Method and system for optimizing internal electric field distribution of silicon carbide high-voltage MOSFET

Abstract

The invention discloses an internal electric field distribution optimization method and system for a silicon carbide high-voltage MOSFET, and relates to the technical field of semiconductors, and the method comprises the steps: building a three-dimensional model of the silicon carbide high-voltage MOSFET, and obtaining an MOSFET device model; constructing a doping optimization module; performing electric field distribution simulation and thermal field distribution simulation to obtain an electric field concentration area and a thermal field concentration area of the drift region; gradient doping is introduced, and first doping optimization distribution is output; gradient doping is introduced, and second doping optimization distribution is output; and carrying out collaborative optimization in the drift region. According to the invention, the technical problem of insufficient performance, stability and reliability of the device caused by poor distribution of the electric field and the thermal field of the drift region in the silicon carbide high-voltage MOSFET technology in the prior art is solved, and the technical effects of optimizing the distribution of the electric field and the thermal field of the drift region of the silicon carbide high-voltage MOSFET and improving the performance, the stability and the reliability of the device are achieved.

Description

Technical Field

[0001] The present invention relates to the field of semiconductor technology, and in particular to a method and system for optimizing the internal electric field distribution of a silicon carbide high-voltage MOSFET. Background Art

[0002] In the current field of semiconductor technology, silicon carbide (SiC) high-voltage metal-oxide-semiconductor field-effect transistors (MOSFETs) are widely used in power electronic systems as an important power device, such as new energy vehicles, high-voltage direct current transmission, and industrial motor drives. However, as the performance requirements of these applications for power devices continue to increase, the existing silicon carbide high-voltage MOSFET technology has gradually exposed some limitations. In the traditional device design and manufacturing process, the electric field and thermal field distribution in the drift region are often difficult to achieve an ideal state. Due to the existence of the electric field concentration area, the local electric field strength may be too high, which will not only increase the risk of electrical breakdown of the device and reduce its withstand voltage capability, but also affect the transport characteristics of carriers, thereby increasing the on-resistance, increasing the power consumption of the device, and reducing the energy conversion efficiency. At the same time, the appearance of the thermal field concentration area will cause the problem of local excessive temperature. Excessive temperature will accelerate the aging and performance degradation of the material, such as causing the mobility of the semiconductor material to decrease and the threshold voltage to drift, which will seriously affect the long-term stability and reliability of the device. In addition, the uneven distribution of the thermal field will also produce thermal stress, which may cause damage to the device structure and further shorten the service life of the device.

[0003] The existing technology has the technical problem that the electric field and thermal field distribution in the drift region of silicon carbide high-voltage MOSFET technology is poor, resulting in insufficient device performance, stability and reliability. Summary of the invention

[0004] The present application provides a method and system for optimizing the internal electric field distribution of a silicon carbide high-voltage MOSFET, which is used to solve the technical problem in the prior art that the electric field and thermal field distribution in the drift region of the silicon carbide high-voltage MOSFET technology is poor, resulting in insufficient device performance, stability and reliability.

[0005] In view of the above problems, the present application provides a method and system for optimizing the internal electric field distribution of a silicon carbide high-voltage MOSFET.

[0006] In a first aspect of the present application, a method for optimizing the internal electric field distribution of a silicon carbide high-voltage MOSFET is provided, the method comprising: A three-dimensional model of a silicon carbide high-voltage MOSFET is established to obtain a MOSFET device model; a doping optimization module is constructed, and an initialization doping distribution is input according to the doping optimization module; based on a TCAD tool, electric field distribution and thermal field distribution simulation are performed on the MOSFET device model according to the initialization doping distribution to obtain an electric field concentration area and a thermal field concentration area in the drift region of the MOSFET device model; the doping optimization module introduces gradient doping in the electric field concentration area and outputs a first doping optimization distribution; the doping optimization module introduces gradient doping in the thermal field concentration area and outputs a second doping optimization distribution; and collaborative optimization is performed in the drift region according to the first doping optimization distribution and the second doping optimization distribution.

[0007] A second aspect of the present application provides an internal electric field distribution optimization system for a silicon carbide high-voltage MOSFET, the system comprising: A MOSFET device model acquisition module is used to establish a three-dimensional model of a silicon carbide high-voltage MOSFET and acquire a MOSFET device model; an initialization doping distribution input module is used to construct a doping optimization module and input an initialization doping distribution according to the doping optimization module; a concentrated area acquisition module is used to perform electric field distribution and thermal field distribution simulation on the MOSFET device model according to the initialization doping distribution based on a TCAD tool to acquire the electric field concentration area and thermal field concentration area of ​​the drift region in the MOSFET device model; a first doping optimization distribution output module is used for the doping optimization module to introduce gradient doping in the electric field concentration area and output a first doping optimization distribution; a second doping optimization distribution output module is used for the doping optimization module to introduce gradient doping in the thermal field concentration area and output a second doping optimization distribution; a collaborative optimization module is used to perform collaborative optimization in the drift region according to the first doping optimization distribution and the second doping optimization distribution.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages: Establish a three-dimensional model of silicon carbide high-voltage MOSFET and obtain the MOSFET device model; construct a doping optimization module, and enter the initialization doping distribution according to the doping optimization module; simulate the electric field distribution and thermal field distribution of the MOSFET device model to obtain the electric field concentration area and thermal field concentration area of ​​the drift region in the MOSFET device model; the doping optimization module introduces gradient doping in the electric field concentration area and outputs the first doping optimization distribution; the doping optimization module introduces gradient doping in the thermal field concentration area and outputs the second doping optimization distribution; and perform collaborative optimization in the drift region according to the first doping optimization distribution and the second doping optimization distribution. The technical effect of optimizing the electric field and thermal field distribution of the drift region of silicon carbide high-voltage MOSFET and improving the device performance, stability and reliability is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0010] Figure 1 A schematic flow chart of a method for optimizing the internal electric field distribution of a silicon carbide high-voltage MOSFET provided in an embodiment of the present application; Figure 2 Schematic diagram of the internal electric field distribution optimization system of the silicon carbide high-voltage MOSFET provided in an embodiment of the present application.

[0011] Explanation of the reference numerals: MOSFET device model acquisition module 10 , initialization doping distribution input module 20 , concentrated area acquisition module 30 , first doping optimization distribution output module 40 , second doping optimization distribution output module 50 , collaborative optimization module 60 . DETAILED DESCRIPTION

[0012] The present application provides a method and system for optimizing the internal electric field distribution of a silicon carbide high-voltage MOSFET, which is used to solve the technical problem in the prior art that the electric field and thermal field distribution in the drift region of the silicon carbide high-voltage MOSFET technology is poor, resulting in insufficient device performance, stability and reliability.

[0013] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0014] Embodiment 1, as Figure 1 As shown, the present application provides a method for optimizing the internal electric field distribution of a silicon carbide high-voltage MOSFET, the method comprising: Step S100: Establish a three-dimensional model of a silicon carbide high-voltage MOSFET and obtain a MOSFET device model.

[0015] Specifically, the process of building a three-dimensional model of silicon carbide high-voltage MOSFET is started by using professional electronic design automation (EDA) software with its powerful modeling function. First, based on the unique physical properties of silicon carbide materials, such as high breakdown electric field and high electron mobility, the material parameters of each layer in the model are accurately set, including key properties such as conductivity, dielectric constant and bandgap width, to ensure that the model can accurately reflect the electrical behavior of the actual device. Then, according to the standard structure of MOSFET, the geometric shapes and sizes of various regions such as source, drain, gate and drift region are carefully depicted to accurately restore the physical architecture of the device from a microscopic level. Among them, the setting of parameters such as the length, width and thickness of the drift region needs to comprehensively consider the withstand voltage requirements and performance indicators such as on-resistance to ensure its rationality. After completing these basic settings, the three-dimensional model is discretized into many tiny units through complex meshing technology, so that the physical equations can be solved more accurately in subsequent numerical calculations and simulation analysis. After a series of rigorous operations and parameter adjustments, we finally successfully obtained a highly accurate MOSFET device model that can truly reflect the physical properties and electrical behavior of silicon carbide high-voltage MOSFETs, providing a solid and reliable basic platform for subsequent doping distribution optimization and electric field and thermal field analysis, ensuring that the entire optimization process can proceed steadily from an accurate starting point.

