A method and device for predicting human body electromagnetic radiation

Abstract

A method and device for predicting human body electromagnetic radiation. The method includes: obtaining simulation model data, material parameters, and a simulation frequency range; constructing a human body electromagnetic radiation simulation prediction environment according to the simulation model data, material parameters, simulation frequency range, and an excitation source of a high-voltage component preset; performing human body electromagnetic radiation prediction simulation in the human body electromagnetic radiation simulation prediction environment to obtain a simulation result; calculating the absorption power density of different human tissues according to the simulation result and material parameters; calculating the temperature change of different human tissues according to the absorption power density; and determining the predicted risk position where the human body electromagnetic radiation exceeds the standard according to the temperature change. It can predict human body electromagnetic radiation in the early stage of the development of an electric vehicle whole vehicle; it can also calculate the average increased temperature of the radiation of different human tissues / organs by the electric vehicle through integration calculation, realize the prediction of the radiation of different human tissues / organs, and improve the practicability and accuracy of the prediction.

Description

Technical Field

[0001] This application relates to the field of electromagnetic technologies, and more particularly, to a method and device for predicting human electromagnetic radiation. Background Art

[0002] At present, the electromagnetic protection of electric vehicles for humans is evaluated by testing the actual vehicle. The test results are the magnetic or electric field intensity values at the corresponding positions of the head, abdomen, and feet of the driver (and passengers) in the vehicle in the 10 Hz - 400 kHz frequency spectrum diagram. And when the magnetic or electric field intensity values at all positions are lower than the limit requirements of the national standard, it is determined to be qualified.

[0003] However, testing, evaluating, and rectifying the actual vehicle can only intervene in the later stage of the overall vehicle design and development, and there are relatively large limitations in rectification. At the same time, the distribution of the electromagnetic field in the vehicle will change due to the presence of the human body, which makes the results obtained by testing with a bench with a magnetic / electric field probe deviate from the actual results. In addition, even if the test results meet the limit requirements of the national standard, it is difficult to explain which test result is better from the magnetic or electric field intensity frequency spectrum diagram (for example, whether the radiation of the vehicle with a relatively high overall low-frequency band in the test results has a greater impact on the human body, or whether the radiation of the vehicle with a large single-frequency point spike value in the high-frequency band in the test results has a greater impact on the human body). Summary of the Invention

[0004] The purpose of the embodiments of this application is to provide a method and device for predicting human electromagnetic radiation, which can predict human electromagnetic radiation in the early stage of the overall development of electric vehicles; and can also calculate the average elevated temperature of the radiation of electric vehicles on different tissues / organs of the human body through integral calculation, thereby realizing the prediction of the radiation of the overall electric vehicle on different tissues / organs of the human body, and improving the practicability and accuracy of human electromagnetic radiation prediction.

[0005] The first aspect of the embodiments of this application provides a method for predicting human electromagnetic radiation, including:

[0006] Obtain simulation model data, material parameters, and a simulation frequency range;

[0007] Construct a human electromagnetic radiation simulation prediction environment according to the simulation model data, the material parameters, the simulation frequency range, and the excitation source of the preset high-voltage component;

[0008] Conduct human electromagnetic radiation prediction simulation in the human electromagnetic radiation simulation prediction environment to obtain simulation results;

[0009] Calculate the absorption power density of different tissues of the human body according to the simulation results and the material parameters;

[0010] Calculate the temperature change of different tissues of the human body according to the absorption power density;

[0011] Determine the predicted risk location where the human body's electromagnetic radiation exceeds the standard according to the temperature change situation.

[0012] In the above implementation process, the method can first obtain simulation model data, material parameters, and a simulation frequency range; then construct a human body electromagnetic radiation simulation prediction environment according to the simulation model data, material parameters, simulation frequency range, and the excitation source of the high-voltage component preset; then perform human body electromagnetic radiation prediction simulation in the human body electromagnetic radiation simulation prediction environment to obtain simulation results; after obtaining the simulation results, calculate the absorption power density of different human tissues according to the simulation results and material parameters; and calculate the temperature change situation of different human tissues according to the absorption power density; finally, determine the predicted risk location where the human body's electromagnetic radiation exceeds the standard according to the temperature change situation. It can be seen that implementing this implementation method can predict the human body's electromagnetic radiation in the early stage of the development of the entire electric vehicle; it can also calculate the average increased temperature of the radiation of the electric vehicle to different human tissues / organs through integration, thereby realizing the prediction of the radiation of the entire electric vehicle to different human tissues / organs, and improving the practicability and accuracy of the prediction of the human body's electromagnetic radiation.

