Passive heat dissipation system based on drone hangar

Abstract

The application discloses a passive heat dissipation system based on a UAV hangar, relates to the technical field of passive heat dissipation, and comprises a heat dissipation layout module, a self-adaptive adjustment module and an optimization module; the heat dissipation layout module is used for arranging heat dissipation units on the hangar according to the layout in the UAV hangar; the application realizes accurate simulation and optimization of heat distribution and air flow in the UAV hangar through the designed heat dissipation layout module; by using computational fluid dynamics software, in combination with the specific size, shape and internal equipment layout of the hangar, the system can determine the position of a key heat source and design an optimal heat dissipation unit layout; the modular heat dissipation unit design, in combination with the self-adaptive adjustment module, can dynamically adjust the aperture size according to the external wind direction and wind speed, thereby not only significantly improving the heat dissipation efficiency, but also enhancing the adaptability of the system to different environmental conditions.

Description

Technical Field

[0001] This invention relates to the field of passive heat dissipation technology, specifically a passive heat dissipation system based on a drone hangar. Background Technology

[0002] With the rapid development of drone technology, the internal heat dissipation problem of drone hangars, as key facilities for storage, maintenance, and automatic charging, has become increasingly apparent. Drone hangars typically house a large number of electronic devices and batteries, which generate significant heat during operation. If this heat cannot be effectively dissipated, the internal temperature of the hangar will rise, affecting equipment performance and lifespan, and potentially even posing safety hazards.

[0003] In existing technologies, most drone hangar cooling systems employ passive cooling methods, such as natural convection. However, these methods have limitations in cooling efficiency, especially in high-temperature or enclosed environments, where they struggle to meet the cooling demands of the hangar. Furthermore, while some hangar cooling systems utilize active cooling technologies, such as forced convection fans, these systems often consume more energy and may increase noise levels inside the hangar, negatively impacting the user experience.

[0004] To address the aforementioned issues, some research and applications have attempted to improve heat dissipation efficiency by refining the design of heat dissipation structures, such as optimizing the layout and shape of heat dissipation units and adjusting the airflow organization inside the hangar. However, these improvements often require customized design based on the specific hangar structure and equipment layout, resulting in low versatility and flexibility. Furthermore, they may face challenges such as limited installation space and insufficient adjustment capabilities in practical applications.

[0005] Furthermore, the cooling systems of drone hangars also face environmental adaptability challenges. Since hangars may be deployed in various environmental conditions, such as different climate zones or terrains, a single cooling design is insufficient to meet diverse environmental requirements. At the same time, with the increasing emphasis on green and environmentally friendly concepts, reducing the energy consumption of cooling systems and minimizing their environmental impact is also an important direction for current technological development.

[0006] In summary, existing drone hangar cooling technologies still have significant room for improvement in terms of heat dissipation efficiency, environmental adaptability, and energy consumption control. This invention aims to address the shortcomings of existing technologies by providing a highly efficient, adaptable, and low-energy-consumption passive cooling system based on a drone hangar.

[0007] To address the aforementioned shortcomings, a technical solution is provided. Summary of the Invention

[0008] The purpose of this invention is to address the significant room for improvement in existing drone hangar heat dissipation technologies in terms of heat dissipation efficiency, environmental adaptability, and energy consumption control, and to propose a passive heat dissipation system based on drone hangars.

[0009] The objective of this invention can be achieved through the following technical solutions: A passive cooling system based on a drone hangar includes: The heat dissipation layout module is used to arrange the heat dissipation units on the hangar according to the layout settings within the drone hangar. The specific process is as follows: First, the size, shape, and internal equipment layout of the drone hangar are assessed. The heat dissipation requirements and key heat source locations are determined through the assessment. Computational fluid dynamics software is used to simulate the heat distribution and airflow inside the hangar. Based on the simulation results, the shape, size and adjustable inner and outer diameter mechanism of the heat dissipation unit were designed. The inner and outer diameters of the heat dissipation unit are adjusted by electronic control. The heat dissipation unit is designed as a modular component for flexible configuration and installation according to different hangar layouts. Based on the simulation results of heat source distribution and airflow within the hangar, several alternative heat dissipation unit layouts were planned. These layouts were then prioritized and selected. Simulation tests were conducted on the alternative layouts, and the performance factors from the tests were comprehensively analyzed to determine the optimal heat dissipation unit layout. Based on the optimal layout of the heat dissipation units, a mounting bracket adapted to the hangar structure is designed to ensure that the heat dissipation units are installed in the preset positions. The adaptive adjustment module is used to dynamically adjust the size of the inner and outer apertures of the heat dissipation unit according to the wind direction and wind speed outside the hangar, so as to optimize the heat dissipation effect; The optimization module optimizes the performance of adjusting the aperture size of the heat dissipation unit based on the optimization signaling generated by the adaptive adjustment module.

