CO2 space efficient thermal management system and optimization method thereof
By adopting CO2 space efficient thermal management system and genetic algorithm optimization technology in the spatial distributed heat source system, the challenge of efficient heat exchange and lightweight in existing systems is solved, and more efficient and lightweight thermal management effects are achieved.
Patent Information
- Application Number
- CN202510297755.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-13
- Publication Date
- 2025-05-16
AI Technical Summary
The existing intermittent high-power thermal management system with spatially distributed heat sources is difficult to ensure the lightweight system and reduce energy consumption while achieving efficient heat exchange.
The CO2 space efficient thermal management system is adopted, combined with the pump-drive cooling cycle and the heat pump heat dissipation cycle, and the heat dissipation temperature in the radiating radiator is achieved through the hub function of the phase change cooling equipment, and the heat dissipation temperature in the radiated radiator is increased through the heat pump cycle. At the same time, genetic algorithms are used to optimize the parameters of radiation radiator, heat retractor and exhaust pressure to achieve optimal overall performance of the system.
It realizes that while ensuring efficient heat dissipation, it reduces the emission mass and volume of the radiation radiator, reduces the energy consumption and total mass of the system, and provides a more efficient and lighter thermal management solution.
Smart Images
Figure CN120012607A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the field of thermal management of space devices and relates to a CO2 space efficient thermal management system and an optimization method thereof. Background Art
[0002] With the development of space technology, the output power of distributed heat sources in space equipment has gradually increased, and the heat dissipation power has increased accordingly, which has put forward higher demands on space heat dissipation devices and has become one of the bottlenecks that currently hinder the development of space technology. Heat pump technology has become a research hotspot in space thermal management technology because it can significantly increase the heat dissipation temperature of the radiant radiator and enhance the heat dissipation efficiency per unit area of the radiant radiator, thereby effectively reducing the volume and emission mass of the radiant radiator while ensuring the heat dissipation. In addition, the high energy density and excellent heat storage capacity of phase change materials give them significant advantages in space heat dissipation applications, making them one of the effective methods to solve the problem of intermittent high-power heat dissipation under limited space resource conditions. Therefore, the combination of heat pump and phase change cold storage has become one of the heat dissipation technologies with broad development prospects.
[0003] However, the introduction of heat pump systems and phase change cold storage devices will add additional thermal management components and mass burden, and also increase the complexity of the system. In addition, the use of compressors consumes additional energy, and the heat dissipation of radiant radiators must also include compressor energy. Existing distributed heat source intermittent high-power thermal management systems are difficult to achieve efficient heat exchange while ensuring the lightweight of the system and reducing energy consumption. Summary of the invention
[0004] The purpose of the present invention is to overcome the shortcomings of the above-mentioned prior art and provide a CO2 space efficient thermal management system and an optimization method thereof to solve the heat dissipation problem of spatial distributed heat sources.
[0005] In order to achieve the above object, the present invention adopts the following technical solutions: A method for optimizing a CO2 space efficient thermal management system comprises the following steps: S1, obtain system initialization parameters and generate the initial population of genetic algorithm; S2, based on the initial population, performs thermodynamic cycle calculation of the heat pump cooling system under constraint conditions, obtains the state point parameters of the system, and further calculates the fitness function value of the system; S3, mutate the genetic algorithm population and obtain a new population through cross evolution; S4, based on the new population, the thermodynamic cycle calculation of the heat pump cooling system is performed under the constraint conditions to obtain the state point parameters of the system, and further calculate the fitness function value of the system; S5, compares the fitness function values obtained in S2 and S4, and selects the population with a better fitness function value as the basis for the next population mutation; S6, repeat S3-S5 until the difference between the function values of the two fitness functions is less than the convergence error, output the parameters corresponding to the current optimal solution, and achieve the optimal comprehensive performance of the thermal management system.
[0006] A further improvement of the present invention is: Preferably, the initial population and the new population both include the regenerator heat exchange area, the radiant heat sink heat exchange area and the exhaust pressure.