[0013] Further, the simulation model data at least includes the digital model of the entire vehicle body, the outer envelope digital model of the high-voltage component, the digital model of the high-voltage cable, and the human body model;

[0014] The material parameters at least include the vehicle body material parameters, the high-voltage component material parameters, the high-voltage cable material parameters, and the human body material parameters.

[0015] Further, the calculating the absorption power density of different human tissues according to the simulation results and the material parameters includes:

[0016] Calculate the radiation field intensity of different human tissues according to the simulation results and the simulation frequency range; wherein, the radiation field intensity includes the electric field intensity and / or the magnetic field intensity;

[0017] Determine the material conductivity and material specific heat capacity according to the material parameters;

[0018] Calculate the absorption power density of different human tissues according to the material conductivity and the radiation field intensity.

[0019] Further, the calculating the temperature change situation of different human tissues according to the absorption power density includes:

[0020] Calculate the local temperature rise of different human tissues according to the absorption power density;

[0021] Generate a transient temperature rise distribution map of different human tissues according to the local temperature rise;

[0022] Determine the power distribution density of different human tissues according to the absorption power density, and perform a volume integral calculation on the power distribution density to obtain the temperature value at each frequency point;

[0023] Generate a temperature rise frequency curve graph according to the temperature value at each frequency point;

[0024] Compare the temperature rise distribution graph and the transient temperature rise distribution graph to obtain the temperature change conditions of different human tissues.

[0025] Further, after determining the predicted risk position of human electromagnetic radiation exceeding the standard according to the temperature change conditions, the method further includes:

[0026] Obtain a rectification plan for reducing human radiation that matches the predicted risk position;

[0027] Output the simulation results, the predicted risk position, and the rectification plan.

[0028] The second aspect of the embodiments of the present application provides a human electromagnetic radiation prediction device, and the human electromagnetic radiation prediction device includes:

[0029] An acquisition unit, configured to acquire simulation model data, material parameters, and a simulation frequency range;

[0030] A construction unit, configured to construct a human electromagnetic radiation simulation prediction environment according to the simulation model data, the material parameters, the simulation frequency range, and an excitation source of a preset high-voltage component;

[0031] A simulation unit, configured to perform human electromagnetic radiation prediction simulation in the human electromagnetic radiation simulation prediction environment to obtain simulation results;

[0032] A first calculation unit, configured to calculate the absorption power density of different human tissues according to the simulation results and the material parameters;

[0033] A second calculation unit, configured to calculate the temperature change conditions of different human tissues according to the absorption power density;

[0034] A determination unit, configured to determine the predicted risk position of human electromagnetic radiation exceeding the standard according to the temperature change conditions.

[0035] In the above implementation process, the human body electromagnetic radiation prediction device can obtain simulation model data, material parameters, and simulation frequency range through an acquisition unit; construct a human body electromagnetic radiation simulation prediction environment according to the simulation model data, material parameters, simulation frequency range, and excitation source of a preset high-voltage component through a construction unit; perform human body electromagnetic radiation prediction simulation in the human body electromagnetic radiation simulation prediction environment through a simulation unit to obtain a simulation result; calculate the absorption power density of different human tissues according to the simulation result and material parameters through a first calculation unit; calculate the temperature change of different human tissues according to the absorption power density through a second calculation unit; and determine the predicted risk location of human body electromagnetic radiation exceeding the standard according to the temperature change through a determination unit. It can be seen that implementing this implementation method can predict human body electromagnetic radiation in the early stage of the development of an electric vehicle as a whole; it can also calculate the average increased temperature of the radiation of the electric vehicle to different human tissues / organs through integral calculation, thereby realizing the prediction of the radiation of the electric vehicle as a whole to different human tissues / organs, and improving the practicability and accuracy of human body electromagnetic radiation prediction.

[0036] Further, the first calculation unit includes:

[0037] A first calculation subunit, configured to calculate the radiation field intensity of different human tissues according to the simulation result and the simulation frequency range; wherein, the radiation field intensity includes electric field intensity and / or magnetic field intensity;

[0038] A determination subunit, configured to determine the material conductivity and material specific heat capacity according to the material parameters;

[0039] The first calculation subunit is further configured to calculate the absorption power density of different human tissues according to the material conductivity and the radiation field intensity.

