Junction temperature calculation method, device and equipment of semiconductor, medium and calculation equipment

Abstract

The invention belongs to the technical field of semiconductor device junction temperature calculation, and particularly relates to a semiconductor junction temperature calculation method, device and equipment, a medium and calculation equipment. The method comprises the steps of obtaining a device type and an electrical parameter of a target semiconductor device; determining device loss and device thermal resistance of the target semiconductor device according to the device type and the electrical parameters; acquiring a preset pipe network, cooling liquid parameters and a thermal resistance flow curve between the preset pipe network and the target semiconductor device; the pipe network flow of the preset pipe network is determined according to the preset pipe network and the cooling liquid parameters; determining the heat resistance of the radiator according to the pipe network flow and the heat resistance flow curve; and determining the calculated junction temperature of the target semiconductor device according to the device loss, the device thermal resistance and the radiator thermal resistance. Compared with other software or calculation methods, the method has the advantages that the calculation efficiency is greatly improved, and the professional threshold of a user is greatly reduced.

Description

Technical Field

[0001] This invention belongs to the technical field of junction temperature calculation for semiconductor devices, specifically relating to methods, apparatus, equipment, media, and computing devices for calculating junction temperature of semiconductors. Background Technology

[0002] The resistance loss of a converter's water-cooling system mainly consists of resistance losses caused by local obstructions such as pipe diameter changes and bends. In engineering design, recommended values ​​for the resistance coefficient and equivalent length of pipes or valves are often obtained by consulting reference books. In engineering calculations, the flow resistance characteristics of each water circuit component can be uniformly equivalent to a straight pipe of a certain equivalent length for network calculation, i.e., the equivalent pipe length method. However, the method of equivalently converting the flow resistance characteristics of components to straight pipes heavily depends on the conversion position on the flow resistance curve, and the characteristics of friction resistance and local obstruction inevitably differ. Summary of the Invention

[0003] To address the aforementioned technical problems, this invention proposes a method, apparatus, device, medium, and computing device for calculating the junction temperature of semiconductors. This application involves: obtaining the device type and electrical parameters of a target semiconductor device; determining the device loss and thermal resistance of the target semiconductor device based on the device type and electrical parameters; obtaining preset piping network and coolant parameters, as well as the thermal resistance-flow curve between the preset piping network and the target semiconductor device; determining the piping network flow rate based on the preset piping network and coolant parameters; determining the heat sink thermal resistance based on the piping network flow rate and the thermal resistance-flow curve; and determining the calculated junction temperature of the target semiconductor device based on the device loss, the device thermal resistance, and the heat sink thermal resistance. Compared to other software or calculation methods, this significantly improves computational efficiency and greatly reduces the professional barrier for users.

[0004] To solve the above-mentioned technical problems, the technical solution adopted by the present invention includes five aspects.

[0005] In a first aspect, this application provides a method for calculating the junction temperature of a semiconductor, comprising: obtaining the device type and electrical parameters of a target semiconductor device; determining the device loss and thermal resistance of the target semiconductor device based on the device type and the electrical parameters; obtaining preset pipeline and coolant parameters, as well as a thermal resistance-flow curve between the preset pipeline and the target semiconductor device; determining the pipeline flow rate of the preset pipeline based on the preset pipeline and the coolant parameters; determining the heat sink thermal resistance based on the pipeline flow rate and the thermal resistance-flow curve; and determining the calculated junction temperature of the target semiconductor device based on the device loss, the device thermal resistance, and the heat sink thermal resistance.

[0006] In some embodiments, the preset pipeline network includes: a plurality of pipeline branches, each pipeline branch including: a plurality of pipeline components; the coolant parameters include: a first coolant parameter and a second coolant parameter; determining the pipeline flow rate of the preset pipeline network based on the preset pipeline network and the coolant parameters includes: acquiring the flow resistance characteristic points of each pipeline branch and the component flow resistance curves of each pipeline component; determining the pipeline flow resistance curve based on the flow resistance characteristic points; determining the branch flow resistance curve polynomial of each pipeline branch based on the pipeline flow resistance curve, the component flow resistance curve, and the first coolant parameter; determining the pipeline flow resistance model of the preset pipeline network based on the plurality of branch flow resistance curve polynomials; and determining the pipeline flow rate of the preset pipeline network based on the pipeline flow resistance model and the second coolant parameter.

[0007] In some embodiments, determining the pipeline flow resistance curve based on the flow resistance characteristic point includes: determining the equivalent pipe length of the pipeline branch based on the flow resistance characteristic point; and determining the pipeline flow resistance curve based on the equivalent pipe length.

