Soft magnetic ferrite loss and temperature rise simulation analysis method

Abstract

The invention provides a loss and temperature rise simulation analysis method of soft magnetic ferrite, which is a method for performing finite element simulation analysis on temperature rise of high-frequency low-loss power MnZn ferrite annular and EE type magnetic cores during working by using a magnetothermal coupling method. According to the method, the grid division precision is improved by improving the grid division mode, so that the simulation precision of a complex structure is remarkably improved. A simulation result is compared with an actual measurement result, and the result shows that a simulation analysis result of the loss and the temperature is in good conformity with an experimental result, and a temperature rise error changes along with the change of a loss error. In addition, the temperature change conditions of the annular magnetic core and the EE type magnetic core along with time and the temperature distribution of different positions are provided. The research result shows that the magnetothermal coupling method fitting can be used for determining the heating point position and the temperature rise condition of the special-shaped magnetic core, so that proper heat dissipation measures can be taken during design, and the stability and the reliability of the performance of the power electronic component are improved.

Description

Technical Field

[0001] The present invention relates to a finite element simulation analysis of loss and temperature rise of a high-frequency low-loss soft ferrite magnetic core, and in particular to a finite element simulation analysis of loss and temperature rise of an EE type magnetic core with a more complex shape. Background Art

[0002] Power electronic components are basic components in the field of power electronic technology, and are directly related to the development of the electronic information industry, home furnishing industry, computer industry, communication industry, environmental protection and energy-saving technology. In recent years, with the development of 5G communication technology and new energy electric vehicles, higher requirements have been put forward for the performance, stability and reliability of power electronic components. Soft ferrite materials are the core materials of power electronic components, and the quality of their performance will directly determine the performance of power electronic components. In the process of power conversion, the energy efficiency of power electronic components is reduced due to the generation of magnetic loss in ferrite core materials; at the same time, the lost energy is converted into heat energy, which causes the temperature of electronic components to rise, which greatly affects the stability and reliability of their performance. At present, the industry and academia have little research on the impact of ferrite magnetic loss on the temperature rise of electronic components. In addition, in different application scenarios, the shape of the magnetic core is diverse. In addition to the ring, there are more complex EI type, EE type and PQ type. For complex core shapes, it is more difficult to analyze the relationship between the temperature rise and magnetic loss of the core.

[0003] In recent years, the development of finite element simulation technology, especially the development of electromagnetic field and temperature field coupling methods, has made great progress. For example, in the transformer field, Balci et al. established a thermal model of the ferrite N87 medium frequency transformer under different cooling methods and conducted electromagnetic and thermal analysis on it. Tomczuk et al. used the magnetothermal coupling method to analyze the heating of different solid materials instead of the magnetic core when calculating the heat of the transformer. Liu et al. adjusted the core structure parameters and winding arrangement parameters through magnetothermal coupling analysis, optimized the transformer loss, reduced heat, and designed an integrated transformer without adding any resonant inductance in the LLC resonant converter. In the motor field, Ru et al. used the unique electromagnetic field and thermal field coupling principle to give some calculations and simulations for the immersed evaporative cooling stator, and designed a new insulation structure to enable the evaporative cooling technology to play a better role and improve the cooling effect of the generator. Jiang et al. used the magnetothermal bidirectional coupling method to study the changes in the temperature distribution of the double-convex electromagnetic motor under different working conditions, providing a reference for motor cooling design. Chen Xiaojun and others used finite element analysis software to build a high-speed permanent magnet brushless DC motor magnetothermal coupling analysis model, and conducted transient two-dimensional temperature field analysis on key components such as the motor stator, rotor, and permanent magnet. In terms of cables, Guan Guangyu and others used Matlab-ANSYS joint simulation to establish a superconducting cable electromagnetic thermal coupling operation characteristic simulation system, and simulated and analyzed the current distribution, time to reach thermal stability, and steady-state temperature distribution of the superconducting cable under steady-state operation, and obtained its current, temperature, and magnetic field distribution. The rapid development of magnetothermal coupling methods in the above aspects makes it possible to analyze the relationship between temperature rise and magnetic loss of complex-shaped magnetic cores when the system is working, but currently the industry and academia have little simulation analysis of the loss and temperature rise of complex-shaped ferrite cores at high frequencies.