[0040] Further, the second calculation unit includes:

[0041] A second calculation subunit, configured to calculate the local temperature rise of different human tissues according to the absorption power density;

[0042] A generation subunit, configured to generate a transient temperature rise distribution map of different human tissues according to the local temperature rise;

[0043] The second calculation subunit is further configured to determine the power distribution density of different human tissues according to the absorption power density, and perform volume integral calculation on the power distribution density to obtain the temperature value at each frequency point;

[0044] The generation subunit is further configured to generate a temperature rise frequency curve graph according to the temperature value at each frequency point;

[0045] For this sub-unit, it is used to compare the temperature rise distribution map and the transient temperature rise distribution map to obtain the temperature change conditions of different human tissues.

[0046] In a third aspect of the embodiments of the present application, an electronic device is provided, including a memory and a processor. The memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute the human body electromagnetic radiation prediction method according to any one of the first aspects of the embodiments of the present application.

[0047] In a fourth aspect of the embodiments of the present application, a computer-readable storage medium is provided, which stores computer program instructions. When the computer program instructions are read and run by a processor, the human body electromagnetic radiation prediction method according to any one of the first aspects of the embodiments of the present application is executed. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required to be used in the embodiments of the present application. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as a limitation of the scope. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0049] Figure 1 It is a schematic flowchart of a human body electromagnetic radiation prediction method provided by the embodiments of the present application;

[0050] Figure 2 It is a frequency curve graph of temperature rise of different tissues / organs provided by the embodiments of the present application;

[0051] Figure 3 It is a schematic structural diagram of a human body electromagnetic radiation prediction device provided by the embodiments of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0052] The following will describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application.

[0053] It should be noted that: similar reference numerals and letters denote similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of the present application, the terms "first", "second", etc. are only used for distinguishing descriptions, and cannot be understood as indicating or implying relative importance.

[0054] Embodiment 1

[0055] Please refer to Figure 1 , Figure 1The present application provides a flowchart of a method for predicting human electromagnetic radiation. Among them, the method for predicting human electromagnetic radiation includes:

[0056] S101. Obtain simulation model data, material parameters, and simulation frequency range.

[0057] In this embodiment, the method may preferably import the digital model of the whole vehicle body and set the material parameters.

[0058] In this embodiment, the method should also import the digital models of the outer envelopes of high-voltage components such as the electric drive system, power battery pack, and power supply system, as well as the digital models of high-voltage cables connected to them.

[0059] In this embodiment, high-voltage components such as the electric drive system, power battery pack, and power supply system all adopt solid models, and shielding layers are added to the high-voltage cables connecting them according to the actual type. Material parameters of high-voltage components and high-voltage cables are set. Usually, the material of the high-voltage component housing is aluminum, and the core wire of the high-voltage cable is copper.

[0060] In this embodiment, the simulation model data includes at least the digital model of the whole vehicle body, the digital model of the outer envelope of high-voltage components, the digital model of high-voltage cables, and the human body model.

[0061] In this embodiment, the digital model of the whole vehicle body adopts a sheet model. Usually, the thickness parameter is set to 0.5 mm - 1.5 mm, and the material is stainless steel. This can not only meet the requirements of the skin effect of alternating current on the metal surface but also ensure the simulation calculation efficiency.

[0062] In this embodiment, when importing the human body model, the human body material parameters should also be set.

[0063] In this embodiment, the material parameters include at least the vehicle body material parameters, high-voltage component material parameters, high-voltage cable material parameters, and human body material parameters.

[0064] In this embodiment, the simulation frequency range is the calculation frequency range that needs to be preset in advance.

[0065] In this embodiment, the analysis frequency range is set to 10 Hz - 400 kHz, and the frequency interval is shown in the following table.

[0066] Frequency range 10 Hz - 5 kHz 5 kHz - 50 kHz 50 kHz - 400 kHz Frequency interval 1 Hz 5 Hz 50 Hz

[0067] S102. Construct a simulation prediction environment for human electromagnetic radiation according to the simulation model data, material parameters, simulation frequency range, and preset excitation source of high-voltage components.

[0068] In this embodiment, the method can import electromagnetic models of human tissues, such as the brain, skin, bones, and eyes, etc.; the set material parameters include dielectric constant, conductivity, body density, and specific heat capacity, which can be specifically referred to in the following table.