[0007] Preferably, the calculation formula of the fitness function is:
[0008] in, is the total mass of the original thermal management system, kg; Total power consumption for pumping and motion maintenance of the original thermal management system, W; is the mass of the radiant heat sink, kg; , kg; is the total mass of the remaining components of the thermal management system, kg; Energy consumption to drive the thermal management components, kW / kg; is the power consumption of the compressor, W; k m , n m , k p , n p All are calculation coefficients.
[0009] Preferably, in S2, based on the initialization population, the mass of the radiation radiator, and the energy consumption to drive the movement of thermal management components;
[0010]
[0011]
[0012] in, is the heat transfer area of the radiator, m 2 ; is the heat exchange area of the regenerator, m 2 ; is the mass of the radiant heat sink, kg; , kg; is the total mass of the remaining components of the thermal management system, kg; Energy consumption to drive the movement of thermal management components; The energy consumption required to drive the unit mass of space equipment, kW / kg, , , and All are calculation coefficients.
[0013] Preferably, the constraint condition is:
[0014]
[0015]
[0016]
[0017]
[0018] in, P is the pressure, MPa; T is temperature, °C; x is dryness; , and is the calculation limit.
[0019] Preferably, in S3, during the crossover evolution process, two adjacent chromosomes in the population cross over to generate a random number r between 0 and 1. , the two adjacent chromosomes cross over, otherwise the paternal genes are retained.
[0020] Preferably, in S3, during the mutation process, for each individual in the population, a 0~1 random number r is generated for each gene in turn. If , then the genetic variation of individuals in the population is If the random number in , no mutation is performed.
[0021] Preferably, in S5, the population with a better fitness function is a population with a smaller fitness function value.
[0022] Preferably, in S6, when the convergence error satisfies the following expression, the parameters corresponding to the current optimal solution are output:
[0023] in, For the population, is the convergence error, g( x ) is the fitness function.
[0024] A CO2 space efficient thermal management system for implementing the above optimization method comprises a phase change cold storage device, the phase change cold storage device comprises a cold source and a heat source for exchanging heat with each other, the cold source outlet of the phase change cold storage device is connected to the cold source inlet of a regenerator, the cold source outlet of the regenerator is connected to a CO2 compressor, the outlet of the CO2 compressor is connected to a radiation heat exchanger, the outlet of the radiation heat exchanger is connected to the heat source inlet of the regenerator, and the heat source outlet of the regenerator is connected to the cold source inlet of the phase change cold storage device; The heat source outlet of the phase change cold storage device is connected to the coolant storage tank, the coolant storage tank outlet is connected to the CO2 working fluid pump, and the CO2 working fluid pump outlet is connected to the heat source liquid cooling plate.
[0025] Compared with the prior art, the present invention has the following beneficial effects: The present invention discloses a CO2 space high-efficiency thermal management system, which includes a pump-driven cooling cycle and a heat pump heat dissipation cycle. The system realizes flexible regulation of heat dissipation through the pivotal role of a phase-change cold storage device, and increases the heat dissipation temperature in a radiation radiator through a heat pump cycle, thereby enhancing the heat dissipation capacity and reducing the emission mass of the radiation radiator. The heat pump heat dissipation cycle adopts a regenerator, which can avoid liquid in the suction and effectively increase the system life, and can achieve higher compressor suction temperature and exhaust temperature, further helping to reduce the area of the radiation radiator. In addition, under certain working conditions, the energy efficiency ratio of the system can be improved and the power consumption of the compressor can be reduced.
