Electric aircraft heat dissipation optimization method and system based on numerical simulation model

Abstract

The invention relates to the field of heat dissipation of electric aircrafts, and discloses an electric aircraft heat dissipation optimization method and system based on a numerical simulation model. Respectively analyzing the heat dissipation performance and the heat dissipation efficiency of the model simulation electric aircraft in the wind tunnel test and the numerical simulation so as to evaluate the heat dissipation capability change of the electric aircraft in the wind tunnel test and the numerical simulation, and performing comparative analysis based on the heat dissipation performance and the heat dissipation efficiency to obtain a heat dissipation difference coefficient; the heat dissipation difference coefficient in a period of time is analyzed, the heat dissipation control coefficient is calculated, the heat dissipation control threshold value is set, and the heat dissipation control coefficient is compared with the heat dissipation control threshold value, so that the heat dissipation state is continuously kept within the optimal heat dissipation range, comprehensive evaluation of the heat dissipation performance of the electric aircraft is achieved, and the heat dissipation performance of the electric aircraft is improved. The method is beneficial for realizing fine control of the heat dissipation process, and improves the accuracy of heat dissipation optimization control.

Description

Technical Field

[0001] The present invention relates to the technical field of heat dissipation of electric aircraft, and more particularly to a heat dissipation optimization method and system for electric aircraft based on a numerical simulation model. Background Art

[0002] With the continuous development of electric aircraft technology, the demand for heat dissipation optimization methods is becoming more and more urgent. Traditional heat dissipation design often relies on empirical formulas and experimental data. This method is not only inefficient but also difficult to ensure the optimization of heat dissipation effect. However, the heat dissipation optimization method based on numerical simulation model can accurately simulate the temperature field and flow field in the power cabin, analyze the factors affecting heat dissipation performance, and propose targeted optimization solutions. It can greatly improve the accuracy and efficiency of heat dissipation design and provide an effective solution to the heat dissipation problem of electric aircraft.

[0003] However, the above process still has the following disadvantages:

[0004] First, existing models' heat dissipation optimization methods lack the ability to use wind tunnel test data as comparison data, combine it with numerical simulation data, and analyze the model's heat dissipation process. This makes it impossible to more comprehensively reflect the changes in the electric aircraft's heat dissipation characteristics.

[0005] Second, the existing model's heat dissipation optimization method lacks a comparative analysis of the heat dissipation analysis results of wind tunnel tests and numerical simulations, which makes it impossible to more intuitively understand the changes in the heat dissipation capacity of electric aircraft under different conditions and the differences in heat dissipation performance under different test conditions, resulting in inaccurate heat dissipation optimization control. Summary of the Invention

[0006] In order to overcome the above-mentioned defects of the prior art, the present invention provides an electric aircraft heat dissipation optimization method and system based on a numerical simulation model to solve the problems existing in the above-mentioned background technology.

[0007] The present invention provides the following technical solution: a method for optimizing heat dissipation of an electric aircraft based on a numerical simulation model, comprising:

[0008] S1: Collect relevant data related to wind tunnel test and numerical simulation;

[0009] S2: Preprocessing the collected wind tunnel test related information data and numerical simulation related information data respectively;

[0010] S3: used to analyze the numerical simulation model to simulate the heat dissipation process of the electric aircraft in the wind tunnel test and numerical simulation, including the wind tunnel test heat dissipation analysis unit and the numerical simulation heat dissipation analysis unit, to obtain the test heat dissipation performance monitoring index and the simulation heat dissipation performance monitoring index;

[0011] S4: By analyzing the heat dissipation efficiency of the cooling air system in wind tunnel tests and numerical simulations, the experimental heat dissipation efficiency evaluation coefficient and the simulated heat dissipation efficiency evaluation coefficient are obtained to evaluate the changes in the heat dissipation capacity of the electric aircraft in wind tunnel tests and numerical simulations respectively;

[0012] S5: By comparing the heat dissipation analysis results of the wind tunnel test and the heat dissipation analysis results of the numerical simulation, the heat dissipation difference coefficient is obtained;

[0013] S6: Analyze the heat dissipation difference coefficient over a period of time and calculate the heat dissipation control coefficient to optimize the heat dissipation process;

[0014] S7: By setting a heat dissipation control threshold and comparing the heat dissipation control coefficient with the heat dissipation control threshold, it is determined whether the heat dissipation state needs to be optimized and the heat dissipation state is continuously maintained within the optimal heat dissipation range;

[0015] S8: used to provide feedback on the heat dissipation control results and automatically generate a heat dissipation optimization test report based on the heat dissipation control process.

[0016] Preferably, the S1 places a model in a wind tunnel to simulate the actual airflow environment, directly measures and records the model wind tunnel test related information data, calculates the model through computer software, and thus records the numerical simulation related information data. The wind tunnel test related information data includes wind speed, temperature, humidity, model surface pressure, model surface temperature, gas flow rate, electric aircraft internal temperature, fan speed and radiator pressure. The numerical simulation related information data includes fluid field data, thermal transfer data, model surface pressure in numerical simulation, model surface temperature in numerical simulation and airflow velocity in numerical simulation.