[0069]

[0070] In this embodiment, the method can add radiation source excitation to high-voltage components such as power supplies, power battery packs, and electric drive systems, add voltage excitation or current excitation to high-voltage cables interconnected by high-voltage components, and add excitation sources under stationary, uniform, rapid acceleration, and rapid deceleration conditions, so as to realize the prediction of human electromagnetic protection performance under different conditions.

[0071] For example, the method imports the digital model of the whole vehicle body simplified into a surface model, the digital model of high-voltage components simplified into a volume model, the interconnected high-voltage cable model (i.e., the radiation emission simulation model of an electric vehicle whole vehicle), then imports the human electromagnetic model, and then adds the material parameters of human tissues / organs (including dielectric constant, conductivity, body density, and specific heat capacity). Then, according to different conditions, different voltage sources, current source excitations, and radiation source excitations are added to high-voltage components.

[0072] S103. Conduct human electromagnetic radiation prediction simulation in the human electromagnetic radiation simulation prediction environment to obtain simulation results.

[0073] S104. Calculate the radiation field intensity of different human tissues according to the simulation results and the simulation frequency range; among them, the radiation field intensity includes electric field intensity and / or magnetic field intensity.

[0074] S105. Determine the material conductivity and material specific heat capacity according to the material parameters.

[0075] S106. Calculate the absorbed power density of different human tissues according to the material conductivity and the radiation field intensity.

[0076] In this embodiment, the method calculates the near electric field / magnetic field of different human tissues through simulation. And according to the material conductivity and the electric field intensity, the absorbed power density of different human tissues is calculated.

[0077] In this embodiment, the method needs to calculate the electric field intensity, magnetic field intensity, and the absorbed power density of different tissues / organs of the human body inside the vehicle.

[0078] S107. Calculate the local temperature rise of different human tissues according to the absorbed power density.

[0079] In this embodiment, the method calculates the temperature change of different human tissues (i.e., the local temperature rise of different human tissues) according to the material specific heat capacity and the absorbed power density.

[0080] S108. Generate a transient temperature rise distribution map of different human tissues based on the local temperature rise.

[0081] In this embodiment, the calculation formula for the temperature change of different human tissues / organs is:

[0082] Local temperature rise = (absorbed power density * cumulative time) / (body density * volume * specific heat capacity of the material);

[0083] Among them, by calculating the local temperature rise based on the absorbed power density of each tissue / organ, a visual transient temperature rise distribution map of different human tissues / organs can be obtained.

[0084] In this embodiment, this method can obtain a visual transient temperature rise distribution map of different human tissues / organs through the absorbed power density distribution map according to the temperature formula.

[0085] S109. Determine the power distribution density of different human tissues based on the absorbed power density, and perform volume integration calculation on the power distribution density to obtain the temperature value at each frequency point.

[0086] In this embodiment, this method can first determine the power distribution density according to the absorbed power density, and then perform volume integration calculation on the power distribution density to further obtain the temperature value at each frequency point.

[0087] S110. Generate a temperature rise frequency curve graph based on the temperature value at each frequency point.

[0088] In this embodiment, this method can perform volume integration on the absorbed power density of different human tissues / organs, calculate the temperature value at each frequency point, so as to obtain a temperature rise frequency curve graph; at the same time, according to the temperature rise frequency curve graph, frequency integration can be performed to obtain the average elevated temperature of different tissues / organs.

[0089] In this embodiment, for tissues / organs other than the skin, the local temperature rise should not exceed 0.4 °C / m³, and for important parts such as the eyes and brain, the average elevated temperature under the cumulative time should not exceed 0.1 °C.

[0090] Please refer to Figure 2 , Figure 2 , which shows a frequency curve graph of the temperature rise of different tissues / organs. Among them, this method performs volume integration on the power density of different human tissues / organs, calculates the elevated temperature value at each frequency point, and obtains a frequency curve graph of the temperature rise of different tissues / organs as shown in Figure 2 . Among them, the top curve corresponds to bone, the second curve from top to bottom corresponds to skin, the third curve from top to bottom corresponds to brain, and the fourth curve from top to bottom corresponds to eyes.

[0091] S111. Compare the temperature rise distribution map and the transient temperature rise distribution map to obtain the temperature change conditions of different human tissues.