[0026] The present invention discloses a method for optimizing a high-efficiency thermal management system for CO2 space. The method uses a genetic algorithm to optimize the three parameters of the radiant heat sink, the regenerator, and the exhaust pressure, and uses a comprehensive performance evaluation factor as the overall evaluation standard for the system's emission quality and energy consumption, ultimately achieving the collaborative optimization goals of reducing the emission quality and energy consumption of the thermal management system. The method minimizes the energy consumption and emission quality of the distributed heat source intermittent high-power thermal management system, providing a more efficient and lightweight thermal management solution. BRIEF DESCRIPTION OF THE DRAWINGS
[0027] Figure 1 This is a diagram of a CO2 space efficient thermal management system of the present invention; Figure 2 It is an optimization logic diagram of a CO2 space efficient thermal management system of the present invention; Figure 3 This is a flow chart of an optimization algorithm for a CO2 space efficient thermal management system of the present invention; Among them, 1. heat source liquid cooling plate; 2. phase change cold storage equipment; 3. coolant storage tank; 4. CO2 working fluid pump; 5. CO2 compressor; 6. radiation radiator; 7. regenerator; 8. expansion valve. DETAILED DESCRIPTION
[0028] In the following, the terms "first", "second", "third", and "fourth" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, a feature defined as "first", "second", "third", and "fourth" may explicitly or implicitly include one or more of the features.
[0029] The co-shooting method provided in the embodiment of the present application can be applied to terminal devices such as mobile phones, tablet computers, wearable devices, vehicle-mounted devices, augmented reality (AR) / virtual reality (VR) devices, laptop computers, ultra-mobile personal computers (UMPC), netbooks, personal digital assistants (PDA), etc. The embodiment of the present application does not impose any restrictions on the specific type of the terminal device.
[0030] It should be noted that the terms "first", "second", etc. in the specification and drawings of the present invention are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.
[0031] See also Figure 1 As shown, the present invention provides a CO2 space efficient thermal management system with a phase change cold storage device, which includes a heat source liquid cooling plate 1, a phase change cold storage device 2, a coolant storage tank 3, a CO2 working fluid pump 4, a CO2 compressor 5, a radiation radiator 6, a heat regenerator 7 and an expansion valve 8.
[0032] The pump-driven cooling cycle includes a heat source liquid cold plate 1, a phase-change cold storage device 2, a coolant storage tank 3 and a CO2 working medium pump 4; the heat pump heat dissipation cycle includes a phase-change cold storage device 2, a CO2 compressor 5, a radiation radiator 6, a regenerator 7 and an expansion valve 8. The phase-change medium flowing in the pump-driven cooling cycle is the CO2 coolant, and the phase-change medium flowing in the heat pump heat dissipation cycle is the CO2 refrigerant.
[0033] Specifically, in the pump-driven cooling cycle, the outlet of the CO2 working fluid pump 4 is connected to the inlet of the heat source liquid cooling plate 1, the outlet of the heat source liquid cooling plate 1 is connected to the heat source inlet of the phase change cold storage device 2, the heat source outlet of the phase change cold storage device 2 is connected to the inlet of the coolant storage tank 3, and the outlet of the coolant storage tank 3 is connected to the inlet of the CO2 working fluid pump 4. Driven by the CO2 working fluid pump 4, the two-phase CO2 flows into the heat source liquid cooling plate 1 to absorb the heat of the distributed heat source. After the heat absorption is completed, the CO2 coolant flows to the phase change cold storage device 2 to release heat to the phase change medium in the device. After that, CO2 flows through the coolant storage tank 3 and returns to the CO2 working fluid pump 4 again, and the cycle repeats. The pump-driven cooling cycle can quickly and efficiently absorb the heat generated by the distributed heat source, control its temperature in a suitable range, and thus ensure the stable operation of the heat source.
[0034] Furthermore, in this process, CO2 phase change working fluid is used, which has a low standard boiling point and high density. The temperature in the two-phase region changes little along the flow direction, thereby effectively improving the temperature uniformity of the distributed heat source.