[0008] In some embodiments, the first coolant parameters include: a first coolant density and a first coolant viscosity; the step of determining the branch flow resistance curve polynomial of each of the pipe branches based on the pipe flow resistance curve, the device flow resistance curve, and the first coolant parameters includes: obtaining a preset first expected error; determining a density correction value based on the first coolant density; determining a viscosity correction value based on the first coolant viscosity; determining a pipe flow resistance quadratic polynomial based on the density correction value, the viscosity correction value, and the pipe flow resistance curve; determining a device flow resistance quadratic polynomial based on the density correction value, the viscosity correction value, and the device flow resistance curve; and determining a device flow resistance quadratic polynomial based on the device flow resistance quadratic polynomial and the pipe flow resistance quadratic polynomial. The polynomial determines the average fitting error; based on the first expected error and the average fitting error, it is determined whether the device flow resistance quadratic polynomial and the pipeline flow resistance quadratic polynomial meet the requirements; when the device flow resistance quadratic polynomial and the pipeline flow resistance quadratic polynomial do not meet the requirements, the device flow resistance quadratic polynomial and the pipeline flow resistance quadratic polynomial are iteratively fitted based on the average fitting error until the device flow resistance quadratic polynomial and the pipeline flow resistance quadratic polynomial meet the requirements; when the device flow resistance quadratic polynomial and the pipeline flow resistance quadratic polynomial meet the requirements, the branch flow resistance curve polynomial of the pipeline branch is determined based on the device flow resistance quadratic polynomial and the pipeline flow resistance quadratic polynomial.

[0009] In some embodiments, the second coolant parameters include: second coolant viscosity, second coolant density, and total flow rate; determining the pipeline flow rate of the preset pipeline based on the pipeline flow resistance model and the second coolant parameters includes: obtaining a preset target accuracy range and a second expected error; iteratively calculating the coolant viscosity, coolant density, total flow rate, and pipeline flow resistance model using Newton's iteration method to obtain the pipeline approximate flow rate; determining the approximate accuracy based on the pipeline approximate flow rate; determining the accuracy error based on the approximate accuracy and the target accuracy; determining whether the pipeline approximate flow rate meets the requirements based on the accuracy error and the second expected error; when it is determined that the pipeline approximate flow rate does not meet the requirements, iterating the pipeline approximate flow rate until the pipeline approximate flow rate meets the requirements; when the pipeline approximate flow rate meets the requirements, determining the pipeline approximate flow rate as the pipeline flow rate.

[0010] In some embodiments, the method further includes: obtaining the desired junction temperature of the target semiconductor device; determining whether the piping network meets the requirements based on the desired junction temperature and the calculated junction temperature; and when the piping network does not meet the requirements, determining an adjustment strategy for the preset piping network and / or the coolant parameters based on the desired junction temperature and the calculated junction temperature.

[0011] Secondly, this application also proposes a semiconductor junction temperature calculation device, comprising: a first acquisition module for acquiring the device type and electrical parameters of a target semiconductor device; a second acquisition module for acquiring preset pipe network and coolant parameters, as well as a thermal resistance-flow curve between the preset pipe network and the target semiconductor device; a first determination module for determining the pipe network flow rate of the preset pipe network based on the preset pipe network and coolant parameters; a second determination module for determining the device loss and device thermal resistance of the target semiconductor device based on the device type and the electrical parameters; a third determination module for determining the heat sink thermal resistance based on the pipe network flow rate and the thermal resistance-flow curve; and a fourth determination module for determining the calculated junction temperature of the target semiconductor device based on the device loss, the device thermal resistance, and the heat sink thermal resistance.

[0012] Thirdly, this application proposes an electronic device, characterized in that it comprises: a memory and a processor, wherein the memory stores a computer program, which, when executed by the processor, performs the method described in any of the first aspects.

[0013] Fourthly, this application proposes a storage medium, characterized in that the computer program stored in the storage medium can be executed by one or more processors, the computer program being able to implement the method described in any of the first aspects.

[0014] Fifthly, this application proposes a junction temperature calculation device, comprising: a flow resistance curve calculation module, a pipe network calculation module, and a junction temperature calculation module; the flow resistance curve calculation module is used to calculate the branch flow resistance curve polynomial of each branch in a preset pipe network; the pipe network calculation module is connected to the flow resistance curve calculation module and is used to calculate the pipe network flow rate of the preset pipe network based on the branch flow resistance curve polynomial and coolant parameters; the junction temperature calculation module is connected to the pipe network calculation module and is used to calculate the calculated junction temperature of a target semiconductor device based on the pipe network flow rate and the pipe network flow resistance.

