Optimized winding method and system for high-frequency transformer winding

Abstract

The invention provides an optimized winding method and system for a high-frequency transformer winding. A comprehensive parameter database based on current density distribution data of a high-frequency switching power supply is established, the axial temperature of a winding layer is collected in real time in combination with a self-calibration multi-axis winding device, and tension and interlayer gap compensation parameters are generated through temperature gradient feedback. The tension parameter drives the machine to adjust the winding tightness, and the gap parameter optimizes the heat dissipation channel. And synchronously fusing the current distortion data of the LLC resonant topology and an electromagnetic field simulation result, and generating a resonant frequency adjustment signal to suppress abnormal high-frequency current distribution. And dynamic matching of winding tightness, current distribution and heat dissipation requirements is realized through cooperative control. According to the system, electromagnetic, mechanical and thermal field multi-dimensional linkage is adopted, the skin effect and hot spot concentration are reduced, the temperature rise gradient is balanced, and the high-frequency working condition stability is enhanced. According to the technical scheme, through electromagnetic, mechanical and thermal field cooperative regulation and control, the temperature rise peak value of the high-frequency winding is greatly reduced, and the efficiency is greatly improved.

Description

Technical Field

[0001] This application relates to the field of optimized winding technology, and in particular to a method and system for optimized winding of high-frequency transformer windings. Background Technology

[0002] High-frequency switching power supplies need to meet the requirements of high power density and long-term full-load operation in applications such as new energy grid connection and electric vehicle charging piles. Due to the skin effect, proximity effect, and multi-physics coupling, the high-frequency transformer windings are prone to localized overheating, leading to accelerated insulation aging and deterioration of electromagnetic compatibility. Core requirements include: achieving synergistic suppression of high-frequency eddy current losses and copper losses in a multi-layer winding structure; optimizing winding tension and gap to enhance heat dissipation efficiency based on dynamic matching of temperature gradients and current density distributions between winding layers; and simultaneously ensuring compatibility with the electromagnetic field distortion compensation requirements of high-frequency resonant topologies to avoid the risk of partial discharge or core saturation caused by uneven temperature rise.

[0003] Current mainstream solutions employ multiphysics-coupled simulation for winding structure optimization. This method establishes a multi-dimensional electromagnetic-thermal-mechanical joint simulation model to quantitatively analyze the influence of parameters such as winding wire diameter, interlayer gap, and core air gap on temperature rise distribution. Combining genetic algorithms or particle swarm optimization algorithms, with the maximum temperature rise, leakage inductance, and distributed capacitance of the winding as constraints, iteratively solves for the optimal combination of winding parameters, such as the turn allocation of segmented helical windings and the insertion position of the shielding layer. During implementation, finite element analysis is used to verify the hot spot areas of the winding, and a cross-transposition winding process is employed to reduce AC resistance, while ferrite magnetic rings are used to suppress common-mode interference conduction paths.

[0004] This scheme relies on precise assumptions about electromagnetic parameter boundary conditions. However, the temperature sensitivity of the core material and the nonlinear changes in the dielectric properties of the winding insulation layer in actual operating conditions are not adequately modeled, resulting in a typical error of 15%-20% between the simulation results and the measured temperature rise. Furthermore, the optimization algorithm is sensitive to multi-objective weight allocation and struggles to adjust winding parameters in real time under dynamic load scenarios. For example, the instantaneous temperature rise caused by current distortion in the LLC resonant topology cannot be effectively captured by the preset model. While the cross-transfer process reduces AC resistance, it exacerbates the electric field distortion at the edge of the interlayer air gap, potentially leading to partial discharge risks at MHz-level high frequencies, requiring additional insulation thickness, which in turn weakens the heat dissipation channels. Summary of the Invention

[0005] This application provides a method and system for optimizing the winding of high-frequency transformers to solve the problems of high temperature rise and low efficiency in the prior art.

[0006] In a first aspect, this application provides a method for optimizing the winding of a high-frequency transformer, including: A comprehensive parameter database is established based on the current density distribution data of high-frequency switching power supplies. The axial temperature change data of the winding layer during the winding process is collected in real time through a multi-axis winding device with self-calibration function. The axial temperature change data is converted into winding tension compensation parameters and interlayer gap compensation parameters. The winding tension compensation parameters generate mechanical action commands through a temperature gradient feedback system to drive the winding device to perform real-time adjustments. The interlayer gap compensation parameters are used to generate axial gap adjustment commands between winding layers. By combining the current waveform distortion data of the LLC resonant topology with the electromagnetic field simulation results in the comprehensive parameter database, a resonant frequency adjustment signal is generated to match the high-frequency current distribution suppression requirements of the winding. By synchronously executing the mechanical action command, the axial gap adjustment command, and the resonant frequency adjustment signal, the tightness distribution of the winding layers and the high-frequency current distribution characteristics are matched in real time during the winding process. The axial gap adjustment command controls the gap distribution between the winding layers to match the heat dissipation requirements, thereby reducing the peak temperature rise of the winding and improving the heat dissipation efficiency between the winding layers.

[0007] Optionally, by synchronously executing the mechanical action command, the axial clearance adjustment command, and the resonant frequency adjustment signal, the tightness distribution of the winding layers during winding is matched in real time with the high-frequency current distribution characteristics. The axial clearance adjustment command controls the gap distribution between the winding layers to match heat dissipation requirements, thereby reducing the peak temperature rise of the winding and improving the heat dissipation efficiency between the winding layers. This includes: The mechanical action command is associated with the axial movement distance of the winding device, and the winding speed is dynamically adjusted based on the gradient change direction of the axial temperature change data, so that the winding tightness distribution is locally matched with the current high-frequency current distribution characteristics. An axial clearance adjustment command is input to the interlayer support structure of the winding device. A linear compensation coefficient is generated based on the distribution difference of the axial temperature change data. The linear compensation coefficient is then input to the interlayer support structure of the winding device to drive the axial displacement. The resonant frequency adjustment signal is mapped to the axial position of the winding layer. Based on the high-frequency harmonic components in the current waveform distortion data and the magnetic field intensity distribution characteristics in the electromagnetic field simulation results, a frequency correction value for a specific region of the winding layer is generated to suppress high-frequency current concentration. By synchronously linking the winding speed adjustment of the mechanical action command, the interlayer displacement control of the axial gap adjustment command, and the frequency correction value of the resonant frequency adjustment signal, the winding tightness distribution, interlayer gap distribution, and high-frequency current distribution characteristics are dynamically adapted segment by segment along the winding layer axis, thereby reducing the peak temperature rise of the winding and improving the heat dissipation efficiency between the winding layers.

[0008] Optionally, the axial temperature change data is converted into winding tension compensation parameters and interlayer gap compensation parameters. The winding tension compensation parameters generate mechanical action commands through a temperature gradient feedback system to drive the winding device to perform real-time adjustments. The interlayer gap compensation parameters are used to generate axial gap adjustment commands between winding layers, including: Based on the axial temperature change data collected in real time by the multi-axis winding device, temperature change curves are generated at equal intervals according to the axial position of the winding layer. The temperature difference between adjacent intervals in the temperature change curve is converted into winding tension compensation parameters. The winding tension compensation parameters are associated with the winding speed threshold interval through the temperature gradient feedback system to generate mechanical action commands to drive the winding device to perform real-time adjustments. Based on the overall slope of the temperature change curve, the initial compensation amount of the axial gap of the winding layer is calculated, and the interlayer gap compensation parameters are generated by combining the nonlinear proportional relationship between the winding layer thickness and the gap width. Based on the initial compensation amount, an interlayer gap adjustment command is generated by combining the ratio of the winding layer thickness to the gap width. The gap distribution is controlled by the interlayer support structure of the winding device, so that the gap width and the gradient direction of the axial temperature change data form an inverse matching relationship.

[0009] Optionally, by combining the current waveform distortion data of the LLC resonant topology with the electromagnetic field simulation results in the comprehensive parameter database, a resonant frequency adjustment signal is generated to match the high-frequency current distribution suppression requirements of the winding, including: The amplitude abrupt change points of high-frequency harmonic components are extracted from the current waveform distortion data, and the axial position of the winding layer corresponding to the amplitude abrupt change points is determined based on the switching frequency modulation characteristics of the LLC resonant topology. The amplitude abrupt change point is spatially aligned with the magnetic field intensity distribution data in the electromagnetic field simulation results to generate the axial magnetic field intensity correction parameter of the winding layer. Based on the nonlinear mapping relationship between the axial magnetic field strength correction parameter and the winding layer current density, the resonant frequency adjustment coefficient table is called from the comprehensive parameter database to generate a resonant frequency adjustment signal that matches the current high-frequency current distribution characteristics. The resonant frequency adjustment signal is dynamically adjusted through a closed-loop feedback mechanism, so that the tightness distribution of the winding layer is adapted to the current suppression requirements of the LLC resonant topology segment by segment in the axial direction.

[0010] Optionally, a comprehensive parameter database is established based on the current density distribution data of the high-frequency switching power supply. A multi-axis winding device with self-calibration function is used to collect real-time data on the axial temperature change of the winding layer during the winding process, including: The current density distribution data of the high-frequency switching power supply is decomposed into a superposition of high-frequency components and basic components according to the axial position of the winding layer. Based on the distribution ratio of the high-frequency components in the superposition, the current density variation curve of the winding layer is generated, and the current density variation curve is stored to form a comprehensive parameter database. By utilizing the self-calibration function of the multi-axis winding device, temperature acquisition nodes are deployed at equal intervals along the winding layer. The data acquisition frequency of these nodes is dynamically adjusted according to the winding speed, so that the distribution density of the temperature acquisition nodes matches the peak range of the current density in the winding layer, thereby obtaining axial temperature change data.

[0011] Optionally, an axial clearance adjustment command is input to the interlayer support structure of the winding device, a linear compensation coefficient is generated based on the distribution difference of the axial temperature change data, and the linear compensation coefficient is input to the interlayer support structure of the winding device to drive the axial displacement, including: The axial clearance adjustment command is input to the interlayer support structure of the winding device. The absolute value of the temperature difference between adjacent nodes in the axially equally spaced temperature acquisition nodes of the winding layer of the interlayer support structure is extracted. If the absolute value exceeds a preset threshold, the area where the adjacent nodes are located is marked as a temperature difference zone. The absolute values ​​of the temperature differences in the temperature difference region are accumulated and multiplied by a weighting factor dynamically adjusted based on the thermal conductivity of the winding layer material to obtain the linear compensation coefficient for that region. The linear compensation coefficient is input into the interlayer support structure of the winding device. The linear compensation coefficient is multiplied by the preset displacement scaling factor through the displacement converter built into the support structure to generate the axial displacement of the temperature difference zone. The axial displacement drives the interlayer support structure to expand and contract in the winding layer axially, so that the gap width of the temperature difference zone expands proportionally to the linear compensation coefficient, and the gap expansion of adjacent areas transitions according to the gradient of the displacement difference of the temperature difference zone.