[0010] Furthermore, the specific steps for the heat dissipation layout module to determine the optimal heat dissipation unit location layout are as follows: The simulation test was conducted by evaluating the location layout of the alternative heat dissipation units. The performance factors of the test were comprehensively analyzed, including thermal performance indicators, system performance and economic indicators, and environmental and human comfort indicators. The thermal value, system performance and environmental comfort value were obtained by analyzing the performance factors respectively. After normalizing the obtained thermal values, system longitudinal values, and circumferential values, respectively, they are substituted into the following formula: To obtain the optimal value QYZ, where xr, xj, and sh are the thermal value, coefficient of performance, and circumferential value, respectively. The preset weighting coefficients are thermal performance value, system performance value and environmental performance value, respectively, and the optimal value QYZ is used as the standard to measure the priority of the layout of the candidate heat dissipation unit; Sort all candidate heat dissipation unit location layouts by their best value and select the candidate heat dissipation unit location layout with the largest best value as the optimal heat dissipation unit location layout.

[0011] Furthermore, the specific operational steps for obtaining the thermal value, system performance score, and environmental performance score of the heat dissipation layout module through performance factor analysis are as follows: The thermal performance indicators in the performance factors include: Average temperature reduction: The degree of reduction in the average temperature inside the hangar after the test compared to before the test, and is measured by the average temperature reduction. Hotspot elimination efficiency: Evaluate the effectiveness of the layout in eliminating high-temperature hotspot areas, measured by the percentage of hotspot elimination; Temperature uniformity: The uniformity of temperature distribution in different areas inside the hangar. The smaller the temperature difference, the better the uniformity. Temperature is collected from different areas and the variance of temperature in different areas is calculated. This temperature variance is used as a measure of temperature uniformity. Heat dissipation unit efficiency: The amount of heat that each heat dissipation unit can dissipate per unit time, which is recorded as the average heat dissipation value; Heat exchange area: The total heat exchange area of ​​the heat dissipation unit, which is directly proportional to the heat dissipation capacity; Heat exchange rate: The efficiency of heat exchange between the heat dissipation unit and the air; After normalizing the obtained average temperature reduction, hot spot elimination percentage, temperature variance, average heat dissipation value, heat exchange area, and heat exchange rate, a cone model is established by multiplying the average temperature reduction by the hot spot elimination percentage as the base radius and multiplying the average heat dissipation value by the heat exchange area by the heat exchange rate as the height. Then, a spherical model is established by using the vertex of the cone model as the center of the sphere and the product of the temperature variance and the correction factor as the radius. The cone model is then cut using the spherical model, and the surface area of ​​the remaining irregular body is calculated and recorded as the thermal value. This thermal value is used as the standard for evaluating the thermal performance index of the location layout of the candidate heat dissipation unit. System performance and economic indicators include: Pressure loss: The pressure loss of air flowing through the heat dissipation unit, which affects the resistance to airflow; Total system energy consumption: The total energy consumption required for the cooling system to operate, including the fans and control system; Response time: The time it takes for the system to start dissipating heat after receiving a signal indicating a temperature increase; Maintenance costs: the frequency and cost of maintaining the heat dissipation unit; Service life: The expected service life of the heat dissipation unit; Economic efficiency: The overall economic efficiency of the cooling system, including initial investment and operating costs; The system performance and economic indicators are assigned scores from 1 to 20 respectively. The corresponding scores are multiplied by the corresponding preset weight coefficients and summed to obtain a comprehensive score, which is recorded as the system economic score. This system economic score is used as the standard to measure the system performance and economic indicators of the candidate heat dissipation unit location layout system. Environmental and human comfort indicators include: Environmental adaptability: The ability of the heat dissipation system to adapt to different environmental conditions; Thermal comfort: The impact of the cooling system on internal thermal comfort in hangars that require personnel access; Environmental impact: The potential impact of the heat dissipation system on the external environment, including the heat island effect; The above-mentioned environmental adaptability is measured through temperature range adaptability, humidity adaptability and weather resistance tests. Temperature range adaptability measures the operating efficiency and stability of the heat dissipation system under different temperature conditions; humidity adaptability evaluates the performance changes of the heat dissipation system under different humidity conditions; and weather resistance test simulates the impact of different environmental conditions on the heat dissipation system. Thermal comfort is measured by temperature uniformity, airflow velocity, and thermal radiation intensity. Temperature uniformity is assessed by measuring temperature at multiple points inside the hangar using temperature sensors and calculating the standard deviation or variance of the temperature distribution. Airflow velocity is measured by measuring the speed of airflow inside the hangar. Thermal radiation intensity is assessed by evaluating the surface temperature of the heat dissipation unit. The environmental impact is comprehensively analyzed through heat island effect assessment, energy consumption analysis, and emission assessment. The heat island effect assessment evaluates the impact of the heat dissipation system on the surrounding ambient temperature by measuring the surface temperature of different areas outside the hangar; the energy consumption analysis calculates the energy consumption of the heat dissipation system; and the emission assessment evaluates the potential environmental impact of leaks from the heat dissipation units. Collect the corresponding data for the above indicators, and set a quantitative standard or scoring system for each indicator, specifically using a scoring range of 1 to 10, where 10 represents the best performance. Each indicator is assigned a weight based on its importance. A weighted average is used to combine the quantitative values ​​of all indicators with their weights to calculate a comprehensive score, which is recorded as the environmental comfort value. This environmental comfort value is then used as a standard to measure the environmental and human comfort of the proposed heat dissipation unit location layout.