[0017] Preferably, the S2 is based on data cleaning, data transformation, data filtering and data calibration of the collected wind tunnel test related information data, and data cleaning, data standardization, data verification, data integration and reconstruction of the collected numerical simulation related information data.

[0018] Preferably, S3 analyzes the wind tunnel test related information data in the wind tunnel test by a wind tunnel test heat dissipation analysis unit to obtain a test heat dissipation performance monitoring index for monitoring the actual heat dissipation effect of the heat dissipation system in the wind tunnel test; and analyzes the numerical simulation related information data in the numerical simulation by a numerical simulation heat dissipation analysis unit to obtain a simulation heat dissipation performance monitoring index for monitoring the heat dissipation performance of the heat dissipation model in the numerical simulation;

[0019] The specific analysis method of the test heat dissipation performance monitoring index is as follows:

[0020] Step S311: By collecting and recording the temperatures of multiple locations on the model surface and in the environment during the wind tunnel test, the difference between the average temperature of the model surface and the average temperature of the environment is calculated. Among them, T 表，i Represents the temperature value of the i-th measurement point on the model surface, T 环，j represents the temperature value of the jth measurement position in the environment, n represents the number of temperature measurement points on the model surface, and m represents the number of measurement positions in the environment;

[0021] Step S312: Analyze the current radiator pressure and atmospheric pressure and calculate the difference between the radiator pressure and atmospheric pressure as ΔP=P r -P a , where P r Indicates the radiator pressure value, P a Indicates the atmospheric pressure value;

[0022] Step S313: Using the recorded temperature T inside the electric aircraft 内 The test heat dissipation performance monitoring index is comprehensively analyzed based on the fan speed, and the test heat dissipation performance monitoring index is calculated as follows:

[0023] The specific analysis method of the simulated heat dissipation performance monitoring index is as follows:

[0024] Step S321: extract the temperature H of the cooling medium when it enters the radiator from the numerical simulation results. 入 The temperature H of the cooling medium flowing out after heat exchange in the radiator 出 , to calculate the temperature difference between inlet and outlet is ΔH=H 入 -H 出 ;

[0025] Step S322: Extract the radiator surface temperature H from the numerical simulation results 表 、Ambient temperature H 环 And the total heat flow W through the radiator is analyzed, and the thermal resistance of the radiator is calculated as

[0026]

[0027] Step S323: Based on the comprehensive analysis of the temperature difference between the inlet and outlet and the thermal resistance of the radiator, the simulated heat dissipation performance monitoring index is calculated as where l represents the power consumed by the heat sink extracted from the numerical simulation results.

[0028] Preferably, the specific analysis method of the experimental heat dissipation efficiency evaluation coefficient is:

[0029] Step S411: Calculate the heat released by the radiator as Q based on the gas mass flow rate q flowing through the radiator 放 =q×c×(T 进 -T 出 ), where c represents the specific heat capacity of the gas, T 进 Indicates the temperature of the radiator inlet, T 出 Indicates the temperature of the radiator outlet;

[0030] Step S412: The internal power p of the electric aircraft is 内 And the efficiency η of the heat dissipation system, the heat output of the system is calculated to be Q 入 =p 内 ×η;

[0031] Step S413: Based on the heat Q output by the system 入 And the heat released by the radiator Q 放 Conduct a comprehensive analysis and calculate the test heat dissipation efficiency evaluation coefficient as follows: Among them, λ represents the heat dissipation influence factor;

[0032] The simulated heat dissipation efficiency evaluation coefficient is calculated by extracting the numerical simulation related information data from the numerical simulation results and analyzing the fluid field data and thermal transmission data using the principles of fluid mechanics. h represents the convection heat transfer coefficient, S represents the heat dissipation area of ​​the model surface, and H 表 Indicates the radiator surface temperature, H 环 represents the ambient temperature, κ represents the radiation emissivity, σ represents the Stefan-Boltzmann constant, L represents the power of the heat source, and t represents the time of heat input.

[0033] Preferably, the specific calculation formula of the heat dissipation difference coefficient is: Among them, R represents the experimental heat dissipation performance monitoring index, I represents the simulated heat dissipation performance monitoring index, V represents the experimental heat dissipation efficiency evaluation coefficient, F represents the simulated heat dissipation efficiency evaluation coefficient, and β1 and β2 are weight coefficients.

[0034] Preferably, the S6 calculates the heat dissipation control coefficient by recording the heat dissipation difference coefficient calculated in each time interval and analyzing the fluctuation of the heat dissipation difference coefficient in a period of time. The specific calculation formula is: Among them, C represents the heat dissipation control coefficient, D x represents the heat dissipation difference coefficient recorded in the xth time interval, It represents the average value of all heat dissipation difference coefficients within a period of time, and X represents the number of recorded time intervals.

