A thermal management system for TMBS semiconductor devices

Abstract

The present application relates to the field of semiconductor thermal management technology. The present application provides a thermal management system for a TMBS semiconductor device, including: an acquisition module, a temperature reading module, a simulation module, an analysis module and a strategy execution module; the acquisition module is used to obtain data related to thermal management when the TMBS semiconductor device is running, and the source includes but is not limited to a temperature sensor, and the temperature sensor is set in each key area of ​​the TMBS semiconductor device; the temperature reading module is used to read and process the temperature data of the temperature sensor; the simulation module is used to establish a thermal model of the TMBS semiconductor device and obtain a temperature distribution diagram when the TMBS semiconductor device is running; the analysis module is used to obtain a color-labeled temperature distribution diagram; the strategy execution module is used to adjust the heat dissipation system and power output; the present application realizes accurate monitoring and adjustment of the temperature of the TMBS semiconductor device through the coordinated work of multiple modules to ensure that its thermal management during operation is more efficient and stable.

Description

Technical Field

[0001] The invention belongs to the field of semiconductor thermal management, and in particular relates to a thermal management system of a TMBS semiconductor device. Background Art

[0002] TMBS (Tunneling-Metal-Insulator-Semiconductor) is a specific type of semiconductor device, a new type of power device that combines the MOS drain structure and the Schottky barrier, with the advantages of low leakage current, fast switching speed and low turn-on voltage drop, and is widely used in power management, electric vehicles, aerospace and other fields. The basic structure of this device usually includes metal, insulator and semiconductor layers, and uses the tunneling effect in quantum mechanics to realize the flow of current.

[0003] Thermal management is crucial in the operation of TMBS semiconductor devices. Since TMBS semiconductor devices generate a lot of heat when working, if this heat cannot be effectively dissipated, it may cause the device to overheat, thereby affecting performance, reducing efficiency, and even damaging the device.

[0004] However, the existing thermal management of TMBS semiconductor devices often relies on temperature sensors in fixed positions, which may not be able to fully reflect the temperature distribution of the entire device. Secondly, the existing technology usually simply uses the collected temperature data to formulate cooling strategies without comprehensively considering multiple sensor data or performing more complex calculations. This cannot accurately reflect the complex thermal distribution inside the device. Summary of the invention

[0005] In view of the above-mentioned defects of the prior art, the present invention proposes a thermal management system for a TMBS semiconductor device. The technical solution designed by the present invention includes:

[0006] Acquisition module, temperature reading module, simulation module, analysis module and strategy execution module;

[0007] The acquisition module is used to obtain data related to thermal management from different sources when the TMBS semiconductor device is running, the sources include but are not limited to temperature sensors, environmental sensors, current sensors and voltage sensors, and the temperature sensors are arranged in various key areas of the operation of the TMBS semiconductor device;

[0008] The temperature reading module is used to read the temperature data of the temperature sensor and the historical simulation results, gradually adjust the temperature data weights of each key area and fuse and output the target temperature data;

[0009] The simulation module is used to establish a thermal model of the TMBS semiconductor device and obtain a temperature distribution diagram of the TMBS semiconductor device when it is running;

[0010] The analysis module is used to map the temperature data in the temperature distribution map into grayscale values ​​to obtain the grayscale values ​​of the corresponding temperatures, and map the grayscale values ​​of the corresponding temperatures to a specific hue range according to the temperature through the HSV model to obtain temperature data with color information and remap it back to the temperature distribution map to obtain a color-labeled temperature distribution map;

[0011] The strategy execution module is used to adjust the power output of the heat dissipation system and the TMBS semiconductor device according to the color-coded temperature distribution diagram;

[0012] The stepwise adjustment of the temperature data weights of each key area includes:

[0013] Calculate the attention of the temperature data of each key area and the historical simulation results, and normalize the attention as the weight of the temperature data of each key area;

[0014] The attention formula is as follows:

[0015]

[0016] In the formula, is the attention level of the temperature data and historical simulation results of key area i, is the temperature data of key area i, is the historical simulation result of key area i, is the hyperbolic tangent function, is the mask matrix function.