[0015] The beneficial effects of this invention are as follows: This application obtains the device type and electrical parameters of a target semiconductor device; determines the device loss and thermal resistance of the target semiconductor device based on the device type and electrical parameters; obtains preset piping network and coolant parameters, as well as the thermal resistance-flow curve between the preset piping network and the target semiconductor device; determines the piping network flow rate based on the preset piping network and coolant parameters; determines the heat sink thermal resistance based on the piping network flow rate and the thermal resistance-flow curve; and determines the calculated junction temperature of the target semiconductor device based on the device loss, the device thermal resistance, and the heat sink thermal resistance. Compared to other software or calculation methods, this significantly improves computational efficiency and greatly reduces the professional threshold for users. Attached Figure Description

[0016] The scope of this disclosure can be better understood by reading the following detailed description of exemplary embodiments in conjunction with the accompanying drawings. The accompanying drawings are:

[0017] Figure 1 A flowchart illustrating a semiconductor junction temperature calculation method provided in this application embodiment;

[0018] Figure 2 A structural block diagram of a semiconductor junction temperature calculation device provided in an embodiment of this application;

[0019] Figure 3 This is a structural block diagram of a junction temperature calculation device provided in an embodiment of this application. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] In the following description, references are made to “some embodiments,” which describe a subset of all possible embodiments. However, it is understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0022] If the application documents contain similar descriptions such as "first, second, third", the following explanation shall be added: In the following description, the terms "first, second, third" are used only to distinguish similar objects and do not represent a specific order of objects. It is understood that "first, second, third" may be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0023] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0024] The resistance loss of a converter's water-cooling system mainly consists of resistance losses caused by local obstructions such as pipe diameter changes and bends. In engineering design, recommended values ​​for the resistance coefficient and equivalent length of pipes or valves are often obtained by consulting reference books. In engineering calculations, the flow resistance characteristics of each water circuit component can be uniformly equivalent to a straight pipe of a certain equivalent length for network calculation, i.e., the equivalent pipe length method. However, the method of equivalently converting the flow resistance characteristics of components to straight pipes heavily depends on the conversion position on the flow resistance curve, and the characteristics of friction resistance and local obstruction inevitably differ.

[0025] To address the problems existing in the current technology, such as Figure 1 As shown, this application provides a method, apparatus, device, medium, and computing device for calculating the junction temperature of a semiconductor. The method is applied to electronic devices, such as servers, mobile terminals, computers, and cloud platforms. The functions implemented by the device data processing provided in this application embodiment can be achieved by the processor of the electronic device calling program code, which can be stored in a computer storage medium. The semiconductor junction temperature calculation method includes:

[0026] Step S1: Obtain the device type and electrical parameters of the target semiconductor device.

[0027] The objective of this application is to calculate the junction temperature of a semiconductor device, which is related to the cooling effect of the cooling system and the heat generation of the semiconductor device. Therefore, to calculate the junction temperature of a semiconductor device, this application first needs to obtain the device type and electrical parameters of the semiconductor device.

[0028] Step S2: Obtain the preset pipe network and coolant parameters, as well as the thermal resistance-flow curve between the preset pipe network and the target semiconductor device.

[0029] In step S1, we primarily acquire parameters related to the heat generation of the target semiconductor device. Step S2, however, requires acquiring parameters related to cooling and heat conduction. The main influencing factors on cooling effectiveness are the piping structure and coolant parameters; therefore, we need to obtain preset piping and coolant parameters. The data related to heat conduction is the thermal resistance-flow rate curve, which reflects the relationship between flow rate and temperature difference.

[0030] Step S3: Determine the flow rate of the preset pipeline network based on the preset pipeline network and the coolant parameters.

[0031] The cooling effect of a pipe network mainly depends on the flow of coolant in the pipes. The flow of coolant carries away heat. However, the design of a pipe network inevitably involves multiple pipe branches, and each branch has various flow resistance characteristics. These flow resistance characteristics affect the flow of coolant in the pipe network. In addition, there may be pipe fittings in the branches, which also affect the resistance of the pipes, thus affecting the flow of coolant in the pipe network. Therefore, to determine the cooling effect of a pipe network, we need to first determine the flow resistance of the pipe network, and then obtain the flow rate based on the flow resistance. The flow resistance of the pipe network is composed of the flow resistance of each branch.

[0032] In some embodiments, step S3, "determining the network flow rate of the preset network based on the preset network and the coolant parameters," includes:

[0033] Step S31: Obtain the flow resistance characteristic points of each pipeline branch and the device flow resistance curves of each pipeline component.

[0034] Step S32: Determine the pipeline flow resistance curve based on the flow resistance characteristic points.

[0035] Therefore, to obtain the flow resistance of the preset pipeline network, we need to determine the flow resistance of each branch. The flow resistance of each branch is affected by the flow resistance characteristic point and the flow resistance curve of the device. Therefore, we need to first determine the flow resistance curve of the branch based on the flow resistance characteristic point.

