Wind turbine generator converter efficient heat dissipation device based on heat pipe technology and control method

Abstract

The invention provides a wind turbine generator converter efficient heat dissipation device based on a heat pipe technology and a control method. The wind turbine generator converter efficient heat dissipation device comprises a heat pipe array module, a phase change energy storage module, a bionic fin set, a self-cleaning system and an intelligent temperature control module. Acquiring IGBT surface temperature field distribution in real time; establishing a heat pipe-phase change material composite heat transfer efficiency evaluation model, and calculating comprehensive heat dissipation efficiency; an asymmetric fuzzy control algorithm is established, and a heat dissipation mode switching threshold value is calculated based on temperature field distribution and comprehensive heat dissipation efficiency; triggering a self-cleaning pulse sequence according to the dynamic pressure field distribution; operating parameters of the liquid cooling system are adjusted in real time through a multi-objective optimization algorithm; the invention aims to solve the problems of low efficiency, difficulty in considering the service life of a device and the heat dissipation requirement and poor environmental adaptability in the existing heat dissipation technology. Through a unique device structure and a control method, heat dissipation efficiency is improved, energy consumption and heat dissipation performance are balanced, the service life of devices is prolonged, environmental adaptability is enhanced, and stable and reliable operation of the converter is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of wind power generation equipment management, and in particular to a high-efficiency heat dissipation device and a control method for a wind turbine converter based on heat pipe technology. Background Art

[0002] In wind power generation systems, wind power converters are one of the core components. Their performance directly affects the grid-connected performance, power generation quality, and reliability of the entire wind turbine. In recent years, with the rapid growth of global demand for clean energy, the wind power industry has developed rapidly, and the market size of wind power converters has also continued to expand. According to relevant market reports, the scale of China's wind power converter market reached 36 billion yuan in 2020, a year-on-year increase of 17.8%, and it is expected to continue to expand in the future. Heat dissipation is crucial in the actual operation of wind power converters. Wind turbines typically operate in harsh environments, such as the low temperatures and large temperature differences in Northeast and North China, the windy and sandy conditions in the Northwest, and the high humidity along the coast. They also require long periods of continuous full-load operation, even for months at a time during windy seasons. This puts wind power converters under severe pressure. Furthermore, the long-term, frequent, and wide-ranging random output fluctuations of wind turbines subject their energy conversion units to continuous and severe thermal stress. IGBT (insulated-gate bipolar transistor) modules are the most susceptible to failure, and cumulative fatigue damage caused by thermal stress cycles during operation is a major cause of failure. Within the normal operating range, the device failure rate doubles for every 10°C increase in the average IGBT module temperature. Excessive temperature rise can also lead to permanent device failure. Currently, common heat dissipation technologies include forced air cooling and water cooling. While forced air cooling offers advantages such as low cost and a simple and compact structure, making it popular in industrial applications, its forced convection heat transfer coefficient is low. To reduce thermal resistance, the heat sink often needs to be designed to be large to achieve a larger heat transfer area. This makes it difficult to effectively reduce the average junction temperature of the IGBT module in environments with limited space and high power density requirements. Water cooling, on the other hand, presents problems such as complex systems, prone to fluid leakage, high costs for additional equipment, complex maintenance, and the addition of multiple detection and control signals. In addition, most existing heat dissipation designs focus solely on sufficient heat dissipation, reducing thermal resistance, or reducing the temperature rise of power devices. They rarely consider the relationship between the service life of power devices in wind power converters and the number of temperature cycles (i.e., the frequency of temperature exceeding the preset normal fluctuation range). The unilateral pursuit of heat dissipation may seriously affect the life of the converter's power devices. At the same time, some heat dissipation methods suffer from low heat dissipation efficiency, making it difficult to meet high-power operating requirements.

[0003] Therefore, there is an urgent need in the art for a high-efficiency heat dissipation device and control method for a wind turbine converter based on heat pipe technology to solve the above problems. Summary of the Invention

[0004] The present invention provides a high-efficiency heat dissipation device and control method for a wind turbine converter based on heat pipe technology, aiming to solve the problems of low efficiency, difficulty in balancing device life and heat dissipation requirements, and poor adaptability in harsh environments in existing heat dissipation technologies. Through a unique device structure and control method, the present invention improves heat dissipation efficiency, balances energy consumption and heat dissipation performance, extends device life, enhances environmental adaptability, and ensures stable and reliable operation of the converter.

[0005] In one aspect, the present invention provides a high-efficiency heat dissipation device for a wind turbine converter based on heat pipe technology, comprising: The heat pipe array module has an evaporation end that fits the heating surface of the converter IGBT module, and a condensation end that uses a variable-section spiral sintered heat pipe. This is used to transfer the heat generated by the IGBT module to the subsequent heat dissipation structure. The phase-change energy storage module is filled with phase-change material between the evaporation end and the IGBT module to form a gradient pore structure. When the IGBT module generates a transient thermal shock, the phase-change material's phase-change characteristics are utilized to absorb and store heat, thereby buffering against drastic temperature changes and preventing the IGBT module from experiencing a significant temperature increase within a short period of time. Furthermore, the phase-change energy storage module is in close contact with the evaporation end of the heat pipe array module to ensure that heat can be quickly transferred to the heat pipes. The bionic fin assembly comprises shark skin textured fin units arranged in a multi-stage staggered arrangement, coupled to the condensing end via a shape memory alloy bracket, and having a V-groove array on the fin surface; the fin assembly is used to receive heat transferred from the condensing end of the heat pipe array module and dissipate the heat to the environment through heat exchange with the air; The self-cleaning system consists of a hydrophobic nano-coating, a piezoelectrically driven pulse nozzle array, and a differential pressure feedback unit, covering the surface of the bionic fin. The differential pressure feedback unit monitors the pressure difference before and after the bionic fin in real time. When the pressure difference reaches a set threshold, the piezoelectrically driven pulse nozzle array is triggered to eject pulsed airflow, which, combined with the hydrophobic nano-coating, removes impurities from the fin surface. The intelligent temperature control module includes a distributed fiber optic temperature sensor array, a microchannel liquid cooling manifold and an adaptive PID controller, which realizes heat dissipation mode switching through thermal-electrical-mechanical multi-field coupling; the distributed fiber optic temperature sensor array is arranged at key positions of the IGBT module and the heat pipe array module, collects temperature data in real time and transmits it to the adaptive PID controller; the adaptive PID controller controls the coolant flow and flow direction parameters of the microchannel liquid cooling manifold based on a preset temperature threshold and real-time temperature data through thermal-electrical-mechanical multi-field coupling analysis, realizing switching between different modes such as passive heat dissipation and active liquid cooling, ensuring that the IGBT module operates within a reasonable temperature range.

[0006] According to the present invention, a high-efficiency heat dissipation device for a wind turbine converter based on heat pipe technology is provided. The variable-section spiral sintered heat pipe of the heat pipe array module comprises: The evaporation section is a spiral tube structure with a gradually decreasing radius, and the spiral rise angle θ satisfies 5°≤θ≤10°; The condensing section is provided with periodically raised annular fins, and the fin spacing δ and the heat pipe diameter D satisfy δ=0.3D±0.05D.