[0012] Furthermore, the specific operation steps of the adaptive adjustment module to dynamically adjust the size of the inner and outer apertures of the heat dissipation unit are as follows: By installing wind speed and direction sensors outside the hangar, environmental conditions are monitored in real time. The central control system receives sensor data and processes adjustment commands. The adjustment mechanism of the heat dissipation unit is preset to change the aperture size according to the control signal, including electric motors, hydraulic systems or mechanical linkages. An adjustment algorithm is developed to calculate the optimal adjustment of the inner and outer aperture sizes based on specific data of wind speed and direction, ensuring that the heat dissipation unit is designed to be modular for integrating the adjustment mechanism and allowing for independent or regional adjustment. Before implementation, simulation software was used to simulate the working effect of the adaptive adjustment module to ensure the effectiveness of the algorithm and design, and the heat dissipation unit was integrated with the adaptive adjustment module and the central control system. The sensors and adjustment mechanisms were calibrated in a real-world environment, and the ability of the adaptive adjustment module to correctly adjust the size of the heat dissipation unit apertures based on changes in wind direction and speed was verified. Performance was evaluated by collecting response parameters.

[0013] Furthermore, the specific steps for the adaptive adjustment module to perform performance evaluation by collecting response parameters are as follows: Response parameters include: Aperture adjustment accuracy: The difference between the actual aperture size after adjustment and the expected value is measured and recorded as the accuracy error value; Adjustment response time: The time required from when the sensor detects a change in wind direction and speed to when the aperture adjustment is completed is recorded as the response time value; Heat dissipation efficiency: The heat dissipation efficiency is evaluated by calculating the amount of heat reduction within a preset time, and is recorded as heat loss value; System energy consumption: Monitor the energy consumption of the adaptive adjustment module during operation, including sensors, actuators, and control systems, and calculate the total energy consumption. Substitute the obtained precision error value, response time value, heat loss value, energy consumption, and normalization into the following formula: The evaluation value YPZ is obtained, where jcz, xsz, rjz and nhh are the accuracy error, response time, heat loss and energy consumption, respectively. The calculated evaluation value is then compared with the preset evaluation threshold. If the evaluation value is greater than the preset evaluation threshold, the adaptive adjustment module is deemed to have passed the verification. Otherwise, the adaptive adjustment module's performance in adjusting the size of the heat dissipation unit aperture according to changes in wind direction and wind speed does not meet the standard, and an optimization signal is generated.

[0014] Furthermore, the specific steps by which the optimization module optimizes the performance of adjusting the size of the heat dissipation unit aperture based on the optimization signaling generated by the adaptive adjustment module are as follows: Collect operational data from the adaptive adjustment module, including sensor readings, adjustment actions, environmental conditions, and heat dissipation effects; analyze the collected data to identify performance bottlenecks and data that do not meet standards. Define optimization objectives and key performance indicators, including tuning accuracy, response time and heat dissipation efficiency; develop optimization algorithms based on performance indicators, including machine learning, artificial intelligence or control theory methods; test optimization algorithms in a simulation environment and evaluate their impact on performance indicators. The optimization algorithm is integrated into the adaptive adjustment module, real-time monitoring is implemented, the optimized adjustment actions and environmental response data are collected, and the performance data before and after optimization are compared to verify the effectiveness of the optimization algorithm. Adjust the parameters of the optimization algorithm based on the performance comparison results, collect user feedback to evaluate the actual effect of the optimization, set the optimization process as an iterative process, and continuously adjust the optimization algorithm based on new data and feedback; During the optimization process, redundancy and fault tolerance mechanisms are used to ensure that the system can maintain performance even when some components fail. The hardware is evaluated to determine whether it meets the requirements of the optimized system and hardware upgrades are performed. A long-term performance tracking mechanism is established to monitor the system’s performance under different environments and long-term use. The automatic correction mechanism enables the optimization module to identify performance degradation and automatically apply optimization measures.

