Satellite platform and load multi-dimensional nonlinear cooperative intelligent thermal management method and system

Abstract

The invention provides a satellite platform and load multi-dimensional nonlinear cooperative intelligent thermal management method and system. The method comprises the following steps: establishing a relation model; according to the relation model, constructing a satellite platform and load multi-dimensional nonlinear cooperative intelligent thermal management model; and solving the nonlinear collaborative intelligent thermal management model. According to the method, under the constraint of a load set working mode, load heat consumption and a whole-satellite thermal control heater are subjected to collaborative optimization adjustment in a time domain dimension, and the start-up time sequence and the start-up duration of a satellite load single machine and the thermal control heater serve as adjustment variables of whole-satellite thermal management at the same time; the advantages that the dynamic response of the load single-machine temperature to the load heat consumption is faster than that of a thermal control compensation heater and the steady-state response amplitude is larger are fully utilized, and compared with a conventional satellite thermal management method, the whole satellite thermal management adjustment is faster, the consumption of resources such as power consumption is smaller, and the stability is higher. And the minimization of the heating compensation power consumption of the thermal control subsystem in the power utilization peak periods such as the earth shadow period and the month shadow period is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of satellite intelligent thermal management, and specifically, relates to a multi-dimensional nonlinear collaborative intelligent thermal management method and system for a satellite platform and a payload, in particular to a nonlinear intelligent thermal management method and system for a satellite payload and a platform. Background Art

[0002] With the increasing complexity of space exploration missions, satellite payloads have the characteristics of multiple points, high heat consumption, and high heat flow. In order to effectively solve the problem of heat dissipation during the operation of the payload, each payload is installed on the main heat dissipation surface of the satellite. However, the multi-mode working state of the payload with no time limit and no time limit will cause large dynamic changes in the thermal load of the payload. For the satellite heat dissipation surface when the payload is not turned on, a large thermal control compensation power consumption is required to achieve the control of the low temperature index of the single machine; for the satellite heat dissipation surface when the payload is turned on, on the one hand, it is necessary to consider the heat dissipation problem of the single machine with high heat consumption after the payload is turned on, and it is also necessary to consider the initial startup of the payload. Under the constraint of meeting the operating temperature of the payload, the thermal control compensation power consumption cannot be too high to ensure that the entire satellite has enough energy to meet the needs of different working modes of the payload.

[0003] The document "Intelligent Control Technology in Spacecraft Thermal Control Autonomous Management" discusses the intelligent control strategy of electric heater thermal control autonomous management technology in combination with satellite application examples, and through a survey of domestic and foreign developments, proposes the idea of ​​developing intelligent control technology for thermal control autonomous management in the direction of precision, intelligence, and integration with autonomous management in other areas of spacecraft, but lacks specific implementation methods. The document "Overview of the Development of Thermal Management Technology for Manned Spacecraft" introduces a method based on fluid circuits and convection ventilation to complete the heat collection, transmission, utilization and dissipation of spacecraft, but this thermal management method system is relatively complex, and the fluid circuit system consumes a lot of weight and power consumption resources. The document "Integrated Analysis of Thermal Management Systems for Large Spacecraft" takes a virtual space laboratory as an example and uses numerical simulation methods to simulate the temperature and other parameters of the non-steady-state process of the thermal management system of a large spacecraft, providing a platform for the design of large thermal management systems, energy balance analysis, and power / heat matching analysis, but lacks implementation methods for spacecraft thermal management.

[0004] Patent document "Method and system for saving power consumption during satellite shadow period thermal compensation based on heat capacity difference" (CN112528488A) discloses a method and system for saving power consumption during satellite shadow period thermal compensation based on heat capacity difference, which can save labor costs, save satellite weight, and ensure the safety of satellite electricity use. However, the patent only manages the satellite temperature through a thermal control compensation heater, and the regulation efficiency is limited.

[0005] The patent document "Method and System for Saving Thermal Control Compensation Power in Shadow Period of Non-measurement and Control Arc" (CN111086655A) provides a method for saving thermal control compensation power in shadow period of non-measurement and control arc, which can effectively save thermal control compensation power in satellite shadow period and greatly reduce the risk of battery over-discharge. However, the patent only regulates the compensation heater of the thermal control system, and the adjustment space is limited. Summary of the invention

[0006] In view of the defects in the prior art, the purpose of the present invention is to provide a satellite platform and payload multi-dimensional nonlinear collaborative intelligent thermal management method and system.

[0007] A satellite platform and payload multi-dimensional nonlinear collaborative intelligent thermal management method provided by the present invention includes:

[0008] Step S1: Establish a relationship model;

[0009] Step S2: construct a multi-dimensional nonlinear collaborative intelligent thermal management model of the satellite platform and payload based on the relational model;

[0010] Step S3: Solve the nonlinear collaborative intelligent thermal management model.

[0011] Preferably, the step S1 comprises:

[0012] Single machine heat consumption step: According to the satellite mission planning and payload working mode, the single machine heat consumption P is obtained. i , P i =f1(satellite mission, payload working mode).