[0035] Preferably, the S7 analyzes historical heat dissipation data, including the heat dissipation difference coefficient and the heat dissipation efficiency, and sets the heat dissipation control threshold according to the analysis results, and the heat dissipation control threshold can be adjusted according to the equipment performance and safety requirements; and compares the calculated heat dissipation control coefficient C with the heat dissipation control threshold μ to determine whether the heat dissipation state needs to be optimized and controlled. If the heat dissipation control coefficient C ≤ the heat dissipation control threshold μ, it is considered that the heat dissipation state is good, and the heat dissipation state continues to be monitored. If the heat dissipation control coefficient C > the heat dissipation control threshold μ, it is considered that the heat dissipation performance at this time has decreased, and heat dissipation optimization adjustment measures must be taken immediately to adjust the heat dissipation state until the heat dissipation control coefficient value is lower than the heat dissipation control threshold, and then the adjustment of the heat dissipation state is stopped.

[0036] Preferably, the S8 monitors the heat dissipation optimization adjustment process and the heat dissipation status control and analysis process in real time, and automatically generates a heat dissipation optimization test report according to the heat dissipation status control and analysis process and sends it to the administrator terminal.

[0037] To achieve the above objectives, the present invention provides the following technical solutions: an electric aircraft heat dissipation optimization system based on a numerical simulation model, implementing the above electric aircraft heat dissipation optimization method based on a numerical simulation model, comprising:

[0038] Data acquisition module: collects wind tunnel test related information data and numerical simulation related information data;

[0039] Data preprocessing module: preprocesses the collected wind tunnel test related information data and numerical simulation related information data respectively;

[0040] Heat dissipation performance analysis module: used to analyze the heat dissipation process of electric aircraft in wind tunnel tests and numerical simulations using numerical simulation models, including wind tunnel test heat dissipation analysis units and numerical simulation heat dissipation analysis units, to obtain test heat dissipation performance monitoring index and simulation heat dissipation performance monitoring index;

[0041] Heat dissipation efficiency analysis module: By analyzing the heat dissipation efficiency of the cooling air system in wind tunnel tests and numerical simulations, the test heat dissipation efficiency evaluation coefficient and the simulation heat dissipation efficiency evaluation coefficient are obtained to evaluate the changes in the heat dissipation capacity of the electric aircraft in wind tunnel tests and numerical simulations respectively;

[0042] Heat dissipation difference comparison module: By comparing the heat dissipation analysis results of the wind tunnel test and the heat dissipation analysis results of the numerical simulation, the heat dissipation difference coefficient is obtained;

[0043] Heat dissipation control module: Analyzes the heat dissipation difference coefficient over a period of time and calculates the heat dissipation control coefficient to optimize the heat dissipation process;

[0044] Heat dissipation optimization judgment module: By setting the heat dissipation control threshold and comparing the heat dissipation control coefficient with the heat dissipation control threshold, it determines whether the heat dissipation status needs to be optimized and keeps the heat dissipation status within the optimal heat dissipation range;

[0045] Control result feedback module: used to feedback the heat dissipation control results and automatically generate a heat dissipation optimization test report based on the heat dissipation control process.

[0046] Technical effects and advantages of the present invention:

[0047] The present invention realizes diversified fusion of data by preprocessing the collected wind tunnel test related information data and numerical simulation related information data, which helps to more comprehensively reflect the heat dissipation characteristics of the electric aircraft, avoid the one-sidedness that may be caused by a single data source, reduce errors in the data analysis process, and improve the accuracy of heat dissipation performance evaluation. The wind tunnel test heat dissipation analysis unit and the numerical simulation heat dissipation analysis unit are used to respectively analyze the heat dissipation process of the electric aircraft in the wind tunnel test and the numerical simulation by the numerical simulation simulation model. By respectively analyzing the heat dissipation efficiency of the wind tunnel test and the numerical simulation cold air system, the changes in the heat dissipation capacity of the electric aircraft in the wind tunnel test and the numerical simulation are respectively evaluated. By comparing and analyzing the heat dissipation analysis results of the wind tunnel test and the heat dissipation analysis results of the numerical simulation, the heat dissipation difference coefficient is obtained. By analyzing the heat dissipation difference coefficient over a period of time, and calculating the heat dissipation Control coefficient, and set the heat dissipation control threshold, compare the heat dissipation control coefficient with the heat dissipation control threshold to determine whether the heat dissipation state needs to be optimized and controlled, and keep the heat dissipation state continuously within the optimal heat dissipation range. By analyzing the heat dissipation performance and heat dissipation efficiency in the wind tunnel test and numerical simulation heat dissipation process, a comprehensive evaluation of the heat dissipation performance of the electric aircraft is achieved, which helps to more accurately identify the heat dissipation bottleneck and optimization direction, and can more intuitively understand the changes in the heat dissipation capacity of the electric aircraft under different conditions, providing strong support for heat dissipation optimization. By comparing and analyzing the heat dissipation analysis results of the wind tunnel test and numerical simulation, it is possible to more intuitively understand the changes in the heat dissipation capacity of the electric aircraft under different conditions and the differences in heat dissipation performance under different test conditions, which is conducive to achieving refined control of the heat dissipation process and ensuring that the heat dissipation state is continuously maintained within the optimal heat dissipation range, thereby improving the accuracy of heat dissipation optimization control. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 A diagram showing the steps of the method of the present invention.