[0004] In summary, the use of finite element simulation combined with magnetothermal coupling method to analyze the temperature rise of complex-shaped ferrites at high frequencies has important applications and value. Summary of the invention

[0005] In view of the existing problems, the present invention proposes a method for simulating and analyzing the loss and temperature rise of high-frequency and low-loss soft ferrite.

[0006] The technical solution adopted by the present invention is as follows:

[0007] A method for simulating and analyzing the loss and temperature rise of a soft ferrite, comprising:

[0008] Step 1: geometrically model the soft ferrite to be analyzed to obtain a core model and a coil model;

[0009] Step 2: Obtain the basic parameters of the soft ferrite to be analyzed, including relative dielectric constant, conductivity, density, and relative magnetic permeability; and set the materials of the core model and the coil model based on the basic parameters of the soft ferrite material to be analyzed;

[0010] Step 3: setting boundary conditions based on the magnetic core model and coil model obtained in step 1;

[0011] Step 4: Cut a cross section of the coil model obtained in step 1 through the XY plane according to each coil and assign excitation to the cross section;

[0012] Step 5: mesh the magnetic core model and coil model obtained in step 1 in a static field solver and import the meshing results into an eddy current field or transient field solver;

[0013] Step 6: Set the solution parameters and use the eddy current field or transient field solver to simulate the loss;

[0014] Step 7: Solve the temperature field based on the loss results to obtain the temperature rise results.

[0015] Furthermore, the soft magnetic ferrite is one of manganese-zinc ferrite, nickel-zinc ferrite, and metal soft magnetic material.

[0016] Furthermore, the geometric structure of the soft ferrite core structure, wherein the core is a toroidal type, an EI type, an EE type or a PQ type.

[0017] Furthermore, in step one, the geometric modeling simplifies the double coil of the magnetic core into a single coil for modeling.

[0018] Furthermore, in step five, the meshing is performed by surface meshing or volume meshing, wherein the surface meshing includes two meshing methods based on skin depth and length, and the volume meshing includes a meshing method based on length.

[0019] An electronic device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the loss and temperature rise simulation analysis method of a soft ferrite as described in any one of claims 1 to 5 is implemented.

[0020] A storage medium containing computer executable instructions, which can implement the loss and temperature rise simulation analysis method of soft ferrite when executed by a computer processor.

[0021] A computer program product includes a computer program / instruction, which, when executed by a processor, implements the steps of a method for simulating and analyzing the loss and temperature rise of a soft ferrite.

[0022] Compared with the prior art, the magnetothermal coupling method proposed in the present invention has the following beneficial effects in the finite element simulation analysis of the temperature rise of power ferrite cores of different shapes at high frequencies:

[0023] 1. The shape of the toroidal magnetic core is relatively simple, and the loss and temperature rise are relatively regular, which makes it easy and convenient to measure. However, in different application scenarios, the shape of the magnetic core is varied. In addition to the toroidal shape, there are more complex EI, EE and PQ types. For complex magnetic core shapes, the temperature rise at each position of the magnetic core is not uniform, and it is more difficult to analyze the relationship between the temperature rise and magnetic loss of the magnetic core, but it is very meaningful. The present invention improves the mesh division method and improves the mesh division accuracy, thereby significantly improving the simulation accuracy of complex structures.

[0024] 2. The temperature field solved by the magnetothermal coupling method in the present invention can more intuitively predict the temperature rise and hot spot position of the magnetic core, and can also obtain the relationship between the core temperature and time change. Moreover, the simulation analysis method proposed in the present invention is more efficient than the experiment.