[0016] Step S200: constructing a doping optimization module, and inputting an initialization doping distribution according to the doping optimization module.

[0017] Specifically, we use advanced programming technology and professional circuit design software tools to carefully build a doping optimization module. This module has powerful functions and flexible parameter configuration capabilities, aiming to provide strong support for subsequent doping distribution optimization. When entering the initialization doping distribution, we first clearly define the range of doping concentrations. The determination of this range requires comprehensive consideration of the inherent characteristics of silicon carbide materials, the expected electrical performance of the device, and past experimental data and theoretical research results. Next, an exponential decay model was used as the doping distribution formula, in which the maximum doping concentration was precisely set on the side close to the source in the MOSFET device model. Its value was determined after an in-depth analysis of the carrier injection and transport characteristics near the source to ensure that a suitable conductive channel could be formed in this area; the parameters that affect the doping concentration decay rate were accurately assigned through simulation and research on the electric field distribution and carrier diffusion law in the drift region, thereby achieving uniform doping of the drift region. Finally, an initialization doping distribution that met actual needs and had a scientific basis was successfully entered, laying a key foundation for subsequent electric and thermal field simulations and further optimization work based on this distribution, guiding the entire doping optimization process to move forward in an orderly manner in the expected direction.

[0018] Step S300: performing electric field distribution and thermal field distribution simulation on the MOSFET device model according to the initialization doping distribution based on a TCAD tool to obtain an electric field concentration area and a thermal field concentration area in a drift region in the MOSFET device model.

[0019] Specifically, the powerful simulation capabilities of the TCAD (Technology Computer-Aided Design) tool are fully utilized to accurately apply the previously determined initial doping distribution to the constructed MOSFET device model. Based on the basic principles of semiconductor physics and complex numerical algorithms, the TCAD tool performs comprehensive and in-depth simulation calculations on the transport behavior of electrons and holes in the model, the generation and distribution of electric fields, and the conduction mechanism of current. In terms of electric field distribution simulation, by solving the Poisson equation and the current continuity equation, the distribution of the electric field in various regions of the MOSFET device, especially the drift region, is accurately depicted, and areas with high and concentrated electric field intensity can be clearly identified. These areas are often formed due to the unevenness of doping concentration, the geometry of the device structure, or the influence of working conditions, and may have a key impact on the voltage resistance performance of the device. At the same time, in the thermal field distribution simulation, the Joule heat generated when the current passes through the device and the heat transfer mechanisms such as heat conduction and heat convection are taken into account, and the thermal physical parameters such as thermal conductivity and specific heat capacity of the material are combined to calculate the distribution state of the thermal field in the entire device in detail, and then accurately locate the thermal field concentration area, which may cause material performance degradation and reduced reliability due to excessive temperature. Through this series of rigorous and complex simulation processes, the electric field concentration area and thermal field concentration area of ​​the drift region in the MOSFET device model are finally accurately obtained, providing a key target area for subsequent targeted doping optimization, so that the optimization measures can directly hit the core issues that affect device performance and reliability, and effectively promote the process of optimizing the internal electric field distribution of silicon carbide high-voltage MOSFETs, ensuring that the device can operate in a more stable and efficient state.

[0020] Step S400: The doping optimization module introduces gradient doping in the electric field concentration region and outputs a first doping optimization distribution.

[0021] Specifically, with the help of the constructed doping optimization module, key optimization operations are carried out for the electric field concentration area accurately located by simulation. First, based on the in-depth understanding of the electrical characteristics of silicon carbide high-voltage MOSFET and the support of a large amount of experimental data and theoretical models, the initial parameters for introducing gradient doping in this area are determined, that is, the first initial doping concentration and the first gradient width are obtained. Among them, the selection of the first initial doping concentration should comprehensively consider the degree of electric field concentration, the original doping distribution and the desired electric field uniformization effect. Through precise calculation and empirical judgment, a starting doping concentration value that can effectively adjust the electric field distribution is set; and the determination of the first gradient width needs to be combined with factors such as the size, shape and surrounding doping environment of the electric field concentration area to ensure that the gradient doping can gradually adjust the electric field distribution within a suitable spatial range to avoid over-doping or under-doping. Subsequently, the pre-set doping distribution formula is called. The formula has been carefully designed to accurately calculate the doping concentration changes at different positions in the electric field concentration area according to the input parameters. The doping optimization module strictly follows the setting of the first initial doping concentration and the first gradient width, and performs a detailed linear gradient doping operation on the electric field concentration area. In this process, the electric field distribution after doping is continuously monitored and analyzed in real time, and the electric field intensity change in the electric field concentration area and the uniformity index of its distribution are accurately identified through a complex electric field calculation model. If it is found through detection that the uniformity of the electric field intensity distribution in the electric field concentration area is less than the preset uniformity at this time, this indicates that the current doping effect has not yet reached the ideal state and needs further optimization. Therefore, the iterative simulation process is started with the preset uniformity as a clear optimization target. In each iteration, the doping optimization module will intelligently fine-tune the parameters such as the first initial doping concentration and the first gradient width according to the results of the previous simulation, and then perform doping and electric field distribution calculation again, so that it is repeated and continuously approaching the requirements of the preset uniformity. After multiple rigorous iterative simulations, the first optimized initial doping concentration and the first optimized gradient width that can make the uniformity of the electric field intensity distribution in the electric field concentration area meet the preset requirements are finally determined, and the first doping optimization distribution is output based on these optimized parameters. This distribution will serve as an important component in subsequent collaborative optimization steps, laying a solid foundation for comprehensively improving the electric field distribution uniformity and overall performance of silicon carbide high-voltage MOSFETs, and effectively promoting the entire device optimization process to develop in a more stable and efficient direction.

[0022] Step S500: The doping optimization module introduces gradient doping in the thermal field concentration area and outputs a second doping optimization distribution.

[0023] Specifically, the existing doping optimization module is used to focus on the thermal field concentration area to implement the optimization strategy. First, relying on the deep understanding of the thermal properties of silicon carbide materials and the heat conduction mechanism of MOSFET devices, combined with the previous simulation data and the thermal field optimization experience of similar devices, the second initial doping concentration and the second gradient width suitable for the thermal field concentration area are determined. The selection of the second initial doping concentration needs to consider the thermal field distribution, the thermal stability of the material and the desired thermal balance effect. After rigorous theoretical calculation and practical verification, a starting doping concentration value that helps to improve the thermal field is set; and the determination of the second gradient width is based on the geometric characteristics of the thermal field concentration area, the direction of the heat flow and the thermal coupling relationship with the surrounding area, ensuring that the gradient doping can accurately act on the thermal field concentration area, realize effective thermal field regulation, and avoid new thermal problems caused by improper doping. Then, the established doping distribution formula is called. The formula is optimized and adjusted for the characteristics of the thermal field concentration area, and can accurately calculate the doping concentration changes at various locations in the thermal field concentration area according to the input parameters, thereby guiding the doping optimization module to carry out fine linear gradient doping operations on the thermal field concentration area according to the second initial doping concentration and the second gradient width. During this process, advanced thermal field analysis models are continuously used to monitor and quantitatively evaluate the temperature rise in the concentrated area of ​​the thermal field in real time, and accurately identify the temperature rise indicators in the concentrated area of ​​the thermal field, including key parameters such as temperature peak, average temperature rise rate, and uniformity of temperature distribution. If it is detected that the temperature rise index in the concentrated area of ​​the thermal field is less than the preset temperature rise index, it means that the current degree of thermal field optimization has not met expectations, and the iterative simulation process is then started with the preset temperature rise index as a clear optimization target. In each iteration, the doping optimization module cleverly adjusts key parameters such as the second initial doping concentration and the second gradient width based on the results of the previous round of simulation, implements doping and thermal field calculations again, and evaluates the new temperature rise index. This cycle is repeated, and through multiple rigorous iterative simulations, the second optimized initial doping concentration and the second optimized gradient width that can make the temperature rise index of the concentrated area of ​​the thermal field meet the preset requirements are finally determined, and then the second doping optimization distribution is output based on these optimized parameters. This distribution will participate in the subsequent collaborative optimization links together with the first doping optimization distribution, providing strong support for effectively solving the thermal field concentration problem of MOSFET devices, improving the thermal stability and overall reliability of the devices, and further promoting the optimization process of the internal electric field and thermal field distribution of silicon carbide high-voltage MOSFETs, ensuring that the devices can operate stably and reliably under complex working conditions, extending their service life and improving their working performance.