[0012] Optionally, based on the overall slope of the temperature change curve, the initial compensation amount for the axial gap of the winding layer is calculated, and interlayer gap compensation parameters are generated by combining the nonlinear proportional relationship between the winding layer thickness and the gap width, including: The axial temperature change curve of the winding layer is piecewise linearly fitted, and the continuous fitted segment with the largest absolute value of the temperature difference between the first and last ends of the axial winding layer is selected. The absolute value of its slope is calculated as the overall slope. Multiply the overall slope by the preset gap compensation ratio factor to obtain the initial compensation amount for the axial gap of the winding layer. Based on the measured ratio between the winding layer thickness and the gap width, the compensation increment of the square value of the winding layer thickness is superimposed on the initial compensation amount to generate the corrected interlayer gap compensation parameters.

[0013] Secondly, this application provides a high-frequency transformer winding optimization system, comprising: The acquisition module is used to establish a comprehensive parameter database based on the current density distribution data of the high-frequency switching power supply, and to acquire the axial temperature change data of the winding layer in real time during the winding process through a multi-axis winding device with self-calibration function. The generation module is used to convert the axial temperature change data into winding tension compensation parameters and interlayer gap compensation parameters. The winding tension compensation parameters generate mechanical action commands through the temperature gradient feedback system to drive the winding device to perform real-time adjustments. The interlayer gap compensation parameters are used to generate axial gap adjustment commands between winding layers. The matching module is used to combine the current waveform distortion data of the LLC resonant topology with the electromagnetic field simulation results in the comprehensive parameter database to generate a resonant frequency adjustment signal to match the high-frequency current distribution suppression requirements of the winding. The heat dissipation module is used to synchronize the mechanical action command, the axial gap adjustment command and the resonant frequency adjustment signal to make the tightness distribution of the winding layer and the high-frequency current distribution characteristics match in real time during the winding process. The axial gap adjustment command controls the gap distribution between the winding layers to match the heat dissipation requirements, thereby reducing the peak temperature rise of the winding and improving the heat dissipation efficiency between the winding layers.

[0014] Thirdly, embodiments of this application provide a computing device, including a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are to be invoked and executed by the processing component to implement a high-frequency transformer winding optimization method as described in the first aspect above.

[0015] Fourthly, embodiments of this application provide a computer storage medium storing a computer program, which, when executed by a computer, implements a high-frequency transformer winding optimization method as described in the first aspect.

[0016] This application establishes a comprehensive parameter database based on current density distribution data of high-frequency switching power supplies, enabling digital modeling of the winding's electromagnetic characteristics and providing precise data support for winding process optimization. A multi-axis winding device with self-calibration capabilities collects axial temperature change data of the winding layers in real time during winding, dynamically monitoring the evolution of the winding's thermal state and providing real-time feedback for process parameter adjustments. By converting the axial temperature change data into winding tension compensation parameters and interlayer gap compensation parameters, a mapping relationship between temperature gradient and mechanical parameters is established, achieving closed-loop control of the winding process. The winding tension compensation parameters drive the winding device to perform real-time adjustments, dynamically matching the winding tightness distribution with the high-frequency current distribution characteristics. The interlayer gap compensation parameters generate axial gap adjustment commands, optimizing the winding's heat dissipation channel layout and improving heat transfer efficiency. By combining current waveform distortion data of the LLC resonant topology with electromagnetic field simulation results to generate a resonant frequency adjustment signal, adaptive compensation of the winding's high-frequency characteristics is achieved. By simultaneously executing mechanical action commands, axial gap adjustment commands, and resonant frequency adjustment signals, a multi-physics collaborative control mechanism involving electromagnetic, mechanical, and thermal fields is constructed, significantly improving winding performance.

[0017] Furthermore, by associating mechanical motion commands with the axial movement distance of the winding device and dynamically adjusting the winding speed based on the temperature gradient, precise control of local winding tightness can be achieved; by inputting axial clearance adjustment commands into the interlayer support structure and generating linear compensation coefficients, intelligent adjustment of the heat dissipation channel can be achieved; by mapping the resonant frequency adjustment signal to the axial position of the winding layer and generating a frequency correction value, the phenomenon of high-frequency current concentration can be effectively suppressed; by synchronously linking winding speed adjustment, interlayer displacement control, and frequency correction value matching, dynamic optimization of the performance parameters of each axial segment of the winding can be achieved. Its technical effects are: breakthroughs... Overcoming the limitations of fixed parameters in traditional winding processes, an adaptive compensation mechanism is constructed based on real-time monitoring data. This mechanism achieves optimal matching between winding tightness distribution and current density characteristics, reducing skin effect losses by up to 30%. By intelligently adjusting the interlayer gap distribution, an optimal heat dissipation path is constructed, reducing the peak winding temperature rise by more than 25%. Combined with dynamic correction of the resonant frequency, high-frequency magnetic field distortion is effectively suppressed, improving electromagnetic compatibility performance by 15%. Ultimately, an intelligent winding system integrating electromagnetic optimization, mechanical adjustment, and thermal management is formed, achieving a comprehensive improvement in the performance of high-frequency transformer windings and providing reliable technical support for high-power-density power supply equipment.

[0018] These or other aspects of this application will become more apparent in the following description of the embodiments. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 A flowchart of an optimized winding method for a high-frequency transformer provided in this application is shown; Figure 2 This application provides a schematic diagram of the structure of an optimized winding system for high-frequency transformer windings. Figure 3 A schematic diagram of the structure of a computing device provided in this application is shown. Detailed Implementation

[0021] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0022] In some of the processes described in the specification, claims, and accompanying drawings of this application, multiple operations appearing in a specific order are included. However, it should be clearly understood that these operations may not be executed in the order they appear herein, or may be executed in parallel. The operation numbers, such as 101, 102, etc., are merely used to distinguish different operations and do not themselves represent any execution order. Furthermore, these processes may include more or fewer operations, and these operations may be executed sequentially or in parallel. It should be noted that the descriptions such as "first," "second," etc., in this document are used to distinguish different messages, devices, modules, etc., and do not represent a chronological order, nor do they limit "first" and "second" to different types.

[0023] Researchers have found that existing high-frequency transformer winding processes mainly rely on fixed parameters or single-physics field simulations, making it difficult to dynamically match the electromagnetic, mechanical, and thermal multi-field coupling characteristics under high-frequency operating conditions. Furthermore, real-time control during the winding process lacks a coordinated response to current distribution and temperature gradients, leading to problems such as increased winding temperature and low heat dissipation efficiency. Based on this, a high-frequency transformer winding optimization method is proposed. This method can achieve dynamic optimization of winding performance through multi-physics field data fusion and closed-loop feedback control. The technical solution of this application is applicable to the manufacturing of high-frequency transformers for high-power-density power supply equipment such as new energy converters and electric vehicle charging modules.

[0024] The entire R&D process embodies the technological synergy of electromagnetic characteristic modeling, real-time sensing, and dynamic compensation, aiming to overcome the shortcomings of existing solutions, such as fixed winding parameters, lag in thermal field response, and insufficient high-frequency suppression. A comprehensive parameter database is constructed through real-time monitoring of current density and temperature field, overcoming the limitations of traditional winding processes in adapting to dynamic operating conditions. By combining waveform distortion analysis and electromagnetic field simulation of LLC resonant topology, a collaborative decision-making mechanism for frequency compensation and mechanical adjustment is established to achieve dynamic matching between the winding's electromagnetic characteristics and heat dissipation requirements. Based on the self-calibration function of the multi-axis winding device, the problem of independent control of winding tension and interlayer gap in traditional methods is solved. This method significantly improves the high-frequency performance and heat dissipation efficiency of the winding through multi-physics closed-loop optimization and real-time execution mechanisms.

[0025] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] Figure 1 A flowchart of a high-frequency transformer winding optimization method is provided in this application embodiment, as shown below. Figure 1 As shown, the method includes: 101. Establish a comprehensive parameter database based on the current density distribution data of high-frequency switching power supplies, and collect the axial temperature change data of the winding layer in real time during the winding process through a multi-axis winding device with self-calibration function. In this step, the integrated parameter database refers to a structured dataset that integrates the current density distribution, electromagnetic field simulation results, and material properties of the high-frequency switching power supply winding under different operating conditions. The self-calibration function refers to a closed-loop control system that corrects the axial positioning error of the robotic arm in real time using a laser rangefinder. The axial temperature change data refers to the measured temperature gradient data acquired at a high sampling frequency through an array of infrared thermocouples distributed on the surface of the winding mold.

[0027] In this embodiment, firstly, a three-dimensional electromagnetic model of the high-frequency switching power supply is established in finite element analysis software, and the initial current density distribution spectrum is obtained by solving Maxwell's equations. Secondly, a self-calibration module is installed on each motion axis of the multi-axis winding device. This module includes a laser ranging unit and a strain gauge sensor, which can perform position calibration every 50ms during the winding process to eliminate mechanical transmission errors. Next, axial temperature change data is collected at a sampling rate of 200Hz using a flexible thermocouple array arranged on the surface of the winding layer, and the displacement and velocity data of the winding machine are spatiotemporally aligned with the temperature measurements. Finally, a Kalman filter algorithm is used to fuse simulation data and measured data to construct a comprehensive parameter database with timestamps.

[0028] During the winding process of a high-frequency transformer, the self-calibration module of the multi-axis winding device detected a 0.15 mm trajectory offset on the X-axis, triggering the servo motor to compensate for the 0.12 mm displacement within 5 milliseconds. When the winding reached the 4th layer, the infrared thermocouple array arranged on the mold surface measured a sudden 9-degree Celsius increase in the axial temperature of section 3. The system immediately retrieved the current density threshold of 8.2 amperes per square millimeter for the 0.3 mm diameter enameled wire from the comprehensive parameter database, determining that the current density in the current area had reached 9.1 amperes per square millimeter. Subsequently, the winding machine was driven to reduce the feed speed from 45 revolutions per minute to 38 revolutions per minute, allowing the temperature in that area to drop back to the design allowable range within 15 seconds.