[0015] Compared with the prior art, the beneficial effects of the present invention are: This invention, through its designed heat dissipation layout module, achieves precise simulation and optimization of heat distribution and airflow inside a UAV hangar. Utilizing computational fluid dynamics software, combined with the hangar's specific dimensions, shape, and internal equipment layout, the system can determine the location of key heat sources and design the optimal heat dissipation unit layout. The modular heat dissipation unit design, combined with an adaptive adjustment module, can dynamically adjust the aperture size according to external wind direction and speed, significantly improving heat dissipation efficiency and enhancing the system's adaptability to different environmental conditions. Furthermore, the quantitative scoring mechanism for system performance and economic indicators ensures that the heat dissipation system maintains high-efficiency heat dissipation while also considering economy and maintainability. This invention fully considers environmental and human comfort indicators in its design. By assessing environmental adaptability, thermal comfort, and potential impacts on the external environment, a series of measures are taken to reduce adverse effects on operators and the surrounding environment. At the same time, through energy consumption analysis and emission assessment, the system's environmental impact, such as the heat island effect, is reduced. These measures not only improve the user experience but also conform to the current trend of green and environmentally friendly development. This invention features an intelligent control and optimization mechanism. The adaptive adjustment module can respond to environmental changes in real time and automatically adjust the heat dissipation unit through algorithms to achieve the best heat dissipation effect. The introduction of the optimization module enables the system to continuously learn and adjust based on actual operating data to identify and overcome performance bottlenecks. The system's redundancy and fault-tolerant design ensures that it can maintain efficient and stable heat dissipation performance even if some components fail. The establishment of a long-term performance tracking and automatic correction mechanism further guarantees the reliability and effectiveness of the system under different environments and long-term use. Attached Figure Description

[0016] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings; Figure 1 This is the overall system block diagram of the present invention. Detailed Implementation

[0017] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] It should be understood that the terms “comprising” and “including” used in this disclosure and claims indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0019] It should also be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this disclosure. As used in this disclosure and claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this disclosure and claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations.