[0024] Step S600: performing collaborative optimization in the drift region according to the first optimized doping distribution and the second optimized doping distribution.

[0025] Specifically, based on the first doping optimization distribution and the second doping optimization distribution, a comprehensive and in-depth collaborative optimization process is carried out in the drift region of the MOSFET device. First, the close coupling relationship between the electric field and the thermal field, as well as the mutual influence of their distribution in the drift region, is fully considered. The first doping optimization distribution aims to improve the uniformity of the electric field distribution in the electric field concentration area, while the second doping optimization distribution focuses on alleviating the temperature rise problem in the thermal field concentration area, but the two are not isolated, but interrelated. During the collaborative optimization, the overall doping distribution of the drift region is comprehensively adjusted through complex numerical algorithms and physical models. According to the electric field control area and the doping concentration variation law determined by the first doping optimization distribution, combined with the thermal field optimization area and the corresponding doping scheme targeted by the second doping optimization distribution, the doping concentration of each position in the drift region is accurately allocated. For example, in the overlapping part of the electric field and thermal field concentration area, the two will be weighed and coordinated according to the optimization goals of the two to avoid the deterioration of the other party due to the unilateral optimization of the electric field or thermal field, and ensure that while improving the electric field distribution, it will not cause excessive thermal effects, and vice versa. At the same time, during the optimization process, the key parameters of the electric field and thermal field are continuously monitored, such as the uniformity of the electric field intensity distribution, the temperature rise index of the thermal field, and the changes in the electrical performance parameters of the overall device (such as on-resistance, breakdown voltage, etc.). Based on these monitoring data, the doping concentration and distribution are dynamically fine-tuned, and the optimization scheme is continuously iterated to achieve the best balance of the electric field and thermal field distribution in the drift region, so that the MOSFET device can minimize the negative impact of electric field concentration and thermal field concentration under complex working conditions such as high voltage and high current, improve the reliability, stability and overall performance of the device, and provide solid technical support for the widespread application of silicon carbide high-voltage MOSFET in the field of power electronics.

[0026] In a possible implementation, step S200 further includes: Step S210: define the doping concentration range and the doping distribution formula, the doping distribution formula is an exponential decay model, and the expression is as follows: .

[0027] in, For location The doping concentration, is the coordinate of any spatial position in the length direction of the drift zone, is the maximum doping concentration in the doping concentration range, located on the side close to the source in the MOSFET device model, To affect the decay rate of doping concentration, Used to describe the trend of doping concentration decaying exponentially with distance x.

[0028] Uniform doping is performed according to the doping concentration range and the doping distribution formula to obtain an initialization doping distribution.

[0029] Specifically, the doping concentration range must be clearly defined. The determination of this range is the basis for the entire initialization doping distribution. It is not set arbitrarily, but requires comprehensive consideration of multiple factors. On the one hand, the unique physical and chemical properties of silicon carbide materials themselves must be fully considered. Its high breakdown electric field, high electron mobility and other characteristics have inherent limitations and requirements on the doping concentration. For example, excessively high doping concentrations may affect the originally excellent electrical properties of silicon carbide materials, leading to some negative effects such as decreased carrier mobility. On the other hand, it is also necessary to combine the expected electrical performance goals of the device, such as the expected on-resistance, breakdown voltage and other indicators, which are closely related to the doping concentration. Through the analysis of a large amount of experimental data and the reference to theoretical research results, a doping concentration range that is consistent with the characteristics of silicon carbide materials and meets the expected device performance is accurately defined. Determine the doping distribution formula and use the exponential decay model as the doping distribution formula , in this formula Description location The doping concentration of is the coordinate of any spatial position in the length direction of the drift region, which can accurately describe the change of doping concentration at different positions in the drift region. is the maximum doping concentration in the doping concentration range, and its position is set close to the source side in the MOSFET device model. This setting has important electrical significance. A higher doping concentration is required near the source to ensure effective carrier injection, thereby forming a good conductive channel to ensure that the device can smoothly conduct current in the on state. It is used to control the doping concentration with distance The decay rate determines how fast the doping concentration decreases from the source. The value of can achieve precise control of the doping concentration distribution of the entire drift region to meet the expected electrical performance requirements. is the base of natural logarithms The exponential function, in mathematics, the exponential function (in is the independent variable) is used to describe a In this doping distribution formula, it reflects the exponential growth or decay relationship of the doping concentration with distance. It shows an exponential decay trend, that is, as The doping concentration increases according to of The law of the power gradually decreases. This exponential decay characteristic can make the doping concentration change smoothly from the source in the drift region, which meets the specific requirements of the internal electric field distribution optimization of silicon carbide high-voltage MOSFET for doping concentration distribution. It is helpful to achieve more precise control and adjustment in the subsequent electric field and thermal field distribution simulation and the entire optimization process, so as to achieve the purpose of improving device performance.

[0030] After clarifying the above parameters, the drift region is uniformly doped according to the doping distribution formula. , calculated according to the formula , and then doping is performed in the entire drift region at this concentration, thereby obtaining an initial doping distribution distributed according to the exponential decay law. This distribution serves as the basis for subsequent TCAD tool simulations and lays the starting conditions for the entire optimization process. Subsequent optimization operations are carried out from this starting point, and are gradually adjusted and improved to achieve the ultimate goal of optimizing the electric field distribution and improving device performance.

[0031] In a possible implementation, step S400 further includes: Step S410: obtaining a first initial doping concentration and a first gradient width.

[0032] Step S420: calling the doping distribution formula, the doping optimization module performs linear gradient doping on the electric field concentration area according to the first initial doping concentration and the first gradient width, and identifies the electric field strength of the electric field concentration area.

[0033] Step S430: If the distribution uniformity of the electric field intensity in the electric field concentration area is less than a preset uniformity, an iterative simulation is performed with the preset uniformity as an optimization target, and a first optimized initial doping concentration and a first optimized gradient width are output.

[0034] Step S440: outputting a first doping optimization distribution according to the first optimized initial doping concentration and the first optimized gradient width.

[0035] Specifically, obtaining the first initial doping concentration and the first gradient width is the starting point of the entire electric field concentration area optimization process. The determination of the first initial doping concentration requires comprehensive consideration of multiple factors, including the electric field intensity distribution in the current electric field concentration area, the electric field basis formed by the previously initialized doping distribution, and the ultimately desired electric field uniformization effect. This concentration value cannot be too high or too low. Too high may cause excessive impact on the electric field distribution in other areas, and too low may not effectively improve the electric field concentration problem. It is a preliminary estimate based on an in-depth understanding of the electrical characteristics of silicon carbide high-voltage MOSFETs and the analysis of similar optimization cases and experimental data in the past. The first gradient width is also crucial, and its selection should be based on the actual range size, shape characteristics, and electric field environment of the electric field concentration area and the surrounding area. If the gradient width is too narrow, it may not be able to fully cover the electric field concentration area for effective optimization; if it is too wide, it may cause too much interference to unnecessary areas, affecting the coordination of the overall electric field distribution. The determination of this width requires accurate electric field simulation and careful analysis of the device structure to ensure that the gradient doping can play a role in the appropriate spatial range.