[0025] The present invention uses finite element simulation combined with the magnetothermal coupling method to analyze the temperature rise of complex-shaped ferrites at high frequencies, and conducts actual measurements and comparisons to verify the accuracy of the simulation model. The simulation method can more intuitively predict the temperature rise of different types of magnetic cores, and by post-processing the derived temperature distribution, it can also be used to determine the hot spot position and temperature of the magnetic core. The research results will provide a reference for the actual device to adopt appropriate cooling and heat dissipation, and improve the stability and reliability of the performance of electronic components. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 This is a comparison chart between the experiment and simulation of the power consumption of a high-frequency, low-loss manganese-zinc ferrite ring as the magnetic flux density changes;

[0027] Figure 2 This is a comparison chart between the power consumption of high-frequency, low-loss power manganese-zinc ferrite EE type magnetic core and the change of magnetic flux density between the experiment and simulation;

[0028] Figure 3 This is a comparison chart between the temperature rise of a high-frequency, low-loss power manganese-zinc ferrite ring and the change of magnetic flux density between the experiment and simulation;

[0029] Figure 4 This is a comparison chart between the temperature rise of high-frequency, low-loss power manganese-zinc ferrite EE type magnetic core as the magnetic flux density changes with the experiment and simulation;

[0030] Figure 5 This is the temperature field simulation result diagram of high-frequency, low-loss power manganese-zinc ferrite ring and EE-type magnetic core under 2000kHz and 30mT conditions;

[0031] Figure 6This is the temperature field simulation result diagram of high-frequency, low-loss power manganese-zinc ferrite ring and EE-type magnetic core under 2000kHz and 40mT conditions;

[0032] Figure 7 This is the temperature field simulation result diagram of high-frequency low-loss power manganese-zinc ferrite ring and EE-type magnetic core under 2000kHz and 50mT conditions;

[0033] Figure 8 This is the temperature field simulation result of high-frequency, low-loss power manganese-zinc ferrite ring and EE-type magnetic core under 2000kHz and 60mT conditions. DETAILED DESCRIPTION

[0034] The present invention is further described in detail below.

[0035] Example 1: Preparation of soft ferrite

[0036] The high-frequency low-loss MnZn ferrite powders used in this embodiment are all prepared by oxide ceramic technology, and the specific operation steps are as follows:

[0037] (1) Ingredients: The purity and impurity types of the raw materials used in the experiment will greatly affect the magnetic properties of the product. Trace amounts of harmful impurities in the raw materials will destroy the magnetic properties of the materials, while high-purity raw materials are conducive to the solid-phase reaction in the preparation process of MnZn ferrite and improve the various magnetic properties of the product. In this embodiment, the raw materials are Fe2O3 with a purity of >99.3%, Mn3O4 with a purity of >99%, ZnO with a purity of >99.5%, and Co3O4 with a purity of >99.99%. The proportions are Fe2O3: 55.42mol%, Mn3O4: 44.01mol%, ZnO: 0.24mol%, and Co3O4: 0.33mol%.

[0038] (2) Primary ball milling: Pour the raw materials weighed in the previous step into a special stainless steel ball mill, add deionized water and steel balls of different sizes (large: small = 1:3) in a certain ball-to-material ratio (raw material: steel ball: water = 1:4:2), and then add 4 mL of ammonia water to ensure that the ball milling process is carried out in a weakly alkaline environment to alleviate the corrosion of acidic impurities on the ball mill and steel balls, thereby reducing the increase of iron elements during the ball milling process. Set the ball mill speed to 120 r / min and the ball milling time to 16 hours.

[0039] (3) Drying and sieving: The milled slurry was washed with deionized water and dried in a forced air drying oven. After drying, it was sieved with a commercially available 30-mesh screen.

[0040] (4) Pre-sintering: The purpose of pre-sintering is to make a certain degree of solid phase reaction between the ferrite raw materials, improve the sintering activity of the powder, and then reduce the deformation of the material during the subsequent sintering process. Studies have shown that a suitable sintering temperature can make the powder have excellent sintering activity. On the basis of the unchanged subsequent process, it can greatly improve the microstructure of the sintered body, and make the sintered body have higher magnetic properties and temperature stability. In this embodiment, the sieved sample is placed in a box-type high-temperature furnace, the pre-sintering temperature is 850℃, and the temperature is kept for 3 hours, and then cooled to room temperature with the furnace.

