Method, device, equipment, medium and program product for lifetime prediction of power devices
By performing transient thermal simulation and thermal stress analysis on silicon carbide power modules, the viscoplastic strain energy density of the solder layer was determined, which solved the problems of long life prediction cycle and low accuracy in the existing technology, and achieved more efficient and accurate life prediction.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- ACCOPOWER SEMICON CO LTD
- Filing Date
- 2026-04-01
- Publication Date
- 2026-07-14
AI Technical Summary
Existing technologies for evaluating the lifespan of silicon carbide power modules involve long testing cycles, neglect of load conditions, resulting in distorted results, low computational efficiency, and difficulty in accurately assessing vulnerable points.
By performing transient thermal simulation on power devices to obtain temperature distribution data, and combining this with the viscoplastic strain energy of the solder layer, the viscoplastic strain energy density is determined using transient structural models and thermal stress simulations, thereby predicting the lifetime.
It improves the accuracy and efficiency of lifetime prediction, reduces reliance on local point selection, provides data support that is closer to physical reality, and reduces subjective errors.
Smart Images
Figure CN122389428A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of electronic device testing technology, and in particular to a method, apparatus, computer equipment, computer-readable storage medium, and computer program product for predicting the lifetime of power devices. Background Technology
[0002] Silicon carbide power modules are the core power execution units of electric drive systems in new energy vehicles. They are responsible for high-voltage and high-current power conversion, motor drive, and energy management. Therefore, evaluating the fatigue life of these power devices is of vital engineering significance for optimizing packaging design, improving product reliability, and shortening development cycles.
[0003] In related technologies, extensive testing of silicon carbide power modules is required to fit an empirical formula between module lifespan and macroscopic test parameters, thereby predicting the lifespan of silicon carbide power modules. However, this approach has at least the following drawbacks: 1. Long testing cycles, affecting product development progress; 2. Ignoring the impact of load conditions on power devices, leading to distorted results; 3. During cyclic testing, subjective mesh generation is used to extract local "vulnerable points" of power devices for evaluation. The accuracy of the evaluation results depends on the mesh precision, and the computational efficiency is low when dealing with large areas of power devices. Summary of the Invention
[0004] Therefore, it is necessary to provide a method, apparatus, computer equipment, computer-readable storage medium, and computer program product for predicting the lifespan of power devices, which can improve the accuracy and efficiency of power device lifespan prediction, in response to the above-mentioned technical problems.
[0005] In a first aspect, this application provides a method for predicting the lifetime of power devices, comprising:
[0006] Transient thermal simulation of the power device with the predicted lifetime is performed under power cycling conditions to obtain the first temperature distribution data of the power device.
[0007] Acquire the second temperature distribution data generated by the power device during the manufacturing process;
[0008] The first temperature distribution data and the second temperature distribution data are input into the pre-constructed transient structure model of the power device. The thermal stress of the solder layer of the power device is simulated through the transient structure model to obtain the viscoplastic strain energy of the solder layer.
[0009] The volume of the solder layer is obtained, and the viscoplastic strain energy density of the solder layer under the power cycle condition is determined based on the viscoplastic strain energy and the volume.
[0010] Based on the viscoplastic strain energy density, the lifetime prediction result of the power device is output.
[0011] In one embodiment, the viscoplastic strain energy includes a first viscoplastic strain energy of the solder layer at the start of a power cycle under the power cycling condition, and a second viscoplastic strain energy at the end of the power cycle. Determining the viscoplastic strain energy density of the solder layer under the power cycling condition based on the viscoplastic strain energy and the volume includes:
[0012] The ratio of the first viscoplastic strain energy to the volume is determined to obtain the first viscoplastic strain energy density, and the ratio of the second viscoplastic strain energy to the volume is determined to obtain the second viscoplastic strain energy density. The first viscoplastic strain energy density and the second viscoplastic strain energy density are used as the viscoplastic strain energy density.
[0013] In one embodiment, the step of outputting the lifetime prediction result of the power device based on the viscoplastic strain energy density includes:
[0014] Subtracting the first viscoplastic strain energy density from the second viscoplastic strain energy density yields the increase in the viscoplastic strain energy density of the solder layer under the power cycle condition.
[0015] The viscoplastic strain energy density increment is input into a pre-built device lifetime prediction model, and the lifetime prediction result is output through the device lifetime prediction model.