[0013] Steps for heat flow outside space: obtain heat flow outside space through simulation calculation according to satellite orbit, attitude and the state of thermal control coating on satellite cabin panel

[0014] Influencing factor step: obtain the influence of the nth heater (n = 1, 2, ..., N) of the thermal control system on the temperature T of the controlled single machine through thermal simulation calculation i Impact Factor

[0015] Heat conduction step: Calculate and obtain λ according to the satellite thermal control design state ji , A j ,δ ji (j=1, 2, ..., M), λ ji , A j ,δ ji are respectively and the controlled temperature T i Thermal conductivity, conduction heat transfer area, and thermal resistance for heat exchange through heat conduction.

[0016] Convective heat transfer step: Calculate h according to the satellite thermal control design state ki and A k (k=1、2、……、K),h ki , A k are respectively and the controlled temperature T i Heat transfer coefficient and convection heat transfer area for heat exchange through convection heat transfer.

[0017] Radiation heat transfer step: ε is calculated based on the satellite thermal control design state li and A l (l=1、2、……、L), ε li , A l are respectively and the controlled temperature T i Radiation factor and radiation heat transfer area for heat exchange through radiation heat transfer.

[0018] The relationship model is a relationship model between each controlled temperature field of the satellite and the heat consumption of the single load, the heat flow outside the space, the state of the thermal control heater, the satellite orbit and attitude:

[0019]

[0020] Among them, (c p m) i represents the thermal capacity of the i-th controlled unit;

[0021] T i represents the temperature of the i-th controlled single unit of the satellite;

[0022] HT n Indicates the power of the nth heater in the thermal control system;

[0023] T j represents the temperature of the jth controlled unit of the satellite;

[0024] δ ji It represents the thermal resistance of the j-th controlled unit of the satellite exchanging heat with the i-th controlled unit by heat conduction;

[0025] T k represents the temperature of the kth controlled unit of the satellite;

[0026] T l Indicates the temperature of the lth controlled single unit of the satellite;

[0027] t represents time;

[0028] The subscript r indicates heat flow;

[0029] L represents the temperature T of the controlled unit i The total number of units with radiation heat exchange;

[0030] K represents the temperature of the controlled unit T i The total number of single machines with convective heat transfer;

[0031] M represents the temperature of the controlled unit T i The total number of single machines with heat conduction and heat exchange;

[0032] N represents the total number of heaters in the whole star;

[0033] σ=5.67×10 -8 is the Boltzmann constant.

[0034] The relationship model is obtained according to the satellite thermal bus network and energy balance principle.

[0035] Preferably, the multi-dimensional nonlinear collaborative intelligent thermal management model of the satellite platform and the payload is based on the sum of the thermal control compensation power consumption of the entire satellite. Minimization is the optimization goal, which is:

[0036] Optimization goal:

[0037] Constraints:

[0038] in, Represents a relational model;

[0039] P i min represents the minimum control value of the heat consumption of the ith unit;

[0040] P i max represents the maximum value of the heat consumption of the ith unit;

[0041] HT n min Indicates the minimum control value of the power of the nth thermal control heater;

[0042] HT n max Indicates the maximum value of the power of the nth thermal control heater;

[0043] T i max It represents the upper limit of the temperature index of the ith controlled single unit of the satellite;

[0044] T i min It represents the lower limit of the temperature index of the ith controlled single unit of the satellite.

[0045] Preferably, in step S3, under the constraint conditions, the optimal adjustment variables of each load unit of the entire satellite and each heater of the thermal control system in the time domain latitude are obtained through an algorithm.

[0046] The solution adopts a genetic algorithm or a particle swarm optimization algorithm.

[0047] The constraint conditions include a predetermined load working mode and a single machine temperature index.

[0048] The algorithm is a nonlinear optimization algorithm in multidimensional space.

[0049] The optimization adjustment variables include the startup sequence and startup duration of each satellite payload unit. j (t′-k dd ), ..., P j (t′-1), R j (t′), P j (t′+1), ...P j (t′+k pp )}j=1,...,M and the start-up sequence and start-up duration of each heater in the thermal control system {HT i (t′-k d ),…HT i (t′-1), HT i (t′+k p )}i=1,...,N;

[0050] Among them, [t′-k dd ,t′+k pp ] represents the startup time domain of the optimized load single machine;

[0051] [t′k d ,t′+k p ] represents the start-up time domain of the optimized thermal control system heater;

[0052] t' represents the control time;

[0053] P j represents the power consumption of the jth single machine;

[0054] HT i represents the ith thermal control system heater;

[0055] k dd Indicates the time that a single machine needs to be started in advance;

[0056] k pp Indicates that the stand-alone machine needs to extend the startup time;

[0057] k d Indicates the time in advance that the thermal control heater needs to be turned on;

[0058] k p Indicates that the thermal control heater needs to be turned on for a longer time.

[0059] According to the present invention, a satellite platform and payload multi-dimensional nonlinear collaborative intelligent thermal management system is provided, comprising:

[0060] Module M1: Establishing relationship model;

[0061] Module M2: Based on the relational model, a multi-dimensional nonlinear collaborative intelligent thermal management model of the satellite platform and payload is constructed;

[0062] Module M3: Solving the nonlinear collaborative intelligent thermal management model.

[0063] Preferably, the module M1 comprises:

[0064] Single machine heat consumption module: obtain the single machine heat consumption P according to the satellite mission planning and payload working mode i , P i =f1(satellite mission, payload working mode).