[0049] Figure 2 This is a system structure diagram of the present invention. DETAILED DESCRIPTION

[0050] The technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. In addition, the various structural forms described in the following embodiments are merely illustrative. The electric aircraft heat dissipation optimization method and system based on a numerical simulation model involved in the present invention are not limited to the various structures described in the following embodiments. All other embodiments obtained by ordinary technicians in this field without making any creative efforts fall within the scope of protection of the present invention.

[0051] like Figure 1 This embodiment provides an electric aircraft heat dissipation optimization method based on a numerical simulation model, including:

[0052] S1: Collect relevant information data of wind tunnel test and numerical simulation.

[0053] In this embodiment, the S1 places a model in a wind tunnel to simulate the actual airflow environment, directly measures and records the model wind tunnel test related information data, calculates the model through computer software, and thus records the numerical simulation related information data. The wind tunnel test related information data includes wind speed, temperature, humidity, model surface pressure, model surface temperature, gas flow rate, electric aircraft internal temperature, fan speed and radiator pressure. The numerical simulation related information data includes fluid field data, thermal transmission data, model surface pressure in numerical simulation, model surface temperature in numerical simulation and airflow velocity in numerical simulation.

[0054] It should be specifically explained that the specific method for collecting data related to the wind tunnel test is as follows: by installing hot wire anemometers at multiple locations in the wind tunnel test section, the wind speed in the test is measured in real time; by installing infrared temperature sensors at different locations on the measured surface, the temperature data at different locations on the model surface is measured, and a humidity sensor is used to monitor the relative humidity in the wind tunnel; by installing micro pressure sensors on the model surface, the surface pressure distribution is measured, and a pressure scanning valve system is used to collect data from multiple measuring points; by using a laser Doppler velocimeter to measure the airflow velocity at different locations in the test, at the same time, all data collection tools are connected to a computer via a wireless network to record the data related to the wind tunnel test in real time, and the collected data is synchronously collected and stored.

[0055] The specific method of collecting relevant information data for numerical simulation is as follows: in numerical simulation, the model needs to be meshed first, and then simulation is performed using computational fluid dynamics software to obtain the velocity, pressure and temperature distribution in the flow field; parameters such as heat flux density and temperature gradient are obtained through heat transfer simulation; boundary conditions such as inlet wind speed, temperature, outlet pressure, etc. are set before simulation, and the boundary conditions are set according to wind tunnel test data or actual flight data; the simulation results are analyzed by using post-processing software to obtain the required heat dissipation optimization parameters. The collected data include the analysis results of the average temperature, maximum temperature and heat flow path of a specific area; the data collection for numerical simulation is not directly measured. The numerical simulation results are extracted from the simulation results after the calculation is completed, and the results of the numerical simulation are extracted and converted by scripts, and finally output in the form of data files; the fluid field data of the numerical simulation is the information of the entire flow field obtained by simulation, including velocity field, pressure field and temperature field, the thermal transmission data of the numerical simulation includes heat flux density, temperature distribution and thermal conductivity, the surface air pressure of the model in the numerical simulation is obtained by calculating the pressure of the model surface nodes in the numerical simulation, the surface air temperature of the model in the numerical simulation is obtained by calculating the temperature of the model surface nodes in the numerical simulation, and the airflow velocity in the numerical simulation is the velocity vector field obtained by solving the fluid dynamics equation in the numerical simulation.

[0056] S2: Preprocessing the collected wind tunnel test related information data and numerical simulation related information data respectively.

[0057] In this embodiment, the S2 performs data cleaning, data transformation, data filtering and data calibration on the collected wind tunnel test related information data, and performs data cleaning, data standardization, data verification, data integration and reconstruction on the collected numerical simulation related information data.

[0058] S3: Used to analyze the numerical simulation model to simulate the heat dissipation process of the electric aircraft in the wind tunnel test and numerical simulation, including the wind tunnel test heat dissipation analysis unit and the numerical simulation heat dissipation analysis unit, to obtain the test heat dissipation performance monitoring index and the simulation heat dissipation performance monitoring index.

[0059] In this embodiment, the S3 analyzes the wind tunnel test related information data in the wind tunnel test by the wind tunnel test heat dissipation analysis unit to obtain a test heat dissipation performance monitoring index for monitoring the actual heat dissipation effect of the heat dissipation system in the wind tunnel test; analyzes the numerical simulation related information data in the numerical simulation by the numerical simulation heat dissipation analysis unit to obtain a simulated heat dissipation performance monitoring index for monitoring the heat dissipation performance of the heat dissipation model in the numerical simulation;

[0060] The specific analysis method of the test heat dissipation performance monitoring index is as follows:

[0061] Step S311: By collecting and recording the temperatures of multiple locations on the model surface and in the environment during the wind tunnel test, the difference between the average temperature of the model surface and the average temperature of the environment is calculated. Among them, T 表，i Represents the temperature value of the i-th measurement point on the model surface, T 环，j represents the temperature value of the jth measurement position in the environment, n represents the number of temperature measurement points on the model surface, and m represents the number of measurement positions in the environment;