[0036] The pre-designed doping distribution formula is called. At the same time, the doping optimization module starts to process the electric field concentration area in a targeted manner according to the first initial doping concentration and the first gradient width obtained. The first initial doping concentration, as the starting concentration value of doping, determines the initial doping level when doping begins in the electric field concentration area. It is a key parameter set based on the preliminary judgment of the electric field conditions in the area and the expected optimization effect. The first gradient width limits the spatial range and rate of change of the doping concentration in the electric field concentration area. It determines how large the doping concentration will be and at what speed it will be adjusted from the initial doping concentration. The determination of its size requires precise consideration of the specific characteristics and optimization goals of the electric field concentration area. After the preparations are ready, the doping optimization module performs a detailed linear gradient doping operation in the electric field concentration area according to the established first initial doping concentration and the first gradient width. In this process, for each tiny spatial position in the electric field concentration area, the doping concentration that should be at that position is accurately calculated by the doping distribution formula according to its relative distance from the set gradient starting position and the first gradient width. Then, according to the calculation results, precise doping operations are performed at the corresponding positions, so that the doping concentration is gradually adjusted along the electric field concentration area according to the law of linear change starting from the starting position. This linear gradient doping method can effectively form a smoothly transitioned doping concentration distribution in the electric field concentration area, avoiding the violent fluctuations of the local electric field or other adverse electrical effects that may be caused by the sudden change of the doping concentration, and laying the foundation for improving the uniformity of the electric field distribution. While performing linear gradient doping, the doping optimization module uses electric field monitoring technology to identify the electric field strength in the electric field concentration area in real time. By arranging a series of highly sensitive virtual electric field sensors in the electric field concentration area, these sensors can accurately sense the magnitude of the electric field strength and transmit the data back to the system in real time. Using professional algorithms to process and analyze a large amount of collected electric field strength data can not only obtain the specific values ​​of the electric field strength at each position, but also depict the distribution profile of the electric field strength in the entire electric field concentration area, including the peak and valley values ​​of the electric field strength and their locations, as well as the changing trend of the electric field strength in different directions and other key information. These detailed and accurate electric field strength data provide an indispensable basis for the subsequent judgment of the uniformity of the electric field distribution. At the same time, they also help to gain a deeper understanding of the actual impact of the linear gradient doping operation on the electric field distribution in the electric field concentration area, so that the doping parameters can be further adjusted and optimized when necessary to ensure that the uniformity of the electric field strength distribution is significantly improved, and to promote the optimization of the internal electric field distribution of silicon carbide high-voltage MOSFETs to move steadily towards the expected goal.

[0037] Once it is determined that the uniformity of the electric field intensity distribution in the electric field concentration area is less than the preset uniformity, the preset uniformity is immediately used as a clear optimization target to start the iterative simulation process. First, the uniformity evaluation algorithm is used to accurately quantify the uniformity of the current electric field intensity distribution. The discrete degree index of the electric field intensity in the entire electric field concentration area is calculated. The specific operation is to first divide the electric field concentration area into several small sub-areas, select multiple sampling points in each sub-area, and measure the electric field intensity values ​​of these sampling points. Then, the variance of these electric field intensity values ​​is calculated. The larger the variance, the more uneven the electric field intensity distribution; the smaller the variance, the closer to uniform distribution. When the calculated variance is greater than the preset uniformity threshold, the system determines that the current electric field distribution is not in an ideal state and needs to be optimized, thereby officially starting the iterative simulation process. Entering the iterative simulation stage, each iteration will deeply analyze the difference relationship between the current electric field intensity distribution data and the preset uniformity, and based on this, the first initial doping concentration and the first gradient width are intelligently adjusted. When adjusting the first initial doping concentration, a comprehensive judgment is made based on the specific situation of the electric field intensity distribution. If it is found that the electric field strength in some areas of the electric field concentration area is too high, resulting in poor overall uniformity, the first initial doping concentration is appropriately reduced according to the pre-set adjustment rules. For example, according to a certain proportional coefficient (the coefficient is determined by a large amount of experimental data and theoretical analysis), the value of the first initial doping concentration is correspondingly reduced according to the degree to which the electric field strength exceeds the ideal range. The principle of this is that reducing the initial doping concentration can reduce the number of carriers in the area, thereby reducing the electric field strength and making the electric field distribution more uniform. At the same time, for the adjustment of the first gradient width, the system will also operate according to the characteristics of the electric field strength distribution. If it is found that the electric field strength changes too drastically in a certain direction, that is, the gradient is too large, affecting the overall uniformity, the first gradient width is increased. By expanding the spatial range of the gradient change, the doping concentration changes more slowly in this direction, and then the change of the electric field strength also tends to be moderate, improving the uniformity of the electric field distribution. During the adjustment process, the electric field strength distribution is continuously recalculated and compared with the preset uniformity to evaluate the adjustment effect.

[0038] The first optimized initial doping concentration is used as the starting reference value of the doping concentration change in the electric field concentration area. It determines the initial concentration level when doping begins in this area, providing a basic starting point for the construction of the entire doping distribution. The first optimized gradient width accurately defines the range and rate of change of the doping concentration in space from the starting point. It determines how the doping concentration will be gradually adjusted in the electric field concentration area, just like planning a path and specifying the direction and rhythm of the concentration change. Then, using the pre-set doping distribution formula, the first optimized initial doping concentration and the first optimized gradient width are substituted into it, and the doping concentration is accurately calculated for each tiny spatial position in the electric field concentration area. This formula is constructed based on a deep understanding of the physical properties and electrical behavior of silicon carbide high-voltage MOSFETs, and can accurately describe the complex relationship between doping concentration and spatial position. In the calculation process, for any point in the electric field concentration area, according to its relative distance from the starting position and the first optimized gradient width, the doping concentration value that the point should have is obtained according to the calculation rules specified by the formula. By performing such calculations one by one for all points in the area, a doping concentration distribution that changes continuously and smoothly in the electric field concentration area is constructed. Finally, the calculated doping concentration distribution in the entire electric field concentration area is output as the first doping optimization distribution. This distribution is the result of careful optimization. It fully considers the special electrical requirements of the electric field concentration area and effectively improves the uniformity of the electric field intensity distribution in this area by reasonably adjusting the doping concentration. The first doping optimization distribution will serve as an important part of the subsequent coordinated optimization in the drift region, and will work together with other related optimization distributions to further improve the uniformity of the overall electric field distribution of the silicon carbide high-voltage MOSFET, laying a solid foundation for improving the performance, reliability and stability of the device.

[0039] In a possible implementation, step S500 further includes: Step S510: obtaining a second initial doping concentration and a second gradient width.

[0040] Step S520: calling the doping distribution formula, the doping optimization module performs linear gradient doping on the thermal field concentration area according to the second initial doping concentration and the second gradient width, and identifies the temperature rise index of the thermal field concentration area.

[0041] Step S530: If the temperature rise index of the heat field concentration area is less than the preset temperature rise index, iterative simulation is performed with the preset temperature rise index as the optimization target, and a second optimized initial doping concentration and a second optimized gradient width are output.

[0042] Step S540: outputting a second optimized doping distribution according to the second optimized initial doping concentration and the second optimized gradient width.

[0043] Specifically, obtaining the second initial doping concentration and the second gradient width is the primary link in optimizing the thermal field concentration area. The determination of the second initial doping concentration requires comprehensive consideration of many factors. It should not only be combined with the current temperature rise conditions in the thermal field concentration area, but also consider the thermal properties of silicon carbide materials and the desired thermal balance effect. For example, based on an in-depth understanding of the thermal physical parameters such as thermal conductivity and specific heat capacity of the material, and the analysis of the initial temperature rise data of the thermal field concentration area, a doping concentration value is preliminarily set that can effectively affect the thermal field without causing other negative effects. The determination of the second gradient width is also critical, and its size depends on the geometric shape of the thermal field concentration area, the characteristics of the heat flow distribution, and the thermal coupling relationship with the surrounding area. If the thermal field concentration area is long and narrow, and the heat flow is mainly conducted in a certain direction, then the setting of the second gradient width in this direction needs to be more refined to ensure that the gradient doping can accurately act on the thermal field concentration area, achieve effective thermal field regulation, and avoid problems such as local overheating or uneven heat diffusion caused by improper doping.