[0016] In one embodiment, the transient thermal simulation of the power device whose lifetime is to be predicted under power cycling conditions includes:
[0017] Obtain the convective heat transfer coefficient of the heat dissipation structure of the power device, as well as the preset number of power cycles and the preset input power of the power cycle condition;
[0018] The convective heat transfer coefficient, the preset number of power cycles, and the preset input power are input into the pre-constructed transient thermal model of the power device, and the transient thermal simulation of the power device under power cycle conditions is performed through the transient thermal model.
[0019] In one embodiment, obtaining the convective heat transfer coefficient of the heat dissipation structure of the power device includes:
[0020] The preset input power, preset coolant flow rate, and preset initial temperature are input into the pre-constructed thermal resistance model of the heat dissipation structure, and the convective heat transfer coefficient of the heat dissipation structure is output through the thermal resistance model.
[0021] In one embodiment, the transient thermal simulation of the power device under power cycling conditions using the transient thermal model includes:
[0022] During the transient thermal simulation of the power device under the power cycle condition, the first power of the power device when it reaches the maximum junction temperature in the first power cycle is obtained.
[0023] The difference between the maximum junction temperature and the preset initial temperature is determined to obtain a first temperature difference, and the difference between the preset target junction temperature and the preset initial temperature is determined to obtain a second temperature difference;
[0024] Based on the first temperature difference, the second temperature difference, and the first power, determine the second power of the power device when it reaches the preset target junction temperature;
[0025] The second power is input into the transient thermal model, and the transient thermal simulation of the power device under power cycling conditions is performed through the transient thermal model.
[0026] Secondly, this application also provides a power device lifetime prediction apparatus, comprising:
[0027] The first simulation module is used to perform transient thermal simulation of the power device whose lifetime is to be predicted under power cycling conditions, and to obtain the first temperature distribution data of the power device.
[0028] The first acquisition module is used to acquire the second temperature distribution data generated by the power device during the processing.
[0029] The second simulation module is used to input the first temperature distribution data and the second temperature distribution data into the pre-constructed transient structure model of the power device, and to perform thermal stress simulation on the solder layer of the power device through the transient structure model to obtain the viscoplastic strain energy of the solder layer.
[0030] The second acquisition module is used to acquire the volume of the solder layer and determine the viscoplastic strain energy density of the solder layer under the power cycle condition based on the viscoplastic strain energy and the volume.
[0031] The output module is used to output the lifetime prediction result of the power device based on the viscoplastic strain energy density.
[0032] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:
[0033] Transient thermal simulation of the power device with the predicted lifetime is performed under power cycling conditions to obtain the first temperature distribution data of the power device.
[0034] Acquire the second temperature distribution data generated by the power device during the manufacturing process;
[0035] The first temperature distribution data and the second temperature distribution data are input into the pre-constructed transient structure model of the power device. The thermal stress of the solder layer of the power device is simulated through the transient structure model to obtain the viscoplastic strain energy of the solder layer.
[0036] The volume of the solder layer is obtained, and the viscoplastic strain energy density of the solder layer under the power cycle condition is determined based on the viscoplastic strain energy and the volume.
[0037] Based on the viscoplastic strain energy density, the lifetime prediction result of the power device is output.
[0038] In one embodiment, the viscoplastic strain energy includes a first viscoplastic strain energy of the solder layer at the start of a power cycle under the power cycling condition, and a second viscoplastic strain energy at the end of the power cycle. Determining the viscoplastic strain energy density of the solder layer under the power cycling condition based on the viscoplastic strain energy and the volume includes:
[0039] The ratio of the first viscoplastic strain energy to the volume is determined to obtain the first viscoplastic strain energy density, and the ratio of the second viscoplastic strain energy to the volume is determined to obtain the second viscoplastic strain energy density. The first viscoplastic strain energy density and the second viscoplastic strain energy density are used as the viscoplastic strain energy density.
[0040] In one embodiment, the step of outputting the lifetime prediction result of the power device based on the viscoplastic strain energy density includes:
[0041] Subtracting the first viscoplastic strain energy density from the second viscoplastic strain energy density yields the increase in the viscoplastic strain energy density of the solder layer under the power cycle condition.
[0042] The viscoplastic strain energy density increment is input into a pre-built device lifetime prediction model, and the lifetime prediction result is output through the device lifetime prediction model.
[0043] In one embodiment, the transient thermal simulation of the power device whose lifetime is to be predicted under power cycling conditions includes:
[0044] Obtain the convective heat transfer coefficient of the heat dissipation structure of the power device, as well as the preset number of power cycles and the preset input power of the power cycle condition;
[0045] The convective heat transfer coefficient, the preset number of power cycles, and the preset input power are input into the pre-constructed transient thermal model of the power device, and the transient thermal simulation of the power device under power cycle conditions is performed through the transient thermal model.