[0020] like Figure 1 As shown, the passive heat dissipation system based on the drone hangar includes a heat dissipation layout module, an adaptive adjustment module, and an optimization module. The heat dissipation layout module is used to arrange the heat dissipation units on the hangar according to the layout settings inside the drone hangar; First, the size, shape, and internal equipment layout of the UAV hangar are assessed to determine heat dissipation requirements and key heat source locations. Computational Fluid Dynamics (CFD) software or other thermal simulation tools are used to simulate heat distribution and airflow within the hangar. Based on the simulation results, the shape, size, and adjustable inner and outer aperture mechanisms of the heat dissipation units are designed. The inner and outer wall apertures of the heat dissipation units are electronically controlled to ensure effective heat dissipation from specific areas. The heat dissipation units are designed as modular components for flexible configuration and installation according to different hangar layouts. Based on the simulation results of heat source distribution and airflow within the hangar, several alternative heat dissipation unit layouts are planned. Priority selection is performed on these layouts, and simulation tests are conducted to evaluate the alternative layouts. The performance factors tested are comprehensively analyzed to determine the optimal heat dissipation unit layout. These performance factors include: Thermal performance indicators include: Average Temperature Reduction: The degree to which the average temperature inside the hangar decreases after the test compared to before the test, measured by the average temperature reduction; Hot Spot Elimination Efficiency: Evaluates the effectiveness of the layout in eliminating high-temperature hot spots, measured by the percentage of hot spots eliminated; Temperature Uniformity: The uniformity of temperature distribution in different areas inside the hangar. The smaller the temperature difference, the better the uniformity. Temperature uniformity is measured by collecting temperatures from different areas and calculating the variance of temperatures in different areas; Heat Dissipation Unit Efficiency: The amount of heat dissipated by each heat dissipation unit per unit time, recorded as the average heat dissipation value; Heat Exchange Area: The total heat exchange area of ​​the heat dissipation units, usually proportional to the heat dissipation capacity; Heat Exchange Rate: The efficiency of heat exchange between the heat dissipation unit and the air; After normalizing the obtained average temperature reduction, hot spot elimination percentage, temperature variance, average heat dissipation value, heat exchange area, and heat exchange rate, a cone model is established by multiplying the average temperature reduction by the hot spot elimination percentage as the base radius and multiplying the average heat dissipation value by the heat exchange area by the heat exchange rate as the height. Then, a spherical model is established by using the vertex of the cone model as the center of the sphere and the product of the temperature variance and the correction factor as the radius. The cone model is then cut using the spherical model, and the surface area of ​​the remaining irregular body is calculated and recorded as the thermal value. This thermal value is used as the standard for evaluating the thermal performance index of the location layout of the candidate heat dissipation unit, where the correction factor is set between 0.51 and 1.42. System performance and economic indicators include: Pressure loss: The pressure loss of air flowing through the heat dissipation unit, affecting the resistance to airflow; Total system energy consumption: The total energy consumption required for the operation of the heat dissipation system, including fans (if any), control systems, etc.; Response time: The time from receiving a temperature rise signal to starting heat dissipation; Maintenance cost: The maintenance frequency and cost of the heat dissipation unit; Service life: The expected service life of the heat dissipation unit; Economy: The overall economy of the heat dissipation system, including initial investment and operating costs; The system performance and economy indicators are assigned scores from 1 to 20, and the corresponding scores are multiplied by the corresponding preset weight coefficients and summed to obtain a comprehensive score, which is recorded as the system economy score. This system economy score is used as the standard to measure the system performance and economy indicators of the candidate heat dissipation unit location layout system; Environmental and human comfort indicators include: Environmental adaptability: The ability of the heat dissipation system to adapt to different environmental conditions; Thermal comfort: The impact of the heat dissipation system on the internal thermal comfort of a hangar that requires personnel access; Environmental impact: The potential impact of the heat dissipation system on the external environment, such as the possible heat island effect. The environmental adaptability mentioned above is measured through temperature range adaptability, humidity adaptability, and weather resistance tests. Temperature range adaptability measures the operating efficiency and stability of the heat dissipation system under different temperature conditions (such as high and low temperatures); humidity adaptability assesses the performance changes of the heat dissipation system under different humidity conditions; weather resistance tests simulate the impact of different environmental conditions (such as direct sunlight, rain erosion, etc.) on the heat dissipation system; thermal comfort is measured through temperature uniformity, airflow velocity, and thermal radiation intensity. Temperature uniformity is assessed by measuring the temperature at multiple points inside the hangar using temperature sensors and calculating the standard deviation or variance of the temperature distribution; airflow velocity is measured by measuring the speed of airflow inside the hangar to avoid discomfort caused by excessively high wind speeds; thermal radiation intensity is assessed by evaluating the surface temperature of the heat dissipation unit to prevent thermal radiation from high-temperature surfaces. The environmental impact is comprehensively analyzed through heat island effect assessment, energy consumption analysis, and emission assessment. Heat island effect assessment measures the surface temperature of different areas outside the hangar to evaluate the impact of the cooling system on the surrounding environment. Energy consumption analysis calculates the energy consumption of the cooling system, showing that high-energy-consuming systems may place a greater burden on the environment. Emission assessment evaluates the potential environmental impact of leaks from the cooling units. Data for the above indicators is collected, and a quantitative standard or scoring system is set for each indicator, specifically using a scoring range of 1 to 10, with 10 representing optimal performance. Weights are assigned to each indicator based on its importance, and a weighted average is used to combine the quantitative values ​​of all indicators with their weights to calculate a comprehensive score, which is recorded as the environmental comfort value. This environmental comfort value is used as a standard to measure the environmental and human comfort of the proposed cooling unit location layout. After normalizing the obtained thermal values, system longitudinal values, and circumferential values, respectively, they are substituted into the following formula: To obtain the optimal value QYZ, where xr, xj, and sh are the thermal value, coefficient of performance, and circumferential value, respectively. The preset weighting coefficients for thermal performance, system performance, and environmental performance are set to 1.21, 0.92, and 0.91 respectively, and the optimal value QYZ is used as the standard for evaluating the priority of the layout of the candidate heat dissipation units. Sort all candidate heat dissipation unit location layouts by their best value and select the candidate heat dissipation unit location layout with the best value as the optimal heat dissipation unit location layout. Based on the optimal layout of the heat dissipation units, a mounting bracket adapted to the hangar structure is designed to ensure that the heat dissipation units can be stably installed in the preset positions.