[0017] Preferably, the key areas include but are not limited to nodes, heat sinks, interfaces, packages and substrates.

[0018] Preferably, the mask matrix function formula is as follows:

[0019]

[0020]

[0021] In the formula, is the measurement function of the temperature data of key area i and the historical simulation results, is the mask decision threshold, To control the metric function Contribution To adjust The baseline value, and are all constants.

[0022] Preferably, the formula for fusion output target temperature data is as follows:

[0023]

[0024] In the formula, is the target temperature data.

[0025] Preferably, said establishing the thermal model of the TMBS semiconductor device includes using Silvaco and COMSOL software to perform physical modeling, electrothermal coupling simulation and thermal field simulation.

[0026] Preferably, the thermal model formula of the TMBS semiconductor device is as follows:

[0027]

[0028]

[0029] In the formula, is the internal heat source term, is the density of TMBS semiconductor devices, is the specific heat capacity of the TMBS semiconductor device, is the temperature gradient, is the heat flux vector, is the thermal conductivity.

[0030] Preferably, mapping the grayscale value of the corresponding temperature to a specific hue range according to the temperature through the HSV model includes:

[0031] The Sobel operator is used to calculate the horizontal and vertical coordinate gradients of the temperature distribution map, the edge information of the temperature distribution map is captured, the coordinate gradient data group of the temperature distribution map is constructed, the grayscale value of the corresponding temperature is input into the coordinate gradient data group of the temperature distribution map, the target grayscale value range is preset and the coordinate gradient data group is traversed, the temperature distribution map within the target grayscale value range is retained, the temperature distribution map within the target grayscale value range is normalized and mapped to the HSV hue range, from blue to red indicating temperature from low to high.

[0032] Preferably, the coordinate gradient data set formula of the temperature distribution diagram is as follows:

[0033]

[0034] In the formula, is the abscissa gradient of the temperature distribution diagram, is the vertical gradient of the temperature distribution diagram.

[0035] Beneficial effects:

[0036] 1. The present invention realizes accurate monitoring and regulation of the temperature of TMBS semiconductor devices through the coordinated work of multiple modules, so as to ensure that its thermal management during operation is more efficient and stable;

[0037] 2. The present invention generates a temperature distribution diagram through the simulation module, and uses the color mapping technology of the analysis module to correspond different temperatures to specific color ranges, thereby generating a more intuitive color-annotated temperature diagram, which can make analysis and decision-making more convenient;

[0038] 3. The strategy execution module of the present invention uses color-coded temperature distribution diagrams to automatically or manually adjust the settings of the cooling system and control the power output of the TMBS semiconductor device. When the temperature of the device rises, the system can take prompt action to reduce the temperature and prevent the device from being damaged due to overheating. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a structural schematic diagram of a preferred embodiment of the present invention. DETAILED DESCRIPTION

[0040] The embodiments of the present invention are described in detail below. The following embodiments are implemented on the premise of the technical solution of the present invention, and detailed implementation methods and specific operation processes are given, but the protection scope of the present invention is not limited to the following embodiments.

[0041] The present invention designs a thermal management system for TMBS semiconductor devices, such as Figure 1 As shown, the technical solution specifically includes:

[0042] Acquisition module, temperature reading module, simulation module, analysis module and strategy execution module;

[0043] The acquisition module is used to obtain data related to thermal management from different sources when the TMBS semiconductor device is running, including but not limited to temperature sensors, environmental sensors, current sensors and voltage sensors. The temperature sensors are set in various key areas of the TMBS semiconductor device;

[0044] The temperature reading module is used to read the temperature data of the temperature sensor and the historical simulation results, gradually adjust the temperature data weights of each key area, and fuse and output the target temperature data;

[0045] The simulation module is used to establish a thermal model of the TMBS semiconductor device and obtain the temperature distribution diagram of the TMBS semiconductor device during operation;