[0092] In this embodiment, according to the temperature rise frequency curve graphs of different tissues / organs, perform frequency integration to obtain the average elevated temperatures of different tissues / organs as shown in the following table.

[0093] Status Bone Brain Eye Skin Continuous duration_1 hour 8.65111E-07 0.0063879 0.0051115 1.41245E-06

[0094] S112. Determine the predicted risk positions where the human body's electromagnetic radiation exceeds the standard according to the temperature change conditions.

[0095] In this embodiment, this method can compare the temperature change conditions (transient temperature rise distribution and average elevated temperature) to confirm the predicted risk positions (exceeding the standard risk positions).

[0096] In this embodiment, this method can automatically add shielding materials, etc., so as to achieve corresponding rectification. At the same time, technicians are also allowed to handle it by themselves in this method.

[0097] In this embodiment, technicians can confirm the positions exceeding the standard according to the visual temperature rise distribution map, and add shielding materials to the corresponding high-voltage components for rectification.

[0098] S113. Obtain a rectification plan for reducing human radiation that matches the predicted risk positions.

[0099] S114. Output the simulation results, predicted risk positions, and rectification plans.

[0100] In this embodiment, this method proposes a method that is particularly suitable for evaluating and predicting the electromagnetic protection performance of high-voltage components on the human body during the development of electric vehicles. It can use only the vehicle body, high-voltage components, interconnected high-voltage cables, and the human electromagnetic model, add the corresponding voltage or current excitation and radiation source excitation of the high-voltage components, and then predict the electromagnetic protection performance of the whole vehicle on the human body. It does not require a real vehicle and there is no unnecessary harm to the human body during the testing process. This method truly achieves the pre-design and prediction of the electromagnetic protection performance of electric vehicles on the human body during the whole vehicle development.

[0101] In this embodiment, this method is suitable for the rectification process of the electromagnetic protection performance of electric vehicles on the human body. Specifically, this method can provide the visual electric field intensity, magnetic field intensity, and tissue / organ power density distribution inside the electric vehicle under different working conditions. Such results have no measurement errors, and can quickly, truly, and accurately predict the results, and can also accurately locate the risk points exceeding the standard, thus providing a good theoretical basis for rectification.

[0102] In this embodiment, the method can also derive the transient temperature rise distribution according to a formula, obtain the average elevated temperature by integrating the frequency curve graph of the temperature rise, and reduce the field strength distribution vector to a one-dimensional temperature scalar, realizing the prediction, comparison, and evaluation of the radiation of an electric vehicle to different human tissues / organs, thereby making the method have better feasibility and practicality.

[0103] In this embodiment, the execution subject of the method can be a computing device such as a computer or a server, and no limitation is made in this embodiment.

[0104] In this embodiment, the execution subject of the method can also be a smart device such as a smart phone or a tablet computer, and no limitation is made in this embodiment.

[0105] It can be seen that implementing the human electromagnetic radiation prediction method described in this embodiment can quickly and accurately predict the human electromagnetic protection performance of the entire electric vehicle, and can locate the risk points exceeding the standard through the visualized electric field strength, magnetic field strength, power density, and transient temperature rise distribution diagrams, so that the method can be applied to the early stage of the development of the entire electric vehicle. At the same time, the method can also obtain the average elevated temperature of the radiation of the electric vehicle to different human tissues / organs through integral calculation, thereby realizing the prediction, mutual comparison, and evaluation of the radiation of the entire electric vehicle to different human tissues / organs, and further improving the accuracy and practicality of the prediction.

[0106] Embodiment 2

[0107] Please refer to Figure 3 , Figure 3 which is a schematic structural diagram of a human electromagnetic radiation prediction device provided by an embodiment of the present application. As Figure 3 shown, the human electromagnetic radiation prediction device includes:

[0108] An acquisition unit 210, configured to acquire simulation model data, material parameters, and a simulation frequency range;

[0109] A construction unit 220, configured to construct a human electromagnetic radiation simulation prediction environment according to the simulation model data, material parameters, simulation frequency range, and an excitation source of a preset high-voltage component;

[0110] A simulation unit 230, configured to perform human electromagnetic radiation prediction simulation in the human electromagnetic radiation simulation prediction environment to obtain a simulation result;

[0111] A first calculation unit 240, configured to calculate the absorption power density of different human tissues according to the simulation result and material parameters;

[0112] A second calculation unit 250, configured to calculate the temperature change of different human tissues according to the absorption power density;

[0113] A determination unit 260, configured to determine a predicted risk position where the human body electromagnetic radiation exceeds the standard according to the temperature change situation.

