A method for thermal protection of a maglev motor in a high temperature environment

Abstract

The application discloses a high-temperature environment magnetic suspension motor heat protection method, obtains the armature winding loss, excitation winding loss and core loss of the magnetic suspension motor under the rated working condition; based on the component loss and the corresponding volume, calculates the heat generation rate of each component, and establishes a temperature field mathematical model containing the heat conduction coefficient and the convective heat transfer coefficient; according to the temperature field mathematical model, the node temperature set of the whole magnetic suspension motor is determined, and the node temperature set is divided into temperature intervals; when the highest temperature is higher than the preset safety threshold, the arrangement parameters of the cooling channel are adjusted, and the simulation and adjustment are repeatedly executed until the highest temperature is below the preset safety threshold, and the heat protection is completed. The application verifies the highest temperature through the temperature field simulation, if the highest temperature exceeds the preset safety threshold, the arrangement parameters of the cooling channel are dynamically adjusted and iteratively optimized until the temperature control requirement is met, so that the key components of the motor are effectively prevented from over-temperature under the high-temperature environment.

Description

Technical Field

[0001] This invention belongs to the field of motor thermal management technology, specifically relating to a thermal protection method for magnetic levitation motors suitable for high-temperature operating environments. Background Technology

[0002] Magnetic levitation motors are increasingly widely used in high-end fields such as high-speed trains, flywheel energy storage, and aerospace due to their advantages of being contactless, having low losses, and being highly efficient. However, in high-temperature operating environments, the armature winding, excitation winding, and core generate a large amount of heat due to electromagnetic losses. If heat dissipation is not timely, it can easily lead to excessively high local temperatures, which can then cause insulation failure, magnetic performance degradation, or even structural damage, seriously threatening the safety and reliability of the system.

[0003] To accurately assess motor temperature rise, existing technologies mostly employ thermal analysis methods for modeling. For example, Chinese invention patent CN106446364B proposes a "motor thermal analysis method with direct coupling of temperature field and thermal path." This method uses the finite element method to model some components to capture complex geometry and non-uniform heat sources, while using the thermal path method to model the remaining components to efficiently handle internal convective heat transfer. It couples these two methods through equivalent temperature boundaries and equivalent convective boundaries to solve the overall temperature field in a unified manner. This method balances computational accuracy and efficiency, providing an effective tool for motor thermal analysis.

[0004] Nevertheless, such thermal analysis methods primarily focus on accurately solving for temperature distribution, and have not yet addressed the issue of how to automatically identify key thermal risk areas based on the obtained temperature field and implement targeted cooling. Traditional thermal protection designs often rely on fixed thresholds or empirical judgments to arrange cooling channels, lacking quantitative zoning and risk level classification of the entire temperature data, which can easily lead to wasted cooling resources or insufficient protection against localized overheating.

[0005] Therefore, while existing technologies can accurately obtain the internal temperature distribution of motors, they still have shortcomings such as the inability to objectively distinguish between regions with different thermal risk levels, the lack of precise basis for cooling system layout, and the reliance on repeated trial and error for optimizing thermal protection schemes. There is an urgent need for a thermal protection method that can automatically identify the highest-risk regions based on a high-precision temperature field model and temperature range division, and accordingly construct an integrated cooling system with iterative parameter optimization, in order to achieve efficient, reliable, and intensive thermal management of magnetic levitation motors in high-temperature environments. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the prior art and provide a thermal protection method for magnetic levitation motors in high-temperature environments. This method identifies hot spots and optimizes the cooling arrangement to effectively control temperature rise and ensure the safe and reliable operation of the motor.

[0007] The objective of this invention is achieved through the following technical solution: A thermal protection method for a magnetic levitation motor in a high-temperature environment, the method comprising: Obtain the armature winding loss, excitation winding loss, and core loss of the magnetic levitation motor under rated operating conditions; Based on the losses of each component and their corresponding volumes, the heat generation rate of each component is calculated, and a mathematical model of the temperature field including thermal conductivity and convective heat transfer coefficient is established. Based on the temperature field mathematical model, the set of node temperatures across the entire magnetic levitation motor is determined, and the set of node temperatures is divided into temperature ranges to obtain several temperature bins. By combining the aforementioned temperature bins, a first thermal risk zone and a second thermal risk zone are determined, wherein the temperature of the first thermal risk zone is higher than that of the second thermal risk zone. Cooling channels are arranged in the first thermal risk area to form an integrated cooling system; Temperature field simulation was performed on the magnetic levitation motor integrated with the aforementioned cooling system to obtain its maximum temperature. When the maximum temperature exceeds the preset safety threshold, the arrangement parameters of the cooling channel are adjusted, and the simulation and adjustment are repeated until the maximum temperature drops below the preset safety threshold, thus completing the thermal protection.

[0008] As a preferred method, the step of dividing the node temperature set into temperature ranges to obtain several temperature bins includes: Determine the maximum temperature in the set of node temperatures. and minimum temperature Set the number of temperature-controlled bins. And calculate the width of each temperature bin. ; temperature range Divided into The first continuous temperature bin, the first The range of each temperature bin is: ,in .

[0009] As a preferred method, the determination of the first and second thermal risk zones by combining several temperature bins includes: Count the number of nodes in each temperature bin to obtain the node count sequence. from Begin traversing forward, calculating the ratio of the decrease in the number of nodes in adjacent buckets. When there exists a certain ) makes As a preset mutation threshold, and When ), the first To the The physical areas corresponding to the temperature bins are defined as the first thermal risk area; the first to the second... The physical area corresponding to each temperature bin is determined as the second thermal risk area.