[0036] Therefore, in some embodiments, step S32, "determining the pipeline flow resistance curve based on the flow resistance characteristic point," includes:

[0037] Step S321: Determine the equivalent pipe length of the pipeline branch based on the flow resistance characteristic point.

[0038] Step S322: Determine the pipeline flow resistance curve based on the equivalent pipe length.

[0039] Step S33: Determine the branch flow resistance curve polynomial of each of the pipeline branches based on the pipeline flow resistance curve, the device flow resistance curve, and the first coolant parameters.

[0040] In some embodiments, step S33, "determining the branch flow resistance curve polynomial of each of the pipeline branches based on the pipeline flow resistance curve, the device flow resistance curve, and the first coolant parameters," includes:

[0041] Step S331: Obtain the preset first expected error.

[0042] Step S332: Determine the density correction value based on the density of the first coolant.

[0043] Step S333: Determine the viscosity correction value based on the viscosity of the first coolant.

[0044] Step S334: Determine the quadratic polynomial of the pipeline flow resistance based on the density correction value, the viscosity correction value, and the pipeline flow resistance curve.

[0045] Step S335: Determine the quadratic polynomial of device flow resistance based on the density correction value, the viscosity correction value, and the device flow resistance curve.

[0046] Step S336: Determine the average fitting error based on the device flow resistance quadratic polynomial and the pipeline flow resistance quadratic polynomial.

[0047] Step S337: Determine whether the device flow resistance quadratic polynomial and the pipeline flow resistance quadratic polynomial meet the requirements based on the first expected error and the average fitting error.

[0048] Step S338: When the device flow resistance quadratic polynomial and the pipeline flow resistance quadratic polynomial do not meet the requirements, iteratively fit the device flow resistance quadratic polynomial and the pipeline flow resistance quadratic polynomial according to the average fitting error until the device flow resistance quadratic polynomial and the pipeline flow resistance quadratic polynomial meet the requirements.

[0049] Step S339: When the device flow resistance quadratic polynomial and the pipeline flow resistance quadratic polynomial meet the requirements, determine the branch flow resistance curve polynomial of the pipeline branch based on the device flow resistance quadratic polynomial and the pipeline flow resistance quadratic polynomial.

[0050] Since the flow resistance characteristics of most water-cooled devices closely match those of a quadratic equation, fitting the device flow resistance curve and the pipeline flow resistance curve to a quadratic polynomial effectively eliminates errors caused by the equivalent straight pipe, resulting in a more realistic flow resistance curve polynomial for the final pipeline branch. Because flow resistance expresses the resistance of fluid flowing through a pipeline, we need to incorporate coolant parameters for fitting the quadratic polynomial. The main factors affecting flow resistance are the density and viscosity of the coolant. Therefore, this application uses a quadratic polynomial to fit the device flow resistance curve, coolant viscosity, coolant density, and pipeline flow resistance curve to effectively eliminate errors caused by the equivalent straight pipe, resulting in a more realistic flow resistance curve polynomial for the final pipeline branch. The obtained pipeline characteristic points and device flow resistance curves are based on a liquid with a specific viscosity and density, so we need to correct for these differences using density and viscosity to ensure that the resulting quadratic polynomial is based on the same standard liquid. To ensure the accuracy of the fitting results, an error judgment is made by combining the fitting error and the expected error. If the actual error is too large, iterative fitting is performed based on the fitting error until the error meets the requirements of the expected error, and then the branch flow resistance curve polynomial of each pipeline branch is output.

[0051] Step S34: Determine the network flow resistance model of the preset network based on the polynomial of multiple branch flow resistance curves.

[0052] After obtaining the polynomials of the flow resistance curves of each branch of the pipeline, the flow resistance model of the pipeline network can be obtained by applying the polynomials of the flow resistance curves of each branch to the preset pipeline network.

[0053] The pipeline flow resistance model is a set of polynomials of the flow resistance curves of each branch in the preset pipeline network, which represents the pipeline flow resistance of the preset pipeline network.

[0054] Step S35: Determine the pipeline flow rate of the preset pipeline based on the pipeline flow resistance model and the second coolant parameters.

[0055] In some embodiments, step S34, "determining the network flow resistance model of the preset network based on the polynomial of the multiple branch flow resistance curves," includes:

[0056] Step S351: Obtain the preset target accuracy range and the second expected error.

[0057] Step S352: The coolant viscosity, coolant density, total flow rate, and pipeline flow resistance model are iteratively calculated using the Newton-Raphson iteration method to obtain the approximate flow rate of the pipeline.

[0058] Step S353: Determine the proximity accuracy based on the proximity flow rate of the pipeline network.