[0041] (5) Secondary ball milling: Different from the primary ball milling, a small amount of metal oxides or metal salts need to be added as modifiers during the secondary ball milling process, such as SiO2, CaCO3, Nb2O5, ZrO2, Co2O3, TiO2, SnO2 and NiO. The auxiliary components used in this embodiment include CaCO3: 1600ppm, SiO2: 80ppm, Ta2O5: 1200ppm, based on the weight of the main components. The appropriate secondary ball milling time can break up and disperse the unevenly pre-sintered powder, making the powder particle size more uniform, and then forming a uniform, dense and less porous microstructure in the subsequent sintering process. The different types of modifiers added can improve the microstructure of ferrite from different directions, thereby optimizing the various magnetic properties of the magnetic powder. In this embodiment, the speed of the ball mill is set to 120r / min, and the ball milling time is 16 hours.

[0042] (6) Granulation: Since the powder after ball milling is too fine and has poor plasticity, it is more difficult to directly shape it. In experiments, 10% PVA (8% polyvinyl alcohol solution) is often added as a binder for mechanical granulation. The specific operation is as follows: dry the powder after the second ball milling and pass it through a 30-mesh sieve, add an 8% PVA solution, and the mass ratio of the powder to the PVA solution is 10:1. Pre-press the powder with a relatively low pressure, and finally crush and sieve it. The powder particles finally obtained have good compressibility, high strength, and high compression density.

[0043] (7) Molding: EE type magnetic core: 13.5 g of powder was taken and pressed into a rectangular block (40×22.5×5) at a pressure of 15 KN using a press. The rectangular block was then processed into an EE type magnetic core using an engraving machine and marked.

[0044] Ring core: Take 3.3g of powder and press it into a ring core (Φ13.02×Φ7.6×7.07mm) with a manual molding machine at a pressure of 34KN, and mark it.

[0045] (8) Sintering: This experiment adopts the solid phase sintering method. It is worth noting that the sintering heating rate, temperature, holding time, oxygen partial pressure and cooling rate will directly affect the performance of the product to a great extent. In this embodiment, the pressed magnetic core is placed in an artificial intelligence controllable atmosphere furnace (Haichen Furnace Industry, Changsha Institute of Mining and Metallurgy: RBD14-GSL1T2), and the heating rate is set as follows: 50-200°C is 2°C / min, 200-550°C is 1.17°C / min, 550-800°C is 1.67°C / min, and 800-1170°C is 0.82°C / min; the sintering temperature is 1170°C, and the insulation is 6h, and the core is naturally cooled (cooling: 1170-1100°C is 0.83°C / min, 1100-1050°C is 0.83°C / min, 1050-500°C is 3.06°C / min, and 500-100°C is 2°C / min). The balanced oxygen partial pressure is used throughout the cooling process, and the core is taken out when the furnace temperature is lower than 100°C.

[0046] Loss and temperature rise test:

[0047] (1) Core loss (P cv )

[0048] Test instrument: SY-8218 AC magnetic automatic tester produced by Iwasaki Communication Equipment Co., Ltd. of Japan; winding is a two-wire 3-turn coil, the test frequency is 2000kHz, and the test temperature range is 25-140℃. The temperature characteristic curve of loss (P cv -T), such as Figure 1-4 shown.

[0049] (2) Temperature rise test (℃)

[0050] Test instrument: K-type adhesive thermocouple; TES1310 high-precision K-type thermocouple thermometer; The sample temperature measurement method is to stick the K-type adhesive thermocouple on the outer surface of the ferrite ring and the EE-type magnetic core, and use a high-precision K-type thermocouple thermometer to connect the K-type adhesive thermocouple to measure the temperature rise data.