[0065] Out-of-space heat flow module: obtains out-of-space heat flow based on satellite orbit, attitude and satellite cabin thermal control coating state simulation calculation

[0066] Influencing factor module: thermal simulation calculation obtains the influence of the nth heater (n = 1, 2, ..., N) of the thermal control system on the temperature T of the controlled single machine i Impact Factor

[0067] Heat conduction module: Calculate and obtain λ according to the satellite thermal control design state ji , A j ,δ ji (j=1, 2, ..., M), λ ji , A j ,δ ji are respectively and the controlled temperature T i Thermal conductivity, conduction heat transfer area, and thermal resistance for heat exchange through heat conduction.

[0068] Convective heat transfer module: Calculate and obtain h according to the satellite thermal control design state ki and A k (k=1、2、……、K),h ki , A k are respectively and the controlled temperature T i Heat transfer coefficient and convection heat transfer area for heat exchange through convection heat transfer.

[0069] Radiation heat transfer module: ε is calculated based on the satellite thermal control design state li and A l (l=1、2、……、L), ε li , A lare respectively and the controlled temperature T i Radiation factor and radiation heat transfer area for heat exchange through radiation heat transfer.

[0070] The relationship model is a relationship model between each controlled temperature field of the satellite and the heat consumption of the single load, the heat flow outside the space, the state of the thermal control heater, the satellite orbit and attitude:

[0071]

[0072] Among them, (c p m) i represents the thermal capacity of the i-th controlled unit;

[0073] T i represents the temperature of the i-th controlled single unit of the satellite;

[0074] HT n Indicates the power of the nth heater in the thermal control system;

[0075] T j represents the temperature of the jth controlled unit of the satellite;

[0076] δ ji It represents the thermal resistance of the j-th controlled unit of the satellite exchanging heat with the i-th controlled unit by heat conduction;

[0077] T k represents the temperature of the kth controlled unit of the satellite;

[0078] T l Indicates the temperature of the lth controlled single unit of the satellite;

[0079] t represents time;

[0080] The subscript r indicates heat flow;

[0081] L represents the temperature T of the controlled unit i The total number of units with radiation heat exchange;

[0082] K represents the temperature of the controlled unit T i The total number of single machines with convective heat transfer;

[0083] M represents the temperature of the controlled unit T i The total number of single machines with heat conduction and heat exchange;

[0084] N represents the total number of heaters in the whole star;

[0085] σ=5.67×10 -8 is the Boltzmann constant.

[0086] The relationship model is obtained according to the satellite thermal bus network and energy balance principle.

[0087] Preferably, the multi-dimensional nonlinear collaborative intelligent thermal management model of the satellite platform and the payload is based on the sum of the thermal control compensation power consumption of the entire satellite. Minimization is the optimization goal, which is:

[0088] Optimization goal:

[0089] Constraints:

[0090] in, Represents a relational model;

[0091] P i min represents the minimum control value of the heat consumption of the ith unit;

[0092] P i max represents the maximum value of the heat consumption of the ith unit;

[0093] HT n min Indicates the minimum control value of the power of the nth thermal control heater;

[0094] HT n max Indicates the maximum value of the power of the nth thermal control heater;

[0095] T i max It represents the upper limit of the temperature index of the ith controlled single unit of the satellite;

[0096] T i min It represents the lower limit of the temperature index of the ith controlled single unit of the satellite.

[0097] Preferably, in the module M3, under constraints, an algorithm is used to obtain the optimal adjustment variables of each load unit of the entire satellite and each heater of the thermal control system in the time domain latitude.

[0098] The solution adopts a genetic algorithm or a particle swarm optimization algorithm.

[0099] The constraint conditions include a predetermined load working mode and a single machine temperature index.

[0100] The algorithm is a nonlinear optimization algorithm in multidimensional space.

[0101] The optimization adjustment variables include the startup sequence and startup duration of each satellite payload unit. j (t′-k dd ), ..., P j (t′-1), P j (t′), Pj (t′+1), ..., P j (t′+k pp )}j=1,...,M and the start-up sequence and start-up duration of each heater in the thermal control system {HT i (t′-k d ), ...HT i (t′-1), HT i (t′), HT i (t′+1),…HT i (t′+k p )}i=1,...,N;

[0102] Among them, [t′-k dd ,t′+k pp ] represents the startup time domain of the optimized load single machine;

[0103] [t′-k d ,t′+k p ] represents the start-up time domain of the optimized thermal control system heater;

[0104] t' represents the control time;

[0105] P j represents the power consumption of the jth single machine;

[0106] HT i represents the ith thermal control system heater;

[0107] k dd Indicates the time that a single machine needs to be started in advance;

[0108] k pp Indicates that the stand-alone machine needs to extend the startup time;

[0109] k d Indicates the time in advance that the thermal control heater needs to be turned on;

[0110] k p Indicates that the thermal control heater needs to be turned on for a longer time.

[0111] According to a computer-readable storage medium storing a computer program provided by the present invention, when the computer program is executed by a processor, the steps of the multi-dimensional nonlinear collaborative intelligent thermal management method of the satellite platform and the payload are implemented.