[0059] Step S354: Determine the accuracy error based on the proximity accuracy and the target accuracy.

[0060] Step S355: Determine whether the pipeline network approach flow rate meets the requirements based on the accuracy error and the second expected error.

[0061] Step S356: When it is determined that the pipeline near flow rate does not meet the requirements, the pipeline near flow rate is iterated until the pipeline near flow rate meets the requirements.

[0062] Step S357: When the pipeline near flow rate meets the requirements, determine the pipeline near flow rate as the pipeline flow rate.

[0063] To obtain the pre-defined pipeline flow rate, it is also necessary to define the pipeline flow resistance model and the coolant parameters used to calculate the junction temperature, i.e., the second coolant parameters. Since the pipeline flow rate is also involved here, the second coolant parameters should include the total coolant flow rate in addition to the second coolant density and the second coolant viscosity.

[0064] Then, the pipeline flow rate of the preset pipeline network is calculated using the Newton-Raphson iteration method based on the coolant parameters and the pipeline flow resistance model. Since the Newton-Raphson iteration method is an iterative calculation, to make the calculation results more accurate, we refer to the result directly calculated by the Newton-Raphson iteration method as the pipeline approximate flow rate. Then, the accuracy in the iteration process is determined by combining our preset target accuracy range and second expected error. When the accuracy of the iteration meets the requirements, the current pipeline approximate flow rate is determined as the pipeline flow rate.

[0065] Step S4: Determine the device loss and thermal resistance of the target semiconductor device based on the device type and the electrical parameters.

[0066] This application predefines the thermal resistance of each device type, as well as the device losses of each device type under different electrical parameters. Therefore, after obtaining the device type and electrical parameters, the corresponding device losses and thermal resistance can be obtained.

[0067] Step S5: Determine the thermal resistance of the radiator based on the pipeline flow rate and the thermal resistance-flow curve.

[0068] Since the thermal resistance-flow curve is used to reflect the temperature difference between the heat sink and the device at different flow rates, once the pipeline flow rate is obtained, we can clearly determine the temperature difference between the heat sink and the device at that flow rate, i.e., the thermal resistance of the heat sink.

[0069] Step S6: Determine the calculated junction temperature of the target semiconductor device based on the device loss, the device thermal resistance, and the heat sink thermal resistance.

[0070] Once the device loss, device thermal resistance, heat sink thermal resistance, and pipeline flow rate are obtained, the calculated junction temperature of the target semiconductor device can be calculated.

[0071] This application implements a method for calculating junction temperature based on the provided parameters through steps S1-S6. The purpose of the junction temperature calculation is to determine whether the preset piping network and second coolant parameters are reasonable. Inevitably, situations may arise where expectations are not met.

[0072] Therefore, in some embodiments, the method further includes:

[0073] Step S7: Obtain the desired junction temperature of the target semiconductor device.

[0074] Step S8: Determine whether the preset pipeline network meets the requirements based on the expected junction temperature and the calculated junction temperature.

[0075] Step S9: When the preset piping network does not meet the requirements, determine the adjustment strategy for the preset piping network and / or the coolant parameters based on the expected junction temperature and the calculated junction temperature.

[0076] Since the purpose of calculating the junction temperature is to determine whether the current preset piping and coolant parameters meet the requirements, the user also needs to provide the desired junction temperature. Then, based on the desired and calculated junction temperatures, the system determines whether the preset piping and coolant parameters meet the requirements. If they do not meet the requirements, an adjustment strategy for the preset piping and coolant can be provided based on the desired and calculated junction temperatures.

[0077] When determining the adjustment strategy, the desired junction temperature can be used as the target value. The target pipeline flow rate and target pipeline flow resistance can be calculated in reverse. Then, the target coolant parameters and the target branch flow resistance curve polynomial of each branch pipeline can be calculated in reverse to guide the adjustment of the preset pipeline and coolant.

[0078] The method described in this application can simultaneously calculate the losses and thermal resistance of semiconductor devices, the thermal resistance of heat sinks, and the flow rate of the piping system. By simply inputting standard geometric parameters, the type and operating temperature of the coolant, and the flow resistance curve of the water-cooled material, it can quickly obtain results such as piping flow rate, system pressure loss, device losses, and junction temperature. Compared to other software or calculation methods, this method significantly improves computational efficiency and greatly reduces the professional barrier for users.

[0079] Example 2:

[0080] Based on the foregoing embodiments, this application provides a semiconductor junction temperature calculation device. The various modules and units included in the device can be implemented by a processor in a computer device; of course, they can also be implemented by specific logic circuits. In the implementation process, the processor can be a central processing unit (CPU), a microprocessor (MPU), a digital signal processor (DSP), or a field programmable gate array (FPGA), etc.