[0035] Specifically, in the heat pump heat dissipation cycle, the outlet of the CO2 compressor 5 is connected to the inlet of the radiation radiator 6, the outlet of the radiation radiator 6 is connected to the high-pressure side inlet of the regenerator 7, the high-pressure side outlet of the regenerator 7 is connected to the inlet of the expansion valve 8, the outlet of the expansion valve 8 is connected to the cold source inlet of the phase change cold storage device 2, the cold source outlet of the phase change cold storage device 2 is connected to the low-pressure side inlet of the regenerator 8, and the low-pressure side outlet of the regenerator 8 is connected to the inlet of the CO2 compressor 5. Low-temperature and low-pressure CO2 flows through the phase change cold storage device 2, absorbs the heat in the phase change cold storage device 2, and then CO2 flows into the regenerator 7 and the CO2 at the outlet of the radiation radiator 6 for heat exchange, thereby increasing the suction temperature of the compressor 5, and then is compressed to a high-temperature and high-pressure state through the CO2 compressor 5, flows into the radiation radiator 6 and dissipates heat to the deep space environment through radiation heat exchange, and the CO2 after heat dissipation is further cooled by the regenerator 7, and then flows through the expansion valve 8 to be throttled to a low-temperature and low-pressure state, and then flows into the phase change cold storage device 2 again, and the cycle repeats. The introduction of the regenerator 7 in the heat pump heat dissipation cycle can, on the one hand, avoid liquid in the air intake and effectively increase the system life; on the other hand, it can also increase the exhaust temperature of the CO2 compressor 5, achieve the purpose of radiative heat dissipation at a higher temperature, increase the radiative heat dissipation per unit radiation area, and thus achieve the reduction in size and emission mass of the radiation heat exchanger 6. In addition, the regenerator 7 can reduce the temperature before the valve, and under certain working conditions, it can improve the energy efficiency ratio of the system and reduce the power consumption of the compressor.
[0036] Furthermore, the distributed heat source works intermittently and emits a large amount of heat in the working state. However, due to the short working time in the cycle, the average heat dissipation of the whole cycle is small, and there is no need to use a large-capacity heat dissipation system to match the heat dissipation requirements of the working state. A phase change cold storage device 2 can be used to achieve the average distribution of heat dissipation in the time domain, and the heat pump system maintains the working state with the average heat dissipation of the distributed heat source as the cooling capacity target. Specifically, the pump-driven cooling cycle and the heat pump heat dissipation cycle are connected through the phase change cold storage device 2. When the pump-driven cooling cycle and the heat pump heat dissipation cycle are both running, the phase change cold storage device 2 gradually stores the heat absorbed by the coolant through the heat source liquid cooling plate 1; when the distributed heat source stops running, the pump-driven cooling cycle stops accordingly, and the heat pump heat dissipation cycle continues to run, and the refrigerant continuously absorbs the heat in the phase change cold storage device, which can not only effectively decouple the operation of the distributed heat source from the working state of the radiation radiator, but also can perform radiation heat dissipation according to the average power of the distributed heat source, thereby reducing the size and weight of the radiation radiator and achieving lightweight system.
[0037] Based on the above system content, see Figure 2 and Figure 3 ,The present invention provides an optimization method for a CO2 space efficient thermal management system, aiming to achieve the optimal overall system efficiency. In the optimization process, the displacement size of the compressor and the various components of the pump-driven cooling cycle are taken into account, and are determined according to the average calorific value and the actual calorific value of the distributed heat source, and a certain margin is reserved, so no adjustment is made.
[0038] The use of the regenerator 7 can affect the energy efficiency ratio of the system, thereby affecting the power consumption of the compressor 5, and it will also affect the suction and exhaust temperature of the CO2 compressor 5. It is worth noting that in order to ensure the safe and stable operation of the CO2 compressor 5, there is an upper limit to its exhaust temperature, so the improvement of the heat recovery rate is limited by the upper limit of the exhaust temperature. In addition, the exhaust pressure at the outlet of the CO2 compressor 5 will also affect the exhaust temperature, the energy efficiency of the system and the power consumption of the compressor, which can be controlled by the opening of the expansion valve.