[0062] Step S312: Analyze the current radiator pressure and atmospheric pressure and calculate the difference between the radiator pressure and atmospheric pressure as ΔP=P r -P a , where P r Indicates the radiator pressure value, P a Indicates the atmospheric pressure value;

[0063] Step S313: Using the recorded temperature T inside the electric aircraft 内 The test heat dissipation performance monitoring index is comprehensively analyzed based on the fan speed, and the test heat dissipation performance monitoring index is calculated as follows:

[0064] The specific analysis method of the simulated heat dissipation performance monitoring index is as follows:

[0065] Step S321: extract the temperature H of the cooling medium when it enters the radiator from the numerical simulation results. 入 The temperature H of the cooling medium flowing out after heat exchange in the radiator 出 , to calculate the temperature difference between inlet and outlet is ΔH=H 入 -H 出 ;

[0066] Step S322: Extract the radiator surface temperature H from the numerical simulation results 表 、Ambient temperature H 环 And the total heat flow W through the radiator is analyzed, and the thermal resistance of the radiator is calculated as

[0067]

[0068] Step S323: Based on the comprehensive analysis of the temperature difference between the inlet and outlet and the thermal resistance of the radiator, the simulated heat dissipation performance monitoring index is calculated as where l represents the power consumed by the heat sink extracted from the numerical simulation results.

[0069] S4: By analyzing the heat dissipation efficiency of the cooling air system in wind tunnel tests and numerical simulations respectively, we can obtain the experimental heat dissipation efficiency evaluation coefficient and the simulated heat dissipation efficiency evaluation coefficient to evaluate the changes in the heat dissipation capacity of the electric aircraft in wind tunnel tests and numerical simulations respectively.

[0070] In this embodiment, the specific analysis method of the experimental heat dissipation efficiency evaluation coefficient is:

[0071] Step S411: Calculate the heat released by the radiator as Q based on the gas mass flow rate q flowing through the radiator 放 =q×c×(T 进 -T 出 ), where c represents the specific heat capacity of the gas, T 进 Indicates the temperature of the radiator inlet, T 出 Indicates the temperature of the radiator outlet;

[0072] Step S412: The internal power p of the electric aircraft is 内 And the efficiency η of the heat dissipation system, the heat output of the system is calculated to be Q 入 =p 内 ×η;

[0073] Step S413: Based on the heat Q output by the system 入 And the heat released by the radiator Q 放 Conduct a comprehensive analysis and calculate the test heat dissipation efficiency evaluation coefficient as follows: Among them, λ represents the heat dissipation influence factor;

[0074] The simulated heat dissipation efficiency evaluation coefficient is calculated by extracting the numerical simulation related information data from the numerical simulation results and analyzing the fluid field data and thermal transmission data using the principles of fluid mechanics. h represents the convection heat transfer coefficient, S represents the heat dissipation area of ​​the model surface, and H 表 Indicates the radiator surface temperature, H 环 represents the ambient temperature, κ represents the radiation emissivity, σ represents the Stefan-Boltzmann constant, L represents the power of the heat source, and t represents the time of heat input.

[0075] It should be noted that the specific calculation formula for the heat dissipation influence factor λ is: Where v represents the actual wind speed, A represents the actual surface area of ​​the radiator, k represents the thermal conductivity of the radiator material, T 环 Indicates the ambient temperature, v 参 Indicates the reference wind speed, A 参 represents the reference heat sink surface area, k 参 Denotes the reference thermal conductivity, T a参 Indicates the reference ambient temperature.

[0076] S5: By comparing the heat dissipation analysis results of the wind tunnel test and the heat dissipation analysis results of the numerical simulation, the heat dissipation difference coefficient is obtained.

[0077] In this embodiment, the specific calculation formula of the heat dissipation difference coefficient is: Among them, R represents the experimental heat dissipation performance monitoring index, I represents the simulated heat dissipation performance monitoring index, V represents the experimental heat dissipation efficiency evaluation coefficient, F represents the simulated heat dissipation efficiency evaluation coefficient, and β1 and β2 are weight coefficients.

[0078] S6: Analyze the heat dissipation difference coefficient over a period of time and calculate the heat dissipation control coefficient to optimize the heat dissipation process.

[0079] In this embodiment, S6 calculates the heat dissipation control coefficient by recording the heat dissipation difference coefficient calculated in each time interval and analyzing the fluctuation of the heat dissipation difference coefficient in a period of time. The specific calculation formula is: Among them, C represents the heat dissipation control coefficient, D x represents the heat dissipation difference coefficient recorded in the xth time interval, It represents the average value of all heat dissipation difference coefficients within a period of time, and X represents the number of recorded time intervals.

[0080] S7: By setting a heat dissipation control threshold and comparing the heat dissipation control coefficient with the heat dissipation control threshold, it is determined whether the heat dissipation state needs to be optimized and controlled, and the heat dissipation state is continuously maintained within the optimal heat dissipation range.