[0081] like Figure 2 As shown, a semiconductor junction temperature calculation device includes: a first acquisition module 1, a second acquisition module 2, a first determination module 3, a second determination module 4, a third determination module 5, and a fourth determination module 6.

[0082] The first acquisition module 1 is used to acquire the device type and electrical parameters of the target semiconductor device. The second acquisition module 2 is used to acquire preset piping network and coolant parameters, as well as the thermal resistance-flow curve between the preset piping network and the target semiconductor device. The first determination module 3 is used to determine the piping flow rate of the preset piping network based on the preset piping network and coolant parameters. The second determination module 4 is used to determine the device loss and device thermal resistance of the target semiconductor device based on the device type and electrical parameters. The third determination module 5 is used to determine the heat sink thermal resistance based on the piping flow rate and the thermal resistance-flow curve. The fourth determination module 6 is used to determine the calculated junction temperature of the target semiconductor device based on the device loss, the device thermal resistance, and the heat sink thermal resistance.

[0083] In some embodiments, the first determining module includes: a third obtaining module, a fifth determining module, a sixth determining module, a seventh determining module, and an eighth determining module.

[0084] The third acquisition module is used to acquire the flow resistance characteristic points of each pipeline branch and the device flow resistance curves of each pipeline component. The eighth determination module is used to determine the pipeline flow resistance curve based on the flow resistance characteristic points. The fifth determination module is used to determine the branch flow resistance curve polynomial of each pipeline branch based on the pipeline flow resistance curve, the device flow resistance curve, and the first coolant parameter. The sixth determination module is used to determine the pipeline flow resistance model of the preset pipeline network based on the multiple branch flow resistance curve polynomials. The seventh determination module is used to determine the pipeline flow rate of the preset pipeline network based on the pipeline flow resistance model and the second coolant parameter.

[0085] In some embodiments, the eighth determining module includes a ninth determining module and a tenth determining module.

[0086] The ninth determining module is used to determine the equivalent pipe length of the pipeline branch based on the flow resistance characteristic point. The tenth determining module is used to determine the pipeline flow resistance curve based on the equivalent pipe length.

[0087] In some embodiments, the fifth determining module includes: a fourth obtaining module, an eleventh determining module, a twelfth determining module, a thirteenth determining module, a fourteenth determining module, a fifteenth determining module, a sixteenth determining module, a first execution module, and a seventeenth determining module.

[0088] The fourth acquisition module is used to acquire a preset first expected error. The eleventh determination module is used to determine a density correction value based on the first coolant density, and the twelfth determination module is used to determine a viscosity correction value based on the first coolant viscosity. The thirteenth determination module is used to determine a pipe flow resistance quadratic polynomial based on the density correction value, the viscosity correction value, and the pipe flow resistance curve. The fourteenth determination module is used to determine a device flow resistance quadratic polynomial based on the density correction value, the viscosity correction value, and the device flow resistance curve. The fifteenth determination module is used to determine an average fitting error based on the device flow resistance quadratic polynomial and the pipe flow resistance quadratic polynomial. The sixteenth determination module is used to determine whether the device flow resistance quadratic polynomial and the pipe flow resistance quadratic polynomial meet the requirements based on the first expected error and the average fitting error. The first execution module is used to iteratively fit the device flow resistance quadratic polynomial and the pipe flow resistance quadratic polynomial based on the average fitting error when the device flow resistance quadratic polynomial and the pipe flow resistance quadratic polynomial do not meet the requirements, until the device flow resistance quadratic polynomial and the pipe flow resistance quadratic polynomial meet the requirements. The seventeenth determining module is used to determine the branch flow resistance curve polynomial of the pipeline branch based on the device flow resistance quadratic polynomial and the pipeline flow resistance quadratic polynomial when the device flow resistance quadratic polynomial and the pipeline flow resistance quadratic polynomial meet the requirements.

[0089] In some embodiments, the seventh determining module includes: a fifth obtaining module, a second execution module, an eighteenth determining module, a nineteenth determining module, a twentieth determining module, a third execution module, and a twenty-first determining module.

[0090] The fifth acquisition module is used to acquire a preset target accuracy range and a second expected error. The second execution module is used to iteratively calculate the coolant viscosity, coolant density, total flow rate, and pipeline flow resistance model using Newton's iteration method to obtain the pipeline approximate flow rate. The eighteenth determination module is used to determine the approximation accuracy based on the pipeline approximation flow rate. The nineteenth determination module is used to determine the accuracy error based on the approximation accuracy and the target accuracy. The twentieth determination module is used to determine whether the pipeline approximation flow rate meets the requirements based on the accuracy error and the second expected error. The third execution module is used to iterate the pipeline approximation flow rate until it meets the requirements when it is determined that the pipeline approximation flow rate does not meet the requirements. The twenty-first determination module is used to determine the pipeline approximation flow rate as the pipeline flow rate when the pipeline approximation flow rate meets the requirements.