[0029] 102. The axial temperature change data is converted into winding tension compensation parameters and interlayer gap compensation parameters, wherein the winding tension compensation parameters generate mechanical action commands through the temperature gradient feedback system to drive the winding device to perform real-time adjustments, and the interlayer gap compensation parameters are used to generate axial gap adjustment commands between winding layers. In this step, the winding tension compensation parameter refers to the servo motor torque adjustment coefficient calculated based on the axial temperature gradient change, with a value range defined as ±10% of the rated torque. The interlayer gap compensation parameter refers to the axial gap adjustment amount generated based on the material's thermal expansion coefficient and temperature distribution, with a compensation resolution of 0.01 mm. The temperature gradient feedback system refers to the control logic unit that triggers a mechanical adjustment command when the temperature change rate exceeds a set threshold.

[0030] In this embodiment, firstly, the axial temperature change data collected in step 101 is input into the thermal-tension coupling model, and the winding tension loss in each region is calculated based on the material's thermal expansion coefficient. Secondly, the gradient values ​​of adjacent temperature sensors are calculated using a sliding window algorithm. When the gradient exceeds 0.5℃ / mm, a tension compensation mechanism is triggered to generate proportional and integral adjustment parameters. Next, a gap compensation formula is established based on the interlayer heat dissipation requirements, mapping the temperature distribution to the insulation layer gap adjustment amount. Finally, the tension compensation parameters are sent to the servo driver via the CAN protocol, and the interlayer gap compensation parameters are sent to the pneumatic gap adjustment mechanism via the EtherCAT protocol, generating an axial gap adjustment command between the winding layers.

[0031] Based on the continuous temperature monitoring data of section 3 in step 101, the temperature gradient feedback system detected an axial gradient of 0.7 degrees Celsius per millimeter, exceeding the threshold of 0.5 degrees Celsius per millimeter. The thermal-tension coupling model calculation showed that an 18% increase in winding tension was needed, and the servo motor increased its torque from 4.5 N·m to 5.3 N·m. Simultaneously, the interlayer gap compensation algorithm, based on the temperature field distribution, expanded the interlayer gap of section 3 from 0.10 mm to 0.18 mm, and completed the adjustment within 0.5 seconds via a pneumatic actuator. After adjustment, the temperature gradient of this section decreased to 0.3 degrees Celsius per millimeter, the current density returned to 8.0 amperes per square millimeter, and the temperature difference between adjacent layers decreased by 40%.

[0032] 103. Combining the current waveform distortion data of the LLC resonant topology with the electromagnetic field simulation results in the comprehensive parameter database, a resonant frequency adjustment signal is generated to match the high-frequency current distribution suppression requirements of the winding. In this step, the current waveform distortion data of the LLC resonant topology refers to the harmonic components of the resonant current spectrum acquired through a broadband current probe, with the analysis frequency band covering 1MHz-10MHz. The electromagnetic field simulation results refer to the data on the correspondence between the winding spatial magnetic field strength and eddy current losses stored in the comprehensive parameter database. The resonant frequency adjustment signal refers to the digital control signal generated based on the waveform distortion level, used to adjust the equivalent capacitance value of the resonant capacitor network.

[0033] In this embodiment, firstly, the current waveform of the LLC resonant circuit is captured using a high-speed ADC at a sampling rate of 2MHz, and the amplitudes of the 3rd to 15th harmonics are extracted using a windowed FFT algorithm. Secondly, the harmonic data is compared with simulation results in a comprehensive parameter database to calculate the harmonic distortion rate deviation. Next, a genetic algorithm is used to search for the optimal resonant frequency in the range of 1.2-1.8MHz, achieving optimal combination of distortion rate and temperature rise parameters. Finally, a resonant frequency adjustment signal is generated, and the operating frequency is adjusted by driving the switching transistor through an optocoupler isolation circuit.

[0034] When the winding was connected to the LLC resonant circuit for testing, the broadband current probe detected a 7th harmonic amplitude of 15%, exceeding the 12% limit. The system retrieved the eddy current loss distribution data of the 4th layer of the winding from the comprehensive parameter database and, combined with iterative calculations using a genetic algorithm, determined that the optimal resonant frequency should be adjusted from 1.55 MHz to 1.68 MHz. After the frequency adjustment signal was injected into the control chip through a digital isolator, the measured total harmonic distortion rate decreased to 4.2%, the overall winding temperature rise decreased from 82 degrees Celsius to 71 degrees Celsius, and the power loss decreased by 22%.

[0035] 104. By synchronously executing the mechanical action command, the axial gap adjustment command, and the resonant frequency adjustment signal, the tightness distribution of the winding layers and the high-frequency current distribution characteristics are matched in real time during the winding process. The axial gap adjustment command controls the gap distribution between the winding layers to match the heat dissipation requirements, thereby reducing the peak temperature rise of the winding and improving the heat dissipation efficiency between the winding layers.

[0036] In this step, real-time matching of tension distribution with high-frequency current distribution characteristics refers to dynamically adjusting the winding tension based on the skin depth effect, so that the stress distribution of the winding conductor is negatively correlated with the skin effect of the high-frequency current. Matching gap distribution with heat dissipation requirements refers to dynamically adjusting the interlayer spacing based on a thermal flow simulation model, so that high-loss areas correspond to larger heat dissipation channels.

[0037] In this embodiment, firstly, a multi-instruction synchronous control timing sequence is established, executing mechanical action commands, axial clearance adjustment commands, and resonant frequency adjustment signals in 5ms time slots. Secondly, the electronic gear function of the motion controller achieves phase synchronization between winding speed and frequency compensation, ensuring that the error between mechanical action and electrical parameter adjustment is less than 0.1%. Next, based on the thermal and electrical coupling model, the adjusted temperature rise distribution is predicted, and the gradient distribution of the interlayer gap is dynamically optimized. Finally, real-time process data is uploaded to the MES system via the OPC UA protocol, forming a full-process quality traceability chain.

[0038] After simultaneously performing tension compensation of 5.3 N·m, interlayer gap adjustment of 0.18 mm, and resonant frequency locking of 1.68 MHz, the system maintains multi-parameter coordination through a 5-millisecond control cycle: the electronic gear module ensures that the winding speed of 38 revolutions per minute remains in phase with the frequency adjustment, with an error of less than 0.05 degrees; the thermal flow simulation model dynamically optimizes the gap distribution, expanding the heat dissipation channel in the high-temperature zone by 30%. The final winding hotspot temperature stabilizes at 69±1.5 degrees Celsius, a 26% reduction from the initial value, the required radiator airflow speed decreases from 2.0 meters per second to 1.2 meters per second, and the winding efficiency improves by 20%. All process parameters are uploaded to the MES system via OPC UA, forming a complete traceability chain including timestamps, adjustment parameters, and quality indicators.

[0039] In summary, steps 101 to 104 achieve multi-physics field collaborative optimization of electromagnetic, thermal, and mechanical fields in the high-frequency winding process. A digital twin model of the winding's operating conditions is constructed by integrating current density distribution, electromagnetic field simulation, and material property data through a comprehensive parameter database. A self-calibrating multi-axis winding device is used to collect millimeter-level precision axial temperature gradient data in real time, and winding tension compensation parameters are dynamically generated using a thermal and tension coupling model. Based on LLC resonant current waveform distortion analysis and optimization algorithms, a resonant frequency adjustment signal is generated to suppress high-frequency harmonic losses. A multi-instruction synchronous control mechanism coordinates tension compensation, gap adjustment, and frequency adjustment, ensuring that the winding layer tightness distribution precisely matches the skin effect, and the interlayer gap distribution dynamically adapts to heat dissipation requirements. This scheme significantly reduces the peak temperature rise of the winding, increases power density, and reduces high-frequency losses. Simultaneously, it enables full-process traceability of process parameters through a protocol, providing closed-loop optimization capabilities for the intelligent manufacturing of high-power-density electromagnetic devices.

[0040] In some embodiments, step 104, by synchronously executing the mechanical action command, the axial gap adjustment command, and the resonant frequency adjustment signal, achieves real-time matching between the tightness distribution of the winding layers and the high-frequency current distribution characteristics during the winding process. Furthermore, the axial gap adjustment command controls the gap distribution between the winding layers to match heat dissipation requirements, thereby reducing the peak temperature rise of the winding and improving the heat dissipation efficiency between the winding layers. This includes: 201. Link the mechanical action command to the axial movement distance of the winding device, and dynamically adjust the winding speed based on the gradient change direction of the axial temperature change data, so that the winding tightness distribution and the current high-frequency current distribution characteristics are locally matched. In step 201, the mechanical action command refers to the servo motor drive command that controls the axial movement distance of the winding device, and its value is dynamically generated by the winding tension compensation parameters. The axial movement distance refers to the displacement of the winding machine guide wheel along the coil axis, with an accuracy down to the micrometer level. The gradient change direction of the axial temperature change data refers to the trend of the surface temperature of the winding layer rising or falling along the axial direction, which is acquired in real time through a temperature sensor array. The high-frequency current distribution characteristics refer to the non-uniform current density distribution of the winding conductor under high-frequency operating conditions due to the skin effect.

[0041] In this embodiment, firstly, based on the winding tension compensation parameters generated in step 105, a linear mapping model between mechanical action commands and the axial movement distance of the winding device is established. The compensation parameters are converted into servo motor stepping amounts with a stepping accuracy of 0.001 mm. Secondly, axial temperature change data of the winding layer is collected in real time through a distributed temperature sensor array. The moving average algorithm is used to calculate the direction of temperature gradient change and identify sections with gradients exceeding 0.5 degrees Celsius per millimeter. Next, the winding speed is dynamically adjusted according to the gradient direction. If the gradient direction is positive, i.e., the temperature increases along the axial direction, the winding speed is reduced by 12% to 15%; if it is negative, the speed is increased by 8% to 10%. Finally, the adjusted speed parameters are sent to the winding machine controller via the CAN bus to achieve local matching between the winding tension distribution and the current high-frequency current density peak region.

[0042] 202. Input the axial clearance adjustment command into the interlayer support structure of the winding device, generate a linear compensation coefficient based on the distribution difference of the axial temperature change data, and input the linear compensation coefficient into the interlayer support structure of the winding device to drive the axial displacement. In step 202, the axial clearance adjustment command refers to a digital control signal that controls the displacement of the interlayer support structure, used to adjust the width of the insulation layer gap. The interlayer support structure refers to a pneumatically driven precision displacement platform with a repeatability of 0.005 mm. The linear compensation coefficient refers to a gap adjustment proportional factor calculated based on temperature distribution differences, with a value ranging from 0.8 to 1.2.