[0007] According to the present invention, a high-efficiency heat dissipation device for a wind turbine converter based on heat pipe technology is provided, wherein the phase change energy storage module comprises: The matrix material is expanded graphite / paraffin composite material with a phase transition temperature of 65℃±2℃; The pore structure is distributed in a gradient along the direction of heat flow, and the porosity satisfy:

[0008] in is the vertical distance from the evaporation end of the heat pipe, is the total thickness of the phase change layer.

[0009] According to the invention, a high-efficiency heat dissipation device for a wind turbine converter based on heat pipe technology is provided. The surface of the fin of the bionic fin group is laser-engraved with a V-shaped groove array, the groove depth is 0.2mm±0.05mm, the adjacent groove spacing p and the groove depth h satisfy p=3h±0.2h, and the fin inclination angle is As the radial position changes, it satisfies ,in is the radial coordinate of the fin, representing the distance from the fin to the center point of the condensing end, is the total fin length.

[0010] According to the present invention, a high-efficiency heat dissipation device for a wind turbine converter based on heat pipe technology is provided. The contact angle of the hydrophobic nano-coating of the self-cleaning system is greater than 150°, and the injection pressure of the piezoelectrically driven pulse nozzle array is 0.5-1MPa, and is evenly distributed along the width direction of the bionic fin group.

[0011] According to a high-efficiency heat dissipation device for a wind turbine converter based on heat pipe technology provided by the present invention, the gain parameter of the adaptive PID controller of the intelligent temperature control module satisfies:

[0012] in, is the proportional gain parameter of the adaptive PID controller, which is dynamically adjusted as the real-time temperature difference changes and is used to adjust the response speed and stability of the control system; is the initial value of the proportional gain, It is a preset constant, representing the proportional adjustment capability of the controller in the initial state; is the real-time temperature difference, that is, the difference between the actual system temperature and the set temperature at the current moment; It is a parameter related to the time constant, which is used to control the rate at which the proportional gain changes with the temperature difference. Its value determines the sensitivity of the proportional gain to the temperature difference change.

[0013] in, It is the integral time parameter of the adaptive PID controller, which affects the strength of the controller's integral action on the system error, thereby affecting the system's ability to eliminate steady-state errors; is the initial value of the integral time, which is a pre-set constant and represents the integral time length of the controller in the initial state; is the running time, which means the time from system startup to the current moment; is a period parameter used to determine the period of the sine function so that the integral time parameter can change according to a certain periodic law over time.

[0014] In another aspect, the present invention provides a control method for a high-efficiency heat dissipation device for a wind turbine converter based on heat pipe technology, comprising the following steps: Step 1: Obtain the IGBT surface temperature field distribution in real time through a distributed optical fiber temperature sensor array; Step 2: Establish a heat pipe-phase change material composite heat transfer efficiency evaluation model to calculate the comprehensive heat dissipation efficiency; Step 3: Establish an asymmetric fuzzy control algorithm to calculate the heat dissipation mode switching threshold based on the temperature field distribution and comprehensive heat dissipation efficiency; Step 4: triggering a self-cleaning pulse sequence according to the dynamic pressure field distribution; Step 5: Adjust the operating parameters of the liquid cooling system in real time through a multi-objective optimization algorithm.

[0015] According to a control method for a high-efficiency heat dissipation device of a wind turbine converter based on heat pipe technology provided by the present invention, in step 2, the heat transfer efficiency evaluation model includes a heat pipe equivalent thermal conductivity calculation model and a comprehensive heat dissipation efficiency evaluation model; The equivalent thermal conductivity calculation model is:

[0016] in, is the equivalent thermal conductivity, Heat flow for phase change materials, is the effective length of the heat pipe, is the cross-sectional area of the heat pipe, is the temperature difference between the two ends of the heat pipe, and is the corresponding material constant, is the pressure gradient of the working fluid in the heat pipe; The comprehensive heat dissipation efficiency evaluation model is:

[0017] in, For comprehensive heat dissipation efficiency, For time, is the density of the phase change material, is the specific heat capacity, is the thickness of the phase change layer, is the pressure difference between the fins, is the maximum allowable pressure difference.

[0018] According to a control method for a high-efficiency heat dissipation device of a wind turbine converter based on heat pipe technology provided by the present invention, in step three, the asymmetric fuzzy control algorithm uses a hyperbolic tangent function to calculate the heat dissipation mode switching threshold. The formula is:

[0019] in, is the temperature deviation, is the actual temperature, To set the temperature; parameter 、 、 The dynamic adjustment formula is:

[0020]

[0021]

[0022] in, is the initial proportional coefficient, is the temperature change rate, is the maximum allowable temperature, is the pressure difference between the fins, For comprehensive heat dissipation efficiency; This formula dynamically adjusts the control output by calculating temperature deviation, temperature change rate, pressure difference between fins and comprehensive heat dissipation efficiency parameters. Compared with traditional fuzzy control, it can more accurately calculate the heat dissipation mode switching threshold based on actual heat dissipation needs, thereby achieving more effective control of the heat dissipation system.

[0023] According to a control method for a high-efficiency heat dissipation device of a wind turbine converter based on heat pipe technology provided by the present invention, in step five, the multi-objective optimization algorithm adopts an improved NSGA-II framework; The objective function is to minimize = total energy consumption, = temperature standard deviation, = noise level; The constraints are: : ≤70℃, : ≤200Pa, : ≥0.8; Optimization variables include: Liquid cooling flow rate , fan speed , pulse cleaning cycle ; Obtain the optimal solution set through Pareto frontier search and make decisions using entropy weight method; determine the optimal liquid cooling flow rate for the current cycle , fan speed ; The multi-objective optimization algorithm uses multiple key indicators as optimization targets, and optimizes multiple operating parameters of the heat dissipation system under the constraint of meeting the heat dissipation performance requirements to achieve a balance between energy consumption, temperature stability and noise level.

[0024] Compared with the prior art, the present invention has the following advantages: 1. The variable-section spiral sintered heat pipe design of the heat pipe array module of this application optimizes the heat transfer path. The special structure of the evaporation section and condensation section enhances the heat transfer process, allowing heat to be transferred from the IGBT module to the bionic fin group more quickly. The multi-level staggered arrangement, shark skin texture, and V-groove array design of the bionic fin group greatly reduce air flow resistance and significantly enhance the heat exchange efficiency with the air.

[0025] 2. The phase change energy storage module of the present application adopts expanded graphite / paraffin composite material with a phase change point temperature of 65℃±2℃. When the IGBT module produces instantaneous thermal shock, it can quickly absorb and store heat. The pore structure is gradiently distributed along the direction of heat flow, which can better adapt to heat flow changes, effectively buffer drastic temperature changes, avoid a sharp increase in the temperature of the IGBT module in a short period of time, reduce the damage to the device caused by thermal stress, and extend its service life.