[0081] In this embodiment, S7 analyzes historical heat dissipation data, including the heat dissipation difference coefficient and the heat dissipation efficiency, and sets the heat dissipation control threshold according to the analysis results, and the heat dissipation control threshold can be adjusted according to the equipment performance and safety requirements; and compares the calculated heat dissipation control coefficient C with the heat dissipation control threshold μ to determine whether the heat dissipation state needs to be optimized and controlled. If the heat dissipation control coefficient C ≤ the heat dissipation control threshold μ, it is considered that the heat dissipation state is good and the heat dissipation state continues to be monitored. If the heat dissipation control coefficient C > the heat dissipation control threshold μ, it is considered that the heat dissipation performance at this time has decreased, and heat dissipation optimization and adjustment measures must be taken immediately to adjust the heat dissipation state until the heat dissipation control coefficient value is lower than the heat dissipation control threshold, and then the adjustment of the heat dissipation state is stopped.

[0082] It should be noted that the specific operating process for the heat dissipation optimization adjustment measures is: automatically adjusting the fan speed or pump flow of the cooling system; changing the configuration of the heat dissipation material or increasing the heat dissipation area; optimizing the circulation path of the heat dissipation fluid or replacing it with a more effective heat dissipation fluid; and adjusting the environmental conditions, including temperature or humidity; at the same time, recording all adjustment measures and results for future analysis and improvement.

[0083] S8: used to provide feedback on the heat dissipation control results and automatically generate a heat dissipation optimization test report based on the heat dissipation control process.

[0084] In this embodiment, S8 monitors the heat dissipation optimization adjustment process and the heat dissipation status control and analysis process in real time, and automatically generates a heat dissipation optimization test report according to the heat dissipation status control and analysis process and sends it to the administrator terminal.

[0085] like Figure 2 The embodiment shown provides an implementation system corresponding to the electric aircraft heat dissipation optimization method based on a numerical simulation model, including a data acquisition module, a data preprocessing module, a heat dissipation performance analysis module, a heat dissipation efficiency analysis module, a heat dissipation difference comparison module, a heat dissipation control module, a heat dissipation optimization judgment module and a control result feedback module. The data acquisition module is connected to the data preprocessing module, the data preprocessing module is connected to the heat dissipation performance analysis module, the data preprocessing module is connected to the heat dissipation efficiency analysis module, the heat dissipation performance analysis module is connected to the heat dissipation difference comparison module, the heat dissipation efficiency analysis module is connected to the heat dissipation difference comparison module, the heat dissipation difference comparison module is connected to the heat dissipation control module, the heat dissipation control module is connected to the heat dissipation optimization judgment module, and the heat dissipation optimization judgment module is connected to the control result feedback module.

[0086] The data acquisition module collects wind tunnel test related information data and numerical simulation related information data;

[0087] The data preprocessing module preprocesses the collected wind tunnel test related information data and numerical simulation related information data respectively;

[0088] The heat dissipation performance analysis module is used to analyze the heat dissipation process of the electric aircraft in the wind tunnel test and numerical simulation by the numerical simulation model, including a wind tunnel test heat dissipation analysis unit and a numerical simulation heat dissipation analysis unit, to obtain the test heat dissipation performance monitoring index and the simulation heat dissipation performance monitoring index;

[0089] The heat dissipation efficiency analysis module analyzes the heat dissipation efficiency of the cooling air system in the wind tunnel test and the numerical simulation respectively to obtain the test heat dissipation efficiency evaluation coefficient and the simulation heat dissipation efficiency evaluation coefficient, thereby respectively evaluating the changes in the heat dissipation capacity of the electric aircraft in the wind tunnel test and the numerical simulation;

[0090] The heat dissipation difference comparison module compares and analyzes the heat dissipation analysis results of the wind tunnel test and the heat dissipation analysis results of the numerical simulation to obtain a heat dissipation difference coefficient;

[0091] The heat dissipation control module analyzes the heat dissipation difference coefficient over a period of time and calculates the heat dissipation control coefficient for optimizing the heat dissipation process;

[0092] The heat dissipation optimization judgment module sets a heat dissipation control threshold and compares the heat dissipation control coefficient with the heat dissipation control threshold to determine whether the heat dissipation state needs to be optimized and control, and to keep the heat dissipation state continuously within the optimal heat dissipation range;

[0093] The control result feedback module is used to feed back the heat dissipation control result and automatically generate a heat dissipation optimization test report according to the heat dissipation control process.

[0094] Finally: 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 principles of the present invention should be included in the scope of protection of the present invention.