[0051] The simulation method is as follows:

[0052] (1) Software usage and operation methods

[0053] The ferrite ring and EE type magnetic core were modeled and simulated using the Ansys Maxwell simulation platform. The electromagnetic field part used Ansys Electronics Desktop, and the module was set to Maxwell 3D eddy current field solver; the temperature field part used Ansys Workbench, and the module was set to transient thermal solver. The specific steps are as follows:

[0054] Step 1, open Ansys Electronics Desktop and select the module: Open Ansys Electronics Desktop, select the Maxwell 3D (using finite element analysis (FEA) to solve three-dimensional (3D) electrostatic, static magnetostatic, eddy current and transient problems) module, and select the eddy current field solver. According to the geometric structure of the magnetic ring and the EE-type magnetic core, the corresponding magnetic core model and coil model are modeled in the Maxwell 3D module or CAD and other modeling software. In this embodiment, during the simulation process, because the voltage and frequency at its input end are consistent, and the thickness, length and routing of the wire are the same, the double coil is simplified to a single coil for modeling.

[0055] Step 2, set the material: add the material used in the experiment to the material library in the Maxwell 3D module, select the model in step 1 and assign this material. Specifically: obtain the basic parameters of the soft ferrite to be analyzed, including: relative dielectric constant, conductivity, density, relative magnetic permeability (expressed as BH curve); set the materials of the core model and coil model based on the basic parameters of the soft ferrite material to be analyzed; in the present invention, for the first time, try to use the BH AC meter to measure the nonlinear BH curve of the raw material, and use it as the most critical parameter, so that the software can identify the corresponding material, which provides the possibility of simulating any other material.

[0056] Step 3: Set boundary conditions: Set boundary conditions based on the model built in step 2.

[0057] Step 4. Set excitation: Cut a cross section of the coil model built in step 2 along the XY plane for each coil and assign excitation to the cross section.

[0058] Step 5, meshing: mesh the magnetic core model and coil model obtained in step 1 in a static field solver and import the meshing results into an eddy current field or transient field solver; this embodiment uses surface meshing.

[0059] In the existing eddy current field or transient field solver, the grid can only be divided manually, and manual division may result in insufficient precision or too much calculation. The present invention attempts a new method: first, the grid is divided in the static field solver, where the grid is the best grid calculated by the system, and then the grid obtained by the static field division can be imported into the eddy current field or transient field solver through the grid export / import program. This method not only improves the accuracy but also reduces the consumption of computing resources. In addition, since the accuracy of grid division is improved, the simulation accuracy can also be improved for complex structures, so that the present invention can be applied to complex structures and can accurately simulate and analyze the uneven temperature rise and magnetic loss at various positions of the complex structure.

[0060] Step 6. Simulate loss and post-processing: Add Analysis setup and set the solution frequency, iteration steps, error percentage, etc. Use eddy current field or transient field solver for simulation analysis. After the analysis is completed, first check whether the simulation has any errors, and then check the loss results and magnetic field distribution.

[0061] Step 7. Import the loss results into Ansys Workbench to solve the temperature field: Import the model established in step 1 and the loss results obtained in step 6 into Ansys Workbench, select the transient thermal module, assign parameters (specific heat capacity, thermal conductivity, density, etc.) to the material, solve the temperature field, and obtain the temperature rise results.

[0062] The experimental test and simulation analysis results are as follows Figure 1-4 As shown, it can be seen that the simulation analysis results of the present invention are basically consistent with the experimental test results.

[0063] Figure 5-Figure 8 These are the temperature field simulation results of the ring and EE type magnetic core at 2000kHz, 30mT-60mT conditions.

[0064] Different from the regular annular magnetic core, the location of the heating point of the EE-type magnetic core is not uniform. The present invention can predict the location of the heating point of the EE-type magnetic core, which further illustrates that the method of the present invention can be extended to other magnetic cores of various irregular shapes.

[0065] Corresponding to the embodiment of the loss and temperature rise simulation analysis method of a soft magnetic ferrite mentioned above, the present invention also provides an electronic device, which includes one or more processors for implementing the loss and temperature rise simulation analysis method of a soft magnetic ferrite in the above embodiment.

[0066] The embodiment of the loss and temperature rise simulation analysis method of a soft ferrite of the present invention can be applied to any device with data processing capability, and the device with data processing capability can be a device or apparatus such as a computer.