[0044] The pre-designed doping distribution formula is called. At the same time, the doping optimization module prepares for the treatment of the thermal field concentration area based on the obtained second initial doping concentration and second gradient width. The second initial doping concentration is set as the starting concentration of the doping process in the thermal field concentration area. Its value is determined on the basis of fully considering the initial thermal state of the thermal field concentration area, the thermal properties of silicon carbide materials, and the desired thermal field optimization effect. The second gradient width clarifies the spatial scale and trend of the doping concentration change in the thermal field concentration area. Its size is closely related to the shape of the thermal field concentration area, the direction of heat conduction, and the surrounding thermal environment, ensuring that the gradient doping can accurately adapt to the characteristics of the thermal field concentration area and effectively regulate the thermal field distribution. After the preparations are ready, the doping optimization module carries out a detailed linear gradient doping operation in the thermal field concentration area according to the established second initial doping concentration and second gradient width. In this process, for each tiny spatial position in the thermal field concentration area, according to its relative distance from the set gradient starting position, combined with the second gradient width, the doping concentration that should be at that position is accurately calculated by the doping distribution formula. Then, according to the calculation results, precise doping operations are performed at the corresponding positions, so that starting from the starting position, the doping concentration is gradually adjusted according to the law of linear change along the thermal field concentration area. This linear gradient doping method can form a doping concentration change that matches the thermal field distribution in the thermal field concentration area, avoiding problems such as local thermal runaway or abnormal heat conduction caused by sudden changes in doping concentration, and laying the foundation for subsequent improvement of thermal field distribution. While performing linear gradient doping, the doping optimization module uses advanced thermal field monitoring technology to identify the temperature rise index of the thermal field concentration area in real time. By arranging a series of high-precision temperature sensors in the thermal field concentration area, these sensors can accurately sense small changes in temperature and transmit data in real time. The large amount of collected temperature data is processed and analyzed, which can not only obtain the real-time temperature values ​​of each position in the thermal field concentration area, but also calculate the temperature rise index, such as the rate of temperature rise, the location of the highest temperature rise point, the average temperature rise, and the uniformity of temperature distribution. Key information. These detailed and accurate temperature rise index data provide an indispensable basis for the subsequent judgment of the uniformity of thermal field distribution and the evaluation of thermal field optimization effects. At the same time, it also helps to gain a deeper understanding of the actual impact of linear gradient doping operations on the thermal field distribution in the thermal field concentration area, so that the doping parameters can be further adjusted and optimized when necessary to ensure that the temperature rise index in the thermal field concentration area is effectively improved, and to promote the optimization of the internal thermal field distribution of silicon carbide high-voltage MOSFET to move steadily towards the expected goal.

[0045] When the temperature rise index of the heat field concentration area is monitored to be less than the preset temperature rise index, it indicates that the current heat field state has not achieved the expected optimization effect, and the doping scheme needs to be further adjusted. The preset temperature rise index is a key threshold set based on the thermal stability requirements and reliable operating conditions of silicon carbide high-voltage MOSFET. It reflects the temperature rise limit that the heat field concentration area can withstand under ideal working conditions. At this time, the preset temperature rise index is immediately used as a clear optimization target to start the iterative simulation process, aiming to find the best doping parameter combination that can make the temperature rise index meet the requirements through multiple cycles of optimization. Entering the iterative simulation stage, each iteration, the doping optimization module will deeply analyze the heat field distribution data and temperature rise index information obtained from the previous simulation. Through a complex thermal model, the influence mechanism of the current second initial doping concentration and the second gradient width on the temperature rise of the thermal field is accurately evaluated. Then, based on these analysis results, the intelligent optimization algorithm is used to adjust these two parameters. For example, if it is found that a part of the heat field concentration area is too fast and exceeds the expected temperature rise rate, the second initial doping concentration near the area is appropriately reduced, because the lower doping concentration can reduce the additional heat generation caused by doping in the area, thereby reducing the temperature rise rate. At the same time, the system may also adjust the second gradient width to make the change of doping concentration in this area more gentle, so as to avoid local overheating caused by uneven thermal field distribution due to the sharp change of doping concentration. After each parameter adjustment, the doping operation is performed again, and the temperature rise index of the thermal field concentration area is recalculated based on the new doping distribution. Then, the new temperature rise index is carefully compared with the preset temperature rise index to evaluate the optimization effect. As the number of iterations increases, the temperature rise index will gradually approach the preset value. After multiple cycles of simulation, analysis, and adjustment, when the temperature rise index reaches or exceeds the preset temperature rise index, the iteration process ends. The second initial doping concentration and the second gradient width determined at this time are the optimized second optimized initial doping concentration and the second optimized gradient width. These optimized parameters can ensure that the temperature rise index of the thermal field concentration area meets the preset requirements, provide an accurate and reliable parameter basis for the subsequent output of the second doping optimization distribution, and strongly promote the optimization process of the internal thermal field distribution of silicon carbide high-voltage MOSFET, so that it develops in the direction of more stable and reliable thermal performance, improves the stability and service life of the device in a high-temperature working environment, and meets the needs of power electronic systems for high-performance and high-reliability semiconductor devices.

[0046] Based on the second optimized initial doping concentration and the second optimized gradient width determined by the previous iterative optimization, the second doping optimization distribution is constructed. First, the second optimized initial doping concentration is used as the starting point of the doping concentration change in the thermal field concentration area. It determines the basic concentration level when doping begins in this area, and plays a key guiding role in the doping concentration distribution of the entire thermal field concentration area. The second optimized gradient width accurately defines the spatial variation range and rate of change of the doping concentration from the starting point. The size and direction of the setting are determined according to the geometric shape of the thermal field concentration area, the characteristics of the heat flow distribution, and the thermal coupling relationship with the surrounding area, ensuring that the change in doping concentration can be adapted to the thermal field distribution and effectively regulate the thermal field. Using the pre-set doping distribution formula, the second optimized initial doping concentration and the second optimized gradient width are substituted into it, and the accurate doping concentration calculation is performed for each tiny spatial position in the thermal field concentration area. The doping distribution formula is established based on an in-depth study of the thermal properties, heat conduction mechanism, and doping effect of silicon carbide materials, and can accurately describe the complex relationship between doping concentration and thermal field distribution. During the calculation process, for any point in the thermal field concentration area, according to its relative distance from the starting position and the second optimized gradient width, the calculation rules specified by the formula are used to obtain the doping concentration value that the point should have. By performing such calculations on all points in the area one by one, a doping concentration distribution that changes continuously and smoothly in the thermal field concentration area and is consistent with the thermal field optimization target is constructed. Finally, the calculated doping concentration distribution in the entire thermal field concentration area is output as the second doping optimization distribution. This distribution is the result of careful optimization. It fully considers the special thermal requirements of the thermal field concentration area. By reasonably adjusting the doping concentration, it effectively improves the temperature rise index and thermal field distribution uniformity of the area. The second doping optimization distribution will serve as an important part of the subsequent collaborative optimization in the drift region, cooperating with the first doping optimization distribution to work together on the overall optimization of the drift region. It helps to further improve the thermal stability and reliability of silicon carbide high-voltage MOSFETs, lays a solid foundation for improving the performance of devices under high-temperature and high-power working conditions, and strongly promotes the optimization process of the internal electric and thermal field distribution of the entire silicon carbide high-voltage MOSFET towards a more ideal goal, ensuring that the device can operate stably and efficiently in a complex working environment, and meeting the growing demand of modern power electronics technology for high-performance semiconductor devices.