[0026] 3. The contact angle of the hydrophobic nano-coating of the self-cleaning system of the present application is greater than 150°, and it has super-hydrophobic properties. The spray pressure of the piezoelectrically driven pulse nozzle array is 0.5-1MPa, and is evenly distributed along the width direction of the bionic fin group; the differential pressure feedback unit monitors the pressure difference before and after the bionic fin in real time. When the pressure difference reaches the set threshold, the pulse nozzle is triggered to spray pulse airflow. Combined with the hydrophobic coating, it can effectively remove impurities on the surface of the fin. In harsh environments such as sand and dust, the heat dissipation efficiency can be reduced by less than 5%, which greatly maintains the stability of the heat dissipation performance and enhances the environmental adaptability of the device.

[0027] 4. The temperature control module of the present application collects temperature data of key parts in real time and accurately through a distributed optical fiber temperature sensor array. The adaptive PID controller accurately controls the coolant flow and direction of the microchannel liquid cooling manifold based on the preset temperature threshold and real-time data through thermal-electrical-mechanical multi-field coupling analysis. Under different working conditions, it can intelligently and quickly realize switching from different modes such as passive heat dissipation to active liquid cooling, ensuring that the IGBT module always operates within a reasonable temperature range, thereby improving the reliability and stability of the system.

[0028] 5. In terms of control methods, this application establishes a heat pipe-phase change material composite heat transfer efficiency evaluation model and an asymmetric fuzzy control algorithm, comprehensively considers multiple factors such as temperature deviation, temperature change rate, pressure difference between fins, and comprehensive heat dissipation efficiency, dynamically adjusts the control output, and accurately calculates the heat dissipation mode switching threshold. Compared with traditional control methods, it can control the heat dissipation system more effectively and accurately; adopts an improved NSGA-II framework multi-objective optimization algorithm, with total energy consumption, temperature standard deviation and noise level as optimization targets, and optimizes operating parameters such as liquid cooling flow, fan speed and pulse cleaning cycle under the constraint condition of meeting the heat dissipation performance requirements, achieving a good balance between energy consumption, temperature stability and noise level.

[0029] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0030] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 This is a schematic structural diagram of a high-efficiency heat dissipation device for a wind turbine converter based on heat pipe technology provided by an embodiment of the present invention; Figure 2 The present invention provides a flow chart of a method for controlling a high-efficiency heat dissipation device for a wind turbine converter based on heat pipe technology. DETAILED DESCRIPTION

[0032] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0033] Example 1: The embodiment of the present invention provides a high-efficiency heat dissipation device for wind turbine converter based on heat pipe technology. Figure 1 ,include: The heat pipe array module has an evaporation end that fits the heating surface of the converter IGBT module, and a condensation end that uses a variable-section spiral sintered heat pipe. This is used to transfer the heat generated by the IGBT module to the subsequent heat dissipation structure. The phase-change energy storage module is filled with phase-change material between the evaporation end and the IGBT module to form a gradient pore structure. When the IGBT module generates a transient thermal shock, the phase-change material's phase-change characteristics are utilized to absorb and store heat, thereby buffering against drastic temperature changes and preventing the IGBT module from experiencing a significant temperature increase within a short period of time. Furthermore, the phase-change energy storage module is in close contact with the evaporation end of the heat pipe array module to ensure that heat can be quickly transferred to the heat pipes. The bionic fin assembly comprises shark skin textured fin units arranged in a multi-stage staggered arrangement, coupled to the condensing end via a shape memory alloy bracket, and having a V-groove array on the fin surface; the fin assembly is used to receive heat transferred from the condensing end of the heat pipe array module and dissipate the heat to the environment through heat exchange with the air; The self-cleaning system consists of a hydrophobic nano-coating, a piezoelectrically driven pulse nozzle array, and a differential pressure feedback unit, covering the surface of the bionic fin. The differential pressure feedback unit monitors the pressure difference before and after the bionic fin in real time. When the pressure difference reaches a set threshold, the piezoelectrically driven pulse nozzle array is triggered to eject pulsed airflow, which, combined with the hydrophobic nano-coating, removes impurities from the fin surface. The intelligent temperature control module includes a distributed fiber optic temperature sensor array, a microchannel liquid cooling manifold and an adaptive PID controller, which realizes heat dissipation mode switching through thermal-electrical-mechanical multi-field coupling; the distributed fiber optic temperature sensor array is arranged at key positions of the IGBT module and the heat pipe array module, collects temperature data in real time and transmits it to the adaptive PID controller; the adaptive PID controller controls the coolant flow and flow direction parameters of the microchannel liquid cooling manifold based on a preset temperature threshold and real-time temperature data through thermal-electrical-mechanical multi-field coupling analysis, realizing switching between different modes such as passive heat dissipation and active liquid cooling, ensuring that the IGBT module operates within a reasonable temperature range.

[0034] The principle and beneficial effects of this embodiment are as follows: the evaporation end of the heat pipe array module is tightly fitted to the heating surface of the IGBT module, and the heat generated by the IGBT causes the working fluid in the variable-section spiral sintered heat pipe to quickly vaporize and absorb heat; the unique spiral structure increases the disturbance of the working fluid and strengthens the heat transfer process. Compared with ordinary heat pipes, it can more efficiently transfer heat to the condensation end and then to the bionic fin group; the multi-level staggered arrangement of shark skin texture fin units in the bionic fin group, combined with the surface V-groove array, reduces air flow resistance and greatly enhances the heat exchange efficiency with the air; when the IGBT module generates a transient thermal shock, the phase change material filled in the phase change energy storage module reaches the phase change point and undergoes phase change, absorbing and storing a large amount of heat; its gradient pore structure (porosity changes specifically with the vertical distance from the evaporation end of the heat pipe) can better adapt to heat flow changes, buffer drastic temperature changes, and avoid a sharp increase in the temperature of the IGBT module in a short period of time; the differential pressure feedback unit of the self-cleaning system monitors the pressure difference before and after the bionic fin in real time. When the pressure difference reaches the set threshold, it indicates that the fin is Impurities may have accumulated on the surface, affecting heat dissipation performance. At this time, the piezoelectrically driven pulse nozzle array ejects pulsed airflow, which, combined with the super-hydrophobic properties of the hydrophobic nano-coating, makes it difficult for impurities to adhere to the fin surface, thereby effectively removing impurities from the fin surface. The distributed fiber optic temperature sensor array of the intelligent temperature control module accurately collects temperature data from key parts of the IGBT module and heat pipe array module, and transmits it to the adaptive PID controller. The controller precisely controls the coolant flow and flow direction of the microchannel liquid cooling manifold based on the preset temperature threshold and real-time temperature data through thermal-electrical-mechanical multi-field coupling analysis. Under different operating conditions, it can quickly and intelligently switch between different modes, such as passive heat dissipation and active liquid cooling. For example, when the IGBT module temperature approaches the preset upper limit, the controller automatically increases the coolant flow to enhance heat dissipation. When the temperature drops, the coolant flow can be adjusted in time to avoid overcooling. This ensures that the IGBT module always operates within a reasonable temperature range, improving the reliability and stability of the system while reducing energy consumption.

[0035] In order to further optimize the above embodiment, the variable-section spiral sintered heat pipe of the heat pipe array module includes: The evaporation section is a spiral tube structure with a gradually decreasing radius, and the spiral rise angle θ satisfies 5°≤θ≤10°; The condensing section is provided with periodically raised annular fins, and the fin spacing δ and the heat pipe diameter D satisfy δ=0.3D±0.05D.