[0046] In one embodiment, obtaining the convective heat transfer coefficient of the heat dissipation structure of the power device includes:
[0047] The preset input power, preset coolant flow rate, and preset initial temperature are input into the pre-constructed thermal resistance model of the heat dissipation structure, and the convective heat transfer coefficient of the heat dissipation structure is output through the thermal resistance model.
[0048] In one embodiment, the transient thermal simulation of the power device under power cycling conditions using the transient thermal model includes:
[0049] During the transient thermal simulation of the power device under the power cycle condition, the first power of the power device when it reaches the maximum junction temperature in the first power cycle is obtained.
[0050] The difference between the maximum junction temperature and the preset initial temperature is determined to obtain a first temperature difference, and the difference between the preset target junction temperature and the preset initial temperature is determined to obtain a second temperature difference;
[0051] Based on the first temperature difference, the second temperature difference, and the first power, determine the second power of the power device when it reaches the preset target junction temperature;
[0052] The second power is input into the transient thermal model, and the transient thermal simulation of the power device under power cycling conditions is performed through the transient thermal model.
[0053] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method for predicting the lifetime of power devices.
[0054] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method for predicting the lifetime of power devices.
[0055] The aforementioned power device lifetime prediction method, apparatus, computer equipment, computer-readable storage medium, and computer program product perform transient thermal simulation of the power device based on power cycling conditions to obtain corresponding first temperature distribution data. This first temperature distribution data reflects the heat distribution of the power device under harsh operating conditions. Then, second temperature distribution data is obtained. This second temperature distribution data is used to reconstruct as accurately as possible the actual residual strain or stress field of the power device due to the temperature influence of the manufacturing process, providing reliable and physically accurate data support for subsequent lifetime prediction. The first and second temperature distribution data are input into a pre-constructed transient structural model of the power device. Taking the easily damaged and thermally failed solder layer as the analysis object, the viscoplastic strain energy of the solder layer is determined. Then, the viscoplastic strain energy density is determined based on the overall volume of the solder layer. This eliminates reliance on the accuracy of local point selection and reduces errors caused by subjective point selection, resulting in higher computational efficiency and accuracy. The viscoplastic strain energy density can accurately reflect the plastic energy dissipation and fatigue damage degree of the solder layer, thus obtaining more accurate lifetime prediction results. Attached Figure Description
[0056] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.
[0057] Figure 1 This is a schematic diagram of the application environment provided for an embodiment of this application.
[0058] Figure 2 This is a flowchart illustrating the steps of a power device lifetime prediction method provided in an embodiment of this application.
[0059] Figure 3 This is a flowchart illustrating a process for predicting the lifetime of a power device according to an embodiment of this application.
[0060] Figure 4 This is a structural block diagram of a power device lifetime prediction device provided in an embodiment of this application.
[0061] Figure 5 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation
[0062] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.
[0063] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.
[0064] The power device lifetime prediction method provided in this application embodiment can be applied to, for example, Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104 or placed in the cloud or on another network server. Terminal 102 initiates a request to server 104 for lifetime prediction of a power device. In response to this request, server 104 performs transient thermal simulation of the power device with the predicted lifetime under power cycling conditions to obtain first temperature distribution data of the power device; acquires second temperature distribution data generated during the manufacturing process of the power device; inputs the first and second temperature distribution data into a pre-constructed transient structural model of the power device, and performs thermal stress simulation on the solder layer of the power device using the transient structural model to obtain the viscoplastic strain energy of the solder layer; acquires the volume of the solder layer, and determines the viscoplastic strain energy density of the solder layer under power cycling conditions based on the viscoplastic strain energy and volume; and outputs the lifetime prediction result of the power device based on the viscoplastic strain energy density. Server 104 returns the lifetime prediction result to terminal 102. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, drones, low-altitude aircraft, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, and projection equipment. Portable wearable devices can include smartwatches, smart bracelets, and head-mounted displays. Head-mounted displays can be virtual reality (VR) devices, augmented reality (AR) devices, and smart glasses. Server 104 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.
[0065] In one exemplary embodiment, such as Figure 2 As shown, a method for predicting the lifetime of power devices is provided, which can be applied to... Figure 1Taking server 104 as an example, the explanation includes the following steps 202 to 210. Wherein:
[0066] Step 202: Perform transient thermal simulation on the power device whose lifetime is to be predicted under power cycling conditions to obtain the first temperature distribution data of the power device;
[0067] Power devices may include silicon carbide power modules, insulated gate bipolar transistors, etc.