[0039] Therefore, the components that can be optimized are the radiator 6 and the regenerator 7; the parameter that can be optimized is the exhaust pressure. The heat exchange area of the regenerator and the radiator, as well as the changes in the compressor power consumption and emission quality caused by the exhaust pressure change are comprehensively considered, and a comprehensive performance evaluation factor is proposed to achieve the optimal system performance, which is defined as: (1) in, is the total mass of the original thermal management system, kg; Total power consumption for pumping and motion maintenance of the original thermal management system, W; k m , n m , k p , np To calculate the coefficients, specific values are chosen based on a hierarchical analysis of the importance of quality and energy consumption.
[0040] Furthermore, the mass of the radiator and the regenerator affects the launch cost of the thermal management system and the energy consumption of the components during operation. Specifically, when the structure of the radiator and the regenerator is fixed, the mass of the radiator and the regenerator is a function of the heat exchange area:
[0041]
[0042]
[0043] in, is the heat transfer area of the radiator, m 2 ; is the heat exchange area of the regenerator, m 2 ; is the mass of the radiant heat sink, kg; , kg; is the total mass of the remaining components of the thermal management system, kg; Energy consumption to drive the movement of thermal management components; It is the energy consumption required to drive the unit mass space equipment to move, kW / kg. a1, a2, b1 and b2 are calculation coefficients. Different heat exchangers have different coefficients and can be determined according to specific circumstances in engineering.
[0044] Based on the above, see Figure 3 The present invention provides an optimization algorithm for a CO2 space efficient thermal management system, with the minimum value of the performance evaluation factor as the optimization target, that is, the objective function, and constraints are formulated. The relevant parameters of the heat pump heat dissipation cycle are initialized and input, and the initial regenerator heat exchange area, radiant radiator heat exchange area, and exhaust pressure population are generated using a genetic algorithm. The compressor speed, power consumption, valve opening, and various state points of the CO2 cycle are iteratively calculated and solved to further solve the comprehensive performance evaluation factor. The genetic algorithm population mutates and crosses to generate new regenerator heat exchange area, radiant radiator heat exchange area, and exhaust pressure. The compressor speed, power consumption, valve opening, and various state points of the CO2 cycle are iteratively calculated and solved again. The comprehensive performance evaluation factor is calculated to compare the size of the objective function before and after the population evolution, and the population with better comprehensive performance is selected. If the difference between the optimal objective function values of the current and subsequent iterations is less than the convergence error, the final decision is made, otherwise the iterative calculation continues until the iteration upper limit is reached. Input system initialization parameters, including the average calorific value of the distributed heat source, i.e., the cooling capacity target, the phase change temperature of the phase change material, the compressor capacity, the compressor isentropic, volumetric, and mechanical efficiency, the refrigerant charge Q, and the number of genetic populations. , population mutation rate , crossover probability , the upper limit of the number of iterations N , convergence error The constraints include the upper limit of the compressor exhaust temperature, the compressor suction state without liquid, the upper and lower limits of the quality of the radiator, the upper and lower limits of the quality of the regenerator, the upper and lower limits of the exhaust pressure, etc. The specific method includes the following steps: S1, input system initialization parameters and randomly generate the initial population, including the heat exchange area of the regenerator, the heat exchange area of the radiator and the exhaust pressure; S2, based on the initial population, according to the thermodynamic cycle calculation method of the heat pump cooling system, calculates the parameters of each state point of the cycle under the constraint conditions, obtains the power consumption of the compressor and the mass of the regenerator and radiator, and calculates the comprehensive performance evaluation factor of the CO2 space efficient thermal management system; S3, genetic algorithm population mutation, cross evolution to generate new regenerator, radiant heat exchange area and exhaust pressure as a new population; S4, based on the new population, according to the thermodynamic cycle calculation method of the heat pump cooling system, the parameters of each state point of the cycle are calculated under the constraint conditions, the power consumption of the compressor and the mass of the regenerator and the radiator are obtained, and the comprehensive performance evaluation factor is obtained by further calculation; S5, compares the comprehensive performance evaluation factor obtained in S2 with the comprehensive performance evaluation factor obtained in S4, and selects the population with a better comprehensive performance evaluation factor as the basis for the next population variation; S6, repeat S3~S5. If the difference between the objective function values of the two iterations is less than the convergence error, the solution is completed and the result is output. Otherwise, continue the iterative calculation.