[0112] A satellite system provided according to the present invention includes the satellite platform and the payload multi-dimensional nonlinear collaborative intelligent thermal management system, or the computer-readable storage medium storing a computer program.

[0113] Compared with the prior art, the present invention has the following beneficial effects:

[0114] 1. The present invention fully utilizes the load heat consumption in the time domain dimension and the whole-star thermal control heater as the regulating variables of thermal management, and utilizes the advantages that the dynamic response of the load unit temperature to the load's own heat consumption is faster than that of the thermal control system compensation heater and the steady-state response amplitude is larger.

[0115] 2. Compared with conventional thermal management methods, the present invention can, under the constraints of the established working mode of the load, coordinately optimize and adjust the load heat consumption and the thermal control heater of the entire satellite in the time domain dimension, with the goal of minimizing the power consumption of thermal control compensation heating, and can complete the thermal management of the entire satellite faster and with lower power consumption.

[0116] 3. Under the constraints of the established working mode of the load and the temperature indicators of each single machine, the present invention adopts a nonlinear optimization algorithm in multidimensional space to obtain the optimal startup time series of the whole satellite heater and each load unit and the optimal combination configuration of the load heat consumption and the heater in the time domain, so as to minimize the heating compensation power consumption of the thermal control subsystem during peak electricity consumption periods such as the ground and lunar shadow periods.

[0117] 4. The present invention not only fully utilizes the rapid response characteristics of the temperature of a single machine to the heat consumption of the load, but also retains the global influence of the thermal control heater on the temperature field of the entire satellite, thereby achieving temperature control of all single machines in the entire satellite with minimal power consumption resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0118] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0119] Figure 1 Schematic diagram of the implementation process of the nonlinear collaborative intelligent thermal management method for satellite platform and payload. DETAILED DESCRIPTION

[0120] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0121] According to the present invention, a satellite platform and payload multi-dimensional nonlinear collaborative intelligent thermal management method is provided. Figure 1 As shown, including the following:

[0122] Step S1: Based on the analysis of the satellite thermal bus network and energy balance principle, a relationship model between each controlled temperature field of the satellite and the heat consumption of the single payload, the heat flow outside the space, the state of the thermal control heater, the satellite orbit and attitude is established.

[0123] The temperature of each satellite controlled unit T i (i=1、2、...、M) and single machine heat consumption P i 、Heat flow outside space Heater power of each circuit of thermal control system HT n (n=1, 2, ..., N) relational model:

[0124]

[0125] Among them, (c p m) i represents the thermal capacity of the ith controlled unit, obtained according to its own physical characteristics;

[0126] T j represents the temperature of the jth controlled unit of the satellite;

[0127] δ ji It represents the thermal resistance of the j-th controlled unit of the satellite exchanging heat with the i-th controlled unit by heat conduction;

[0128] T k represents the temperature of the kth controlled unit of the satellite;

[0129] T l Indicates the temperature of the lth controlled single unit of the satellite;

[0130] t represents time;

[0131] The subscript r indicates heat flow;

[0132] L represents the temperature T of the controlled unit i The total number of units with radiation heat exchange;

[0133] K represents the temperature of the controlled unit T i The total number of single machines with convective heat transfer;

[0134] M represents the temperature of the controlled unit T i The total number of single machines with heat conduction and heat exchange;

[0135] N represents the total number of heaters in the whole star.

[0136] The relationship model belongs to the whole-satellite temperature field relationship model under the coordinated drive of load heat consumption and heater.

[0137] Single machine heat consumption step: According to the satellite mission planning and payload working mode, the single machine heat consumption P is obtained. i , that is, P i =f1(satellite mission, payload working mode).

[0138] Steps for heat flow outside space: obtain heat flow outside space through simulation calculation according to satellite orbit, attitude and the state of thermal control coating on satellite cabin panel Right now (orbit, attitude, thermal control coating performance, solar irradiance constant).

[0139] Influencing factor step: obtained through thermal simulation calculation is the temperature T of the controlled unit by the nth heater (n=1, 2, ..., N) of the thermal control system i The impact factor.

[0140] Heat conduction step: λ ji , A j and δ ji (j=1, 2, ..., M) are respectively related to the controlled temperature T i The thermal conductivity, conduction heat transfer area and thermal resistance of heat exchange by heat conduction are calculated according to the satellite thermal control design status.

[0141] Convective heat transfer step: h ki and A k (k=1, 2, ..., K) are respectively related to the controlled temperature T i The heat transfer coefficient and convection heat transfer area of ​​heat exchange by convection heat transfer are calculated according to the satellite thermal control design status.

[0142] Radiation heat transfer step: ε li and A l (l=1, 2, ..., L) are respectively related to the controlled temperature T i The radiation factor and radiation heat transfer area of ​​heat exchange by radiation heat transfer are calculated based on the satellite thermal control design state. σ=5.67×10 -8 is the Boltzmann constant.

[0143] The satellite is controlled to have a single temperature T i Heat consumption P i 、Heat flow outside space Heater power of each circuit of thermal control system HT n The relationship model of (n=1, 2, ..., N) is obtained according to the satellite thermal bus network and energy balance principle.

[0144] Step S2: Construct a multi-dimensional nonlinear collaborative intelligent thermal management model of the satellite platform and payload.