[0021] The adaptive adjustment module is used to dynamically adjust the size of the inner and outer apertures of the heat dissipation unit according to the wind direction and wind speed outside the hangar, so as to optimize the heat dissipation effect; By installing wind speed and direction sensors outside the hangar to monitor environmental conditions in real time, a central control system receives sensor data and processes adjustment commands. A pre-set adjustment mechanism for the heat dissipation unit is used to change the orifice size based on control signals; this may include electric motors, hydraulic systems, or mechanical linkages. An adjustment algorithm is developed to calculate the optimal inner and outer orifice sizes based on specific wind speed and direction data, ensuring the heat dissipation unit is modularly designed to facilitate the integration of the adjustment mechanism and allow for independent or regional adjustment. Before implementation, simulation software is used to model the adaptive adjustment module's operation, ensuring the effectiveness of the algorithm and design, and integrating the heat dissipation unit with the adaptive adjustment module and central control system. The sensors and adjustment mechanism are calibrated in a real environment to ensure accurate response to environmental changes, and the ability of the adaptive adjustment module to correctly adjust the heat dissipation unit orifice size according to wind direction and speed changes is verified. Performance evaluation is performed by collecting response parameters, including: Orifice adjustment accuracy: The difference between the actual orifice adjustment size and the expected value is measured and recorded as the accuracy error value; Adjustment response time: The time required from the sensor detecting changes in wind direction and speed to the completion of orifice adjustment is recorded as the response time value; Heat dissipation efficiency: The heat dissipation efficiency is evaluated by calculating the amount of heat reduction within a specific time period and recorded as the heat loss value; System energy consumption: The energy consumption of the adaptive adjustment module during operation is monitored, including sensors, actuators, and control systems, and the total energy consumption is calculated; Substitute the obtained precision error value, response time value, heat loss value, energy consumption, and normalization into the following formula: The evaluation value YPZ is obtained, where jcz, xsz, rjz, and nhh are the precision error, response time, heat reduction, and energy consumption, respectively. The calculated evaluation value is then compared with the preset evaluation threshold. If the evaluation value is greater than the preset evaluation threshold, the adaptive adjustment module is deemed to have passed the verification. Otherwise, the adaptive adjustment module's performance in adjusting the size of the heat dissipation unit aperture according to changes in wind direction and wind speed does not meet the standard, and an optimization signal is generated.

[0022] The optimization module optimizes the performance of adjusting the size of the heat dissipation unit aperture based on the optimization signaling generated by the adaptive adjustment module; Collect operational data from the adaptive control module, including sensor readings, control actions, environmental conditions, and heat dissipation effects. Analyze the collected data to identify performance bottlenecks and shortcomings. Define optimization objectives and key performance indicators (KPIs), including control accuracy, response time, and heat dissipation efficiency. Develop optimization algorithms based on these KPIs, which may include machine learning, artificial intelligence, or traditional control theory methods. Test the optimization algorithms in a simulation environment to assess their potential impact on performance indicators. Integrate the optimization algorithms into the adaptive control module, implement real-time monitoring, collect optimized control actions and environmental response data, compare performance data before and after optimization, and verify the effectiveness of the optimization algorithms. The parameters of the optimization algorithm are adjusted based on the performance comparison results to further improve performance. User feedback is collected to evaluate the actual effect of the optimization. The optimization process is set as an iterative process, and the optimization algorithm is continuously adjusted based on new data and feedback. Redundancy and fault tolerance mechanisms are used in conjunction with the optimization process to ensure that the system can maintain performance even when some components fail. The hardware is evaluated to see if it meets the requirements of the optimized system. Hardware upgrades are performed when necessary. A long-term performance tracking mechanism is established to monitor the system's performance under different environments and long-term use. Through an automatic correction mechanism, the optimization module can identify performance degradation and automatically apply optimization measures.

[0023] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A passive heat dissipation system based on a drone hangar, characterized in that, include: The heat dissipation layout module is used to arrange the heat dissipation units on the hangar according to the layout settings within the drone hangar. The specific process is as follows: First, the size, shape, and internal equipment layout of the drone hangar are assessed. The heat dissipation requirements and key heat source locations are determined through the assessment. Computational fluid dynamics software is used to simulate the heat distribution and airflow inside the hangar. Based on the simulation results, the shape, size and adjustable inner and outer diameter mechanism of the heat dissipation unit were designed. The inner and outer diameters of the heat dissipation unit are adjusted by electronic control. The heat dissipation unit is designed as a modular component for flexible configuration and installation according to different hangar layouts. Based on the simulation results of heat source distribution and airflow within the hangar, several alternative heat dissipation unit layouts were planned. These layouts were then prioritized and selected. Simulation tests were conducted on the alternative layouts, and the performance factors from the tests were comprehensively analyzed to determine the optimal heat dissipation unit layout. Based on the optimal layout of the heat dissipation units, a mounting bracket adapted to the hangar structure is designed to ensure that the heat dissipation units are installed in the preset positions. The adaptive adjustment module is used to dynamically adjust the size of the inner and outer apertures of the heat dissipation unit according to the wind direction and wind speed outside the hangar, so as to optimize the heat dissipation effect; The optimization module optimizes the performance of adjusting the aperture size of the heat dissipation unit based on the optimization signaling generated by the adaptive adjustment module.

2. The passive heat dissipation system based on a drone hangar according to claim 1, characterized in that, The specific steps for the heat dissipation layout module to determine the optimal heat dissipation unit location layout are as follows: The simulation test was conducted by evaluating the location layout of the alternative heat dissipation units. The performance factors of the test were comprehensively analyzed, including thermal performance indicators, system performance and economic indicators, and environmental and human comfort indicators. The thermal value, system performance and environmental comfort value were obtained by analyzing the performance factors respectively. After normalizing the obtained thermal values, system longitudinal values, and circumferential values, respectively, they are substituted into the following formula: To obtain the optimal value QYZ, where xr, xj, and sh are the thermal value, coefficient of performance, and circumferential value, respectively. The preset weighting coefficients are thermal performance value, system performance value and environmental performance value, respectively, and the optimal value QYZ is used as the standard to measure the priority of the layout of the candidate heat dissipation unit; Sort all candidate heat dissipation unit location layouts by their best value and select the candidate heat dissipation unit location layout with the largest best value as the optimal heat dissipation unit location layout.