[0045] In S1, the initial population is generated, including Each individual has three decision variables:
[0046] S5, during the comparison process, the smaller the comprehensive performance evaluation factor calculated by formula (1), the smaller the comprehensive performance of the thermal management system in this state.
[0047] In S2 and S4, the compressor exhaust temperature limits the increase of the regenerator and exhaust pressure, the compressor suction state is guaranteed to be liquid-free, the mass of the radiator is greater than 0 and less than the mass of the radiator in the original system, the mass of the regenerator is non-negative and less than the upper limit, and the exhaust pressure is less than the upper limit, that is, the constraints are:
[0048]
[0049]
[0050]
[0051]
[0052] in, P is the pressure, MPa, T is the temperature, °C, x For dryness, is the exhaust temperature, °C; is the compressor suction air dryness; is the maximum exhaust temperature, °C; is the maximum value of the regenerator area, m 2 ; is the original radiant heat sink area, m 2 ; is the radiation radiator area, m 2 ; is the maximum exhaust pressure, MPa; is the exhaust pressure, MPa; the specific value shall be adjusted according to the actual system.
[0053] The fitness function is expressed as the objective function. The lower the fitness, the greater the chance of individual survival:
[0054] In S2 and S5, according to And the calculated , , , , Calculate the comprehensive performance evaluation factor with equal power consumption.
[0055] When calculating the specific comprehensive performance evaluation factor, the power consumption of the compressor in the heat pump heat dissipation cycle needs to be calculated by the cycle thermodynamic state. The temperature of the phase change cold storage device, the compressor speed, the valve opening, the structure of the regenerator and the radiator, the heat exchange area, and the set exhaust pressure are known. The suction pressure and suction temperature are assumed. The heat transfer process of the compressor and the radiator is forward calculated from the determined suction state point, and then the heat transfer process in the regenerator is calculated by the outlet state of the radiator and the suction state. The state point before the expansion valve is obtained and the heat transfer process of the evaporator is reversely calculated. The assumed suction pressure is adjusted by the enthalpy difference error before and after the expansion valve, and the assumed suction temperature is adjusted by the difference in the refrigerant mass and charge calculated by each state point and the internal volume of the system. The calculation is iterated continuously until the error is less than the convergence error, and the parameters of each state point are obtained to obtain the compressor energy consumption. Each component is calculated using conventional single-phase or two-phase heat exchange formulas, pressure drop formulas, and mass flow formulas of the compressor throttle valve, etc. These methods are recognized methods in the industry, so they will not be repeated here.
[0056] In S3, during the crossover operation, the two adjacent chromosomes in the population are crossed to generate a random number r between 0 and 1. If , then the two adjacent chromosomes cross over, otherwise the paternal gene is retained:
[0057]
[0058] During the mutation operation, a random number of 0 to 1 is generated for each gene in turn for each individual in the population. , then the gene variation of this individual in the population is If the random number in , without mutation:
[0059] During the selection step, the fitness functions of the population before and after evolution are calculated and compared, and methods such as tournament selection or ranking selection are used to select individuals with smaller fitness functions.
[0060] When the optimal fitness function of the two iterative populations meets the following convergence conditions, the solution is considered complete and the current optimal solution is output:
[0061] Among them, g ( x ) is the fitness function.