[0114] In this embodiment, the simulation model data at least includes a vehicle body digital model, a high-voltage component outer envelope digital model, a high-voltage cable digital model, and a human body model;

[0115] The material parameters at least include vehicle body material parameters, high-voltage component material parameters, high-voltage cable material parameters, and human body material parameters.

[0116] As an alternative embodiment, the first calculation unit 240 includes:

[0117] A first calculation subunit 241, configured to calculate the radiation field intensity of different human tissues according to the simulation results and the simulation frequency range; wherein, the radiation field intensity includes electric field intensity and / or magnetic field intensity;

[0118] A determination subunit 242, configured to determine the material conductivity and the material specific heat capacity according to the material parameters;

[0119] The first calculation subunit 241 is further configured to calculate the absorption power density of different human tissues according to the material conductivity and the radiation field intensity.

[0120] As an alternative embodiment, the second calculation unit 250 includes:

[0121] A second calculation subunit 251, configured to calculate the local temperature rise of different human tissues according to the absorption power density;

[0122] A generation subunit 252, configured to generate a transient temperature rise distribution map of different human tissues according to the local temperature rise;

[0123] The second calculation subunit 251 is further configured to determine the power distribution density of different human tissues according to the absorption power density, and perform a volume integral calculation on the power distribution density to obtain the temperature value at each frequency point;

[0124] The generation subunit 252 is further configured to generate a temperature rise frequency curve graph according to the temperature value at each frequency point;

[0125] A comparison subunit 253, configured to compare the temperature rise distribution map and the transient temperature rise distribution map to obtain the temperature change situation of different human tissues.

[0126] As an alternative embodiment, the human body electromagnetic radiation prediction device further includes:

[0127] An acquisition unit 210, configured to acquire a rectification plan for reducing human body radiation that matches the predicted risk position;

[0128] An output unit 270, configured to output the simulation results, the predicted risk position, and the rectification plan.

[0129] In the embodiments of the present application, the explanation of the human body electromagnetic radiation prediction device can be referred to the description in Embodiment 1, and thus will not be elaborated herein.

[0130] It can be seen that implementing the human body electromagnetic radiation prediction device described in this embodiment can quickly and accurately predict the human body electromagnetic protection performance of an electric vehicle, and can locate the risk points exceeding the standard through the visual distribution maps of electric field strength, magnetic field strength, power density and transient temperature rise, so that this method can be applied to the early stage of the development of the electric vehicle as a whole. At the same time, this method can also obtain the average elevated temperature of the radiation of the electric vehicle to different tissues / organs of the human body through integral calculation, thereby realizing the prediction, mutual comparison and evaluation of the radiation of the electric vehicle as a whole to different tissues / organs of the human body, and further improving the accuracy and practicability of the prediction.

[0131] The embodiments of the present application provide an electronic device, including a memory and a processor, where the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute the human body electromagnetic radiation prediction method in Embodiment 1 of the present application.

[0132] The embodiments of the present application provide a computer-readable storage medium, which stores computer program instructions. When the computer program instructions are read and run by a processor, the human body electromagnetic radiation prediction method in Embodiment 1 of the present application is executed.

[0133] In several embodiments provided by the present application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions and operations of devices, methods and computer program products according to multiple embodiments of the present application. In this regard, each block in the flowchart or block diagram may represent a module, a program segment or a part of code, and the module, program segment or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and the combination of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0134] In addition, in each embodiment of the present application, each functional module can be integrated together to form an independent part, or each module can exist alone, or two or more modules can be integrated to form an independent part.

[0135] If the above-mentioned function is implemented in the form of a software functional module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs.

[0136] The above are only the embodiments of the present application and are not used to limit the protection scope of the present application. For those skilled in the art, the present application can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application. It should be noted that similar reference numerals and letters indicate similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0137] The above is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed by the present application, and all of them should be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0138] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or device comprising the said element.