3. The passive heat dissipation system based on a drone hangar according to claim 2, characterized in that, The specific steps for obtaining thermal values ​​through performance factor analysis in the heat dissipation layout module are as follows: The thermal performance indicators in the performance factors include: Average temperature reduction: The degree of reduction in the average temperature inside the hangar after the test compared to before the test, and is measured by the average temperature reduction. Hotspot elimination efficiency: Evaluate the effectiveness of the layout in eliminating high-temperature hotspot areas, measured by the percentage of hotspot elimination; Temperature uniformity: The uniformity of temperature distribution in different areas inside the hangar. The smaller the temperature difference, the better the uniformity. Temperature is collected from different areas and the variance of temperature in different areas is calculated. This temperature variance is used as a measure of temperature uniformity. Heat dissipation unit efficiency: The amount of heat that each heat dissipation unit can dissipate per unit time, which is recorded as the average heat dissipation value; Heat exchange area: The total heat exchange area of ​​the heat dissipation unit, which is directly proportional to the heat dissipation capacity; Heat exchange rate: The efficiency of heat exchange between the heat dissipation unit and the air; After normalizing the obtained average temperature reduction, hot spot elimination percentage, temperature variance, average heat dissipation value, heat exchange area, and heat exchange rate, a conical model is established with the average temperature reduction multiplied by the hot spot elimination percentage as the base radius and the product of the average heat dissipation value and heat exchange area multiplied by the heat exchange rate as the height. Then, a spherical model is established with the vertex of the conical model as the center and the product of the temperature variance and the correction factor as the radius. The conical model is then cut using the spherical model, and the surface area of ​​the remaining irregular shape is calculated and recorded as the thermal value. This thermal value is used as the standard for evaluating the thermal performance of the candidate heat dissipation unit location layout.

4. The passive heat dissipation system based on a drone hangar according to claim 2, characterized in that, The specific operational steps for obtaining the system economics score through performance factor analysis for the heat dissipation layout module are as follows: The system performance and economic indicators in the performance factors include: Pressure loss: The pressure loss of air flowing through the heat dissipation unit, which affects the resistance to airflow; Total system energy consumption: The total energy consumption required for the cooling system to operate, including the fans and control system; Response time: The time it takes for the system to start dissipating heat after receiving a signal indicating a temperature increase; Maintenance costs: the frequency and cost of maintaining the heat dissipation unit; Service life: The expected service life of the heat dissipation unit; Economic efficiency: The overall economic efficiency of the cooling system, including initial investment and operating costs; The system performance and economic indicators are assigned scores from 1 to 20 respectively. The corresponding scores are multiplied by the corresponding preset weight coefficients and summed to obtain a comprehensive score, which is recorded as the system economic score. This system economic score is used as the standard to measure the system performance and economic indicators of the candidate heat dissipation unit location layout system.

5. The passive heat dissipation system based on a drone hangar according to claim 2, characterized in that, The specific steps for obtaining the environmental comfort value through performance factor analysis in the heat dissipation layout module are as follows: The environmental and human comfort indicators in the performance factors include: Environmental adaptability: The ability of the heat dissipation system to adapt to different environmental conditions; Thermal comfort: The impact of the cooling system on internal thermal comfort in hangars that require personnel access; Environmental impact: The potential impact of the heat dissipation system on the external environment, including the heat island effect; The above-mentioned environmental adaptability is measured through temperature range adaptability, humidity adaptability and weather resistance tests. Temperature range adaptability measures the operating efficiency and stability of the heat dissipation system under different temperature conditions; humidity adaptability evaluates the performance changes of the heat dissipation system under different humidity conditions; and weather resistance test simulates the impact of different environmental conditions on the heat dissipation system. Thermal comfort is measured by temperature uniformity, airflow velocity, and thermal radiation intensity. Temperature uniformity is assessed by measuring temperature at multiple points inside the hangar using temperature sensors and calculating the standard deviation or variance of the temperature distribution. Airflow velocity is measured by measuring the speed of airflow inside the hangar. Thermal radiation intensity is assessed by evaluating the surface temperature of the heat dissipation unit. The environmental impact is comprehensively analyzed through heat island effect assessment, energy consumption analysis, and emission assessment. The heat island effect assessment evaluates the impact of the heat dissipation system on the surrounding ambient temperature by measuring the surface temperature of different areas outside the hangar; the energy consumption analysis calculates the energy consumption of the heat dissipation system; and the emission assessment evaluates the potential environmental impact of leaks from the heat dissipation units. Collect the corresponding data for the above indicators, and set a quantitative standard or scoring system for each indicator, specifically using a scoring range of 1 to 10, where 10 represents the best performance. Each indicator is assigned a weight based on its importance. A weighted average is used to combine the quantitative values ​​of all indicators with their weights to calculate a comprehensive score, which is recorded as the environmental comfort value. This environmental comfort value is then used as a standard to measure the environmental and human comfort of the proposed heat dissipation unit location layout.