[0091] In some embodiments, the apparatus further includes a sixth acquisition module, a twenty-second determination module, and a fourth execution module.

[0092] The sixth acquisition module is used to acquire the desired junction temperature of the target semiconductor device. The twentieth determination module is used to determine whether the preset piping network meets the requirements based on the desired junction temperature and the calculated junction temperature. The fourth execution module is used to determine the adjustment strategy of the preset piping network and / or the coolant parameters based on the desired junction temperature and the calculated junction temperature when the preset piping network does not meet the requirements.

[0093] The modules in the aforementioned semiconductor junction temperature calculation device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor within the device in hardware form, or stored in the memory of the processing device in software form, so that the processor can call and execute the operations corresponding to each module. It should be noted that the module division in this embodiment is illustrative and represents only a logical functional division; in actual implementation, other division methods may be used.

[0094] Example 3:

[0095] The third aspect provides an electronic device including a storage device and a processor, wherein the storage device stores a computer program, and the processor executes the computer program to implement the steps of a method for calculating the junction temperature of a semiconductor.

[0096] Example 4:

[0097] The fourth aspect provides a storage medium storing a computer program that can be executed by one or more processors, the computer program being able to implement the steps of the junction temperature calculation method for any of the semiconductors in the first aspect.

[0098] Example 5:

[0099] like Figure 3 As shown, the fifth aspect provides a junction temperature calculation device, including: a flow resistance curve calculation module 100, a pipeline calculation module 200, and a junction temperature calculation module 300.

[0100] The flow resistance curve calculation module 100 is used to calculate the branch flow resistance curve polynomials of each branch in the preset pipe network. The pipe network calculation module 200 is connected to the flow resistance curve calculation module 100 and is used to calculate the pipe network flow rate of the preset pipe network based on the branch flow resistance curve polynomials and coolant parameters. The junction temperature calculation module 300 is connected to the pipe network calculation module 200 and is used to calculate the calculated junction temperature of the target semiconductor device based on the pipe network flow rate.

[0101] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0102] It should be understood that the phrase "one embodiment" or "an embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. It should be understood that in the various embodiments of this application, the sequence numbers of the above-described processes do not imply a sequential order of execution; the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application. The sequence numbers of the above-described embodiments are merely descriptive and do not represent the superiority or inferiority of the embodiments.

[0103] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0104] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0105] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0106] In addition, each functional unit in the various embodiments of this application can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0107] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, read-only memory (ROM), magnetic disks, or optical disks.

[0108] Alternatively, if the integrated units described above are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, or the parts that contribute to the prior art, 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 cause a controller to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROMs, magnetic disks, or optical disks.

[0109] The above description is merely an embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for calculating the junction temperature of a semiconductor, characterized in that, include: Obtain the device type and electrical parameters of the target semiconductor device; The device loss and thermal resistance of the target semiconductor device are determined based on the device type and the electrical parameters. Obtain preset piping network and coolant parameters, as well as the thermal resistance-flow curve between the preset piping network and the target semiconductor device; The flow rate of the preset pipeline network is determined based on the preset pipeline network and the coolant parameters; The thermal resistance of the radiator is determined based on the pipeline flow rate and the thermal resistance-flow curve. The calculated junction temperature of the target semiconductor device is determined based on the device loss, the device thermal resistance, and the heat sink thermal resistance.

2. The method according to claim 1, characterized in that, The preset pipeline network includes: multiple pipeline branches, each pipeline branch including: multiple pipeline components; the coolant parameters include: a first coolant parameter and a second coolant parameter; determining the pipeline flow rate of the preset pipeline network based on the preset pipeline network and the coolant parameters includes: Obtain the flow resistance characteristic points of each pipeline branch and the device flow resistance curves of each pipeline component. Determine the pipeline flow resistance curve based on the aforementioned flow resistance characteristic points; The branch flow resistance curve polynomial of each of the pipeline branches is determined based on the pipeline flow resistance curve, the device flow resistance curve, and the first coolant parameters. The pipeline flow resistance model of the preset pipeline network is determined based on the polynomial of multiple branch flow resistance curves. The pipeline flow rate of the preset pipeline is determined based on the pipeline flow resistance model and the second coolant parameters.

3. The method according to claim 2, characterized in that, The step of determining the pipeline flow resistance curve based on the flow resistance characteristic point includes: The equivalent pipe length of the pipeline branch is determined based on the flow resistance characteristic point. The flow resistance curve of the pipeline is determined based on the equivalent pipe length.

