t approaches the equilibrium temperature.
6. The method of claim 5, wherein analyzing the cooling process after the task stand-alone operation by the simplified heat balance equation and obtaining a temperature change rule comprises:
taking the cooling process after the task single machine works for analysis, and setting the initial temperature as t 0 Taking the fixed time interval as delta T to obtain the temperature T of a plurality of time nodes 1 、T 2 、T 3 、T 4 ……T ∞ The following rules apply:
the temperature change rule is obtained through the formula.
7. The thermal constraint analysis method of claim 6, wherein the thermal constraint analysis formula is:
wherein, the liquid crystal display device comprises a liquid crystal display device,for balance ratio, Q is the second heat dissipation capacity, Q 0 And the first heat dissipation capacity.
8. The thermal constraint analysis method of claim 7, wherein said performing thermal constraint calculations by said thermal constraint analysis formula comprises:
calculating the single-rail minimum heat generation or heat dissipation capacity of the task single machine through a thermal simulation model, and taking the single-rail minimum heat generation or heat dissipation capacity as the first heat dissipation capacity;
calculating balance proportion of the task single machine through a thermal simulation model;
calculating the second heat dissipation capacity through the thermal constraint analysis formula to obtain the maximum heat dissipation capacity or the maximum allowable heat generation capacity of the task single machine;
and performing on-orbit task planning comprising task single machine thermal constraint analysis based on the maximum heat dissipation capacity or the maximum allowable heat generation.
9. An electronic device, comprising: memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of claims 1 to 8 when the computer program is executed.
10. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method according to any one of claims 1 to 8.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112849437A (en) * | 2021-01-11 | 2021-05-28 | 中国科学院微小卫星创新研究院 | On-orbit thermal control system and thermal control method for spacecraft |
| US20220052756A1 (en) * | 2018-09-10 | 2022-02-17 | Telesat Technology Corporation | Resource deployment optimizer for non-geostationary and/or geostationary communications satellites |
-
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20220052756A1 (en) * | 2018-09-10 | 2022-02-17 | Telesat Technology Corporation | Resource deployment optimizer for non-geostationary and/or geostationary communications satellites |
| CN112849437A (en) * | 2021-01-11 | 2021-05-28 | 中国科学院微小卫星创新研究院 | On-orbit thermal control system and thermal control method for spacecraft |
Non-Patent Citations (2)
| Title |
|---|
| MURAT BULUT, AND NEDIM SÖZBIR: "A practical launcher thermal analysis tool for three-axis stabilized GEO communication satellites", 《2017 8TH INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN SPACE TECHNOLOGIES (RAST)》, pages 317 - 321 * |
| 吴优等: "低轨通信卫星箱式构型设计与散热能力分析", 《哈尔滨工业大学学报》, pages 87 - 94 * |
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