[0043] In this embodiment, firstly, the axial temperature change data processed in step 201 is input into the thermal expansion coefficient model to calculate the linear expansion of each winding layer, with the expansion error controlled within ±0.002 mm. Secondly, a linear compensation coefficient is generated based on the temperature distribution differences. If the temperature difference between adjacent sections exceeds 3 degrees Celsius, the compensation coefficient is set to 1.2; if the temperature difference is less than 1 degree Celsius, the coefficient is set to 0.8. Next, the compensation coefficient is encoded into an EtherCAT protocol data frame and sent to the interlayer support structure controller of the winding device to drive the pneumatic piston to perform axial displacement adjustment, with a displacement resolution of 0.01 mm. Finally, the measured gap width is fed back in real time by a laser interferometer. If the deviation from the target value exceeds 0.005 mm, a secondary compensation cycle is triggered.

[0044] 203. The resonant frequency adjustment signal is mapped to the axial position of the winding layer. Based on the high-frequency harmonic components in the current waveform distortion data and the magnetic field strength distribution characteristics in the electromagnetic field simulation results, a frequency correction value for a specific region of the winding layer is generated to suppress high-frequency current concentration. In step 203, the resonant frequency adjustment signal refers to the PWM control signal that adjusts the switching frequency of the LLC resonant circuit, used to suppress high-frequency harmonics. The axial position of the winding layer refers to the segmented coordinates of the coil along the axial direction, each segment corresponding to a specific magnetic field strength region. High-frequency harmonic components refer to harmonic components in the current waveform with frequencies greater than 1 MHz, extracted through FFT analysis. The magnetic field strength correction parameter refers to the frequency compensation coefficient generated based on the electromagnetic field simulation results.

[0045] In this embodiment, firstly, using the current waveform distortion data extracted in step 401, the amplitude abrupt change point of the high-frequency harmonic component is located. A wavelet transform algorithm is used to determine the axial position of the winding layer corresponding to the abrupt change point, with a coordinate positioning accuracy of 0.1 mm. Secondly, the axial position coordinates are spatially aligned with the electromagnetic field simulation results in the comprehensive parameter database to match the magnetic field strength distribution characteristics. If the magnetic field strength in a certain section exceeds the design threshold by 15%, it is marked as a high-frequency current concentration area. Next, the resonant frequency adjustment coefficient table in the database is called, and a corresponding PWM duty cycle signal is generated based on the magnetic field strength correction parameters. For example, a 1.65 MHz frequency command is generated when the magnetic field exceeds the limit by 20%. Finally, the frequency adjustment signal is transmitted to the LLC resonant controller via optical fiber communication to drive the MOSFET switching transistor to adjust the operating frequency.

[0046] 204. By synchronously linking the winding speed adjustment of the mechanical action command, the interlayer displacement control of the axial gap adjustment command, and the frequency correction value of the resonant frequency adjustment signal, the winding tightness distribution, interlayer gap distribution, and high-frequency current distribution characteristics are dynamically adapted segment by segment along the winding layer axis, thereby reducing the peak temperature rise of the winding and improving the heat dissipation efficiency between the winding layers.

[0047] In step 204, synchronous linkage refers to the simultaneous execution of mechanical actions, gap adjustment, and frequency adjustment commands within a 5-millisecond cycle through a time-triggered mechanism. Segment-by-segment dynamic adaptation refers to the independent adjustment of parameters in 10-millimeter intervals along the winding layer axis, resulting in segmented optimization.

[0048] In this embodiment, firstly, a multi-instruction synchronous control timing sequence is constructed, executing the mechanical action command in step 201, the axial clearance adjustment command in step 202, and the resonant frequency adjustment signal in step 203 in 5-millisecond time slots, with timing deviation controlled within ±10 microseconds. Secondly, the phase synchronization of winding speed and resonant frequency is achieved through the electronic gear module of the motion controller, ensuring that the angle error per revolution of the winding layer is less than 0.03 degrees. Next, based on the thermal and electrical coupling simulation model, the adjusted temperature rise distribution is predicted, and the gradient distribution of the interlayer gap is dynamically optimized: the gap is increased by 0.15 mm in the high-temperature zone and decreased by 0.05 mm in the low-temperature zone. Finally, the real-time process parameters are uploaded to the MES system via the OPC UA protocol, generating a full-process traceability data chain containing timestamps, temperature gradients, and frequency adjustment amounts.

[0049] Here is a specific example: During the winding process of a high-voltage high-frequency reactor, the winding device detected a sudden temperature gradient change in the fifth section of the winding layer, specifically in the axial region from 50 mm to 60 mm. The positive gradient reached 0.8 degrees Celsius per millimeter, triggering the dynamic adjustment mechanism in step 201. Data was collected in real-time using a distributed temperature sensor array, identifying the peak high-frequency current density corresponding to this section as 9.5 amperes per square millimeter. The servo motor reduced the winding speed from 45 revolutions per minute to 38 revolutions per minute, matching the tension distribution to the current skin effect region. Simultaneously, as in step 202, a linear compensation coefficient of 1.18 was generated based on the temperature difference of 4.2 degrees Celsius between adjacent sections 40 mm to 50 mm and 50 mm to 60 mm, driving the pneumatic support structure to adjust the interlayer gap from 0.12 mm to 0.14 mm. A laser interferometer detected a gap deviation of 0.003 mm, triggering secondary compensation to precisely reach the target value. As shown in step 203, electromagnetic field simulation data shows that the magnetic field strength in section 5 exceeds the standard by 18%. Combined with current waveform distortion data, a sudden increase of 22% in the 1.6 MHz harmonic amplitude is detected. The resonant frequency adjustment coefficient table is called to generate a 1.72 MHz PWM signal, which is transmitted to the LLC controller via optical fiber, increasing the switching frequency from 1.5 MHz to 1.68 MHz. As shown in step 204, the multi-instruction synchronous control module coordinates the above parameter adjustments within a 5-millisecond cycle, controlling the winding speed and frequency phase synchronization error within 0.02 degrees. Gap gradient optimization expands the gap from 50 mm to 60 mm in the high-temperature zone to 0.15 mm, and reduces the gap from 30 mm to 40 mm in the low-temperature zone to 0.10 mm. After adjustment, the peak temperature rise in this section decreases from 82 degrees Celsius to 64 degrees Celsius, and the harmonic amplitude is significantly attenuated. All process parameters are uploaded to the MES system via the OPC UA protocol, forming a data chain containing timestamps, temperature distribution, and frequency correction, supporting full-process quality traceability.

[0050] In summary, steps 201 to 204 construct a closed-loop control system for the coordinated optimization of electromagnetic, thermal, and mechanical fields during the high-frequency winding process. Local matching of winding tightness and high-frequency current distribution is achieved through dynamic mapping of mechanical action commands and axial temperature gradients. A linear compensation mechanism based on interlayer gaps, combined with a thermal expansion model and laser feedback technology, dynamically adapts to heat dissipation requirements. Spatial alignment of the resonant frequency adjustment signal and harmonic suppression strategies effectively balance the magnetic field strength distribution. Finally, dynamic parameter adaptation of the winding layer segment by segment is achieved through multi-command synchronous linkage. This scheme significantly reduces the peak temperature rise of the winding, improves heat dissipation efficiency and power density, suppresses high-frequency harmonic losses, and ensures process consistency through full-process data traceability, providing core support for the intelligent manufacturing of high-reliability electromagnetic devices.

[0051] In some embodiments, step 102 involves converting the axial temperature change data into winding tension compensation parameters and interlayer gap compensation parameters. The winding tension compensation parameters generate mechanical action commands through a temperature gradient feedback system to drive the winding device to perform real-time adjustments. The interlayer gap compensation parameters are used to generate axial gap adjustment commands between winding layers, including: 301. Based on the axial temperature change data collected in real time by the multi-axis winding device, a temperature change curve is generated at equal intervals according to the axial position of the winding layer. The temperature difference between adjacent intervals in the temperature change curve is converted into a winding tension compensation parameter. The winding tension compensation parameter is associated with the winding speed threshold interval through a temperature gradient feedback system to generate a mechanical action command to drive the winding device to perform real-time adjustment. In step 301, the temperature change curve refers to a continuous distribution curve of temperature measurements divided at equal intervals along the axial direction of the winding layers, with the horizontal axis representing the axial position and the vertical axis representing the measured temperature value. The winding tension compensation parameter refers to the servo motor torque adjustment coefficient calculated based on the temperature difference between adjacent sections, and its value range is positively correlated with the temperature gradient. The temperature gradient feedback system refers to a closed-loop control system that triggers winding speed adjustment when the temperature difference exceeds a set threshold.

[0052] In this embodiment, firstly, based on the collected axial temperature data, the winding layer is divided into several segments with a spacing of 10 mm, generating a temperature change curve. Secondly, the temperature difference between adjacent segments is calculated using a sliding window algorithm. When the difference exceeds 2 degrees Celsius, a temperature gradient feedback system is triggered. Next, according to a preset tension-temperature mapping table, the temperature difference is converted into winding tension compensation parameters; for example, a 5-degree Celsius temperature difference corresponds to a 12% increase in tension. Finally, the compensation parameters are associated with a winding speed threshold range to generate mechanical action commands that drive the servo motor to adjust the winding speed.

[0053] 302. Based on the overall slope of the temperature change curve, calculate the initial compensation amount of the axial gap of the winding layer, and generate the interlayer gap compensation parameters by combining the nonlinear proportional relationship between the winding layer thickness and the gap width. In step 302, the overall slope refers to the average rate of temperature change along the entire axial length of the temperature change curve, expressed in degrees Celsius per millimeter. The initial compensation amount refers to the basic adjustment value of the interlayer gap calculated based on the overall slope, and its value is proportional to the absolute value of the slope. The nonlinear proportional relationship refers to the exponential relationship between the winding layer thickness and the gap width; for example, for every 0.1 mm increase in thickness, the gap needs to be increased by 0.03 mm.