[0095] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A heat dissipation optimization method for an electric aircraft based on a numerical simulation model, characterized in that Including: S1: Collecting relevant information data of wind tunnel tests and relevant information data of numerical simulations; S2: Based on preprocessing the collected relevant information data of wind tunnel tests and relevant information data of numerical simulations respectively; S3: Used to analyze the heat dissipation process of the numerical simulation model simulating the electric aircraft in wind tunnel tests and numerical simulations, including a wind tunnel test heat dissipation analysis unit and a numerical simulation heat dissipation analysis unit, to obtain a test heat dissipation performance monitoring index and a simulation heat dissipation performance monitoring index; S4: By analyzing the heat dissipation efficiency of the cold air systems in wind tunnel tests and numerical simulations respectively, obtaining a test heat dissipation efficiency evaluation coefficient and a simulation heat dissipation efficiency evaluation coefficient, to evaluate the changes in the heat dissipation capacity of the electric aircraft in wind tunnel tests and numerical simulations respectively; S5: By comparing and analyzing the heat dissipation analysis results of wind tunnel tests and the heat dissipation analysis results of numerical simulations, obtaining a heat dissipation difference coefficient; S6: By analyzing the heat dissipation difference coefficient over a period of time and calculating a heat dissipation control coefficient, used to optimize and control the heat dissipation process; S7: By setting a heat dissipation control threshold and comparing the heat dissipation control coefficient with the heat dissipation control threshold, to determine whether the heat dissipation state needs to be optimized and controlled, and to keep the heat dissipation state continuously within the optimal heat dissipation range; S8: Used to feedback the heat dissipation control result and automatically generate a heat dissipation optimization test report according to the heat dissipation control process.

2. The heat dissipation optimization method for an electric aircraft based on a numerical simulation model according to claim 1, characterized in that The above S1 places a model in the wind tunnel to simulate the actual airflow environment, directly measures and records the relevant information data of the model wind tunnel test, and calculates the model through computer software to record the relevant information data of the numerical simulation. The relevant information data of the wind tunnel test includes wind speed, temperature, humidity, model surface air pressure, model surface temperature, gas flow rate, electric aircraft internal temperature, fan speed, and radiator pressure. The relevant information data of the numerical simulation includes fluid field data, heat transfer data, model surface air pressure in the numerical simulation, model surface air temperature in the numerical simulation, and airflow velocity in the numerical simulation.

3. The heat dissipation optimization method for an electric aircraft based on a numerical simulation model according to claim 1, wherein The above S2 is based on data cleaning, data transformation, data filtering processing, and data calibration for the collected relevant information data of wind tunnel tests, and data cleaning, data standardization, data verification, and data integration and reconstruction for the collected relevant information data of numerical simulations.

4. The heat dissipation optimization method for an electric aircraft based on a numerical simulation model according to claim 1, characterized in that The above S3 analyzes the relevant information data of the wind tunnel test in the wind tunnel test through the wind tunnel test heat dissipation analysis unit to obtain a test heat dissipation performance monitoring index, used to monitor the actual heat dissipation effect of the heat dissipation system in the wind tunnel test; analyzes the relevant information data of the numerical simulation in the numerical simulation through the numerical simulation heat dissipation analysis unit to obtain a simulation heat dissipation performance monitoring index, used to monitor the heat dissipation performance of the heat dissipation model in the numerical simulation; The specific analysis method of the above test heat dissipation performance monitoring index is: Step S311: Calculate the difference between the average temperature of the model surface and the average ambient temperature by collecting and recording the temperatures at multiple different positions on the model surface and in the environment. where T 表，i represents the temperature value at the i-th measurement point on the model surface, and T 环，j represents the temperature value at the j-th measurement position in the environment. n represents the number of temperature measurement points on the model surface, and m represents the number of measurement positions in the environment; Step S312: By analyzing the current radiator pressure and the atmospheric pressure, and calculating the pressure difference between the radiator pressure and the atmospheric pressure as ΔP = P r - P a , where P r represents the radiator pressure value, and P a represents the atmospheric pressure value; Step S313: Comprehensively analyze the test heat dissipation performance monitoring index based on the recorded internal temperature T of the electric aircraft 内 and the fan speed, and calculate that the test heat dissipation performance monitoring index is The specific analysis method of the above simulation heat dissipation performance monitoring index is: Step S321: Calculate the temperature difference ΔH = H 入 when the cooling medium enters the radiator and the temperature H 出 when the cooling medium flows out after heat exchange in the radiator 入 by extracting from the numerical simulation results, and the temperature difference between the inlet and outlet is ΔH = H 出 - H Step S322: Analyze by extracting the surface temperature H of the radiator, the ambient temperature H, and the total heat flow W through the radiator from the numerical simulation results, and calculate the thermal resistance of the radiator as 表 and the ambient temperature H 环 and perform an analysis based on the total heat flow W through the radiator, and calculate the thermal resistance of the radiator as Step S323: Based on the comprehensive analysis of the temperature difference between the inlet and the outlet and the thermal resistance of the radiator, calculate the simulated heat dissipation performance monitoring index as where l represents the power consumed by the radiator extracted from the numerical simulation results.