[0067] The device embodiment can be implemented by software, hardware or a combination of software and hardware. Taking software implementation as an example, as a device in a logical sense, it is formed by the processor of any device with data processing capability in which it is located to read the corresponding computer program instructions in the non-volatile memory into the memory for execution. From the hardware level, the electronic device includes a processor, memory, network interface, and non-volatile memory. In addition, any device with data processing capability in which the device in the embodiment is located can also include other hardware according to the actual function of the device with data processing capability, which will not be described in detail.

[0068] The implementation process of the functions and effects of each unit in the above-mentioned device is specifically described in the implementation process of the corresponding steps in the above-mentioned method, and will not be repeated here.

[0069] For the device embodiment, since it basically corresponds to the method embodiment, the relevant parts can refer to the partial description of the method embodiment. The device embodiment described above is only schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of the present invention. Ordinary technicians in this field can understand and implement it without paying creative work.

[0070] An embodiment of the present invention further provides a computer-readable storage medium having a program stored thereon. When the program is executed by a processor, the loss and temperature rise simulation analysis method of a soft ferrite in the above embodiment is implemented.

[0071] The computer-readable storage medium may be an internal storage unit of any device with data processing capability described in any of the aforementioned embodiments, such as a hard disk or a memory. The computer-readable storage medium may also be any device with data processing capability, such as a plug-in hard disk, a smart media card (SMC), an SD card, a flash card, etc. equipped on the device. Furthermore, the computer-readable storage medium may also include both an internal storage unit of any device with data processing capability and an external storage device. The computer-readable storage medium is used to store the computer program and other programs and data required by any device with data processing capability, and may also be used to temporarily store data that has been output or is to be output.

[0072] The above implementation mode is not a limitation of the present invention, and the present invention is not limited to the above method. Any changes, modifications, additions or substitutions made by technicians in this technical field within the scope of the technical solution of the present invention also belong to the protection scope of the present invention.

Claims

1. A method for simulating and analyzing the loss and temperature rise of soft ferrite, characterized in that: include: Step 1: geometrically model the soft ferrite to be analyzed to obtain a core model and a coil model; Step 2: Obtain the basic parameters of the soft ferrite to be analyzed, including relative dielectric constant, conductivity, density, and relative magnetic permeability; and set the materials of the core model and the coil model based on the basic parameters of the soft ferrite material to be analyzed; Step 3: Setting boundary conditions based on the magnetic core model and coil model obtained in step 1; Step 4: Cut a cross section of the coil model obtained in step 1 through the XY plane according to each coil and assign excitation to the cross section; Step 5: mesh the magnetic core model and coil model obtained in step 1 in a static field solver and import the meshing results into an eddy current field or transient field solver; Step 6: Set the solution parameters and use the eddy current field or transient field solver to simulate the loss; Step 7: Solve the temperature field based on the loss results to obtain the temperature rise results.

2. The method according to claim 1, characterized in that The soft magnetic ferrite is one of manganese-zinc ferrite, nickel-zinc ferrite and metal soft magnetic material.

3. The method according to claim 1, characterized in that The geometric structure of the soft ferrite core structure, wherein the core is a toroidal type, an EI type, an EE type or a PQ type.

4. The method according to claim 3, characterized in that In step 1, the geometric modeling simplifies the double coil of the magnetic core into a single coil for modeling.

5. The method according to claim 1, characterized in that In step five, the meshing is performed by surface meshing or volume meshing, wherein the surface meshing includes two meshing methods based on skin depth and length, and the volume meshing includes a meshing method based on length.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the loss and temperature rise simulation analysis method of soft ferrite according to any one of claims 1 to 5 is implemented.

7. A storage medium comprising computer executable instructions, wherein the computer executable instructions, when executed by a computer processor, implement a loss and temperature rise simulation analysis method for a soft ferrite as claimed in any one of claims 1 to 5.

8. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instruction is executed by a processor, the steps of the loss and temperature rise simulation analysis method of a soft ferrite as described in any one of claims 1 to 5 are implemented.

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