4. The method according to claim 2, characterized in that, The first coolant parameters include: first coolant density and first coolant viscosity; the step of determining the branch flow resistance curve polynomial of each of the pipe branches based on the pipe flow resistance curve, the device flow resistance curve, and the first coolant parameters includes: Obtain the preset first expected error; Determine the density correction value based on the density of the first coolant; Determine the viscosity correction value based on the viscosity of the first coolant; The quadratic polynomial of the pipeline flow resistance is determined based on the density correction value, the viscosity correction value, and the pipeline flow resistance curve. The device flow resistance quadratic polynomial is determined based on the density correction value, the viscosity correction value, and the device flow resistance curve. The average fitting error is determined based on the quadratic polynomial of the device flow resistance and the quadratic polynomial of the pipeline flow resistance. Based on the first expected error and the average fitting error, determine whether the device flow resistance quadratic polynomial and the pipeline flow resistance quadratic polynomial meet the requirements; When the device flow resistance quadratic polynomial and the pipeline flow resistance quadratic polynomial do not meet the requirements, the device flow resistance quadratic polynomial and the pipeline flow resistance quadratic polynomial are iteratively fitted according to the average fitting error until the device flow resistance quadratic polynomial and the pipeline flow resistance quadratic polynomial meet the requirements. When the device flow resistance quadratic polynomial and the pipeline flow resistance quadratic polynomial meet the requirements, the branch flow resistance curve polynomial of the pipeline branch is determined based on the device flow resistance quadratic polynomial and the pipeline flow resistance quadratic polynomial.

5. The method according to claim 2, characterized in that, The second coolant parameters include: second coolant viscosity, second coolant density, and total flow rate; determining the pipeline flow rate of the preset pipeline based on the pipeline flow resistance model and the second coolant parameters includes: Obtain the preset target accuracy range and the second expected error; The coolant viscosity, coolant density, total flow rate, and pipeline flow resistance model are iteratively calculated using the Newton-Raphson iteration method to obtain the approximate flow rate of the pipeline. The proximity accuracy is determined based on the proximity flow rate of the pipeline network. The accuracy error is determined based on the proximity accuracy and the target accuracy. Based on the accuracy error and the second expected error, determine whether the pipeline approximation flow rate meets the requirements; When it is determined that the pipeline near flow rate does not meet the requirements, the pipeline near flow rate is iterated until the pipeline near flow rate meets the requirements. When the pipeline near-flow rate meets the requirements, the pipeline near-flow rate is determined as the pipeline flow rate.

6. The method according to claim 1, characterized in that, The method further includes: Obtain the desired junction temperature of the target semiconductor device; Determine whether the preset pipe network meets the requirements based on the expected junction temperature and the calculated junction temperature; When the preset piping network does not meet the requirements, an adjustment strategy for the preset piping network and / or the coolant parameters is determined based on the expected junction temperature and the calculated junction temperature.

7. A semiconductor junction temperature calculation device, characterized in that, include: The first acquisition module is used to acquire the device type and electrical parameters of the target semiconductor device; The second acquisition module is used to acquire preset pipe network and coolant parameters, as well as the thermal resistance-flow curve between the preset pipe network and the target semiconductor device. The first determining module determines the pipeline flow rate of the preset pipeline network based on the preset pipeline network and the coolant parameters; The second determining module is used to determine the device loss and device thermal resistance of the target semiconductor device based on the device type and the electrical parameters. The third determining module is used to determine the thermal resistance of the radiator based on the pipeline flow rate and the thermal resistance-flow curve. The fourth determining module is used to determine the calculated junction temperature of the target semiconductor device based on the device loss, the device thermal resistance, and the heat sink thermal resistance.

8. An electronic device, characterized in that, include: A memory and a processor, wherein the memory stores a computer program that, when executed by the processor, performs the method as described in any one of claims 1-6.

9. A storage medium, characterized in that, The computer program stored in the storage medium can be executed by one or more processors, and the computer program can be used to implement the method as described in any one of claims 1-6.

10. A junction temperature calculation device, characterized in that, include: Flow resistance curve calculation module, pipeline calculation module, and junction temperature calculation module; The flow resistance curve calculation module is used to calculate the branch flow resistance curve polynomial of each branch in the preset pipeline network. The pipeline network calculation module is connected to the flow resistance curve calculation module and is used to calculate the pipeline flow rate of the preset pipeline network based on the polynomial of the flow resistance curve of each branch and the coolant parameters. The junction temperature calculation module is connected to the pipeline calculation module and is used to calculate the junction temperature of the target semiconductor device based on the pipeline flow rate.

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