[0068] Power cycling conditions refer to the operating state of power devices during actual operation, caused by frequent load switching, acceleration and deceleration, start-stop, and energy recovery operations. This results in the repeated switching of large currents by the power devices, causing rapid rises and falls and periodic, drastic fluctuations in the chip junction temperature. Power cycling conditions represent the most severe stress source faced by power devices during vehicle start-stop and acceleration, leading to the failure of electrical interconnect interfaces (such as interfaces formed by copper clips or chip sintering packaging processes) due to thermomechanical fatigue.
[0069] The first temperature distribution data is used to reflect the temperature distribution of various parts of the power device under power cycling conditions.
[0070] In practical implementation, a physical model corresponding to the power device can be constructed. By inputting environmental parameters or other relevant parameters of the power cycle into the physical model, transient thermal simulation of the power device can be performed, and then the first temperature change distribution data generated by the power device under the simulation environment can be collected and recorded.
[0071] In some embodiments, the transient thermal simulation of the power device whose lifetime is to be predicted under power cycling conditions includes:
[0072] Obtain the convective heat transfer coefficient of the heat dissipation structure of the power device, as well as the preset number of power cycles and the preset input power of the power cycle condition;
[0073] The convective heat transfer coefficient, the preset number of power cycles, and the preset input power are input into the pre-constructed transient thermal model of the power device, and the transient thermal simulation of the power device under power cycle conditions is performed through the transient thermal model.
[0074] The heat dissipation structure can be the PinFin (needle-fin heat dissipation structure) of the power device.
[0075] The convective heat transfer coefficient is a physical parameter that characterizes the intensity of convective heat transfer between a fluid and a solid surface, and can reflect the heat transfer capacity of a heat dissipation structure.
[0076] Among them, the preset power cycle number refers to the total number of complete thermal stress cycles completed by the power device under alternating on and off conditions; the preset input power refers to the input power for transient thermal simulation, which is applied to the inside of the power device and converted into electrical power for heat dissipation, so as to perform transient thermal simulation on the power device.
[0077] The transient thermal model refers to a thermal equivalent model that describes the dynamic temperature change of each node within a power device over time under time-varying loss and heat dissipation conditions. The transient thermal model can include pre-set simulation parameters such as the material assignment, mesh generation, and connectivity of the power device.
[0078] In practical implementation, the convective heat transfer coefficient of the heat dissipation structure can be obtained through simulation calculations, experimental testing and calibration, or correlation fitting. The convective heat transfer coefficient and the preset power cycle number N are then used as the basis for this calculation. f And the preset input power P, and the turn-on time T of the power device. on Closing time T off Input the transient thermal model, and simulate the heating process of the power device under periodic loading and cooling conditions in a simulation environment. The simulation will then proceed until the maximum operating junction temperature T of the power device chip is reached. vj_max When the required power is P2, the simulation calculation yields the first temperature distribution data as the switching state of the power device changes.
[0079] In this embodiment, the heat transfer coefficient of the heat dissipation device can be used to restore the heat transfer capacity of the power device as much as possible, accurately characterize the actual heat dissipation conditions and working load of the power device, and input the above parameters into the pre-constructed transient thermal model to obtain the first temperature distribution data through transient thermal simulation. This can realistically restore the dynamic temperature change law of the power device under power cycling conditions, improve the accuracy and reliability of thermal simulation results, and provide accurate data support for lifetime prediction.
[0080] In some embodiments, obtaining the convective heat transfer coefficient of the heat dissipation structure of the power device includes:
[0081] The preset input power, preset coolant flow rate, and preset initial temperature are input into the pre-constructed thermal resistance model of the heat dissipation structure, and the convective heat transfer coefficient of the heat dissipation structure is output through the thermal resistance model.
[0082] Among them, the preset coolant flow rate refers to the volumetric flow rate of coolant provided to the heat dissipation structure (such as PinFin, etc.) (the unit can be L / min, liters per minute, such as 8L / min). The larger the preset coolant flow rate, the faster the coolant flow rate and the faster the heat exchange speed of the heat dissipation structure. The preset initial temperature refers to the initial temperature boundary of the power device and the heat dissipation structure, that is, the initial reference temperature (such as 65℃).
[0083] In some examples, preset input power, preset coolant flow rate, and preset initial temperature are input into the thermal resistance model. The thermal resistance model calculates the total thermal resistance and convective heat transfer resistance of the heat dissipation structure based on the heat power transfer relationship, fluid convection heat transfer characteristics, and structural geometric parameters. Then, based on the correspondence between thermal resistance and heat transfer coefficient, iterative solution is performed to output the convective heat transfer coefficient of the heat dissipation structure under this operating condition.