[0036] It should be noted that the evaporator section is designed as a spiral tube structure with a tapering radius and a helical rise angle θ of 5° ≤ θ ≤ 10° to enhance fluid flow and heat transfer. This angle range promotes moderate turbulence during the evaporation process, increasing contact with the tube wall and the frequency of heat exchange. As the radius decreases, the fluid flow rate accelerates, enhancing heat transfer and ensuring efficient transfer of heat from the IGBT module to the condenser section. The fin spacing is designed to increase the heat dissipation area and optimize air flow. This fin spacing increases the heat dissipation area within a limited space and improves heat dissipation efficiency. Keeping the spacing within this range ensures smooth air flow between the fins, avoiding excessive air flow resistance caused by too small a spacing or wasted space and reduced heat dissipation caused by too large a spacing.

[0037] In order to further optimize the above embodiment, the phase change energy storage module includes: The matrix material is expanded graphite / paraffin composite material with a phase transition temperature of 65℃±2℃; The pore structure is distributed in a gradient along the direction of heat flow, and the porosity satisfy:

[0038] in is the vertical distance from the evaporation end of the heat pipe, is the total thickness of the phase change layer.

[0039] It should be noted that the expanded graphite / paraffin wax composite was chosen as the matrix material for the phase change energy storage module due to its numerous advantages. Paraffin wax has a high latent heat of phase change, storing a large amount of heat during the phase change process, effectively buffering the transient thermal shock of the IGBT module. Expanded graphite has high thermal conductivity and a porous structure. This not only enhances the overall thermal conductivity of the composite material, enabling rapid heat transfer, but also its porous structure adsorbs paraffin wax, preventing liquid paraffin from leaking during the phase change process and improving material stability. The phase transition point temperature is set at 65°C ± 2°C, primarily based on the operating characteristics of the IGBT module. The IGBT module operates within a certain temperature range during normal operation; performance degrades when the temperature exceeds a certain threshold. This phase transition point temperature is slightly above the normal operating temperature of the IGBT module. When transient thermal shock and temperature rise occur, the phase change material can undergo a timely phase change to absorb heat, preventing excessive temperature increases from impacting IGBT performance. At the same time, the low phase transition point prevents frequent phase changes at normal operating temperatures, which could deplete stored energy. Porosity is distributed in a gradient along the direction of heat flow, with higher porosity near the evaporation end of the heat pipe (where the z value is small) and gradually decreasing away from the evaporation end. This is because the heat flux density is high near the evaporation end, and the larger porosity can accommodate more phase change material and store more heat. As the heat flow transfers, the heat flux density gradually decreases. The smaller porosity ensures both structural stability and optimal material utilization, allowing the entire phase change energy storage module to efficiently store energy and transfer heat in different heat flow regions.

[0040] In order to further optimize the above embodiment, the V-shaped groove array is laser engraved on the fin surface of the bionic fin group, the groove depth is 0.2mm±0.05mm, the adjacent groove spacing p and the groove depth h satisfy p=3h±0.2h, and the fin inclination angle is As the radial position changes, it satisfies ,in is the radial coordinate of the fin, representing the distance from the fin to the center point of the condensing end, is the total fin length.

[0041] It should be noted that the V-grooved array on the surface of the bionic fin assembly simulates the non-smooth structure of shark skin. This structure disrupts the air boundary layer, reducing friction between the air and the fin surface, allowing air to flow more smoothly through the fins and enhancing air mobility, thereby improving the heat exchange efficiency between the fins and the air, achieving more efficient heat dissipation.

[0042] The groove depth is set to 0.2mm±0.05mm, an optimized range derived from experimental and theoretical analysis. This depth ensures effective disturbance of the air boundary layer, enhancing air turbulence and improving heat dissipation, while also ensuring that the fins maintain stability and good heat dissipation performance during long-term use.

[0043] The spacing p between adjacent grooves and the groove depth h satisfies p = 3h ± 0.2h. This proportional relationship ensures effective air disturbance while preventing the grooves from being too dense or too sparse. If the spacing is too large, the air disturbance effect will be weakened, and the heat dissipation enhancement effect of the V-shaped grooves will not be fully realized. If the spacing is too small, the air flow between the grooves will be blocked, increasing flow resistance and even causing airflow turbulence, which is also not conducive to heat dissipation. This proportional relationship ensures that the air forms a stable and efficient heat dissipation flow field on the fin surface.

[0044] The fin inclination angle varies with radial position, resulting in different air guidance effects at different radial positions. Air velocity and flow patterns vary at different radii, and this variable inclination design better adapts to air flow characteristics. In areas with faster airflow, appropriately adjusting the fin inclination angle guides air more evenly across the fins, avoiding localized airflow overshoots or undershoots. This further optimizes the heat exchange process between the air and the fins, improving overall heat dissipation efficiency.

[0045] In order to further optimize the above embodiment, the contact angle of the hydrophobic nanocoating of the self-cleaning system is greater than 150°, the injection pressure of the piezoelectric driven pulse nozzle array is 0.5-1 MPa, and is evenly distributed along the width direction of the bionic fin group.

[0046] It should be noted that when the contact angle of the hydrophobic nanocoating is greater than 150°, water droplets on the coating surface are approximately spherical and have extremely low surface energy. This makes it difficult for impurities such as dust and sand to adhere to the coating surface. Even if a small amount of impurities adhere, they are easily dislodged by external forces such as gravity and airflow. In the actual operating environment of a wind turbine converter, dust and sand easily accumulate on the surface of the bionic fins, affecting heat dissipation efficiency. The superhydrophobic property can effectively reduce impurity adhesion, keep the fin surface clean, maintain good heat dissipation performance, and reduce the attenuation of heat dissipation efficiency caused by impurity accumulation.

[0047] The jet pressure of the piezoelectric pulse nozzle array is set at 0.5-1 MPa, taking into account a variety of factors. On the one hand, this pressure range is sufficient to generate a strong impact force, effectively blowing away and removing impurities such as dust and sand adhering to the surface of the bionic fins. If the pressure is too low, stubborn impurities may not be completely removed; on the other hand, if the pressure is too high, it may damage the fin structure and increase energy consumption. Extensive experiments have verified that this pressure range ensures cleaning effectiveness while ensuring fin safety and energy efficiency.

[0048] The piezoelectrically driven pulse nozzle array is evenly distributed across the width of the bionic fin assembly to ensure effective cleaning across the entire fin surface. Due to the fin's width, uneven nozzle distribution can result in incomplete cleaning of some areas, leaving impurities. This even distribution ensures that the pulsed airflow covers the entire fin width, ensuring that every area receives the same cleaning intensity, thoroughly removing impurities and maintaining balanced heat dissipation across the fins, preventing localized heat dissipation from impacting the converter's normal operation.