5. The heat dissipation optimization method for an electric aircraft based on a numerical simulation model according to claim 1, characterized in that, The specific analysis method of the above test heat dissipation efficiency evaluation coefficient is: Step S411: Calculate the heat released by the radiator as Q through the mass flow rate q of the gas flowing through the radiator 放 = q × c × (T 进 - T 出 ), where c represents the specific heat capacity of the gas, T 进 represents the temperature at the inlet of the radiator, and T 出 represents the temperature at the outlet of the radiator; Step S412: Calculate the heat Q output by the system based on the internal power p of the electric aircraft 内 and the efficiency η of the heat dissipation system, where 入 Q = p 内 × η; Step S413: Based on the heat quantity Q output by the system 入 and the heat quantity Q released by the radiator 放 perform comprehensive analysis and calculate that the evaluation coefficient of the test heat dissipation efficiency is where λ represents the heat dissipation influence factor; The simulated heat dissipation efficiency evaluation coefficient extracts the numerical simulation-related information data from the numerical simulation results, and analyzes the fluid field data and heat transfer data using the principles of fluid mechanics, so as to calculate the simulated heat dissipation efficiency evaluation coefficient as h represents the convective heat transfer coefficient, S represents the heat dissipation area of the model surface, H 表 represents the surface temperature of the radiator, H 环 represents the ambient temperature, κ represents the radiation emissivity, σ represents the Stefan-Boltzmann constant, L represents the power of the heat source, and t represents the time of heat input.

6. The heat dissipation optimization method for an electric aircraft based on a numerical simulation model according to claim 1, characterized in that, The specific calculation formula of the heat dissipation difference coefficient is wherein, R represents the test heat dissipation performance monitoring index, I represents the simulated heat dissipation performance monitoring index, V represents the test heat dissipation efficiency evaluation coefficient, F represents the simulated heat dissipation efficiency evaluation coefficient, and β1 and β2 are weighting coefficients.

7. The heat dissipation optimization method for an electric aircraft based on a numerical simulation model according to claim 1, characterized in that The S6 calculates the heat dissipation control coefficient by recording the heat dissipation difference coefficients calculated within each time interval and analyzing the fluctuating changes in the heat dissipation difference coefficients over a period of time. The specific calculation formula is where C represents the heat dissipation control coefficient, and D x represents the heat dissipation difference coefficient within the x-th time interval recorded, represents the average value of all heat dissipation difference coefficients over a period of time, and X represents the number of recorded time intervals.

8. The heat dissipation optimization method for an electric aircraft based on a numerical simulation model according to claim 1, characterized in that, The S7 sets the heat dissipation control threshold by analyzing historical heat dissipation data, including the heat dissipation difference coefficient and the heat dissipation efficiency, and the heat dissipation control threshold can be adjusted according to the device performance and safety requirements; And by comparing the calculated heat dissipation control coefficient C with the heat dissipation control threshold μ, it is judged whether the heat dissipation state needs to be optimized. If the heat dissipation control coefficient C ≤ the heat dissipation control threshold μ, it is considered that the heat dissipation state is good, and the heat dissipation state continues to be monitored. If the heat dissipation control coefficient C > the heat dissipation control threshold μ, it is considered that the heat dissipation performance has decreased at this time, and heat dissipation optimization adjustment measures need to be taken immediately to adjust the heat dissipation state until the heat dissipation control coefficient value is lower than the heat dissipation control threshold, and the adjustment of the heat dissipation state is stopped.

9. The heat dissipation optimization method for an electric aircraft based on a numerical simulation model according to claim 1, wherein The S8 monitors the heat dissipation optimization adjustment process and the heat dissipation state control analysis process in real time, and automatically generates a heat dissipation optimization test report according to the heat dissipation state control analysis process and sends it to the management personnel terminal.

10. An electric aircraft heat dissipation optimization system based on a numerical simulation model, which implements the electric aircraft heat dissipation optimization method based on a numerical simulation model according to any one of claims 1-9, characterized in that, Including: Data acquisition module: Collect relevant information data of wind tunnel tests and relevant information data of numerical simulations; Data preprocessing module: Based on preprocessing the relevant information data of wind tunnel tests and relevant information data of numerical simulations collected respectively; Heat dissipation performance analysis module: Used to analyze the heat dissipation process of the electric aircraft in the wind tunnel test and numerical simulation by the numerical simulation model, including the wind tunnel test heat dissipation analysis unit and the numerical simulation heat dissipation analysis unit, and obtain the test heat dissipation performance monitoring index and the simulation heat dissipation performance monitoring index; Heat dissipation efficiency analysis module: By analyzing the heat dissipation efficiency of the cold air systems in the wind tunnel test and numerical simulation respectively, obtain the test heat dissipation efficiency evaluation coefficient and the simulation heat dissipation efficiency evaluation coefficient, and evaluate the change of the heat dissipation capacity of the electric aircraft in the wind tunnel test and numerical simulation respectively; Heat dissipation difference comparison module: By comparing and analyzing the heat dissipation analysis results of the wind tunnel test and the heat dissipation analysis results of the numerical simulation, obtain the heat dissipation difference coefficient; Heat dissipation control module: By analyzing the heat dissipation difference coefficient within a period of time and calculating the heat dissipation control coefficient, it is used to optimize the control of the heat dissipation process; Heat dissipation optimization judgment module: By setting the heat dissipation control threshold and comparing the heat dissipation control coefficient with the heat dissipation control threshold, it is judged whether the heat dissipation state needs to be optimized, and the heat dissipation state is continuously maintained within the optimal heat dissipation range; Control result feedback module: Used to feedback the heat dissipation control result and automatically generate a heat dissipation optimization test report according to the heat dissipation control process.

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