[0084] In this embodiment, by inputting actual operating parameters such as preset input power, preset coolant flow rate, and preset initial temperature into the pre-constructed thermal resistance model of the heat dissipation structure, the convective heat transfer coefficient can be determined by combining the working load of the power device and the operating state of the heat dissipation medium. This reduces the error caused by using a fixed empirical value for the convective heat transfer coefficient, improves the accuracy of the heat dissipation performance parameters, provides boundary conditions that fit the actual operating conditions for the subsequent transient thermal simulation of the power device, and further improves the reliability of lifetime prediction.
[0085] In some embodiments, the transient thermal simulation of the power device under power cycling conditions using the transient thermal model includes:
[0086] During the transient thermal simulation of the power device under the power cycle condition, the first power of the power device when it reaches the maximum junction temperature in the first power cycle is obtained.
[0087] The difference between the maximum junction temperature and the preset initial temperature is determined to obtain a first temperature difference, and the difference between the preset target junction temperature and the preset initial temperature is determined to obtain a second temperature difference;
[0088] Based on the first temperature difference, the second temperature difference, and the first power, determine the second power of the power device when it reaches the preset target junction temperature;
[0089] The second power is input into the transient thermal model, and the transient thermal simulation of the power device under power cycling conditions is performed through the transient thermal model.
[0090] The maximum junction temperature in the first power cycle refers to the maximum value of the junction temperature of the power device during the first power cycle, and the first power is the power required to reach this maximum junction temperature; the preset target junction temperature refers to the maximum operating junction temperature that the power device is expected to reach during transient thermal simulation.
[0091] In the specific implementation, under the condition of a preset initial temperature of 65℃, the first power of the power device is obtained as P1, and the maximum junction temperature of the power device during the first power cycle is... The preset target junction temperature is Based on the principle of constant thermal resistance, the second power P2 required for the power device to reach the preset target junction temperature is calculated using the following formula (1):
[0092] (1)
[0093] in, The first temperature difference is 65. This is the second temperature difference.
[0094] Furthermore, the second power is input into the transient thermal model, and the transient thermal model is used to perform transient thermal simulation of the power device under power cycling conditions, and output the first temperature distribution data.
[0095] In this embodiment, although the second power required for the power device to reach the preset target junction temperature can be calculated through the thermal resistance model, there may be differences in the algorithms between the thermal resistance model and the transient thermal model. Therefore, by using the principle of constant thermal resistance to determine the second power based on the same transient thermal simulation, this difference can be eliminated, further improving the accuracy of the first temperature distribution data and providing more reliable data support for the lifetime prediction of the power device.
[0096] Step 204: Obtain the second temperature distribution data generated by the power device during the processing;
[0097] The second temperature distribution data refers to the temperature distribution data of various parts of the power device during the manufacturing process (such as reflow soldering, high-temperature baking, etc.). The temperature generated by the manufacturing process will cause the power device to generate inherent residual stress or strain field.
[0098] Step 206: Input the first temperature distribution data and the second temperature distribution data into the pre-constructed transient structure model of the power device, and perform thermal stress simulation on the solder layer of the power device through the transient structure model to obtain the viscoplastic strain energy of the solder layer;
[0099] Among them, the transient structural model refers to the finite element model established by the packaging structure of the power device, which can simulate the structural mechanical response under the action of load and temperature field that changes with time. It can calculate the transient stress, strain and deformation generated by each component inside the device during power cycling.
[0100] The solder layer refers to the welding material layer in the power device packaging structure used to achieve mechanical connection and heat conduction between adjacent components such as the chip and the substrate, and the substrate and the heat sink.
[0101] In practical implementation, the first temperature distribution data and the second temperature distribution data can be coupled and superimposed for simulation calculation based on the transient structural model. That is, the real situation of the inherent residual stress or strain field of the power device is first restored by the second temperature distribution data, and then the first temperature distribution data under the power cycling condition is superimposed to restore the heating situation of the power device under the power cycling condition. The viscoplastic strain energy of the solder layer is output by the transient structural model that couples and superimposes the two temperature distribution data.
[0102] In some embodiments, the transient structural model can inherit the material assignment, mesh generation, and connectivity of the transient thermal model, and reset the analysis step.
[0103] Step 208: Obtain the volume of the solder layer, and determine the viscoplastic strain energy density of the solder layer under the power cycle condition based on the viscoplastic strain energy and the volume.
[0104] In practical implementation, the equivalent volume of the solder layer can be calculated based on the geometric parameters of the model. According to the correspondence between the viscoplastic strain energy density, the viscoplastic strain energy, and the volume of the solder layer, the entire solder layer is taken as the analysis object, and the viscoplastic strain energy density of the solder layer under the power cycle condition is obtained.