[0046] The analysis module is used to map the temperature data in the temperature distribution map to grayscale values, obtain the grayscale values ​​of the corresponding temperatures, and map the grayscale values ​​of the corresponding temperatures to a specific hue range according to the temperature through the HSV model, obtain the temperature data with color information and remap it back to the temperature distribution map to obtain the color-labeled temperature distribution map;

[0047] The strategy execution module is used to adjust the power output of the cooling system and the TMBS semiconductor device according to the color-coded temperature distribution map;

[0048] Specifically, the policy execution module is also used to set a temperature threshold. When the temperature exceeds the set value, an alarm is triggered and the semiconductor device is automatically stopped. For example, by monitoring the power output and temperature distribution diagram, if the temperature in a certain area is too high, the module can increase the fan speed to speed up air circulation. When the temperature approaches the upper limit, the system can reduce the power of the device to reduce heat generation.

[0049] Gradually adjust the temperature data weights of each key area including:

[0050] Calculate the attention of the temperature data of each key area and the historical simulation results, and normalize the attention as the weight of the temperature data of each key area;

[0051] The attention formula is as follows:

[0052]

[0053] In the formula, is the attention level of the temperature data and historical simulation results of key area i, is the temperature data of key area i, is the historical simulation result of key area i, is the hyperbolic tangent function, is the mask matrix function.

[0054] Preferably, the key areas include but are not limited to nodes, heat sinks, interfaces, packaging and substrates.

[0055] Preferably, the mask matrix function formula is as follows:

[0056]

[0057]

[0058] In the formula, is the measurement function of the temperature data of key area i and the historical simulation results, is the mask decision threshold, To control the metric function Contribution To adjust The baseline value, and are all constants.

[0059] Specifically, the temperature data of different key areas are weighted. Different key areas have different influences on the overall temperature distribution. The weights of each area are initially set, including 0.4 for nodes, 0.3 for heat sinks, 0.2 for interfaces, 0.05 for packages, and 0.05 for substrates. The historical simulation results are analyzed to observe the influence of the temperature of different areas on the thermal distribution map. The weights of each area are gradually adjusted and the temperature data of different areas are integrated to output the target temperature data. For the mask matrix function, through The temperature data of the key area and the sum of the historical simulation results are processed and the sum is limited between -1 and 1. This can prevent extreme values ​​from having too much impact on the subsequent attention calculation. The mask matrix function is used to correct and adjust After obtaining the attention of each area, these attentions are normalized (i.e. adjusted to the same scale, usually between 0 and 1), and then the weights are adjusted using these normalized attentions. The new weights are directly equal to the normalized attentions, that is, the weights of each area are dynamically adjusted according to the difference between the temperature data and the historical simulation results.

[0060] Preferably, the formula for fusion output target temperature data is as follows:

[0061]

[0062] In the formula, is the target temperature data.

[0063] Preferably, establishing the thermal model of the TMBS semiconductor device includes using Silvaco and COMSOL software to perform physical modeling, electrothermal coupling simulation and thermal field simulation.

[0064] Preferably, the TMBS semiconductor device thermal model formula is as follows:

[0065]

[0066]

[0067] In the formula, is the internal heat source term, is the density of TMBS semiconductor devices, is the specific heat capacity of the TMBS semiconductor device, is the temperature gradient, is the heat flux vector, is the thermal conductivity.

[0068] Specifically, the temperature data, environmental data, current data and voltage data collected by the acquisition module have important applications in the establishment of thermal models, helping to improve the accuracy and reliability of the model and ensure that the thermal management system can effectively respond to actual working conditions. For example, temperature data is used to set the initial conditions and boundary conditions of the thermal model and generate temperature distribution diagrams; environmental data is used to determine the working environment of the semiconductor device, and by incorporating ambient temperature data into the model, the thermal behavior of the device under actual environmental conditions can be more accurately simulated; current data and voltage data are used to calculate power consumption, P=VI, where V is voltage and I is current, which is a key factor in the thermal model because power consumption is directly converted into heat. Accurate current measurement helps to establish a more accurate power consumption model and adjust the heat source distribution in the thermal model to make the model more in line with actual conditions.