[0145] The multi-dimensional nonlinear collaborative intelligent thermal management model of the satellite platform and payload is based on the sum of the thermal control compensation power consumption of the entire satellite. Minimization is the optimization goal, that is:

[0146] Optimization goal:

[0147] Constraints:

[0148] The constraint condition includes the satellite controlled temperature field T described in step S1 i Calculation model, minimum control value P of each unit heat consumption i min and the maximum value P i max , the minimum value of the thermal control heater power HT n min and maximum HT n max , the upper limit of the temperature index of each controlled satellite unit T i max and lower limit T i min Require.

[0149] Step S3: Solve the nonlinear collaborative intelligent thermal management model.

[0150] Under the established working mode of the load, the load heat consumption and the heater power consumption are used as optimization adjustment variables to obtain the optimal startup sequence and startup duration of each load unit and each heater of the thermal control system in the time domain.

[0151] Specifically, the load heat consumption and the whole satellite heater in the time domain dimension are used as the optimization adjustment variables of thermal management. The goal is to minimize the heating power consumption of thermal control compensation. Under the constraints of the established working mode of the load and the temperature index of the single machine, a nonlinear optimization algorithm in multidimensional space is used to obtain the optimal startup time series of the whole satellite heater and each load unit.

[0152] The optimization adjustment variables include the startup sequence and startup duration of each satellite payload unit. j (t′-k dd ), ..., P j (t′-1), P j (t′), P j (t′+1), ...P j (t′+k pp )}j=1,...,M and the start-up sequence and start-up duration of each heater in the thermal control system {HT i (t′-k d ),…HT i (t′-1), HT i (t′), HT i (t′+1),…HT i (t′+k p )}i=1,...,N;

[0153] Among them, [t′-k dd ,t′+kpp ] represents the startup time domain of the optimized load single machine;

[0154] [t′-k d ,t′+k p ] represents the start-up time domain of the optimized thermal control system heater;

[0155] t' represents the control time;

[0156] P j represents the power consumption of the jth single machine;

[0157] HT i represents the ith thermal control system heater;

[0158] k dd Indicates the time that a single machine needs to be started in advance;

[0159] k pp Indicates that the stand-alone machine needs to extend the startup time;

[0160] k d Indicates the time in advance that the thermal control heater needs to be turned on;

[0161] k p Indicates that the thermal control heater needs to be turned on for a longer time.

[0162] The solution adopts a genetic algorithm or a particle swarm optimization algorithm.

[0163] The present invention also provides a satellite platform and payload multidimensional nonlinear collaborative intelligent thermal management system, which can be implemented by executing the process steps of the satellite platform and payload multidimensional nonlinear collaborative intelligent thermal management method, that is, technical personnel in this field can understand the satellite platform and payload multidimensional nonlinear collaborative intelligent thermal management method as a preferred implementation mode of the satellite platform and payload multidimensional nonlinear collaborative intelligent thermal management system.

[0164] Those skilled in the art know that, in addition to realizing the system and its various devices, modules, and units provided by the present invention in a purely computer-readable program code, it is entirely possible to realize the same functions in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for realizing various functions can also be regarded as structures within the hardware component; the devices, modules, and units for realizing various functions can also be regarded as both software modules for realizing the method and structures within the hardware component.

[0165] According to the present invention, a satellite platform and payload multi-dimensional nonlinear collaborative intelligent thermal management system is provided, comprising:

[0166] Module M1: Establishing relationship model;

[0167] Module M2: Based on the relational model, a multi-dimensional nonlinear collaborative intelligent thermal management model of the satellite platform and payload is constructed;

[0168] Module M3: Solving the nonlinear collaborative intelligent thermal management model.

[0169] In more preferred embodiments, the module M1 includes:

[0170] Single machine heat consumption module: obtain the single machine heat consumption P according to the satellite mission planning and payload working mode i , P i =f1(satellite mission, payload working mode).

[0171] Out-of-space heat flow module: obtains out-of-space heat flow based on satellite orbit, attitude and satellite cabin thermal control coating state simulation calculation

[0172] Influencing factor module: thermal simulation calculation obtains the influence of the nth heater (n = 1, 2, ..., N) of the thermal control system on the temperature T of the controlled single machine i Impact Factor

[0173] Heat conduction module: Calculate and obtain λ according to the satellite thermal control design state ji , A j ,δ ji (j=1, 2, ..., M), λ ji , A j ,δ ji are respectively and the controlled temperature T i Thermal conductivity, conduction heat transfer area, and thermal resistance for heat exchange through heat conduction.

[0174] Convective heat transfer module: Calculate and obtain h according to the satellite thermal control design state ki and A k (k=1、2、……、K),h ki , A k are respectively and the controlled temperature T i Heat transfer coefficient and convection heat transfer area for heat exchange through convection heat transfer.

[0175] Radiation heat transfer module: ε is calculated based on the satellite thermal control design state li and A l (l=1、2、……、L), ε li , Al are respectively and the controlled temperature T i Radiation factor and radiation heat transfer area for heat exchange through radiation heat transfer.