[0105] In some embodiments, the viscoplastic strain energy includes a first viscoplastic strain energy of the solder layer at the start of a power cycle under the power cycling condition, and a second viscoplastic strain energy at the end of the power cycle. Determining the viscoplastic strain energy density of the solder layer under the power cycling condition based on the viscoplastic strain energy and the volume includes:
[0106] The ratio of the first viscoplastic strain energy to the volume is determined to obtain the first viscoplastic strain energy density, and the ratio of the second viscoplastic strain energy to the volume is determined to obtain the second viscoplastic strain energy density. The first viscoplastic strain energy density and the second viscoplastic strain energy density are used as the viscoplastic strain energy density.
[0107] In a specific implementation, the first viscoplastic strain energy is P se1 The second viscoplastic strain energy is P se2 If the volume of the solder layer is V, then the first viscoplastic strain energy density is... for Second viscoplastic strain energy density for .
[0108] Step 210: Output the lifetime prediction result of the power device based on the viscoplastic strain energy density.
[0109] In practical implementation, the viscoplastic strain energy density of the solder layer is obtained, which can restore the energy dissipation of irreversible plastic deformation of the solder layer under temperature load during power cycling. This allows for precise quantification of the thermal fatigue damage of the solder layer. Furthermore, based on this viscoplastic strain energy density, the lifespan of power devices can be predicted using preset algorithms and simulation models.
[0110] In some embodiments, outputting the lifetime prediction result of the power device based on the viscoplastic strain energy density includes:
[0111] Subtracting the first viscoplastic strain energy density from the second viscoplastic strain energy density yields the increase in the viscoplastic strain energy density of the solder layer under the power cycle condition.
[0112] The viscoplastic strain energy density increment is input into a pre-built device lifetime prediction model, and the lifetime prediction result is output through the device lifetime prediction model.
[0113] In the specific implementation, the first viscoplastic strain energy density is: The second viscoplastic strain energy density is The increase in viscoplastic strain energy density .
[0114] Furthermore, the increase in viscoplastic strain energy density , Preset coefficients, feature length Input a pre-built device lifetime prediction model (e.g., Darveaux model), and output the lifetime prediction results of the power device. :
[0115] (2)
[0116] In this embodiment, the increase in viscoplastic strain energy density during the entire power cycle is calculated by using the first and second viscoplastic strain energy densities of the solder layer at the start and end of the power cycle. The increase in viscoplastic strain energy density directly reflects the degree of thermal fatigue damage to the solder layer, providing an accurate and reliable quantitative indicator for evaluating the lifespan of power device packages.
[0117] In some embodiments, such as Figure 3 As shown, a workflow diagram for lifetime prediction of power devices is also provided, as follows:
[0118] Complete the thermal resistance model modeling, obtain the convective heat transfer coefficient of the heat dissipation structure of the power device through the thermal resistance model, input the convective heat transfer coefficient into the transient thermal model, use Equation (1) to determine the second power of the power device when it reaches the preset target junction temperature, input the second power into the transient thermal model, perform transient thermal simulation on the power device through the transient thermal model, and output the first temperature distribution data. Couple and superimpose the first temperature distribution data and the second temperature distribution data for simulation calculation, take the entire solder layer of the power device as the analysis object, calculate the viscoplastic strain energy of the power device at the beginning and end of the power cycle, combine the volume of the entire solder layer, determine the viscoplastic strain energy density at the beginning and end of the power cycle of the solder layer, and then calculate the viscoplastic strain energy density increment of the solder layer power cycle. By inputting the viscoplastic strain energy density increment and other parameters into the Darveaux model, use Equation (2) to output the lifetime prediction result of the power device.
[0119] The embodiments of this application have the following beneficial effects: Transient thermal simulation of power devices is performed based on power cycling conditions to obtain corresponding first temperature distribution data, which can reflect the heat distribution of power devices under harsh operating conditions. Then, second temperature distribution data is obtained, which can restore the actual situation of residual inherent strain or stress field of power devices due to the temperature influence of the processing technology as much as possible, providing reliable and physically realistic data support for subsequent lifetime prediction. The first and second temperature distribution data are input into the pre-constructed transient structural model of the power device. The solder layer, which is prone to damage and thermal failure, is used as the analysis object to determine the viscoplastic strain energy of the solder layer. Then, the viscoplastic strain energy density is determined by the overall volume of the solder layer. This eliminates the need to rely on the accuracy of local point selection and reduces the error caused by subjective point selection, resulting in higher computational efficiency and accuracy. The viscoplastic strain energy density can accurately reflect the plastic energy consumption and fatigue damage degree of the solder layer, thereby obtaining more accurate lifetime prediction results.