[0069] Preliminary physical modeling includes using Silvaco's TCAD tools Athena and Atlas to build the geometric model and material properties of the TMBS device. Athena is used to generate the two-dimensional or three-dimensional geometric structure of the TMBS device and simulate the manufacturing process, such as doping, oxidation, etching, etc. Atlas simulates the electrical properties on the generated geometric model, such as current-voltage characteristics, electron mobility, etc.; define the thermal properties of the TMBS semiconductor device, such as thermal conductivity, specific heat capacity and density;

[0070] The electrothermal coupling simulation includes: Atlas simulates the electrical characteristics of the TMBS device while taking the self-heating effect into consideration, analyzes the Joule heat generated by the current in the device by setting the simulation conditions, and outputs the results as temperature distribution and power dissipation distribution; after the electrothermal coupling simulation, the heat source data (such as power dissipation distribution) is extracted from Silvaco and used as the heat source input in COMSOL.

[0071] Thermal field simulation includes model import, physical field setting, meshing and solver setting. Model import includes importing the geometric structure generated by Silvaco into COMSOL, and using COMSOL's "LiveLink" function to directly import Silvaco's data seamlessly; physical field setting includes selecting the "heat conduction" module, setting boundary conditions and heat sources, and using the power dissipation data obtained in Silvaco to define the heat source inside the TMBS device; meshing includes setting a suitable mesh for the model to accurately simulate the temperature field distribution. Refining the mesh can improve the simulation accuracy, especially in the high temperature gradient area; setting the solver includes selecting a suitable time step and solver to perform steady-state or transient heat conduction simulation, where the time step uses COMSOL to automatically adjust the time step to adapt to the dynamic changes of the model, and the solver uses the GMRES solver. After the simulation, the temperature distribution diagram of the TMBS device is generated.

[0072] Preferably, mapping the grayscale value of the corresponding temperature to a specific hue range according to the temperature through the HSV model includes:

[0073] The Sobel operator is used to calculate the horizontal and vertical gradients of the temperature distribution map, the edge information of the temperature distribution map is captured, the coordinate gradient data group of the temperature distribution map is constructed, the grayscale value corresponding to the temperature is input into the coordinate gradient data group of the temperature distribution map, the target grayscale value range is preset and the coordinate gradient data group is traversed, the temperature distribution map within the target grayscale value range is retained, the temperature distribution map within the target grayscale value range is normalized and mapped to the HSV hue range, from blue to red indicating temperature from low to high.

[0074] Preferably, the coordinate gradient data set formula of the temperature distribution diagram is as follows:

[0075]

[0076] In the formula, is the abscissa gradient of the temperature distribution diagram, is the vertical gradient of the temperature distribution diagram.

[0077] Specifically, the grayscale values ​​of the temperature distribution graph within the target grayscale value range are normalized to map them to the range of [0,1], so that the temperature values ​​can be conveniently mapped to the hue range. In the HSV color model, the hue is represented by 0° to 360°, representing a circle of colors from blue to red. The saturation and brightness are fixed to maintain the purity and brightness of the color. The fixed saturation is set to 1 (indicating full saturation) and the brightness is set to 1 (indicating the brightest). , its value is {1,-1,0,0}, which means that the gradient is calculated only in the horizontal direction, emphasizing the changes of left and right pixels. , its value is {0,0,1,-1}, which means that the gradient is calculated only in the vertical direction, emphasizing the changes of upper and lower pixels; for example, The {1,-1} can be understood as the difference between the left pixel and the right pixel; {1,-1} is the difference between the upper pixel and the lower pixel. Through such calculation, we can get the rate of change in the temperature distribution map in two directions, and then extract the edge information.

[0078] The preferred specific embodiments of the present invention are described in detail above. It should be understood that ordinary technicians in the field can make many modifications and changes based on the concept of the present invention without creative work. Therefore, all technical solutions that can be obtained by technicians in the technical field based on the concept of the present invention through logical analysis, reasoning or limited experiments on the basis of the prior art should be within the scope of protection determined by the claims.