[0176] The relationship model is a relationship model between each controlled temperature field of the satellite and the heat consumption of the single load, the heat flow outside the space, the state of the thermal control heater, the satellite orbit and attitude:

[0177]

[0178] Among them, (c p m) i represents the thermal capacity of the i-th controlled unit;

[0179] T i represents the temperature of the i-th controlled single unit of the satellite;

[0180] HT n Indicates the power of the nth heater in the thermal control system;

[0181] T j represents the temperature of the jth controlled unit of the satellite;

[0182] δ ji It represents the thermal resistance of the j-th controlled unit of the satellite exchanging heat with the i-th controlled unit by heat conduction;

[0183] T k represents the temperature of the kth controlled unit of the satellite;

[0184] T l Indicates the temperature of the lth controlled single unit of the satellite;

[0185] t represents time;

[0186] The subscript r indicates heat flow;

[0187] L represents the temperature T of the controlled unit i The total number of units with radiation heat exchange;

[0188] K represents the temperature of the controlled unit T i The total number of single machines with convective heat transfer;

[0189] M represents the temperature of the controlled unit T i The total number of single machines with heat conduction and heat exchange;

[0190] N represents the total number of heaters in the whole star;

[0191] σ=5.67×10 -8 is the Boltzmann constant.

[0192] The relationship model is obtained according to the satellite thermal bus network and energy balance principle.

[0193] In more preferred embodiments, the multi-dimensional nonlinear collaborative intelligent thermal management model of the satellite platform and the payload is based on the sum of the thermal control compensation power consumption of the entire satellite. Minimization is the optimization goal, which is:

[0194] Optimization goal:

[0195] Constraints:

[0196] in, Represents a relational model;

[0197] P i min represents the minimum control value of the heat consumption of the ith unit;

[0198] P i max represents the maximum value of the heat consumption of the ith unit;

[0199] HT n min Indicates the minimum control value of the power of the nth thermal control heater;

[0200] HT n max Indicates the maximum value of the power of the nth thermal control heater;

[0201] T i max It represents the upper limit of the temperature index of the ith controlled single unit of the satellite;

[0202] T i min It represents the lower limit of the temperature index of the ith controlled single unit of the satellite.

[0203] In more preferred examples, in the module M3, under constraints, an algorithm is used to obtain the optimal adjustment variables of each load unit of the entire satellite and each heater of the thermal control system in the time domain latitude.

[0204] The solution adopts a genetic algorithm or a particle swarm optimization algorithm.

[0205] The constraint conditions include a predetermined load working mode and a single machine temperature index.

[0206] The algorithm is a nonlinear optimization algorithm in multidimensional space.

[0207] The optimization adjustment variables include the startup sequence and startup duration of each satellite payload unit. j (t′-k dd ), ..., P j (t′-1), P j(t′), P j (t′+1), ...P j (t′+k pp )}j=1,...,M and the start-up sequence and start-up duration of each heater in the thermal control system {HT i (t′-k d ),…HT i (t′-1), HT i (t′), HT i (t′+1),…HT i (t′+k p )}i=1,...,N;

[0208] Among them, [t′-k dd ,t′+k pp ] represents the startup time domain of the optimized load single machine;

[0209] [t′-k d ,t′+k p ] represents the start-up time domain of the heater of the thermal control system obtained by optimization;

[0210] t' represents the control time;

[0211] P j represents the power consumption of the jth single machine;

[0212] HT i represents the ith thermal control system heater;

[0213] k dd Indicates the time that a single machine needs to be started in advance;

[0214] k pp Indicates that the stand-alone machine needs to extend the startup time;

[0215] k d Indicates the time in advance that the thermal control heater needs to be turned on;

[0216] k p Indicates that the thermal control heater needs to be turned on for a longer time.

[0217] By establishing a temperature field relationship model of the entire satellite under the coordinated drive of load heat consumption and heater, and obtaining the optimal combination configuration of load heat consumption and heater in the time domain based on the global multidimensional nonlinear optimization method, we can better solve the problems of high power consumption of the entire satellite, sharp increase in resource allocation requirements and inability to meet global temperature control.

[0218] According to a computer-readable storage medium storing a computer program provided by the present invention, when the computer program is executed by a processor, the steps of the multi-dimensional nonlinear collaborative intelligent thermal management method of the satellite platform and the payload are implemented.

[0219] A satellite system provided according to the present invention includes the satellite platform and the payload multi-dimensional nonlinear collaborative intelligent thermal management system, or the computer-readable storage medium storing a computer program.

[0220] The satellite platform and payload multi-dimensional nonlinear collaborative intelligent thermal management method and system provided by the present invention, under the constraints of the payload's established working mode, collaboratively optimize and adjust the payload heat consumption and the whole satellite thermal control heater in the time domain dimension, and use the startup timing and startup duration of the satellite payload unit and the thermal control heater as adjustment variables for the thermal management of the whole satellite at the same time, and fully utilize the advantages that the dynamic response of the payload unit temperature to the payload's own heat consumption is faster than that of the thermal control compensation heater and the steady-state response amplitude is larger. Compared with conventional satellite thermal management methods, the thermal management adjustment of the whole satellite is faster, and the consumption of resources such as power consumption is smaller, and the heating compensation power consumption of the thermal control subsystem during peak electricity consumption periods such as the Earth and lunar shadow periods is minimized.