[0054] In this embodiment, firstly, the temperature change curve generated in step 301 is linearly fitted to calculate its overall slope. Secondly, the initial compensation amount is determined based on the slope value; if the slope is 0.5 degrees Celsius per millimeter, the compensation amount is 0.15 millimeters; if the slope is 0.2 degrees Celsius per millimeter, the compensation amount is 0.08 millimeters. Next, combined with the winding layer thickness data, the final gap compensation amount is calculated using a nonlinear formula; for example, when the thickness is 0.3 millimeters, the compensation amount is corrected to 1.2 times the initial value. Finally, the compensation amount is encapsulated as an interlayer gap compensation parameter.

[0055] 303. Based on the initial compensation amount, and combined with the ratio of the winding layer thickness to the gap width, an interlayer gap adjustment command is generated, and the gap distribution is controlled by the interlayer support structure of the winding device, so that the gap width and the gradient direction of the axial temperature change data form an inverse matching relationship.

[0056] In step 303, the interlayer gap adjustment command refers to a digital control command that controls the displacement of the aerodynamic support structure, with an accuracy of 0.01 mm. The reverse matching relationship means that the gap width adjustment direction is opposite to the temperature gradient direction; for example, the gap is widened in the high-temperature zone and narrowed in the low-temperature zone.

[0057] In this embodiment, firstly, the interlayer gap compensation parameters generated in step 302 are input into the aerodynamic support structure controller. Secondly, the gap is dynamically adjusted according to the temperature gradient direction. If the temperature gradient in a certain section is positive, the gap compensation in that section is increased by 110%; if it is negative, the compensation is reduced by 90%. Next, the gap width is monitored in real time using a laser displacement sensor. If the measured value deviates from the target value by more than 5%, secondary compensation is triggered. Finally, the adjusted gap distribution data is synchronized to the comprehensive parameter database.

[0058] Here is a specific example: During the winding process of a high-frequency reactor, the multi-axis winding device detected an abnormal temperature gradient in the axial region between 60 mm and 70 mm when winding the 6th layer, with a positive gradient reaching 0.9 degrees Celsius per millimeter. As in step 301, the system divides the temperature acquisition nodes into 10 mm intervals, generates a temperature change curve, and identifies a 7-degree Celsius temperature difference between adjacent sections 60-70 mm and 70-80 mm, triggering the temperature gradient feedback system. According to a preset mapping table, a 7-degree Celsius temperature difference corresponds to an 18% increase in the winding tension compensation parameter. The servo motor reduces the winding speed from 48 rpm to 40 rpm, generating a mechanical action command to drive the winding head to adjust the tension distribution. As in step 302, the temperature change curve is linearly fitted, and the overall slope is measured to be 0.6 degrees Celsius per millimeter, with an initial compensation of 0.18 mm. Combining this with the winding layer thickness of 0.32 mm, the final gap compensation is calculated using a nonlinear formula to be 0.21 mm, with the error controlled within 0.004 mm. As in step 303, after receiving the compensation parameters, the pneumatic support structure controller expands the 60-70 mm gap in the high-temperature zone from 0.15 mm to 0.23 mm, and reduces the 50-60 mm gap in the low-temperature zone from 0.15 mm to 0.12 mm. Real-time monitoring by the laser displacement sensor shows that the gap adjustment accuracy meets the standard, with a deviation of less than 0.003 mm. After adjustment, the peak temperature rise in this section drops from 88 degrees Celsius to 65 degrees Celsius, and the harmonic amplitude attenuates significantly. The process parameters are simultaneously uploaded to the MES system to form traceability data.

[0059] In summary, steps 301 to 303 construct a closed-loop control system for the multi-field coupling of heat, force, and electricity during the high-frequency winding process. By driving the dynamic mapping of winding tension and speed through axial temperature gradient data, local adaptation of winding tightness and current density distribution is achieved. Based on the coordinated control of a nonlinear compensation model and aerodynamic support structure, the interlayer gap gradient is dynamically optimized, forming a negative feedback mechanism for heat dissipation efficiency and temperature distribution. Combined with laser sensing and a closed-loop algorithm, mechanical displacement errors are precisely corrected. This scheme significantly suppresses winding temperature rise hotspots, improves the uniformity of current distribution under high-frequency operating conditions, and enables controllable iteration of process parameters through full-process data traceability, providing core support for the intelligent manufacturing of high-power-density electromagnetic devices.

[0060] In some embodiments, step 103, which involves combining the current waveform distortion data of the LLC resonant topology with the electromagnetic field simulation results in the integrated parameter database to generate a resonant frequency adjustment signal to match the high-frequency current distribution suppression requirements of the winding, includes: 401. Extract the amplitude abrupt change points of high-frequency harmonic components from the current waveform distortion data, and determine the axial position of the winding layer corresponding to the amplitude abrupt change points based on the switching frequency modulation characteristics of the LLC resonant topology. In step 401, the amplitude abrupt change point refers to the frequency point in the current waveform distortion data where the harmonic amplitude suddenly increases by more than 20%, which is located using a wavelet transform algorithm. Axial position refers to the coordinates of the winding layer along the axial direction, with an accuracy of 0.1 mm. Switching frequency modulation characteristics refer to the nonlinear response of the LLC resonant circuit to harmonic suppression at different frequencies.

[0061] In this embodiment, firstly, the LLC resonant current waveform is acquired using a broadband current probe at a sampling rate of 2MHz. Secondly, wavelet packet decomposition algorithm is applied to extract the 3rd to 15th harmonic components, identifying frequency points where the amplitude abruptly exceeds 20%. Next, based on the switching frequency modulation characteristics, the axial position of the winding layer corresponding to the abrupt frequency point is determined; for example, the 1.5MHz harmonic corresponds to the 5th winding layer. Finally, the position coordinates are marked as high-frequency current concentration areas.

[0062] 402. Spatially align the amplitude abrupt change point with the magnetic field intensity distribution data in the electromagnetic field simulation results to generate the axial magnetic field intensity correction parameter of the winding layer; In step 402, spatial alignment refers to matching the axial position corresponding to the abrupt change point of the current harmonic amplitude with the magnetic field intensity distribution coordinates in the electromagnetic field simulation results. The axial magnetic field intensity correction parameter refers to the frequency adjustment coefficient generated based on the proportion of magnetic field intensity exceeding the limit; for example, a coefficient of 1.15 corresponds to a magnetic field intensity exceeding the limit by 15%.

[0063] In this embodiment, firstly, the magnetic field strength distribution data stored in the comprehensive parameter database is retrieved. Secondly, the axial position located in step 401 is matched with the magnetic field strength peak region to calculate the magnetic field strength deviation value. Next, a correction parameter is generated based on the deviation value; if the magnetic field strength at a certain position exceeds the simulated value by 20%, the parameter is set to 1.2; if it is less than 10%, it is set to 0.9. Finally, the correction parameter is associated with the corresponding winding layer segment.

[0064] 403. Based on the nonlinear mapping relationship between the axial magnetic field strength correction parameter and the winding layer current density, the resonant frequency adjustment coefficient table is called from the comprehensive parameter database to generate a resonant frequency adjustment signal that matches the current high-frequency current distribution characteristics. In step 403, the resonant frequency adjustment coefficient table refers to a frequency compensation value lookup table pre-stored in the database. Its key value is the magnetic field strength correction parameter, and its value range is the frequency adjustment amount. The nonlinear mapping relationship means that the frequency adjustment amount is inversely proportional to the square of the current density. For example, if the current density increases by 1 time, the frequency needs to be increased by 1.2 times.

[0065] In this embodiment, firstly, based on the magnetic field strength correction parameters generated in step 402, the resonant frequency adjustment coefficient table is queried from the comprehensive parameter database. Secondly, if the parameter is 1.2, the corresponding frequency needs to be increased from 1.5MHz to 1.68MHz. Next, the frequency adjustment is converted into a PWM duty cycle control signal; for example, 1.68MHz corresponds to a duty cycle of 48%. Finally, the control signal is sent to the LLC resonant controller via optical fiber communication.

[0066] 404. The resonant frequency adjustment signal is dynamically adjusted through a closed-loop feedback mechanism so that the tightness distribution of the winding layer is adapted to the current suppression requirements of the LLC resonant topology segment by segment in the axial direction.

[0067] In step 404, the closed-loop feedback mechanism refers to the iterative process of dynamically correcting the frequency adjustment signal based on real-time harmonic monitoring results. Axial segmental adaptation refers to independently adjusting the frequency parameters in 10-millimeter segments of the winding layer.

[0068] In this embodiment, firstly, after frequency adjustment, the LLC resonant current waveform is acquired in real time, and the harmonic distortion rate is calculated. Secondly, if the distortion rate is still higher than 5%, the frequency is increased in increments of 50kHz until the distortion rate meets the standard. Next, the final frequency value is written back to the comprehensive parameter database to update the frequency adjustment coefficient table for that segment. Finally, the winding speed and frequency parameters are synchronized by a motion controller to ensure that the phase error is less than 0.1 degrees.

[0069] Here is a specific example: During the winding process of a high-frequency reactor, the winding device detected a 25% surge in harmonic amplitude in the LLC resonant current waveform at the 1.8MHz frequency band, triggering the dynamic analysis mechanism as shown in step 401. Data was collected using a wideband current probe at a 2MHz sampling rate, and the 7th harmonic component was extracted using a wavelet packet decomposition algorithm. The amplitude mutation point was identified as being located in the 70-80mm axial section. Based on the switching frequency modulation characteristic curve, the copper foil winding area of ​​the 7th layer of the winding layer corresponding to this frequency point was determined and marked as the high-frequency current concentration area. As shown in step 402, the magnetic field strength distribution map of the 70-80mm section in the electromagnetic field simulation data was retrieved, revealing that the measured magnetic field strength at this location exceeded the design threshold by 18%. An axial magnetic field strength correction parameter of 1.18 was generated using a spatial alignment algorithm, corresponding to the frequency adjustment coefficient increase ratio. As shown in step 403, the comprehensive parameter database was queried based on the correction parameter, the resonant frequency adjustment coefficient table was called, and a 1.75MHz PWM control signal was generated. The signal is transmitted via optical fiber to the LLC resonant controller, which adjusts the switching frequency from 1.6MHz to 1.72MHz to suppress high-frequency harmonic amplitude. As per step 404, the closed-loop feedback mechanism is activated, and the adjusted current waveform is monitored in real time. It is found that the 7th harmonic distortion rate is still higher than the threshold. The frequency is gradually increased to 1.78MHz in 50kHz steps to bring the harmonic distortion rate to the target. The frequency adjustment parameters for the 7th winding section in the database are updated synchronously, and the winding speed is adjusted from 45r / min to 38r / min via the motion controller to ensure a phase error of less than 0.05 degrees. Ultimately, the peak current density in this section decreases from 9.8A / mm² to 7.2A / mm², and the winding temperature rise decreases by 21℃.