[0120] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.
[0121] Based on the same inventive concept, this application also provides a power device lifetime prediction apparatus for implementing the power device lifetime prediction method described above. The solution provided by this apparatus is similar to the implementation scheme described in the above method; therefore, the specific limitations of one or more power device lifetime prediction apparatus embodiments provided below can be found in the limitations of the power device lifetime prediction method described above, and will not be repeated here.
[0122] In one exemplary embodiment, such as Figure 4 As shown, a power device lifetime prediction device is provided, comprising:
[0123] The first simulation module 402 is used to perform transient thermal simulation of the power device whose lifetime is to be predicted under power cycling conditions, and to obtain the first temperature distribution data of the power device.
[0124] The first acquisition module 404 is used to acquire the second temperature distribution data generated by the power device during the processing.
[0125] The second simulation module 406 is used to input the first temperature distribution data and the second temperature distribution data into the pre-constructed transient structure model of the power device, and to perform thermal stress simulation on the solder layer of the power device through the transient structure model to obtain the viscoplastic strain energy of the solder layer.
[0126] The second acquisition module 408 is used to acquire the volume of the solder layer and determine the viscoplastic strain energy density of the solder layer under the power cycle condition based on the viscoplastic strain energy and the volume.
[0127] Output module 410 is used to output the lifetime prediction result of the power device based on the viscoplastic strain energy density.
[0128] In some embodiments, the viscoplastic strain energy includes a first viscoplastic strain energy of the solder layer at the start of a power cycle under the power cycling condition, and a second viscoplastic strain energy at the end of the power cycle. Determining the viscoplastic strain energy density of the solder layer under the power cycling condition based on the viscoplastic strain energy and the volume includes:
[0129] The ratio of the first viscoplastic strain energy to the volume is determined to obtain the first viscoplastic strain energy density, and the ratio of the second viscoplastic strain energy to the volume is determined to obtain the second viscoplastic strain energy density. The first viscoplastic strain energy density and the second viscoplastic strain energy density are used as the viscoplastic strain energy density.
[0130] In some embodiments, the step of outputting the lifetime prediction result of the power device based on the viscoplastic strain energy density includes:
[0131] Subtracting the first viscoplastic strain energy density from the second viscoplastic strain energy density yields the increase in the viscoplastic strain energy density of the solder layer under the power cycle condition.
[0132] The viscoplastic strain energy density increment is input into a pre-built device lifetime prediction model, and the lifetime prediction result is output through the device lifetime prediction model.
[0133] In some embodiments, the transient thermal simulation of the power device whose lifetime is to be predicted under power cycling conditions includes:
[0134] Obtain the convective heat transfer coefficient of the heat dissipation structure of the power device, as well as the preset number of power cycles and the preset input power of the power cycle condition;
[0135] The convective heat transfer coefficient, the preset number of power cycles, and the preset input power are input into the pre-constructed transient thermal model of the power device, and the transient thermal simulation of the power device under power cycle conditions is performed through the transient thermal model.
[0136] In some embodiments, obtaining the convective heat transfer coefficient of the heat dissipation structure of the power device includes:
[0137] The preset input power, preset coolant flow rate, and preset initial temperature are input into the pre-constructed thermal resistance model of the heat dissipation structure, and the convective heat transfer coefficient of the heat dissipation structure is output through the thermal resistance model.
[0138] In some embodiments, the transient thermal simulation of the power device under power cycling conditions using the transient thermal model includes:
[0139] During the transient thermal simulation of the power device under the power cycle condition, the first power of the power device when it reaches the maximum junction temperature in the first power cycle is obtained.
[0140] The difference between the maximum junction temperature and the preset initial temperature is determined to obtain a first temperature difference, and the difference between the preset target junction temperature and the preset initial temperature is determined to obtain a second temperature difference;
[0141] Based on the first temperature difference, the second temperature difference, and the first power, determine the second power of the power device when it reaches the preset target junction temperature;
[0142] The second power is input into the transient thermal model, and the transient thermal simulation of the power device under power cycling conditions is performed through the transient thermal model.
[0143] Each module in the aforementioned power device lifetime prediction 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 in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.
[0144] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 5 As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores data including, but not limited to, first temperature distribution data and second temperature distribution data. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When executed by the processor, the computer program implements a method for predicting the lifetime of power devices.
[0145] Those skilled in the art will understand that Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.