Claims

1. A thermal management system for a TMBS semiconductor device, characterized in that: include: Acquisition module, temperature reading module, simulation module, analysis module and strategy execution module; The acquisition module is used to obtain data related to thermal management from different sources when the TMBS semiconductor device is running, the sources include but are not limited to temperature sensors, environmental sensors, current sensors and voltage sensors, and the temperature sensors are arranged in various key areas of the operation of the TMBS semiconductor device; The temperature reading module is used to read the temperature data of the temperature sensor and the historical simulation results, gradually adjust the temperature data weights of each key area and fuse and output the target temperature data; The simulation module is used to establish a thermal model of the TMBS semiconductor device and obtain a temperature distribution diagram of the TMBS semiconductor device when it is running; The analysis module is used to map the temperature data in the temperature distribution map into grayscale values ​​to obtain the grayscale values ​​of the corresponding temperatures, and map the grayscale values ​​of the corresponding temperatures to a specific hue range according to the temperature through the HSV model to obtain temperature data with color information and remap it back to the temperature distribution map to obtain a color-labeled temperature distribution map; The strategy execution module is used to adjust the power output of the heat dissipation system and the TMBS semiconductor device according to the color-coded temperature distribution diagram; The stepwise adjustment of the temperature data weights of each key area includes: Calculate the attention of the temperature data of each key area and the historical simulation results, and normalize the attention as the weight of the temperature data of each key area; The attention formula is as follows: ; In the formula, is the attention level of the temperature data and historical simulation results of key area i, is the temperature data of key area i, is the historical simulation result of key area i, is the hyperbolic tangent function, is the mask matrix function.

2. A thermal management system for a TMBS semiconductor device according to claim 1, characterized in that: The key areas include but are not limited to nodes, heat sinks, interfaces, packaging and substrates.

3. The thermal management system of a TMBS semiconductor device according to claim 1, characterized in that: The mask matrix function formula is as follows: ; ; In the formula, is the measurement function of the temperature data of key area i and the historical simulation results, is the mask decision threshold, To control the metric function Contribution To adjust The baseline value of and are all constants.

4. The thermal management system of a TMBS semiconductor device according to claim 3, characterized in that: The formula for fusion output target temperature data is as follows: ; In the formula, is the target temperature data.

5. The thermal management system of a TMBS semiconductor device according to claim 1, characterized in that: The establishment of the TMBS semiconductor device thermal model includes using Silvaco and COMSOL software to perform physical modeling, electrothermal coupling simulation and thermal field simulation.

6. The thermal management system of a TMBS semiconductor device according to claim 5, characterized in that: The TMBS semiconductor device thermal model formula is as follows: ; ; In the formula, is the internal heat source term, is the density of TMBS semiconductor devices, is the specific heat capacity of the TMBS semiconductor device, is the temperature gradient, is the heat flux vector, is the thermal conductivity.

7. The thermal management system of a TMBS semiconductor device according to claim 1, characterized in that: The method of mapping the grayscale value of the corresponding temperature to a specific hue range according to the temperature through the HSV model includes: The Sobel operator is used to calculate the horizontal and vertical coordinate gradients of the temperature distribution map, the edge information of the temperature distribution map is captured, the coordinate gradient data group of the temperature distribution map is constructed, the grayscale value of the corresponding temperature is input into the coordinate gradient data group of the temperature distribution map, the target grayscale value range is preset and the coordinate gradient data group is traversed, the temperature distribution map within the target grayscale value range is retained, the temperature distribution map within the target grayscale value range is normalized and mapped to the HSV hue range, from blue to red indicating temperature from low to high.

8. The thermal management system of a TMBS semiconductor device according to claim 7, characterized in that: The coordinate gradient data set formula of the temperature distribution diagram is as follows: ; In the formula, is the abscissa gradient of the temperature distribution diagram, is the vertical gradient of the temperature distribution diagram.

Images