[0049] In order to further optimize the above embodiment, the gain parameters of the adaptive PID controller of the intelligent temperature control module satisfy:

[0050] in, is the proportional gain parameter of the adaptive PID controller, which is dynamically adjusted as the real-time temperature difference changes and is used to adjust the response speed and stability of the control system; is the initial value of the proportional gain, It is a preset constant, representing the proportional adjustment capability of the controller in the initial state; is the real-time temperature difference, that is, the difference between the actual system temperature and the set temperature at the current moment; It is a parameter related to the time constant, which is used to control the rate at which the proportional gain changes with the temperature difference. Its value determines the sensitivity of the proportional gain to the temperature difference change.

[0051] in, It is the integral time parameter of the adaptive PID controller, which affects the strength of the controller's integral action on the system error, thereby affecting the system's ability to eliminate steady-state errors; is the initial value of the integral time, which is a pre-set constant and represents the integral time length of the controller in the initial state; is the running time, which means the time from system startup to the current moment; is a period parameter used to determine the period of the sine function so that the integral time parameter can change according to a certain periodic law over time.

[0052] It should be noted that the initial value of the proportional gain It is usually set based on preliminary analysis and experience of the system. When designing an intelligent temperature control module, engineers will determine a suitable initial value through theoretical calculations and preliminary simulation tests based on factors such as the power size of the wind turbine converter, the heat dissipation characteristics of the IGBT module, and the response speed requirements of the system. For example, if the system is expected to respond more quickly to temperature changes in the initial stage, the initial value can be appropriately increased. If you pay more attention to the stability of the system and avoid over-adjustment, you will choose a relatively small value. value.

[0053] Real-time temperature difference The distributed optical fiber temperature sensor array collects temperature data of key parts of the IGBT module and heat pipe array module in real time, and calculates the difference between the actual system temperature and the set temperature at the current moment. The sensor converts the temperature signal into an electrical signal or an optical signal and transmits it to the adaptive PID controller. The calculation unit inside the controller processes these signals and obtains the real-time temperature difference. .

[0054] Time constant related parameters Generally, it is determined by comprehensive analysis of the system's heat transfer characteristics, thermal inertia, and control accuracy requirements. The system can be tested for step response to observe the system's dynamic response process when the temperature changes, and then adjusted according to the characteristics of the response curve. If the system has large thermal inertia and slow response, the proportional gain can be appropriately reduced to make it follow the temperature difference more promptly. On the contrary, if the system response is too sensitive and prone to oscillation, it is necessary to increase value.

[0055] Initial value of integration time and Similarly, it is also based on experience and system characteristics. In the early stage of system debugging, engineers will preliminarily determine the system's allowable steady-state error range, response speed, and the impact of integral action on system stability. If you want the system to eliminate the steady-state error quickly, you can appropriately reduce ;but If the value is too small, it may cause the system to experience integral saturation, which will affect the control effect. Therefore, it needs to be continuously optimized during actual debugging.

[0056] The running time t is obtained by the timing module inside the system. It starts from the system startup and is continuously updated as time goes by, providing a time benchmark for the dynamic adjustment of the integral time parameters.

[0057] The period parameter T is determined based on the system's operating conditions and control requirements. For example, if the temperature fluctuations in a wind turbine converter exhibit a certain periodicity, T can be set to a value close to this periodicity, allowing the integral time parameter to better adapt to the system's dynamic changes. Alternatively, the T value can be set based on the temperature variation patterns identified by analyzing the system's historical operating data.

[0058] Proportional gain parameter With real-time temperature difference Dynamic adjustment is used to adjust the response speed and stability of the control system. When it is larger, will increase accordingly, making the controller respond more quickly to temperature deviations, increasing the adjustment force and quickly reducing the temperature difference; when When smaller, Reduce, avoid system oscillation due to over-regulation, and ensure stable operation of the system. When the temperature of the IGBT module rises rapidly, the adaptive PID controller increases Rapidly increase the coolant flow rate of the microchannel liquid cooling manifold to speed up heat dissipation and suppress further temperature increase.

[0059] Integration time parameters Affects the controller's integral action strength on system error. When the system has a steady-state error, the integral action will accumulate the error signal. The strength of the integral effect can be controlled. As time t changes according to the sine law , can dynamically adjust the integral action during system operation. During the system startup phase or when the temperature deviation is large, the relatively large It can avoid the system overshoot caused by excessive integral action; when approaching the set temperature and steady-state error needs to be eliminated, a smaller It can enhance the integral effect, enable the system to reach a stable state more quickly, and ensure that the temperature of the IGBT module is stable within the set range.

[0060] The methods for obtaining the above parameters are existing technical means and will not be further elaborated in this application.

[0061] Example 2: The embodiment of the present invention provides a control method for a high-efficiency heat dissipation device of a wind turbine converter based on heat pipe technology. Figure 2 , including the following steps: Step 1: Obtain the IGBT surface temperature field distribution in real time through a distributed optical fiber temperature sensor array; Step 2: Establish a heat pipe-phase change material composite heat transfer efficiency evaluation model to calculate the comprehensive heat dissipation efficiency; Step 3: Establish an asymmetric fuzzy control algorithm to calculate the heat dissipation mode switching threshold based on the temperature field distribution and comprehensive heat dissipation efficiency; Step 4: triggering a self-cleaning pulse sequence according to the dynamic pressure field distribution; Step 5: Adjust the operating parameters of the liquid cooling system in real time through a multi-objective optimization algorithm.

[0062] The principles and beneficial effects of this embodiment are as follows: the distributed fiber optic temperature sensor array acts as the device's "temperature sensing nerves," collecting IGBT surface temperature data in real time and providing a basis for subsequent control decisions. A heat pipe-phase change material composite heat transfer efficiency evaluation model comprehensively considers factors such as the heat pipe's equivalent thermal conductivity, phase change material physical properties, time, and inter-fin pressure difference to accurately evaluate the performance of the cooling system. An asymmetric fuzzy control algorithm uses temperature deviation, temperature change rate, inter-fin pressure difference, and overall heat dissipation efficiency as inputs. It dynamically adjusts the control output using a hyperbolic tangent function, calculates the heat dissipation mode switching threshold that meets actual heat dissipation requirements, and achieves intelligent and precise control. Dynamic pressure field distribution monitoring is used to determine the cleanliness of the bionic fin surface. When the pressure difference reaches a set threshold, a self-cleaning pulse sequence is triggered to maintain the fin's heat dissipation performance. A multi-objective optimization algorithm uses total energy consumption, temperature standard deviation, and noise level as optimization targets. While meeting heat dissipation performance constraints, it optimizes parameters such as liquid cooling flow rate, fan speed, and pulse cleaning cycle to find the optimal balance.

[0063] In order to further optimize the above embodiment, in step 2, the heat transfer efficiency evaluation model includes a heat pipe equivalent thermal conductivity calculation model and a comprehensive heat dissipation efficiency evaluation model; The equivalent thermal conductivity calculation model is:

[0064] in, is the equivalent thermal conductivity, Heat flow for phase change materials, is the effective length of the heat pipe, is the cross-sectional area of the heat pipe, is the temperature difference between the two ends of the heat pipe, and is the corresponding material constant, is the pressure gradient of the working fluid in the heat pipe; The comprehensive heat dissipation efficiency evaluation model is:

[0065] in, For comprehensive heat dissipation efficiency, For time, is the density of the phase change material, is the specific heat capacity, is the thickness of the phase change layer, is the pressure difference between the fins, is the maximum allowable pressure difference.