[0047] In a possible implementation, step S500 further includes: Step S550: After collaboratively optimizing the drift region according to the first optimized doping distribution and the second optimized doping distribution, an optimized doping distribution is obtained.

[0048] Step S560: re-inputting the optimized doping distribution into the MOSFET device model to detect whether the electric field concentration area and the thermal field concentration area are included.

[0049] Step S570: the MOSFET device model includes an electric field concentration area and a thermal field concentration area, and the first doping optimization distribution and the second doping optimization distribution are feedback updated according to the electric field concentration area and the thermal field concentration area.

[0050] Specifically, based on the first doping optimization distribution and the second doping optimization distribution, collaborative optimization is carried out in the drift region to obtain the optimized doping distribution. First, the complex coupling relationship between the electric field and the thermal field in the drift region, as well as the structural characteristics of the drift region itself and the properties of silicon carbide materials are comprehensively considered. In-depth exploration of how the electric field affects the Joule heat generation in the thermal field, and how the thermal field reacts to the electric field distribution by changing the material parameters, while combining the geometric shape, size and other factors of the drift region to lay the foundation for collaborative optimization. Using the multi-physics field coupling calculation model, the first and second doping optimization distributions are input into it, and the doping concentration of the drift region is finely adjusted based on the physical equations of the electric field and thermal field, such as the Poisson equation and the heat conduction equation, while considering the carrier continuity equation and the relationship between the material parameters and the field. In the calculation process, the optimization requirements of the electric field and the thermal field are dynamically balanced. For example, in the area where the electric field is concentrated, the electric field distribution is optimized by adjusting the doping concentration to reduce heat generation. At the same time, in the area where the thermal field is concentrated, the doping concentration is adjusted to improve heat conduction to optimize the electric field distribution. After multiple iterative calculations, the electric field and the thermal field reach the optimal equilibrium state in the drift region. The optimized doping distribution finally determined fully takes into account the uniformity of electric field strength and the control of thermal field temperature rise, effectively improves the voltage resistance and thermal stability of the drift region, reduces the on-resistance, and enhances the overall reliability of the device. This distribution will serve as a key basis for subsequent evaluation and further optimization, and will strongly promote the high-performance operation of silicon carbide high-voltage MOSFET in high-voltage and high-power applications, meet the strict requirements of power electronics technology for high-performance semiconductor devices, and point out the direction for the entire device optimization process, helping it to continue to develop towards an ideal state.

[0051] The optimized doping distribution obtained after collaborative optimization is accurately re-input into the constructed MOSFET device model. This process requires ensuring the accuracy and completeness of the data so that the model can perform subsequent calculations and analyses based on the new doping distribution information. After the input is completed, a series of initialization settings and parameter adjustments are performed on the MOSFET device model to adapt it to the new doping distribution state, so as to prepare for the accurate detection of the electric field concentration area and the thermal field concentration area. Then, the MOSFET device model with the optimized doping distribution input is scanned comprehensively and carefully using professional electric field and thermal field analysis software tools. In terms of electric field distribution detection, the electric field intensity values ​​at various positions in the model are calculated by solving the Poisson equation and the current continuity equation based on the new doping distribution. These calculations involve accurate simulation of the motion behavior, charge distribution, and electric field interaction of electrons and holes in different doping concentration regions. At the same time, in the process of thermal field distribution detection, the temperature values ​​of each point in the model are calculated based on the thermal conductivity, specific heat capacity and other thermophysical parameters of the material, as well as the thermal conduction and thermal convection mechanisms of the current passing through the device to generate Joule heat, so as to obtain complete thermal field distribution information. After obtaining the distribution data of the electric field and thermal field, the model is judged to determine whether there are electric field concentration areas and thermal field concentration areas according to the pre-set judgment criteria. For the electric field concentration area, by comparing the electric field strength of each point with the set electric field strength threshold, if it is found that the electric field strength of some areas is significantly higher than the surrounding area and exceeds the threshold, it is determined to be an electric field concentration area; for the thermal field concentration area, the temperature of each point is also compared with the preset temperature threshold. If there is an area with a local temperature that is too high, it is identified as a thermal field concentration area. Finally, the detection results are accurately output to clearly indicate whether the model contains electric field concentration areas and thermal field concentration areas, providing a basis for possible further optimization. If these concentrated areas are detected, the next step will be triggered to feedback and update the first doping optimization distribution and the second doping optimization distribution; if not detected, it can be preliminarily considered that the current optimization scheme has made the electric field and thermal field distribution of the device reach a relatively ideal state, and it can be decided whether to conduct further optimization evaluation or end the optimization process according to actual needs.

[0052] After determining that there are electric field concentration areas and thermal field concentration areas in the MOSFET device model, the characteristics of these areas are deeply analyzed. For the electric field concentration area, the details of the electric field intensity distribution and the coupling relationship with the surrounding area are carefully studied, and the optimization direction is to reduce the excessive electric field intensity peak, smooth its change gradient and coordinate the overall electric field distribution; for the thermal field concentration area, the temperature rise index and thermal conductivity characteristics are comprehensively analyzed, and the optimization goal is to reduce the excessive temperature rise point temperature, balance the temperature rise rate and improve the heat accumulation condition. Based on the above analysis, the first doping optimization distribution is feedback updated, the doping concentration is appropriately reduced at the peak of the electric field intensity to reduce carrier accumulation, the gradient width is adjusted according to the gradient of the electric field intensity change to make the change smooth, and the surrounding doping concentration is fine-tuned considering the coupling relationship; at the same time, for the thermal field concentration area, the doping concentration of the corresponding area is reduced or adjusted according to the temperature rise situation, the gradient change is optimized, and the thermal diffusion capacity is enhanced, such as adjusting the doping concentration difference with the low temperature area to promote thermal conduction. After completing the careful adjustment of the first and second doping optimization distributions, a new doping optimization scheme is formed, and it is prepared to return to the previous step based on this, and carry out collaborative optimization in the drift region again to start a new round of iterative optimization cycle. This process is repeated continuously, and the doping distribution is continuously improved until the termination conditions are met, so that the electric and thermal field distributions of the device are optimized, and the performance, reliability and stability are improved to meet the needs of high-voltage and high-power applications.

[0053] In a possible implementation, step S300 further includes: Step S310: determining whether the electric field concentration region and the thermal field concentration region output by the MOSFET device model include overlapping concentration regions.

[0054] Step S320: If the overlapping concentrated area is not included, the electric field concentrated area and the thermal field concentrated area are output, wherein the distribution uniformity of the electric field strength of the electric field concentrated area is greater than or equal to the preset uniformity, and the temperature rise index of the thermal field concentrated area is greater than or equal to the preset temperature rise index.

[0055] Specifically, by conducting detailed data analysis and spatial position comparison of the electric field concentration area and thermal field concentration area output by the MOSFET device model, it is determined whether there is an overlapping concentration area between the two. This process involves the precise interpretation of the electric field and thermal field distribution data, as well as an in-depth study of the regional boundaries and internal characteristics. Using data analysis tools, the position and range of the electric field concentration area and the thermal field concentration area in three-dimensional space are visualized to more intuitively observe the relationship between them. At the same time, the spatial intersection of the two and the correlation between the electric field strength and temperature change in the intersection area are calculated, which serves as an important basis for determining whether there is an overlapping concentration area.