[0221] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A satellite platform and payload multi-dimensional nonlinear collaborative intelligent thermal management method, characterized in that: include: Step S1: Establish a relationship model; Step S2: construct a multi-dimensional nonlinear collaborative intelligent thermal management model of the satellite platform and payload based on the relational model; Step S3: Solve the nonlinear collaborative intelligent thermal management model.

2. The satellite platform and payload multi-dimensional nonlinear collaborative intelligent thermal management method according to claim 1 is characterized in that: The step S1 comprises: Single machine heat consumption step: According to the satellite mission planning and payload working mode, the single machine heat consumption P is obtained. i , P i =f1(satellite mission, payload working mode); Steps for heat flow outside space: obtain heat flow outside space through simulation calculation according to satellite orbit, attitude and the state of thermal control coating on satellite cabin panel (orbit, attitude, thermal control coating performance, solar irradiance constant); Influencing factor step: Through thermal simulation calculation, obtain the influence of the nth heater (n = 1, 2, ..., N) of the thermal control system on the temperature T of the controlled single machine i Impact Factor Heat conduction step: Calculate and obtain λ according to the satellite thermal control design state ji , A j , δ ji (j=1, 2, ..., M), λ ji , A j , δ ji are respectively and the controlled temperature T i Thermal conductivity, conduction heat transfer area, and thermal resistance for heat exchange by heat conduction; Convective heat transfer step: Calculate h according to the satellite thermal control design state ki and A k (k=1、2、……、K),h ki , A k are respectively and the controlled temperature T i Heat transfer coefficient and convection heat transfer area for heat exchange by convection heat transfer; Radiation heat transfer step: ε is calculated based on the satellite thermal control design state li and A l (l=1、2、……、L), ε li , A l are respectively and the controlled temperature T i The radiation factor and radiation heat transfer area of ​​heat exchange by radiation heat transfer; The relationship model is a relationship model between each controlled temperature field of the satellite and the heat consumption of the single load, the heat flow outside the space, the state of the thermal control heater, the satellite orbit and attitude: Among them, (c p m) i represents the thermal capacity of the i-th controlled unit; T i represents the temperature of the i-th controlled single unit of the satellite; HT n Indicates the power of the nth heater in the thermal control system; T j represents the temperature of the jth controlled unit of the satellite; δ ji It represents the thermal resistance of the j-th controlled unit of the satellite exchanging heat with the i-th controlled unit by heat conduction; T k represents the temperature of the kth controlled unit of the satellite; T l Indicates the temperature of the lth controlled single unit of the satellite; t represents time; The subscript r indicates heat flow; L represents the temperature T of the controlled unit i The total number of units with radiation heat exchange; K represents the temperature of the controlled unit T i The total number of single machines with convective heat transfer; M represents the temperature of the controlled unit T i The total number of single machines with heat conduction and heat exchange; N represents the total number of heaters in the whole star; σ=5.67×10 -8 is the Boltzmann constant; The relationship model is obtained according to the satellite thermal bus network and energy balance principle.

3. The satellite platform and payload multi-dimensional nonlinear collaborative intelligent thermal management method according to claim 1 is characterized in that: The multi-dimensional nonlinear collaborative intelligent thermal management model of the satellite platform and payload is based on the sum of the thermal control compensation power consumption of the entire satellite. Minimization is the optimization goal, which is: in, Represents a relational model; P i min represents the minimum control value of the heat consumption of the ith unit; P i max represents the maximum value of the heat consumption of the ith unit; HT n min Indicates the minimum control value of the power of the nth thermal control heater; HT n max Indicates the maximum value of the power of the nth thermal control heater; T i max It represents the upper limit of the temperature index of the ith controlled single unit of the satellite; T i min It represents the lower limit of the temperature index of the ith controlled single unit of the satellite.

4. The satellite platform and payload multi-dimensional nonlinear collaborative intelligent thermal management method according to claim 1, characterized in that: In step S3, under the constraint conditions, the optimal adjustment variables of each load unit of the entire satellite and each heater of the thermal control system in the time domain latitude are obtained through an algorithm; The solution adopts genetic algorithm or particle swarm optimization algorithm; The constraint conditions include a predetermined load working mode and a single machine temperature index; The algorithm is a nonlinear optimization algorithm in multidimensional space; The optimized adjustment variables include the startup sequence and startup duration of each satellite payload unit {Pj(t′-kdd), ..., Pj(t′-1), Pj(t′), Pj(t′+1), ...Pj(t′+kpp)}j=1, ..., M and the startup sequence and startup duration of each heater of the thermal control system Among them, [t′-k dd , t′+k pp ] represents the startup time domain of the optimized load single machine; [t′-k d , t+k p ] represents the start-up time domain of the heater of the thermal control system obtained by optimization; t' represents the control time; P j represents the power consumption of the Jth single machine; HT i represents the ith thermal control system heater; k dd Indicates the time that a single machine needs to be started in advance; k pp Indicates that the stand-alone machine needs to extend the startup time; k d Indicates the time in advance that the thermal control heater needs to be turned on; k p Indicates that the thermal control heater needs to be turned on for a longer time.

5. A satellite platform and payload multi-dimensional nonlinear collaborative intelligent thermal management system, characterized in that: include: Module M1: Establishing relationship model; Module M2: Based on the relational model, a multi-dimensional nonlinear collaborative intelligent thermal management model of the satellite platform and payload is constructed; Module M3: Solving the nonlinear collaborative intelligent thermal management model.