Claims

1. A method for predicting human body electromagnetic radiation, characterized in that, Including: Obtain simulation model data, material parameters, and simulation frequency range; Construct a human body electromagnetic radiation simulation prediction environment according to the simulation model data, the material parameters, the simulation frequency range, and an excitation source of a preset high-voltage component; Conduct human body electromagnetic radiation prediction simulation in the human body electromagnetic radiation simulation prediction environment to obtain a simulation result; Calculate the absorption power density of different human tissues according to the simulation result and the material parameters; Calculate the temperature change of different human tissues according to the absorption power density; Determine the predicted risk position where human body electromagnetic radiation exceeds the standard according to the temperature change; Among them, calculating the temperature change of different human tissues according to the absorption power density includes: Calculate the local temperature rise of different human tissues according to the absorption power density; Generate a transient temperature rise distribution map of different human tissues according to the local temperature rise; Determine the power distribution density of different human tissues according to the absorption power density, and perform volume integration calculation on the power distribution density to obtain the temperature value of each frequency point; Generate a temperature rise frequency curve graph according to the temperature value of each frequency point; Compare the temperature rise frequency curve graph and the transient temperature rise distribution map to obtain the temperature change of different human tissues.

2. The human body electromagnetic radiation prediction method according to claim 1, characterized in that The simulation model data at least includes a vehicle body digital model, a high-voltage component outer envelope digital model, a high-voltage cable digital model, and a human body model; The material parameters at least include vehicle body material parameters, high-voltage component material parameters, high-voltage cable material parameters, and human body material parameters.

3. The human body electromagnetic radiation prediction method according to claim 1, wherein Calculating the absorption power density of different human tissues according to the simulation result and the material parameters includes: Calculate the radiation field intensity of different human tissues according to the simulation result and the simulation frequency range; wherein, the radiation field intensity includes electric field intensity and / or magnetic field intensity; Determine the material conductivity and material specific heat capacity according to the material parameters; Calculate the absorption power density of different human tissues according to the material conductivity and the radiation field intensity.

4. The human body electromagnetic radiation prediction method according to claim 1, characterized in that After determining the predicted risk position where human body electromagnetic radiation exceeds the standard according to the temperature change, the method further includes: Obtain a rectification plan for reducing human body radiation that matches the predicted risk position; Output the simulation result, the predicted risk position, and the rectification plan.

5. A human body electromagnetic radiation prediction device, characterized in that The human body electromagnetic radiation prediction device includes: An acquisition unit for acquiring simulation model data, material parameters, and simulation frequency range; A construction unit for constructing a human body electromagnetic radiation simulation prediction environment according to the simulation model data, the material parameters, the simulation frequency range, and an excitation source of a preset high-voltage component; A simulation unit for conducting human body electromagnetic radiation prediction simulation in the human body electromagnetic radiation simulation prediction environment to obtain a simulation result; A first calculation unit for calculating the absorption power density of different human tissues according to the simulation result and the material parameters; A second calculation unit for calculating the temperature change of different human tissues according to the absorption power density; A determination unit for determining the predicted risk position where human body electromagnetic radiation exceeds the standard according to the temperature change; Among them, the second calculation unit includes: A second calculation subunit, configured to calculate the local temperature rise of different human tissues according to the absorption power density; A generation subunit, configured to generate a transient temperature rise distribution map of different human tissues according to the local temperature rise; The second calculation subunit is further configured to determine the power distribution density of different human tissues according to the absorption power density, and perform a volume integral calculation on the power distribution density to obtain the temperature value at each frequency point; The generation subunit is further configured to generate a temperature rise frequency curve graph according to the temperature value at each frequency point; A comparison subunit, configured to compare the temperature rise frequency curve graph and the transient temperature rise distribution map to obtain the temperature change conditions of different human tissues.

6. The human body electromagnetic radiation prediction device according to claim 5, wherein The first calculation unit includes: A first calculation subunit, configured to calculate the radiation field intensity of different human tissues according to the simulation result and the simulation frequency range; wherein, the radiation field intensity includes an electric field intensity and / or a magnetic field intensity; A determination subunit, configured to determine the material conductivity and the material specific heat capacity according to the material parameters; The first calculation subunit is further configured to calculate the absorption power density of different human tissues according to the material conductivity and the radiation field intensity.

7. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory is configured to store a computer program, and the processor runs the computer program to enable the electronic device to execute the human electromagnetic radiation prediction method according to any one of claims 1 to 4.

8. A readable storage medium, characterized in that, Computer program instructions are stored in the readable storage medium, and when the computer program instructions are read and run by a processor, the human electromagnetic radiation prediction method according to any one of claims 1 to 4 is executed.

Images