[0066] It should be noted that the heat flux of the phase change material is directly measured by placing heat flow sensors inside the phase change material or at key locations in contact with the heat pipe. The heat flow sensors monitor the rate of heat transfer through these locations in real time, thereby obtaining data on the heat flux of the phase change material. Alternatively, indirect calculations can be performed based on the properties of the phase change material and the system's energy balance, combined with known temperature distribution and theoretical heat conduction formulas.

[0067] The effective length and cross-sectional area of heat pipes are determined during the design and manufacture of heat pipe array modules. Accurate values can be obtained by measurement or by consulting design drawings. For example, heat pipe dimensions are inspected during production, and the actual length and cross-sectional area are recorded.

[0068] The temperature difference between the two ends of the heat pipe is measured using distributed fiber optic temperature sensors, which measure the temperature at the evaporation and condensation ends of the heat pipe, respectively. The difference between the two is the temperature difference between the two ends of the heat pipe. The sensor converts the temperature signal into an electrical or optical signal and transmits it to the control system for processing and calculation.

[0069] Material constants are derived through extensive experimental testing and theoretical analysis based on the properties of the working fluid within the heat pipe and the materials used to construct it. Research institutions or material suppliers conduct experiments on specific materials to obtain these constants and provide reference data. In actual applications, refer directly to the corresponding data sheet for the selected heat pipe material and working fluid.

[0070] The pressure gradient of the working fluid within a heat pipe is determined by placing pressure sensors at appropriate locations within the heat pipe, measuring the pressure at different locations, and then calculating the ratio of the pressure difference to the distance difference between adjacent measurement points. Theoretical calculations can also be performed based on a theoretical model of the working fluid flow within the heat pipe, taking into account factors such as the heat pipe's structural parameters, the physical properties of the working fluid, and operating conditions.

[0071] The time t is obtained through the timing device inside the system. The timing starts when the system starts running and continues to accumulate as the running process progresses.

[0072] The density and specific heat capacity of a phase change material depend on its composition and properties. For a specific phase change material, such as the expanded graphite / paraffin wax composite material described in the examples, these values can be measured using material testing equipment. Standard values can also be obtained by referring to relevant material research literature or data sheets provided by material suppliers.

[0073] After the phase change energy storage module is manufactured, the thickness of the phase change layer can be directly measured using measuring tools (such as calipers, micrometers, etc.). Alternatively, the thickness of the phase change layer can be determined during the design phase and quality control can be performed during the manufacturing process to ensure that it meets the design requirements.

[0074] The pressure differential between the fins is measured using pressure sensors placed at various locations within the bionic fin assembly. The maximum allowable pressure differential is determined through theoretical calculations and experimental verification based on the structural strength of the bionic fin assembly, air flow performance, and the overall design requirements of the cooling system. During the system design phase, mechanical analysis of the fin structure and flow field simulations are performed to comprehensively consider various factors to determine this threshold.

[0075] The overall heat dissipation efficiency reflects the heat dissipation performance of the entire cooling system at a specific moment. A high overall heat dissipation efficiency indicates that, under the current operating conditions, the cooling system is effectively transferring heat generated by the IGBT module and dissipating it into the environment. This means that the heat pipe is efficiently transferring heat, the phase change material is fully utilizing its energy storage and heat transfer functions, and air flow between the fins is smooth, resulting in good overall heat dissipation. The temperature of the IGBT module can be effectively controlled, ensuring stable inverter operation. Conversely, a low overall heat dissipation efficiency indicates possible issues with the cooling system, such as decreased heat pipe heat transfer efficiency, poor phase change material performance, or obstructed air flow between the fins. By analyzing the changing trends in the overall heat dissipation efficiency and the impact of various parameters on it, weak links in the cooling system can be identified, providing a basis for optimizing the cooling system's operating parameters or improving the structure of the cooling device, thereby improving the overall performance of the cooling system.

[0076] In order to further optimize the above embodiment, in step 3, the asymmetric fuzzy control algorithm uses the hyperbolic tangent function to calculate the heat dissipation mode switching threshold. The formula is:

[0077] in, is the temperature deviation, is the actual temperature, To set the temperature; parameter 、 、 The dynamic adjustment formula is:

[0078]

[0079]

[0080] in, is the initial proportional coefficient, is the temperature change rate, is the maximum allowable temperature, is the pressure difference between the fins, For comprehensive heat dissipation efficiency; This formula dynamically adjusts the control output by calculating temperature deviation, temperature change rate, pressure difference between fins and comprehensive heat dissipation efficiency parameters. Compared with traditional fuzzy control, it can more accurately calculate the heat dissipation mode switching threshold based on actual heat dissipation needs, thereby achieving more effective control of the heat dissipation system.

[0081] It's important to note that the cooling mode switching threshold u(t) is a key decision-making factor for intelligent control of the entire cooling system. It comprehensively considers multiple factors, including temperature deviation, temperature change rate, inter-fin pressure difference, and overall cooling efficiency. During wind turbine converter operation, varying operating conditions lead to constantly changing cooling requirements. The threshold accurately reflects the current cooling demand and provides a quantitative switching standard for the control system.

[0082] When the calculated u(t) is compared with the preset switching ranges for different cooling modes, the control system can determine whether the cooling mode needs to be switched. For example, when u(t) reaches a certain high threshold, it indicates that the current cooling demand is urgent and passive cooling alone can no longer meet the requirements. The system needs to switch to a more powerful cooling method such as active liquid cooling. If u(t) is at a lower level, it indicates that the cooling situation is good and the current more energy-efficient passive cooling mode can be maintained. This allows the cooling system to operate efficiently and stably under various operating conditions, ensuring that the IGBT module is always within the appropriate operating temperature range.

[0083] A distributed fiber optic temperature sensor array continuously collects temperature data from key locations on the IGBT module and heat pipe array module to determine the actual temperature. An adaptive PID controller compares the actual temperature with the set temperature to determine the temperature deviation. This deviation is then combined with the temperature change rate, the inter-fin pressure differential obtained from other sensors, and the overall heat dissipation efficiency calculated using a heat transfer efficiency evaluation model. Parameters K, a, and b are calculated using the corresponding formulas, thereby determining the heat dissipation mode switching threshold u(t).

[0084] The control system pre-sets u(t) threshold ranges for different cooling modes. For example, the threshold for switching from passive cooling mode to active liquid cooling is set to u1, and the threshold for switching from active liquid cooling mode to a higher cooling power mode is set to u2 (u2>u1). When the calculated u(t) is less than u1, the control system determines that the current cooling demand is low and maintains the passive cooling mode, relying solely on natural convection between the bionic fin assembly and the air for heat dissipation. When u(t) is greater than or equal to u1 and less than u2, the control system decides to activate the active liquid cooling mode. The adaptive PID controller adjusts the microchannel liquid cooling manifold's coolant flow rate, flow direction, and other parameters based on the current u(t) value to enhance heat dissipation. If u(t) is greater than or equal to u2, the control system further increases the liquid cooling intensity or activates other auxiliary cooling methods to ensure stable IGBT module temperature.