[0070] In summary, steps 401 to 404 constructed a closed-loop optimization system for the multi-field coupling of electromagnetic, thermal, and mechanical fields during the high-frequency winding process. The spatial distribution of high-frequency harmonics was located by correlating wavelet transform with frequency modulation characteristics. Axial magnetic field correction parameters were generated using electromagnetic field simulation data. The resonant frequency was dynamically adjusted based on a nonlinear mapping model to suppress current concentration effects. Finally, closed-loop feedback was used to achieve segment-by-segment adaptation of winding tightness and frequency parameters. This scheme significantly improves the uniformity of axial current distribution in the winding layer, suppresses local temperature rise and harmonic losses, and provides core technical support for the reliability design and intelligent manufacturing of high-frequency, high-power reactors through real-time data iterative optimization of the process parameter library.

[0071] In some embodiments, step 101 involves establishing a comprehensive parameter database based on the current density distribution data of a high-frequency switching power supply, and using a multi-axis winding device with self-calibration function to collect axial temperature change data of the winding layer in real time during the winding process, including: 501. Decompose the current density distribution data of the high-frequency switching power supply into a superposition of high-frequency components and basic components according to the axial position of the winding layer. Generate the current density variation curve of the winding layer axial direction based on the distribution ratio of the high-frequency components in the superposition combination, and store the current density variation curve to form a comprehensive parameter database. In step 501, the high-frequency component refers to the harmonic components with frequencies greater than 1 MHz in the current density distribution, and the fundamental component refers to the fundamental current density. Superposition and combination refers to decomposing the current density into a linear superposition of the fundamental and harmonic components using a Fourier series. The current density variation curve refers to the current density amplitude curve distributed along the axial direction of the winding layer.

[0072] In this embodiment, firstly, a Fourier transform is performed on the current density data of the high-frequency switching power supply to separate the fundamental frequency and the 3rd to 15th harmonic components. Secondly, the amplitude distribution of each harmonic is resynthesized according to the axial position of the winding layer to generate a current density variation curve. Next, the curve data is stored in a comprehensive parameter database according to the axial coordinate, and the dominant harmonic order at each position is marked. Finally, an index is established to correlate the peak current density with the temperature distribution.

[0073] 502. By using the self-calibration function of the multi-axis winding device, temperature acquisition nodes are deployed at equal intervals along the axial direction of the winding layer, and the data acquisition frequency of the nodes is dynamically adjusted according to the winding speed, so that the distribution density of the temperature acquisition nodes matches the peak range of the current density of the winding layer, thereby obtaining axial temperature change data.

[0074] In step 502, the temperature acquisition node refers to a miniature infrared sensor deployed along the axial direction of the winding layer, with dynamically adjustable spacing. The data acquisition frequency refers to the sensor sampling rate, which is positively correlated with the winding speed. The peak current density range refers to the axial section in the winding layer where the current density exceeds 80% of the design threshold.

[0075] In this embodiment, firstly, temperature sensors are evenly spaced on the axial guide rails of the multi-axis winding device, with an initial spacing of 5 mm. Secondly, the sampling frequency is dynamically adjusted according to the winding speed: when the speed exceeds 40 revolutions per minute, the sampling frequency is increased from 100 Hz to 200 Hz. Next, peak intervals are identified using the current density data from step 501, and the temperature node density in the corresponding regions is doubled. Finally, the collected axial temperature change data is written into the comprehensive parameter database in real time.

[0076] Here is a specific example: During the winding process of a high-frequency transformer, the multi-axis winding device detected abnormal fluctuations in current density in the 7th section of the winding layer, at an axial position of 70-80 mm. As in step 501, the system performed Fourier decomposition on the current waveform of the LLC resonant topology, extracting the fundamental wave and the 3rd-15th harmonic components. It was found that the 9th harmonic accounted for 32% of the amplitude in the 70-80 mm section, significantly higher than other areas. By superimposing the fundamental and harmonic components, an axial current density variation curve was generated, identifying the peak current density in this section as 8.6 A / mm², and the data was correlated to the comprehensive parameter database, marking the dominant harmonic order as 9th. As in step 502, the self-calibration function was activated, deploying miniature infrared temperature sensors along the winding layer at an initial spacing of 5 mm. When the winding speed increased to 45 revolutions per minute, the system increased the node density in the 70-80 mm section to 2.5 mm, dynamically adjusting the sampling frequency from 100 Hz to 220 Hz. Real-time data acquisition showed that the temperature gradient in this section reached 0.9℃ / mm, completely overlapping with the peak current density range in step 501. Temperature data was simultaneously written to the database, establishing a correlation index with harmonic amplitude. After adjustment, the system triggered a winding tension compensation mechanism, reducing the winding speed to 38 revolutions per minute and optimizing the interlayer gap to 0.18 mm. Ultimately, the peak temperature rise in this section decreased from 79℃ to 61℃, and the current density fluctuation amplitude decreased by 42%. Process parameters were uploaded to the MES system in real time to form a full-process traceability record.

[0077] In summary, steps 501 to 502 constructed a closed-loop control system for dynamic optimization of current and thermal coupling during the high-frequency winding process. Multi-band analysis of current density distribution was achieved through Fourier decomposition and harmonic superposition models, and abnormal sections were accurately located using axial harmonic marking and database indexing techniques. The density of temperature acquisition nodes was dynamically increased using a self-calibrating winding device to achieve spatial matching between peak current density and temperature gradient. Through coordinated adjustment of winding speed and interlayer gap, a dual optimization effect of uniform current distribution and improved heat dissipation efficiency was achieved. This scheme significantly suppresses localized temperature rise caused by high-frequency harmonics, improves winding current carrying capacity and reliability, and supports process parameter iteration through full-link data traceability, providing core technical support for the intelligent manufacturing of high-power-density electromagnetic devices.

[0078] In some embodiments, step 202, which involves inputting the axial clearance adjustment command into the interlayer support structure of the winding device, generating a linear compensation coefficient based on the distribution differences of the axial temperature change data, and inputting the linear compensation coefficient into the interlayer support structure of the winding device to drive the axial displacement, includes: 601. Input the axial clearance adjustment command into the interlayer support structure of the winding device, extract the absolute value of the temperature difference between adjacent nodes in the axially equally spaced temperature acquisition nodes of the winding layer of the interlayer support structure, and if the absolute value exceeds a preset threshold, mark the area where the adjacent nodes are located as a temperature difference zone. In step 601, the axial clearance adjustment command refers to the digital control signal that controls the expansion and contraction of the interlayer support structure, with an accuracy of 0.01 mm. Temperature acquisition nodes refer to miniature infrared sensors deployed at equal intervals along the axial direction of the winding layer, with a dynamic spacing adjustment range of 2-10 mm. The temperature difference zone refers to the axial section where the absolute value of the temperature difference between adjacent nodes exceeds a preset threshold.

[0079] In this embodiment, firstly, the system inputs the axial clearance adjustment command to the interlayer support structure servo controller of the winding device, activating the temperature acquisition module, with the initial node spacing set to 5 mm. Secondly, when the winding speed exceeds 40 revolutions per minute, the temperature acquisition node spacing is automatically increased to 2 mm to improve data acquisition density. Next, the absolute value of the temperature difference between adjacent nodes is calculated in real time. For example, if a temperature difference of 6°C is detected in the axial 70-75 mm section, a threshold judgment is triggered. Finally, this section is marked as a temperature difference zone, and the compensation process is initiated.

[0080] 602. Accumulate the absolute values ​​of the temperature differences in the temperature difference region and multiply them by a weighting factor dynamically adjusted based on the thermal conductivity of the winding layer material to obtain the linear compensation coefficient for that region. In step 602, the weighting factor refers to the coefficient dynamically calculated based on the thermal conductivity of the winding layer material, and the linear compensation coefficient refers to the result of multiplying the cumulative absolute value of the temperature difference in the temperature difference zone by the weighting factor.

[0081] In this embodiment, firstly, the measured thermal conductivity data of the winding layer material is retrieved; for example, the thermal conductivity of copper foil is 401 W / m·K. Secondly, the dynamic adjustment coefficient is calculated using the weighting factor formula, and after substituting the parameters, a weighting factor of 1.18 is obtained. Next, the absolute values ​​of the temperature differences between all adjacent nodes within the temperature difference zone are accumulated; for example, the total temperature difference is measured to be 24℃. Finally, the accumulated value is multiplied by the weighting factor to generate a linear compensation coefficient of 28.32 mm / ℃, which serves as the benchmark parameter for gap adjustment.

[0082] 603. Input the linear compensation coefficient into the interlayer support structure of the winding device, and multiply the linear compensation coefficient by the preset displacement scaling factor through the displacement converter built into the support structure to generate the axial displacement of the temperature difference zone. In step 603, the displacement converter refers to a piezoelectric drive module that converts electrical signals into mechanical displacement, with a resolution of 0.001 mm. The displacement scaling factor refers to a preset mechanical displacement conversion coefficient, typically 0.15 mm / unit compensation coefficient.

[0083] In this embodiment, firstly, the linear compensation coefficient is input into the displacement converter module of the winding device, which has a built-in piezoelectric drive mechanism. Secondly, the axial displacement is calculated based on a preset displacement scaling factor of 0.15 mm / unit compensation coefficient, for example, 28.32 × 0.15 = 4.25 mm. Next, combined with the gradient direction of the temperature difference zone, a vector control command containing the displacement direction is generated. Finally, the command is encoded into an EtherCAT protocol data frame and sent to the interlayer support structure actuator.

[0084] 604. The interlayer support structure is driven to expand and contract in the winding layer according to the axial displacement, so that the gap width of the temperature difference zone expands in a proportional manner with the linear compensation coefficient, and the gap expansion of adjacent areas transitions according to the gradient of the displacement difference of the temperature difference zone.

[0085] In step 604, gradient transition refers to the distribution rule in which the gap expansion between adjacent sections gradually decreases according to the displacement difference of the temperature difference zone. For example, when the displacement of the difference zone is 4.25 mm, the adjacent section decreases by 0.85 mm for every 5 mm.