[0146] In one exemplary embodiment, a computer device is provided, including a memory and a processor, the memory storing a computer program that, when executed by the processor, implements the above-described method for predicting the lifetime of power devices.
[0147] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the above-described method for predicting the lifetime of power devices.
[0148] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the above-described method for predicting the lifetime of power devices.
[0149] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.
[0150] 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 above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.
[0151] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.
[0152] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.
Claims
1. A method for predicting the lifetime of a power device, characterized in that, The method includes: Transient thermal simulation of the power device with the predicted lifetime is performed under power cycling conditions to obtain the first temperature distribution data of the power device. Acquire the second temperature distribution data generated by the power device during the manufacturing process; The first temperature distribution data and the second temperature distribution data are input into the pre-constructed transient structure model of the power device. The thermal stress of the solder layer of the power device is simulated through the transient structure model to obtain the viscoplastic strain energy of the solder layer. The volume of the solder layer is obtained, and the viscoplastic strain energy density of the solder layer under the power cycle condition is determined based on the viscoplastic strain energy and the volume. Based on the viscoplastic strain energy density, the lifetime prediction result of the power device is output.
2. The method according to claim 1, characterized in that, The viscoplastic strain energy includes a first viscoplastic strain energy of the solder layer at the start of the power cycle under the power cycling condition, and a second viscoplastic strain energy at the end of the power cycle. Determining the viscoplastic strain energy density of the solder layer under the power cycling condition based on the viscoplastic strain energy and the volume includes: The ratio of the first viscoplastic strain energy to the volume is determined to obtain the first viscoplastic strain energy density, and the ratio of the second viscoplastic strain energy to the volume is determined to obtain the second viscoplastic strain energy density. The first viscoplastic strain energy density and the second viscoplastic strain energy density are used as the viscoplastic strain energy density.
3. The method according to claim 2, characterized in that, The step of outputting the lifetime prediction result of the power device based on the viscoplastic strain energy density includes: Subtracting the first viscoplastic strain energy density from the second viscoplastic strain energy density yields the increase in the viscoplastic strain energy density of the solder layer under the power cycle condition. The viscoplastic strain energy density increment is input into a pre-built device lifetime prediction model, and the lifetime prediction result is output through the device lifetime prediction model.
4. The method according to any one of claims 1 to 3, characterized in that, The transient thermal simulation of the power device with the predicted lifetime under power cycling conditions includes: Obtain the convective heat transfer coefficient of the heat dissipation structure of the power device, as well as the preset number of power cycles and the preset input power of the power cycle condition; The convective heat transfer coefficient, the preset number of power cycles, and the preset input power are input into the pre-constructed transient thermal model of the power device, and the transient thermal simulation of the power device under power cycle conditions is performed through the transient thermal model.
5. The method according to claim 4, characterized in that, The step of obtaining the convective heat transfer coefficient of the heat dissipation structure of the power device includes: The preset input power, preset coolant flow rate, and preset initial temperature are input into the pre-constructed thermal resistance model of the heat dissipation structure, and the convective heat transfer coefficient of the heat dissipation structure is output through the thermal resistance model.
6. The method according to claim 5, characterized in that, The transient thermal simulation of the power device under power cycling conditions using the transient thermal model includes: During the transient thermal simulation of the power device under the power cycle condition, the first power of the power device when it reaches the maximum junction temperature in the first power cycle is obtained. The difference between the maximum junction temperature and the preset initial temperature is determined to obtain a first temperature difference, and the difference between the preset target junction temperature and the preset initial temperature is determined to obtain a second temperature difference; Based on the first temperature difference, the second temperature difference, and the first power, determine the second power of the power device when it reaches the preset target junction temperature; The second power is input into the transient thermal model, and the transient thermal simulation of the power device under power cycling conditions is performed through the transient thermal model.
7. A power device lifetime prediction device, characterized in that, The device includes: The first simulation module is used to perform transient thermal simulation of the power device whose lifetime is to be predicted under power cycling conditions, and to obtain the first temperature distribution data of the power device. The first acquisition module is used to acquire the second temperature distribution data generated by the power device during the processing. The second simulation module is used to input the first temperature distribution data and the second temperature distribution data into the pre-constructed transient structure model of the power device, and to perform thermal stress simulation on the solder layer of the power device through the transient structure model to obtain the viscoplastic strain energy of the solder layer. The second acquisition module is used to acquire the volume of the solder layer and determine the viscoplastic strain energy density of the solder layer under the power cycle condition based on the viscoplastic strain energy and the volume. The output module is used to output the lifetime prediction result of the power device based on the viscoplastic strain energy density.
8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.
10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.