[0085] During the cooling process, various parameters change in real time, and u(t) is dynamically adjusted accordingly. If, in active liquid cooling mode, the IGBT module temperature drops and various parameters change, causing the calculated u(t) to fall below u1, the control system will switch back to passive cooling mode to reduce energy consumption. This threshold-based dynamic switching mechanism allows for flexible adjustment of cooling modes based on actual cooling needs, enabling precise and efficient control of the cooling system.

[0086] According to a control method for a high-efficiency heat dissipation device of a wind turbine converter based on heat pipe technology provided by the present invention, in step five, the multi-objective optimization algorithm adopts an improved NSGA-II framework; The objective function is to minimize = total energy consumption, = temperature standard deviation, = noise level; The constraints are: : ≤70℃, : ≤200Pa, : ≥0.8; Optimization variables include: Liquid cooling flow rate , fan speed , pulse cleaning cycle ; Obtain the optimal solution set through Pareto frontier search and make decisions using entropy weight method; determine the optimal liquid cooling flow rate for the current cycle , fan speed ; The multi-objective optimization algorithm uses multiple key indicators as optimization targets, and optimizes multiple operating parameters of the heat dissipation system under the constraint of meeting the heat dissipation performance requirements to achieve a balance between energy consumption, temperature stability and noise level.

[0087] It should be noted that the original NSGA-II (Non-dominated Sorting Genetic Algorithm II) framework is a multi-objective optimization algorithm. It is based on the basic framework of the genetic algorithm and mainly includes the following key components: 1. Population initialization: Randomly generate a certain number of individuals within the feasible solution space to form the initial population. Each individual represents a set of decision variables, which in this case correspond to a combination of values for optimization variables such as liquid cooling flow rate, fan speed, and pulse cleaning cycle.

[0088] 2. Non-dominated sorting: Individuals in a population are stratified according to dominance relationships. If individual A is not inferior to individual B on all objective functions and is superior to individual B on at least one objective function, then A is said to dominate B. Individuals not dominated by any other individual belong to the first stratum (non-dominated stratum). After removing individuals from the first stratum, the remaining individuals are subjected to the same dominance relationship determination to form the second stratum, and so on. This sorting method can distinguish different optimization levels and identify solutions that cannot be surpassed by other solutions.

[0089] 3. Crowding Calculation: For individuals in the same non-dominated layer, the crowding degree is calculated for each objective function direction. The crowding degree of an individual in objective function direction j is calculated by the difference between the individual and its neighbors in objective function j, as well as the maximum and minimum values of the objective function in that layer. The crowding degree reflects the distribution density of solutions around an individual and is used to maintain population diversity.

[0090] 4. Selection, Crossover, and Mutation: Genetic operations such as tournament selection, simulated binary crossover, and polynomial mutation are employed. Tournament selection randomly selects a certain number of individuals from the population and selects those with the best fitness (typically based on non-dominated sorting and crowding in multi-objective optimization) to advance to the next generation. Crossover exchanges genes among selected individuals to generate new individuals. Mutation randomly alters the genes of individuals to introduce new solutions. These operations continuously evolve the population, gradually approaching the Pareto frontier.

[0091] The original NSGA-II framework can optimize multiple conflicting objectives simultaneously and find a set of Pareto optimal solutions. Each solution in the Pareto optimal solution set represents a balance between multiple objectives. No solution can improve one objective without degrading other objectives. The improved algorithm retains the core principles of the original NSGA-II framework. In the population initialization phase, an initial set of individuals containing optimization variables such as liquid cooling flow, fan speed, and pulse cleaning cycle is still randomly generated in the feasible solution space to provide a basis for subsequent evolution. The non-dominated sorting and congestion calculation parts are also used. Non-dominated sorting is used to distinguish solutions of different optimization levels, and congestion is used to maintain population diversity, ensuring that the search process can cover different areas of the Pareto frontier. In terms of genetic operations such as selection, crossover, and mutation, it is also based on the basic methods of the original framework, but adjustments may be made to specific parameter settings or operation details to adapt to the cooling system optimization problem of the present invention.

[0092] In this embodiment, the improved algorithm leverages the principles of the original framework to optimize the cooling system's operating parameters while maintaining the required cooling performance. It balances total energy consumption, temperature standard deviation, and noise level while ensuring that the IGBT module temperature does not exceed the upper limit, the inter-fin pressure difference, and the overall cooling efficiency meet standards. For example, this optimization can reduce the energy consumption of the liquid cooling pump and fan while still meeting cooling requirements, thereby reducing system operating costs.

[0093] By improving upon the original framework, the algorithm is now more efficient and accurate in searching for the Pareto frontier. It can more quickly find optimal solutions and more accurately determine the optimal combination of liquid cooling flow, fan speed, and pulse cleaning cycles under different operating conditions. For example, under high-temperature and high-load conditions, it can quickly determine parameter settings that meet cooling requirements while controlling noise and energy consumption, improving the overall performance and responsiveness of the cooling system.

[0094] The improved algorithm uses an entropy weighting method to make decisions, selecting the optimal liquid cooling flow rate and fan speed for the current cycle from the Pareto optimal solution set. This method assigns weights based on the importance of each objective, ensuring that the decision-making results are more aligned with practical needs. In practice, operations and maintenance personnel can use this method to determine more optimal operating parameters based on their priorities (e.g., focusing on energy consumption or temperature stability), providing strong support for cooling system operation and management.

[0095] A Pareto optimal solution refers to a situation where, among multiple objectives, there is no solution that improves one objective without degrading the others. The Pareto frontier is the set of all Pareto optimal solutions. This is a known technique and will not be further elaborated here.

[0096] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A high-efficiency heat dissipation device for a wind turbine converter based on heat pipe technology, characterized in that: include: The heat pipe array module has an evaporation end that fits closely to the heating surface of the converter IGBT module, and a variable-section spiral sintered heat pipe at the condensation end. Used to transfer the heat generated by the IGBT module to the subsequent heat dissipation structure; A phase change energy storage module is filled with phase change material between the evaporation end and the IGBT module to form a gradient pore structure; When the IGBT module generates a transient thermal shock, the phase change characteristics of the phase change material are used to absorb and store heat, thereby buffering the drastic temperature change and preventing the IGBT module temperature from rising sharply in a short period of time. At the same time, the phase change energy storage module is in close contact with the evaporation end of the heat pipe array module to ensure that heat can be quickly transferred to the heat pipe. A bionic fin assembly comprising shark skin texture fin units arranged in a multi-stage staggered arrangement, coupled to the condensation end via a shape memory alloy bracket, and having a V-groove array on the fin surface; Used to receive the heat transferred from the condensing end of the heat pipe array module and dissipate the heat into the environment through heat exchange with the air; The self-cleaning system consists of a hydrophobic nano-coating, a piezoelectrically driven pulse nozzle array, and a differential pressure feedback unit, covering the surface of the bionic fin; The differential pressure feedback unit monitors the pressure difference before and after the bionic fin in real time. When the pressure difference reaches a set threshold, it triggers the piezoelectric driven pulse nozzle array to spray pulse airflow, which, combined with the hydrophobic nano coating, removes impurities on the fin surface. The intelligent temperature control module includes a distributed fiber optic temperature sensor array, a microchannel liquid cooling manifold and an adaptive PID controller, which realizes heat dissipation mode switching through thermal-electrical-mechanical multi-field coupling; the distributed fiber optic temperature sensor array is arranged at key positions of the IGBT module and the heat pipe array module, collects temperature data in real time and transmits it to the adaptive PID controller; the adaptive PID controller controls the coolant flow and flow direction parameters of the microchannel liquid cooling manifold based on a preset temperature threshold and real-time temperature data through thermal-electrical-mechanical multi-field coupling analysis, realizing switching between different modes such as passive heat dissipation and active liquid cooling, ensuring that the IGBT module operates within a reasonable temperature range.