[0056] When it is determined that overlapping concentrated areas are not included, the electric field concentrated areas and thermal field concentrated areas are further evaluated to ensure that they meet specific performance index requirements. For the electric field concentrated area, the distribution uniformity of the electric field strength needs to be greater than or equal to the preset uniformity. This means that the distribution of the electric field in this area is relatively smooth, and there is no obvious sudden change in the electric field strength or local excessiveness. The uniformity of the electric field concentrated area is verified by calculating the variance, gradient and other statistical parameters of the electric field strength and comparing them with the preset uniformity indicators. For the thermal field concentrated area, its temperature rise index must be greater than or equal to the preset temperature rise index, which indicates that the temperature rise of the thermal field in this area is within an acceptable range and will not cause device performance degradation or damage due to overheating. By monitoring the temperature rise rate, maximum temperature value and uniformity of the temperature distribution in the thermal field concentrated area, and comparing with the preset temperature rise index, ensure that the thermal field performance meets the requirements. Only when both the electric field concentration area and the thermal field concentration area meet their respective performance indicators can they be accurately output, providing accurate regional range and basic performance information for subsequent separate optimization of the electric field and thermal field, so that more targeted optimization measures can be taken to improve the overall performance and reliability of silicon carbide high-voltage MOSFET and ensure its stable operation in high-voltage, high-power application scenarios.

[0057] In a possible implementation, step S310 further includes: Step S311: If the overlapping concentrated area is included, identify the electric field-thermal field coupling influence coefficient.

[0058] Step S312: Obtain the first optimized doping distribution and the second optimized doping distribution corresponding to the overlapping concentrated area.

[0059] Step S313: coupling and updating the first doping optimization distribution and the second doping optimization distribution corresponding to the overlapping concentration area according to the electric field-thermal field coupling influence coefficient.

[0060] Specifically, when it is determined that there is an overlapping concentrated area between the electric field concentration area and the thermal field concentration area output by the MOSFET device model, the electric field-thermal field coupling influence coefficient is first identified. The determination of this coefficient requires comprehensive consideration of multiple complex factors, including the interaction strength of the electric field and thermal field in the overlapping area, the change in the transport characteristics of carriers under the combined action of the electric field and temperature, and the evolution of the physical properties of silicon carbide materials in the electric field-thermal field coupling environment. By using multi-physics field coupling analysis theory and numerical calculation methods, the influence of changes in electric field intensity on heat generation and heat conduction, as well as the changes in electrical parameters such as carrier mobility and diffusion coefficient caused by temperature changes, are deeply studied, so as to accurately quantify the degree of coupling between the electric field and thermal field and obtain an accurate coupling influence coefficient.

[0061] In order to obtain the first doping optimization distribution and the second doping optimization distribution corresponding to the overlapping concentration area, it is necessary to clarify the specific position information of the overlapping concentration area in the entire MOSFET device model, and determine the spatial range occupied by the overlapping parts of the two, such as the key position parameters such as the starting point and end point coordinates in each dimension, through a detailed analysis of the electric field concentration area and the thermal field concentration area in the model. Then, for the first doping optimization distribution data set obtained by the complex calculation and optimization process before, it contains the doping concentration values ​​set for different positions of the electric field concentration area. According to the determined overlapping area position, the part of the data corresponding to the overlapping area is screened out from this huge data set, and the position corresponding to each data is checked one by one whether it is within the overlapping area range. If so, it is extracted, and the first doping optimization distribution data set for the overlapping area is gradually constructed. The same operation is also applied to the acquisition process of the second doping optimization distribution data. In the existing thermal field optimization related data, according to the position information of the overlapping area, the doping concentration data belonging to the overlapping area are accurately found, and it is sorted and summarized, so as to obtain the second doping optimization distribution corresponding to the complete overlapping concentration area. Through such rigorous and meticulous operations, we ensure that these two key doping optimization distribution data can be obtained accurately, providing a solid and reliable data foundation for subsequent further optimization processing of the overlapping concentrated areas, so as to better balance the interaction between the electric field and thermal field in this area and improve the overall performance and stability of the device.

[0062] According to the determined electric field-thermal field coupling influence coefficient, the first doping optimization distribution and the second doping optimization distribution corresponding to the overlapping concentrated area are coupled and updated. The interaction relationship between the electric field and the thermal field in the overlapping area reflected by the coupling influence coefficient is deeply analyzed. If the coupling influence coefficient shows that the influence of the electric field on the thermal field is more significant, for example, in some positions, the local heat generation increases sharply due to the excessive electric field intensity, thereby affecting the thermal field distribution, then when updating the first doping optimization distribution, for these key positions, the doping concentration is appropriately reduced to reduce the excessive heat generated by the electric field. At the same time, when adjusting the second doping optimization distribution, the gradient of the doping concentration will be optimized in the area where the thermal field is concentrated and is greatly affected by the electric field, so that the heat can be diffused more efficiently and the local overheating phenomenon is alleviated. On the contrary, if the coupling influence coefficient indicates that the effect of the thermal field on the electric field is more prominent, for example, high temperature causes a large change in carrier mobility, which affects the uniformity of the electric field, then when updating the first doping optimization distribution, the doping concentration will be fine-tuned in the area where the carrier mobility is severely affected to balance the electric field distribution. For the second doping optimization distribution, the distribution of the thermal field will be considered, and the doping concentration will be appropriately changed to minimize the adverse effects of the thermal field on the electric field. Through such meticulous and targeted adjustments, the two doping optimization distributions are fully coupled and updated according to the electric field-thermal field coupling influence coefficient, so that the doping distribution in the overlapping concentrated area can better adapt to the complex electric field-thermal field coupling environment, effectively improve the performance and stability of the silicon carbide high-voltage MOSFET in this area, and provide a strong guarantee for the efficient operation of the entire device.

[0063] Embodiment 2, based on the same inventive concept as the method for optimizing the internal electric field distribution of silicon carbide high-voltage MOSFET in the above embodiment, Figure 2 As shown, the present application provides an internal electric field distribution optimization system for silicon carbide high-voltage MOSFET, and the system and method embodiments in the embodiments of the present application are based on the same inventive concept. The system includes: The MOSFET device model acquisition module 10 is used to establish a three-dimensional model of the silicon carbide high-voltage MOSFET and acquire the MOSFET device model.

[0064] The initialization doping distribution input module 20 is used to construct a doping optimization module and input the initialization doping distribution according to the doping optimization module.

[0065] The concentrated area acquisition module 30 performs electric field distribution and thermal field distribution simulation on the MOSFET device model according to the initialization doping distribution based on the TCAD tool to obtain the electric field concentrated area and thermal field concentrated area of ​​the drift region in the MOSFET device model.

[0066] The first doping optimization distribution output module 40 is used for the doping optimization module to introduce gradient doping in the electric field concentration area and output a first doping optimization distribution.

[0067] The second doping optimization distribution output module 50 is used for the doping optimization module to introduce gradient doping in the thermal field concentration area and output a second doping optimization distribution.

[0068] The collaborative optimization module 60 is used to perform collaborative optimization in the drift region according to the first doping optimization distribution and the second doping optimization distribution.

[0069] Furthermore, the initialization doping profile entry module further includes: The doping concentration range and doping distribution formula are defined. The doping distribution formula is an exponential decay model, and the expression is as follows: .

[0070] in, For location The doping concentration, is the coordinate of any spatial position in the length direction of the drift zone, is the maximum doping concentration in the doping concentration range, located on the side close to the source in the MOSFET device model, To affect the decay rate of doping concentration, It is used to describe the exponential decay trend of the doping concentration with the distance x. Uniform doping is performed according to the doping concentration range and the doping distribution formula to obtain the initialization doping distribution.

[0071] Furthermore, the first doping optimization distribution output module 40 further includes: The first gradient width acquisition unit is used to acquire a first initial doping concentration and a first gradient width.

[0072] The electric field strength identification unit is used to call the doping distribution formula, and the doping optimization module performs linear gradient doping on the electric field concentration area according to the first initial doping concentration and the first gradient width to identify the electric field strength of the electric field concentration area.

[0073] The first optimized gradient width output unit is used to perform iterative simulation with the preset uniformity as the optimization target if the distribution uniformity of the electric field strength in the electric field concentration area is less than the preset uniformity, and output the first optimized initial doping concentration and the first optimized gradient width.

[0074] The first doping optimized distribution output unit is used to output a first doping optimized distribution according to the first optimized initial doping concentration and the first optimized gradient width.