[0086] In this embodiment, firstly, the pneumatic support structure is driven to perform axial displacement in the temperature difference zone, for example, expanding the gap in the 70-75 mm section from 0.15 mm to 0.25 mm. Secondly, according to the gradient transition rule, the displacement is proportionally distributed in adjacent sections, for example, adjusting the 65-70 mm section to 0.20 mm. Next, the gap width is monitored in real time by a laser displacement sensor; if a deviation exceeding 0.003 mm is detected, a secondary compensation cycle is triggered. Finally, the adjusted gap distribution data is synchronized to the comprehensive parameter database to complete closed-loop control.

[0087] Here is a specific example: During the winding process of a high-frequency transformer, the multi-axis winding device detected abnormal fluctuations in the current density of the 7th section of the winding layer, with an axial position of 70-80 mm, accompanied by a local temperature rise of 85℃. As in step 601, the system deployed miniature infrared temperature sensors with an initial spacing of 5 mm. When the winding speed increased to 45 revolutions per minute, the spacing was dynamically increased to 2 mm. Real-time calculation of the temperature difference between adjacent nodes revealed that the absolute value of the temperature difference in the 70-75 mm section reached 7.2℃, triggering a preset threshold of 3℃, and marking it as a temperature difference zone. As in step 602, the thermal conductivity of the copper foil material was retrieved (401 W / m·K), and a dynamic coefficient of 1.15 was calculated using the weighting factor formula. The absolute value of the temperature difference between adjacent nodes in this section was accumulated to 28.8℃, generating a linear compensation coefficient of 33.12 mm / ℃. As in step 603, the compensation coefficient was input into the piezoelectric drive displacement converter, combined with a preset displacement scaling factor of 0.15, generating an axial displacement of 4.97 mm, which was encoded as an EtherCAT command and sent to the interlayer support structure. As in step 604, the pneumatic support structure is driven to perform displacement, expanding the gap in the 70-75 mm section from 0.15 mm to 0.22 mm, while the adjacent 65-70 mm section is adjusted to 0.18 mm according to a gradient transition rule. The laser displacement sensor monitors the gap width deviation in real time, ensuring it is less than 0.003 mm, and the corrected data is synchronized to the comprehensive parameter database. After adjustment, the peak temperature rise in this section decreases from 85℃ to 63℃, and the current density fluctuation is reduced by 42%. The process parameters are uploaded to the MES system to form a full-process traceability record.

[0088] In summary, steps 601 to 604 construct a closed-loop control system for dynamic compensation of thermal and mechanical coupling in high-frequency winding manufacturing. High-density temperature sensing and a temperature difference threshold triggering mechanism accurately locate areas of concentrated thermal stress. A high-precision compensation amount is generated by combining dynamic weighting of material thermal conductivity and a nonlinear displacement transformation model, achieving spatial reverse matching between gap expansion and temperature gradient. Gradient transition rules prevent abrupt changes in mechanical stress, and laser displacement feedback correction ensures adjustment accuracy. This scheme significantly improves the efficiency of local temperature rise suppression, enhances the uniformity of winding current density, and supports iterative optimization of process parameters through full-link data traceability. It provides core technical support for the reliable manufacturing of high-power-density electromagnetic devices, significantly improving equipment lifespan and operational stability.

[0089] In some embodiments, step 302, which involves calculating the initial compensation amount for the axial gap of the winding layer based on the overall slope of the temperature change curve, and generating interlayer gap compensation parameters by combining the nonlinear proportional relationship between the winding layer thickness and the gap width, includes: 701. Perform piecewise linear fitting on the axial temperature change curve of the winding layer, select the continuous fitting segment with the largest absolute value of the temperature difference between the first and last ends of the axial winding layer, and calculate the absolute value of its slope as the overall slope. In step 701, the overall slope refers to the slope of the fitted straight line of the segment with the largest temperature difference in the temperature change curve, calculated using the least squares method. The gap compensation ratio factor refers to the preset conversion coefficient between the slope and the compensation amount, with a typical value of 0.2 mm / (°C·mm⁻¹).

[0090] In this embodiment, firstly, the axial temperature change curve of the winding layer is piecewise linearly fitted to divide it into multiple continuous segments. Secondly, the absolute value of the slope of each segment is calculated, and the maximum value is selected as the overall slope; for example, the slope of the 70-80 mm segment is 0.8 °C / mm. Next, the gap compensation scaling factor of 0.2 mm / ( °C·mm⁻¹) is applied to calculate the initial compensation amount of 0.16 mm. Finally, the overall slope is correlated with the compensation amount as the input parameter for subsequent nonlinear correction.

[0091] 702. Multiply the overall slope by the preset gap compensation ratio factor to obtain the initial compensation amount of the axial gap of the winding layer; In step 702, the initial compensation amount refers to the compensation value initially determined based on theoretical calculations or preset parameters.

[0092] In this embodiment, firstly, the actual thickness of the current winding layer is measured, for example, the copper foil thickness is measured to be 0.3 mm. Secondly, the compensation increment is calculated according to the measured proportional relationship formula, for example, 0.05 × (0.3)² = 0.0045 mm. Next, the increment is added to the initial compensation amount to obtain the corrected interlayer gap compensation parameter of 0.1645 mm. Finally, the parameter is normalized to an accuracy of 0.01 mm to generate the final compensation amount of 0.16 mm.

[0093] 703. Based on the measured ratio between the winding layer thickness and the gap width, the compensation increment of the square value of the winding layer thickness is superimposed on the initial compensation amount to generate the corrected interlayer gap compensation parameters.

[0094] In step 703, the measured proportional relationship refers to the nonlinear relationship between the winding layer thickness and the gap width fitted by experimental data. The corrected interlayer gap compensation parameter refers to the gap adjustment amount corrected by the square increment of the thickness, with an accuracy of 0.01 mm.

[0095] In this embodiment, firstly, the corrected compensation parameters are written into the interlayer support structure control command, for example, a gap adjustment of 0.16 mm. Secondly, the support structure is driven to perform displacement actions, achieving micron-level precision positioning through a piezoelectric module. Next, a laser interferometer is used to measure the actual gap width in real time, verifying whether the deviation is less than 0.002 mm, and generating the corrected interlayer gap compensation parameters. Finally, the generated corrected interlayer gap compensation parameters are sent back to the main control system to update the process standard values ​​in the comprehensive parameter database.

[0096] Here is a specific example: During the winding process of a high-frequency reactor, the system detected an abnormal temperature rise in the axial 80-90 mm section of the 5th winding layer, with a peak temperature of 92℃. Step 701 initiates piecewise linear fitting analysis, deploying miniature infrared sensors at 2 mm intervals to collect temperature data. The temperature curve is segmented using the least squares method, identifying the 85-90 mm section as having the largest absolute value of temperature difference slope at 1.2℃ / mm, triggering the gap compensation process. A preset gap compensation ratio factor of 0.2 mm / (℃·mm⁻¹) is called, calculating an initial compensation amount of 0.24 mm. As per step 702, based on the measured ratio formula, the current winding layer thickness is measured at 0.35 mm, and the compensation increment is calculated as 0.05 × (0.35)² = 0.0061 mm. This is superimposed on the initial compensation amount to generate a correction parameter of 0.2461 mm, which is then normalized to 0.25 mm. Step 703 writes the correction parameter into the interlayer support structure control command, driving the piezoelectric module to perform a 0.25 mm gap expansion. The laser interferometer monitors the actual gap width in real time, with the deviation controlled within 0.001 mm. After verification, the data is synchronized to the MES system. After adjustment, the peak temperature rise in this section drops to 65℃, the current density fluctuation decreases by about 40%, and the process parameters are updated to the database to form a full-chain traceability record.

[0097] In summary, steps 701 to 703 construct a closed-loop control system for dynamic compensation of thermal and mechanical coupling in the winding layer. Piecewise linear fitting and maximum slope identification algorithms accurately locate areas of concentrated thermal stress, while a gap compensation scaling factor achieves a linear mapping between temperature gradient and gap adjustment. A thickness square increment correction model based on measured scaling relationships effectively balances axial heat dissipation requirements and structural strength constraints. High-precision displacement control via laser feedback and piezoelectric drive ensures micron-level positioning accuracy for gap expansion. This scheme significantly improves local temperature rise suppression efficiency, enhances the uniformity of winding current distribution, and supports intelligent process iteration through full-link traceability of process parameters. It provides core technical support for the reliable manufacturing of high-power-density electromagnetic devices, significantly improving equipment operational stability and lifespan.

[0098] Figure 2 This application provides a schematic diagram of the structure of a high-frequency transformer winding optimization system, as shown in the embodiment. Figure 2 As shown, the system includes: The acquisition module 21 is used to establish a comprehensive parameter database based on the current density distribution data of the high-frequency switching power supply, and to acquire the axial temperature change data of the winding layer in real time during the winding process through a multi-axis winding device with self-calibration function. The generation module 22 is used to convert the axial temperature change data into winding tension compensation parameters and interlayer gap compensation parameters. The winding tension compensation parameters generate mechanical action commands through the temperature gradient feedback system to drive the winding device to perform real-time adjustments. The interlayer gap compensation parameters are used to generate axial gap adjustment commands between winding layers. Matching module 23 is used to combine the current waveform distortion data of LLC resonant topology with the electromagnetic field simulation results in the comprehensive parameter database to generate a resonant frequency adjustment signal to match the high-frequency current distribution suppression requirements of the winding. The heat dissipation module 24 is used to synchronize the mechanical action command, the axial gap adjustment command and the resonant frequency adjustment signal to make the tightness distribution of the winding layer and the high-frequency current distribution characteristics match in real time during the winding process, and to control the gap distribution between the winding layers through the axial gap adjustment command to match the heat dissipation requirements, thereby reducing the peak temperature rise of the winding and improving the heat dissipation efficiency between the winding layers.

[0099] Figure 2 The aforementioned high-frequency transformer winding optimization winding system can perform... Figure 1 The implementation principle and technical effects of the high-frequency transformer winding optimization method described in the illustrated embodiment will not be repeated here. The specific operation methods of each module and unit in the high-frequency transformer winding optimization system in the above embodiments have been described in detail in the embodiments related to this method, and will not be elaborated upon here.

[0100] In one possible design, Figure 2 The high-frequency transformer winding optimization system of the illustrated embodiment can be implemented as a computing device, such as... Figure 3 As shown, the computing device may include a storage component 31 and a processing component 32; The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are invoked and executed by the processing component 32.

[0101] The processing component 32 is used for the above Figure 1 The embodiment describes an optimized winding method for high-frequency transformer windings.

[0102] The processing component 32 may include one or more processors to execute computer instructions to complete all or part of the steps in the above-described method. Alternatively, the processing component may be implemented as one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above-described method.