2. The high-efficiency heat dissipation device for a wind turbine converter based on heat pipe technology according to claim 1, characterized in that: The variable-section spiral sintered heat pipe of the heat pipe array module includes: The evaporation section is a spiral tube structure with a gradually decreasing radius, and the spiral rise angle θ satisfies 5°≤θ≤10°; The condensing section is provided with periodically raised annular fins, and the fin spacing δ and the heat pipe diameter D satisfy δ=0.3D±0.05D.

3. The high-efficiency heat dissipation device for a wind turbine converter based on heat pipe technology according to claim 2, characterized in that: The phase change energy storage module includes: The matrix material is expanded graphite / paraffin composite material with a phase transition temperature of 65℃±2℃; The pore structure is distributed in a gradient along the direction of heat flow, and the porosity satisfy: in is the vertical distance from the evaporation end of the heat pipe, is the total thickness of the phase change layer.

4. The high-efficiency heat dissipation device for a wind turbine converter based on heat pipe technology according to claim 3 is characterized in that: The V-shaped groove array is laser-engraved on the fin surface of the bionic fin group. The groove depth is 0.2mm±0.05mm, the adjacent groove spacing p and the groove depth h satisfy p=3h±0.2h, and the fin inclination angle is As the radial position changes, it satisfies ,in is the radial coordinate of the fin, representing the distance from the fin to the center point of the condensing end, is the total fin length.

5. The high-efficiency heat dissipation device for a wind turbine converter based on heat pipe technology according to claim 4, characterized in that: The contact angle of the hydrophobic nano coating of the self-cleaning system is greater than 150°, and the injection pressure of the piezoelectric driven pulse nozzle array is 0.5-1 MPa and is evenly distributed along the width direction of the bionic fin group.

6. The high-efficiency heat dissipation device for a wind turbine converter based on heat pipe technology according to claim 5, characterized in that: The gain parameters of the adaptive PID controller of the intelligent temperature control module satisfy: in, is the proportional gain parameter of the adaptive PID controller, which is dynamically adjusted as the real-time temperature difference changes and is used to adjust the response speed and stability of the control system; is the initial value of the proportional gain, It is a preset constant, representing the proportional adjustment capability of the controller in the initial state; is the real-time temperature difference, that is, the difference between the actual system temperature and the set temperature at the current moment; It is a parameter related to the time constant, which is used to control the rate at which the proportional gain changes with the temperature difference. Its value determines the sensitivity of the proportional gain to the temperature difference change. in, It is the integral time parameter of the adaptive PID controller, which affects the strength of the controller's integral action on the system error, thereby affecting the system's ability to eliminate steady-state errors; is the initial value of the integral time, which is a pre-set constant and represents the integral time length of the controller in the initial state; is the running time, which means the time from system startup to the current moment; is a period parameter used to determine the period of the sine function so that the integral time parameter can change according to a certain periodic law over time.

7. A control method for a high-efficiency heat dissipation device for a wind turbine converter based on heat pipe technology, based on the device according to claims 1-6, characterized in that: The following steps are involved: Step 1: Obtain the IGBT surface temperature field distribution in real time through a distributed optical fiber temperature sensor array; Step 2: Establish a heat pipe-phase change material composite heat transfer efficiency evaluation model to calculate the comprehensive heat dissipation efficiency; Step 3: Establish an asymmetric fuzzy control algorithm to calculate the heat dissipation mode switching threshold based on the temperature field distribution and comprehensive heat dissipation efficiency; Step 4: triggering a self-cleaning pulse sequence according to the dynamic pressure field distribution; Step 5: Adjust the operating parameters of the liquid cooling system in real time through a multi-objective optimization algorithm.

8. The control method of the high-efficiency heat dissipation device for a wind turbine converter based on heat pipe technology according to claim 7, characterized in that: In step 2, the heat transfer efficiency evaluation model includes a heat pipe equivalent thermal conductivity calculation model and a comprehensive heat dissipation efficiency evaluation model; The equivalent thermal conductivity calculation model is: in, is the equivalent thermal conductivity, Heat flow for phase change materials, is the effective length of the heat pipe, is the cross-sectional area of the heat pipe, is the temperature difference between the two ends of the heat pipe, and is the corresponding material constant, is the pressure gradient of the working fluid in the heat pipe; The comprehensive heat dissipation efficiency evaluation model is: in, For comprehensive heat dissipation efficiency, For time, is the density of the phase change material, is the specific heat capacity, is the thickness of the phase change layer, is the pressure difference between the fins, is the maximum allowable pressure difference.

9. The control method of a high-efficiency heat dissipation device for a wind turbine converter based on heat pipe technology according to claim 8, characterized in that: In step 3, the asymmetric fuzzy control algorithm uses the hyperbolic tangent function to calculate the heat dissipation mode switching threshold The formula is: in, is the temperature deviation, is the actual temperature, To set the temperature; parameter 、 、 The dynamic adjustment formula is: in, is the initial proportional coefficient, is the temperature change rate, is the maximum allowable temperature, is the pressure difference between the fins, For comprehensive heat dissipation efficiency; This formula dynamically adjusts the control output by calculating temperature deviation, temperature change rate, pressure difference between fins and comprehensive heat dissipation efficiency parameters. Compared with traditional fuzzy control, it can more accurately calculate the heat dissipation mode switching threshold based on actual heat dissipation needs, thereby achieving more effective control of the heat dissipation system.

10. The control method of the high-efficiency heat dissipation device of a wind turbine converter based on heat pipe technology according to claim 9, characterized in that: In step 5, the multi-objective optimization algorithm adopts the improved NSGA-II framework; The objective function is to minimize = total energy consumption, = temperature standard deviation, = noise level; The constraints are: : ≤70℃, : ≤200Pa, : ≥0.8; Optimization variables include: Liquid cooling flow rate , fan speed , pulse cleaning cycle ; Obtain the optimal solution set through Pareto frontier search and make decisions using entropy weight method; determine the optimal liquid cooling flow rate for the current cycle , fan speed ; The multi-objective optimization algorithm uses multiple key indicators as optimization targets, and optimizes multiple operating parameters of the heat dissipation system under the constraint of meeting the heat dissipation performance requirements to achieve a balance between energy consumption, temperature stability and noise level.

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