[0075] Furthermore, the second doping optimization distribution output module 50 further includes: The second gradient width acquisition unit is used to acquire the second initial doping concentration and the second gradient width.

[0076] The temperature rise index identification unit is used to call the doping distribution formula, and the doping optimization module performs linear gradient doping on the thermal field concentration area according to the second initial doping concentration and the second gradient width to identify the temperature rise index of the thermal field concentration area.

[0077] The second optimized gradient width output unit is used to perform iterative simulation with the preset temperature rise index as the optimization target if the temperature rise index of the thermal field concentration area is less than the preset temperature rise index, and output the second optimized initial doping concentration and the second optimized gradient width.

[0078] The second doping optimized distribution output unit is configured to output a second doping optimized distribution according to the second optimized initial doping concentration and the second optimized gradient width.

[0079] Furthermore, the second doping optimization distribution output module 50 further includes: A collaborative optimization unit is used to obtain an optimized doping distribution after collaboratively optimizing the drift region according to the first doping optimization distribution and the second doping optimization distribution.

[0080] The thermal field concentration area detection unit is used to re-input the optimized doping distribution into the MOSFET device model to detect whether the electric field concentration area and the thermal field concentration area are included.

[0081] A feedback updating unit is used to detect an electric field concentration area and a thermal field concentration area in the MOSFET device model, and to feedback update the first doping optimization distribution and the second doping optimization distribution according to the electric field concentration area and the thermal field concentration area.

[0082] Furthermore, the concentrated area acquisition module 30 further includes: The overlapping concentration area determination unit is used to determine whether the electric field concentration area and the thermal field concentration area output by the MOSFET device model include an overlapping concentration area.

[0083] The concentrated area output unit is used to output the electric field concentrated area and the thermal field concentrated area if the overlapping concentrated area is not included, wherein the distribution uniformity of the electric field strength of the electric field concentrated area is greater than or equal to the preset uniformity, and the temperature rise index of the thermal field concentrated area is greater than or equal to the preset temperature rise index.

[0084] Furthermore, the overlapping concentrated area determination unit further includes: The electric field-thermal field coupling influence coefficient identification unit is used to identify the electric field-thermal field coupling influence coefficient if the overlapping concentrated area is included.

[0085] The doping optimization distribution acquisition unit is used to acquire the first doping optimization distribution and the second doping optimization distribution corresponding to the overlapping concentration area.

[0086] A coupling update unit is used to couple and update the first doping optimization distribution and the second doping optimization distribution corresponding to the overlapping concentration area according to the electric field-thermal field coupling influence coefficient.

[0087] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0088] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

[0089] This specification and the drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. A method for optimizing the internal electric field distribution of a silicon carbide high-voltage MOSFET, characterized in that: The method comprises: Establish a three-dimensional model of silicon carbide high-voltage MOSFET and obtain the MOSFET device model; Constructing a doping optimization module, and inputting an initialization doping distribution according to the doping optimization module; Based on the TCAD tool, the electric field distribution and thermal field distribution of the MOSFET device model are simulated according to the initialization doping distribution to obtain the electric field concentration area and thermal field concentration area of ​​the drift region in the MOSFET device model; The doping optimization module introduces gradient doping in the electric field concentration region and outputs a first doping optimization distribution; The doping optimization module introduces gradient doping in the thermal field concentration area and outputs a second doping optimization distribution; Co-optimization is performed in the drift region according to the first optimized doping distribution and the second optimized doping distribution.

2. The method according to claim 1, characterized in that Entering the initial doping profile includes: The doping concentration range and doping distribution formula are defined. The doping distribution formula is an exponential decay model, and the expression is as follows: ; in, For location The doping concentration, is the coordinate of any spatial position in the length direction of the drift zone, is the maximum doping concentration in the doping concentration range, located on the side close to the source in the MOSFET device model, To affect the decay rate of doping concentration, Used to describe how doping concentration varies with distance The trend is exponential decay; Uniform doping is performed according to the doping concentration range and the doping distribution formula to obtain an initialization doping distribution.

3. The method according to claim 2, characterized in that The doping optimization module introduces gradient doping in the electric field concentration area and outputs a first doping optimization distribution, and the method includes: Acquiring a first initial doping concentration and a first gradient width; The doping distribution formula is called, and the doping optimization module performs linear gradient doping on the electric field concentration area according to the first initial doping concentration and the first gradient width, and identifies the electric field strength of the electric field concentration area; If the distribution uniformity of the electric field intensity in the electric field concentration area is less than the preset uniformity, performing iterative simulation with the preset uniformity as the optimization target, and outputting a first optimized initial doping concentration and a first optimized gradient width; A first doping optimization distribution is output according to the first optimized initial doping concentration and the first optimized gradient width.

4. The method according to claim 2, characterized in that The doping optimization module introduces gradient doping in the thermal field concentration area and outputs a second doping optimization distribution, and the method includes: Acquire a second initial doping concentration and a second gradient width; The doping distribution formula is called, and the doping optimization module performs linear gradient doping on the thermal field concentration area according to the second initial doping concentration and the second gradient width, and identifies a temperature rise index of the thermal field concentration area; If the temperature rise index of the heat field concentration area is less than the preset temperature rise index, iterative simulation is performed with the preset temperature rise index as the optimization target, and a second optimized initial doping concentration and a second optimized gradient width are output; A second doping optimization distribution is outputted according to the second optimized initial doping concentration and the second optimized gradient width.

5. The method according to claim 1, characterized in that After collaboratively optimizing the drift region according to the first optimized doping distribution and the second optimized doping distribution, obtaining an optimized doping distribution; Re-inputting the optimized doping distribution into the MOSFET device model to detect whether the electric field concentration area and the thermal field concentration area are included; The MOSFET device model includes an electric field concentration area and a thermal field concentration area, and the first doping optimization distribution and the second doping optimization distribution are feedback updated according to the electric field concentration area and the thermal field concentration area.

6. The method according to claim 1, characterized in that The method for obtaining the electric field concentration region and the thermal field concentration region of the drift region in the MOSFET device model includes: Determining whether the electric field concentration region and the thermal field concentration region output by the MOSFET device model include overlapping concentration regions; If the overlapping concentrated area is not included, the electric field concentrated area and the thermal field concentrated area are output, wherein the distribution uniformity of the electric field strength of the electric field concentrated area is greater than or equal to the preset uniformity, and the temperature rise index of the thermal field concentrated area is greater than or equal to the preset temperature rise index.

7. The method according to claim 6, characterized in that If the overlapping concentrated area is included, identify the electric field-thermal field coupling influence coefficient; Acquire a first doping optimization distribution and a second doping optimization distribution corresponding to the overlapping concentrated area; The first doping optimization distribution and the second doping optimization distribution corresponding to the overlapping concentration area are coupled and updated according to the electric field-thermal field coupling influence coefficient.

8. Internal electric field distribution optimization system of silicon carbide high voltage MOSFET, characterized in that: The system is used to execute the internal electric field distribution optimization method of the silicon carbide high-voltage MOSFET according to any one of claims 1 to 7, and the system comprises: MOSFET device model acquisition module, used to establish a three-dimensional model of silicon carbide high-voltage MOSFET and obtain the MOSFET device model; An initialization doping distribution input module is used to construct a doping optimization module and input the initialization doping distribution according to the doping optimization module; A concentrated area acquisition module, which performs electric field distribution and thermal field distribution simulation on the MOSFET device model according to the initialization doping distribution based on a TCAD tool, and obtains an electric field concentrated area and a thermal field concentrated area in the drift region of the MOSFET device model; A first doping optimization distribution output module, used for the doping optimization module to introduce gradient doping in the electric field concentration area and output a first doping optimization distribution; A second doping optimization distribution output module, used for the doping optimization module to introduce gradient doping in the thermal field concentration area and output a second doping optimization distribution; A collaborative optimization module is used to perform collaborative optimization in the drift region according to the first doping optimization distribution and the second doping optimization distribution.

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