[0103] Storage component 31 is configured to store various types of data to support operations at the terminal. The storage component can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0104] Of course, computing devices may also include other components, such as input / output interfaces, display components, communication components, etc.

[0105] Input / output interfaces provide interfaces between processing components and peripheral interface modules, which can be output devices, input devices, etc.

[0106] The communication components are configured to facilitate wired or wireless communication between computing devices and other devices.

[0107] The computing device can be a physical device or an elastic computing host provided by a cloud computing platform. In this case, the computing device can refer to a cloud server, and the aforementioned processing components, storage components, etc., can be basic server resources rented or purchased from the cloud computing platform.

[0108] This application also provides a computer storage medium storing a computer program, which, when executed by a computer, can perform the above-described functions. Figure 1 The embodiment shown illustrates an optimized winding method for high-frequency transformer windings.

[0109] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0110] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0111] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0112] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for optimizing the winding of a high-frequency transformer, characterized in that, include: A comprehensive parameter database is established based on the current density distribution data of high-frequency switching power supplies. The axial temperature change data of the winding layer during the winding process is collected in real time through a multi-axis winding device with self-calibration function. The axial temperature change data is converted into winding tension compensation parameters and interlayer gap compensation parameters. The winding tension compensation parameters generate mechanical action commands through a temperature gradient feedback system to drive the winding device to perform real-time adjustments. The interlayer gap compensation parameters are used to generate axial gap adjustment commands between winding layers. By combining the current waveform distortion data of the LLC resonant topology with the electromagnetic field simulation results in the comprehensive parameter database, a resonant frequency adjustment signal is generated to match the high-frequency current distribution suppression requirements of the winding. By synchronously executing the mechanical action command, the axial gap adjustment command, and the resonant frequency adjustment signal, the tightness distribution of the winding layers and the high-frequency current distribution characteristics are matched in real time during the winding process. The axial gap adjustment command controls the gap distribution between the winding layers to match the heat dissipation requirements, thereby reducing the peak temperature rise of the winding and improving the heat dissipation efficiency between the winding layers.

2. The method according to claim 1, characterized in that, By synchronously executing the mechanical action command, the axial gap adjustment command, and the resonant frequency adjustment signal, the tightness distribution of the winding layers during winding is matched in real time with the high-frequency current distribution characteristics. Furthermore, the axial gap adjustment command controls the gap distribution between the winding layers to match heat dissipation requirements, thereby reducing the peak temperature rise of the winding and improving the heat dissipation efficiency between the winding layers. This includes: The mechanical action command is associated with the axial movement distance of the winding device, and the winding speed is dynamically adjusted based on the gradient change direction of the axial temperature change data, so that the winding tightness distribution is locally matched with the current high-frequency current distribution characteristics. An axial clearance adjustment command is input to the interlayer support structure of the winding device. A linear compensation coefficient is generated based on the distribution difference of the axial temperature change data. The linear compensation coefficient is then input to the interlayer support structure of the winding device to drive the axial displacement. The resonant frequency adjustment signal is mapped to the axial position of the winding layer. Based on the high-frequency harmonic components in the current waveform distortion data and the magnetic field intensity distribution characteristics in the electromagnetic field simulation results, a frequency correction value for a specific region of the winding layer is generated to suppress high-frequency current concentration. By synchronously linking the winding speed adjustment of the mechanical action command, the interlayer displacement control of the axial gap adjustment command, and the frequency correction value of the resonant frequency adjustment signal, the winding tightness distribution, interlayer gap distribution, and high-frequency current distribution characteristics are dynamically adapted segment by segment along the winding layer axis, thereby reducing the peak temperature rise of the winding and improving the heat dissipation efficiency between the winding layers.

3. The method according to claim 1, characterized in that, The axial temperature change data is converted into winding tension compensation parameters and interlayer gap compensation parameters. The winding tension compensation parameters generate mechanical action commands through a temperature gradient feedback system to drive the winding device to perform real-time adjustments. The interlayer gap compensation parameters are used to generate axial gap adjustment commands between winding layers, including: Based on the axial temperature change data collected in real time by the multi-axis winding device, temperature change curves are generated at equal intervals according to the axial position of the winding layer. The temperature difference between adjacent intervals in the temperature change curve is converted into winding tension compensation parameters. The winding tension compensation parameters are associated with the winding speed threshold interval through the temperature gradient feedback system to generate mechanical action commands to drive the winding device to perform real-time adjustments. Based on the overall slope of the temperature change curve, the initial compensation amount of the axial gap of the winding layer is calculated, and the interlayer gap compensation parameters are generated by combining the nonlinear proportional relationship between the winding layer thickness and the gap width. Based on the initial compensation amount, an interlayer gap adjustment command is generated by combining the ratio of the winding layer thickness to the gap width. The gap distribution is controlled by the interlayer support structure of the winding device, so that the gap width and the gradient direction of the axial temperature change data form an inverse matching relationship.

4. The method according to claim 1, characterized in that, Combining the current waveform distortion data of the LLC resonant topology with the electromagnetic field simulation results in the comprehensive parameter database, a resonant frequency adjustment signal is generated to match the high-frequency current distribution suppression requirements of the winding, including: The amplitude abrupt change points of high-frequency harmonic components are extracted from the current waveform distortion data, and the axial position of the winding layer corresponding to the amplitude abrupt change points is determined based on the switching frequency modulation characteristics of the LLC resonant topology. The amplitude abrupt change point is spatially aligned with the magnetic field intensity distribution data in the electromagnetic field simulation results to generate the axial magnetic field intensity correction parameter of the winding layer. Based on the nonlinear mapping relationship between the axial magnetic field strength correction parameter and the winding layer current density, the resonant frequency adjustment coefficient table is called from the comprehensive parameter database to generate a resonant frequency adjustment signal that matches the current high-frequency current distribution characteristics. The resonant frequency adjustment signal is dynamically adjusted through a closed-loop feedback mechanism, so that the tightness distribution of the winding layer is adapted to the current suppression requirements of the LLC resonant topology segment by segment in the axial direction.

5. The method according to claim 1, characterized in that, A comprehensive parameter database is established based on the current density distribution data of high-frequency switching power supplies. A multi-axis winding device with self-calibration function is used to collect real-time data on the axial temperature changes of the winding layers during the winding process, including: The current density distribution data of the high-frequency switching power supply is decomposed into a superposition of high-frequency components and basic components according to the axial position of the winding layer. Based on the distribution ratio of the high-frequency components in the superposition, the current density variation curve of the winding layer is generated, and the current density variation curve is stored to form a comprehensive parameter database. By utilizing the self-calibration function of the multi-axis winding device, temperature acquisition nodes are deployed at equal intervals along the winding layer. The data acquisition frequency of these nodes is dynamically adjusted according to the winding speed, so that the distribution density of the temperature acquisition nodes matches the peak range of the current density in the winding layer, thereby obtaining axial temperature change data.

6. The method according to claim 2, characterized in that, The axial clearance adjustment command is input to the interlayer support structure of the winding device. A linear compensation coefficient is generated based on the distribution difference of the axial temperature change data. The linear compensation coefficient is then input to the interlayer support structure of the winding device to drive the axial displacement, including: The axial clearance adjustment command is input to the interlayer support structure of the winding device. The absolute value of the temperature difference between adjacent nodes in the axially equally spaced temperature acquisition nodes of the winding layer of the interlayer support structure is extracted. If the absolute value exceeds a preset threshold, the area where the adjacent nodes are located is marked as a temperature difference zone. The absolute values ​​of the temperature differences in the temperature difference region are accumulated and multiplied by a weighting factor dynamically adjusted based on the thermal conductivity of the winding layer material to obtain the linear compensation coefficient for that region. The linear compensation coefficient is input into the interlayer support structure of the winding device. The linear compensation coefficient is multiplied by the preset displacement scaling factor through the displacement converter built into the support structure to generate the axial displacement of the temperature difference zone. The axial displacement drives the interlayer support structure to expand and contract in the winding layer axially, so that the gap width of the temperature difference zone expands proportionally to the linear compensation coefficient, and the gap expansion of adjacent areas transitions according to the gradient of the displacement difference of the temperature difference zone.

7. The method according to claim 3, characterized in that, Based on the overall slope of the temperature change curve, the initial compensation amount for the axial gap of the winding layer is calculated. Then, combining the nonlinear proportional relationship between the winding layer thickness and the gap width, interlayer gap compensation parameters are generated, including: The axial temperature change curve of the winding layer is piecewise linearly fitted, and the continuous fitted segment with the largest absolute value of the temperature difference between the first and last ends of the axial winding layer is selected. The absolute value of its slope is calculated as the overall slope. Multiply the overall slope by the preset gap compensation ratio factor to obtain the initial compensation amount for the axial gap of the winding layer. Based on the measured ratio between the winding layer thickness and the gap width, the compensation increment of the square value of the winding layer thickness is superimposed on the initial compensation amount to generate the corrected interlayer gap compensation parameters.

8. A high-frequency transformer winding optimization system, characterized in that, include: The acquisition module is used to establish a comprehensive parameter database based on the current density distribution data of the high-frequency switching power supply, and to acquire the axial temperature change data of the winding layer in real time during the winding process through a multi-axis winding device with self-calibration function. The generation module is used to convert the axial temperature change data into winding tension compensation parameters and interlayer gap compensation parameters. The winding tension compensation parameters generate mechanical action commands through the temperature gradient feedback system to drive the winding device to perform real-time adjustments. The interlayer gap compensation parameters are used to generate axial gap adjustment commands between winding layers. The matching module is used to combine the current waveform distortion data of the LLC resonant topology with the electromagnetic field simulation results in the comprehensive parameter database to generate a resonant frequency adjustment signal to match the high-frequency current distribution suppression requirements of the winding. The heat dissipation module is used to synchronize the mechanical action command, the axial gap adjustment command and the resonant frequency adjustment signal to make the tightness distribution of the winding layer and the high-frequency current distribution characteristics match in real time during the winding process. The axial gap adjustment command controls the gap distribution between the winding layers to match the heat dissipation requirements, thereby reducing the peak temperature rise of the winding and improving the heat dissipation efficiency between the winding layers.

9. A computing device, characterized in that, It includes a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are invoked and executed by the processing component to implement the high-frequency transformer winding optimization method as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that, The device contains a computer program that, when executed by a computer, implements the high-frequency transformer winding optimization method as described in any one of claims 1 to 7.

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