6. The passive heat dissipation system based on a drone hangar according to claim 1, characterized in that, The specific steps for the adaptive adjustment module to dynamically adjust the size of the inner and outer apertures of the heat dissipation unit are as follows: By installing wind speed and direction sensors outside the hangar, environmental conditions are monitored in real time. The central control system receives sensor data and processes adjustment commands. The adjustment mechanism of the heat dissipation unit is preset to change the aperture size according to the control signal, including electric motors, hydraulic systems or mechanical linkages. An adjustment algorithm is developed to calculate the optimal adjustment of the inner and outer aperture sizes based on specific data of wind speed and direction, ensuring that the heat dissipation unit is designed to be modular for integrating the adjustment mechanism and allowing for independent or regional adjustment. Before implementation, simulation software was used to simulate the working effect of the adaptive adjustment module to ensure the effectiveness of the algorithm and design, and the heat dissipation unit was integrated with the adaptive adjustment module and the central control system. The sensors and adjustment mechanisms were calibrated in a real-world environment, and the ability of the adaptive adjustment module to correctly adjust the size of the heat dissipation unit apertures based on changes in wind direction and speed was verified. Performance was evaluated by collecting response parameters.

7. The passive heat dissipation system based on a drone hangar according to claim 6, characterized in that, The specific steps for the adaptive adjustment module to perform performance evaluation by collecting response parameters are as follows: Response parameters include: Aperture adjustment accuracy: The difference between the actual aperture size after adjustment and the expected value is measured and recorded as the accuracy error value; Adjustment response time: The time required from when the sensor detects a change in wind direction and speed to when the aperture adjustment is completed is recorded as the response time value; Heat dissipation efficiency: The heat dissipation efficiency is evaluated by calculating the amount of heat reduction within a preset time, and is recorded as heat loss value; System energy consumption: Monitor the energy consumption of the adaptive adjustment module during operation, including sensors, actuators, and control systems, and calculate the total energy consumption. Substitute the obtained precision error value, response time value, heat loss value, energy consumption, and normalization into the following formula: The evaluation value YPZ is obtained, where jcz, xsz, rjz and nhh are the accuracy error, response time, heat loss and energy consumption, respectively. The calculated evaluation value is then compared with the preset evaluation threshold. If the evaluation value is greater than the preset evaluation threshold, the adaptive adjustment module is deemed to have passed the verification. Otherwise, the adaptive adjustment module's performance in adjusting the size of the heat dissipation unit aperture according to changes in wind direction and wind speed does not meet the standard, and an optimization signal is generated.

8. The passive heat dissipation system based on a drone hangar according to claim 1, characterized in that, The specific steps of the optimization module in optimizing the performance of adjusting the size of the heat dissipation unit aperture based on the optimization signaling generated by the adaptive adjustment module are as follows: Collect operational data from the adaptive adjustment module, including sensor readings, adjustment actions, environmental conditions, and heat dissipation effects; analyze the collected data to identify performance bottlenecks and data that do not meet standards. Define optimization objectives and key performance indicators, including tuning accuracy, response time and heat dissipation efficiency; develop optimization algorithms based on performance indicators, including machine learning, artificial intelligence or control theory methods; test optimization algorithms in a simulation environment and evaluate their impact on performance indicators. The optimization algorithm is integrated into the adaptive adjustment module, real-time monitoring is implemented, the optimized adjustment actions and environmental response data are collected, and the performance data before and after optimization are compared to verify the effectiveness of the optimization algorithm. Adjust the parameters of the optimization algorithm based on the performance comparison results, collect user feedback to evaluate the actual effect of the optimization, set the optimization process as an iterative process, and continuously adjust the optimization algorithm based on new data and feedback; During the optimization process, redundancy and fault tolerance mechanisms are used to ensure that the system can maintain performance even when some components fail. The hardware is evaluated to determine whether it meets the requirements of the optimized system and hardware upgrades are performed. A long-term performance tracking mechanism is established to monitor the system’s performance under different environments and long-term use. The automatic correction mechanism enables the optimization module to identify performance degradation and automatically apply optimization measures.

Images