6. The satellite platform and payload multi-dimensional nonlinear collaborative intelligent thermal management system according to claim 5, characterized in that: The module M1 comprises: Single machine heat consumption module: obtain the single machine heat consumption P according to the satellite mission planning and payload working mode i , P i =f1(satellite mission, payload working mode); Out-of-space heat flow module: obtains out-of-space heat flow based on satellite orbit, attitude and satellite cabin thermal control coating state simulation calculation (orbit, attitude, thermal control coating performance, solar irradiance constant); Influencing factor module: thermal simulation calculation obtains the influence of the nth heater (n = 1, 2, ..., N) of the thermal control system on the temperature T of the controlled single machine i Impact Factor Heat conduction module: Calculate and obtain λ according to the satellite thermal control design state ji , A j , δ ji (j=1, 2, ..., M), λ ji , A j , δ ji are respectively and the controlled temperature T i Thermal conductivity, conduction heat transfer area, and thermal resistance for heat exchange by heat conduction; Convective heat transfer module: Calculate and obtain h according to the satellite thermal control design state ki and A k (k=1、2、……、K),h ki , A k are respectively and the controlled temperature T i Heat transfer coefficient and convection heat transfer area for heat exchange by convection heat transfer; Radiation heat transfer module: ε is calculated based on the satellite thermal control design state li and A l (l=1、2、……、L), ε li , A l are respectively and the controlled temperature T i The radiation factor and radiation heat transfer area of ​​heat exchange by radiation heat transfer; The relationship model is a relationship model between each controlled temperature field of the satellite and the heat consumption of the single load, the heat flow outside the space, the state of the thermal control heater, the satellite orbit and attitude: Among them, (c p m) i represents the thermal capacity of the i-th controlled unit; T i represents the temperature of the i-th controlled single unit of the satellite; HT n Indicates the power of the nth heater in the thermal control system; T j represents the temperature of the jth controlled unit of the satellite; δ ji It represents the thermal resistance of the j-th controlled unit of the satellite exchanging heat with the i-th controlled unit by heat conduction; T k represents the temperature of the kth controlled unit of the satellite; T l Indicates the temperature of the lth controlled single unit of the satellite; t represents time; The subscript r indicates heat flow; L represents the temperature T of the controlled unit i The total number of units with radiation heat exchange; K represents the temperature of the controlled unit T i The total number of single machines with convective heat transfer; M represents the temperature of the controlled unit T i The total number of single machines with heat conduction and heat exchange; N represents the total number of heaters in the whole star; σ=5.67×10 -8 is the Boltzmann constant; The relationship model is obtained according to the satellite thermal bus network and energy balance principle.

7. The satellite platform and payload multi-dimensional nonlinear collaborative intelligent thermal management system according to claim 5, characterized in that: The multi-dimensional nonlinear collaborative intelligent thermal management model of the satellite platform and payload is based on the sum of the thermal control compensation power consumption of the entire satellite. Minimization is the optimization goal, which is: in, Represents a relational model; P i min represents the minimum control value of the heat consumption of the ith unit; P i max represents the maximum value of the heat consumption of the ith unit; HT n min Indicates the minimum control value of the power of the nth thermal control heater; HT n max Indicates the maximum value of the power of the nth thermal control heater; T i max It represents the upper limit of the temperature index of the ith controlled single unit of the satellite; T i min It represents the lower limit of the temperature index of the ith controlled single unit of the satellite.

8. The satellite platform and payload multi-dimensional nonlinear collaborative intelligent thermal management system according to claim 5, characterized in that: In the module M3, under the constraint conditions, the optimal adjustment variables of each load unit of the entire satellite and each heater of the thermal control system in the time domain latitude are obtained through an algorithm; The solution adopts genetic algorithm or particle swarm optimization algorithm; The constraint conditions include a predetermined load working mode and a single machine temperature index; The algorithm is a nonlinear optimization algorithm in multidimensional space; The optimization adjustment variables include the startup sequence and startup duration of each satellite payload unit. j (t′-k dd ), ..., P j (t′-1), P j (t′), P j (t′+1), ...P j (t′+k pp )} j＝1，...，M The startup sequence and startup duration of each heater in the thermal control system Among them, [t′-k dd , t′+k pp ] represents the startup time domain of the optimized load single machine; [t′-k d , t′+k p ] represents the start-up time domain of the heater of the thermal control system obtained by optimization; t' represents the control time; P j represents the power consumption of the jth single machine; HT i represents the ith thermal control system heater; k dd Indicates the time that a single machine needs to be started in advance; k pp Indicates that the stand-alone machine needs to extend the startup time; k d Indicates the time in advance that the thermal control heater needs to be turned on; k p Indicates that the thermal control heater needs to be turned on for a longer time.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the satellite platform and payload multi-dimensional nonlinear collaborative intelligent thermal management method described in any one of claims 1 to 4 are implemented.

10. A satellite system, characterized in that: It comprises the satellite platform and payload multi-dimensional nonlinear collaborative intelligent thermal management system as described in any one of claims 5 to 8, or the computer-readable storage medium storing a computer program as described in claim 9.

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