[0062] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims
1. A method for optimizing a CO2 space efficient thermal management system, characterized in that: The following steps are involved: S1, obtain system initialization parameters and generate the initial population of genetic algorithm; S2, based on the initial population, performs thermodynamic cycle calculation of the heat pump cooling system under constraint conditions, obtains the state point parameters of the system, and further calculates the fitness function value of the system; S3, mutate the genetic algorithm population and obtain a new population through cross evolution; S4, based on the new population, the thermodynamic cycle calculation of the heat pump cooling system is performed under the constraint conditions to obtain the state point parameters of the system, and further calculate the fitness function value of the system; S5, compares the fitness function values obtained in S2 and S4, and selects the population with a better fitness function value as the basis for the next population mutation; S6, repeat S3-S5 until the difference between the function values of the two fitness functions is less than the convergence error, output the parameters corresponding to the current optimal solution, and achieve the optimal comprehensive performance of the thermal management system.
2. The optimization method of a CO2 space efficient thermal management system according to claim 1, characterized in that: The initial population and the new population both include the regenerator heat exchange area, the radiant heat sink heat exchange area and the exhaust pressure.
3. The optimization method of a CO2 space efficient thermal management system according to claim 1, characterized in that: The calculation formula of the fitness function is: in, is the total mass of the original thermal management system, kg; Total power consumption for pumping and motion maintenance of the original thermal management system, W; is the mass of the radiant heat sink, kg; , kg; is the total mass of the remaining components of the thermal management system, kg; Energy consumption to drive the thermal management components, kW / kg; is the power consumption of the compressor, W; k m , n m , k p , n p All are calculation coefficients.
4. The optimization method of a CO2 space efficient thermal management system according to claim 3, characterized in that: In S2, based on the initial population, the mass of the radiation radiator, and the energy consumption to drive the movement of thermal management components; in, is the heat transfer area of the radiator, m 2 ; is the heat exchange area of the regenerator, m 2 ; is the mass of the radiant heat sink, kg; , kg; is the total mass of the remaining components of the thermal management system, kg; Energy consumption to drive the movement of thermal management components; The energy consumption required to drive the unit mass of space equipment, kW / kg, , , and All are calculation coefficients.
5. The optimization method of a CO2 space efficient thermal management system according to claim 1, characterized in that: The constraints are: in, P is the pressure, MPa; T is temperature, °C; x is dryness; , and is the calculation limit.
6. The optimization method of a CO2 space efficient thermal management system according to claim 1, characterized in that: In S3, during the crossover evolution, two adjacent chromosomes in the population cross over to generate a random number r between 0 and 1. , the two adjacent chromosomes cross over, otherwise the paternal genes are retained.
7. The optimization method of a CO2 space efficient thermal management system according to claim 1, characterized in that: In S3, during the mutation process, a random number r of 0~1 is generated for each gene in turn for each individual in the population. , then the genetic variation of individuals in the population is If the random number in , no mutation is performed.
8. The optimization method of a CO2 space efficient thermal management system according to claim 1, characterized in that: In S5, the population with a better fitness function is a population with a smaller fitness function value.
9. The optimization method of a CO2 space efficient thermal management system according to claim 1, characterized in that: In S6, when the convergence error satisfies the following expression, the parameters corresponding to the current optimal solution are output: in, For the population, is the convergence error, g( x ) is the fitness function.
10. A CO2 space efficient thermal management system for implementing the optimization method of claim 1, characterized in that: The phase-change cold storage device (2) comprises a cold source and a heat source for exchanging heat with each other, the cold source outlet of the phase-change cold storage device (2) is connected to the cold source inlet of a regenerator (7), the cold source outlet of the regenerator (7) is connected to a CO2 compressor (5), the outlet of the CO2 compressor (5) is connected to a radiation heat exchanger (6), the outlet of the radiation heat exchanger (6) is connected to the heat source inlet of the regenerator (7), and the heat source outlet of the regenerator (7) is connected to the cold source inlet of the phase-change cold storage device (2); The heat source outlet of the phase-change cold storage device (2) is connected to the coolant storage tank (3), the outlet of the coolant storage tank (3) is connected to the CO2 working fluid pump (4), and the outlet of the CO2 working fluid pump (4) is connected to the heat source liquid cooling plate (1).