[0010] As a preferred embodiment, the arrangement of cooling channels in the first heat-risk area includes: Obtain the set of spatial coordinates of the first thermal risk area. ; Within the structurally permissible area of ​​the magnetic levitation motor, all areas where pipes can be installed are identified. ;calculate and intersection ;exist Cooling channels are arranged along the direction of maximum local temperature gradient, ensuring that the angle between the centerline of the cooling channels and the direction of this local temperature gradient is less than 1. A cooling medium is introduced into the cooling channel to form the integrated cooling system.

[0011] As a preferred embodiment, the temperature field simulation of the magnetic levitation motor integrated with the cooling system includes: Set the inlet flow rate and inlet temperature of the cooling medium; The standard k-ε turbulence model and standard wall function are selected; By coupling electromagnetic and thermofluid multiphysics fields, the temperature field distribution across the entire motor domain and the pressure field distribution within the cooling channel are obtained.

[0012] As a preferred method, adjusting the layout parameters of the cooling channels includes: When the pressure difference between the inlet and outlet of the cooling channel obtained from the simulation exceeds the pump power limit, increase the channel cross-sectional area or reduce the number of bends. If the maximum temperature is still higher than the preset safety threshold, increase the flow rate of the cooling medium or reduce the inlet temperature.

[0013] As a preferred approach, the operation of the cooling system must meet the constraint of energy consumption and temperature drop synergistic optimization. The energy consumption and temperature drop collaborative optimization constraint is expressed by the following formula: in, This represents the pressure difference between the inlet and outlet of the cooling system, expressed in Pa. This refers to the volumetric flow rate of cooling water, in cubic meters per second (m³). 3 / s; This refers to the density of cooling water, expressed in kg / m³. 3 ; This refers to the specific heat capacity of cooling water at constant pressure, expressed in J / (kg·℃). and These are the inlet and outlet temperatures of the cooling water, respectively, in °C. The system energy efficiency coefficient is, and .

[0014] As a preferred approach, after completing thermal protection, the following are also included: Infrared images of the surface of the magnetic levitation motor during actual operation were acquired using an infrared thermal imager. The infrared image is subjected to median filtering to eliminate random noise, resulting in a denoised two-dimensional surface temperature distribution map.

[0015] As a preferred embodiment, after performing median filtering on the infrared image, the method further includes: Based on the geometry of the magnetic levitation motor, the denoised two-dimensional surface temperature distribution map is divided into several sub-regions; Within each sub-region, pixels with a temperature gradient greater than a preset gradient threshold are selected as candidate feature points. From all candidate feature points, a representative set of feature points that is spatially balanced and covers all key heat-generating areas is selected; After obtaining the representative feature point set, the following is also included: Read the measured temperature data and spatial coordinates of several temperature sensors embedded inside the magnetic levitation motor; The infrared temperature of the representative feature points and the measured temperature of the internal sensor are used together as observation data for subsequent temperature field reconstruction.

[0016] As a preferred approach, when reconstructing the temperature field using observational data, a temperature field fusion consistency constraint is introduced to ensure that the reconstruction result simultaneously fits both infrared surface data and internal sensor data; the temperature field fusion consistency constraint is expressed by the following formula: in, Output the three-dimensional temperature field model to be reconstructed; , For the first The location of each internal sensor and the measured temperature; , For the first The location and infrared temperature of a representative feature point; The weighting coefficient has a range of values. ; This is the tolerance threshold.

[0017] The present invention has at least the following beneficial effects: By acquiring the armature winding loss, excitation winding loss, and core loss of a magnetic levitation motor under rated operating conditions, and calculating the heat generation rate of each component based on its volume, a complete thermal field mathematical model was constructed that comprehensively considers the thermal conductivity of materials and the boundary convective heat transfer coefficient, reflecting the distribution of heat sources and heat transfer characteristics inside the motor. Based on this, multiple temperature zones were formed by dividing the temperature range according to the global node temperature set, thus scientifically distinguishing between the first thermal risk zone (higher temperature and more severe thermal risk) and the second thermal risk zone (lower level). Subsequently, cooling channels were strategically arranged only in the first thermal risk zone to construct a compact and resource-efficient integrated cooling system. The highest temperature was verified through temperature field simulation. If the preset safety threshold was exceeded, the cooling channel arrangement parameters were dynamically adjusted and iteratively optimized until the temperature control requirements were met. This effectively ensures that key components of the motor do not overheat, insulation does not fail, and performance does not degrade under high-temperature environments, significantly improving the accuracy, reliability, and engineering practicality of thermal protection. Attached Figure Description

[0018] To reveal the technical details of the embodiments of the present invention, the accompanying drawings involved in the embodiments will be briefly described below. It should be emphasized that these drawings only present several embodiments of the present invention and should not be considered as defining the scope of the invention. For those skilled in the art, other related drawings can still be derived based on these drawings without inventive effort.

[0019] Figure 1 A schematic diagram of a thermal protection method for a magnetic levitation motor in a high-temperature environment; Figure 2 Schematic diagram of cooling channel layout parameter adjustment strategy; Figure 3 This is a flowchart of the data processing for the surface temperature distribution of a magnetic levitation motor. Detailed Implementation

[0020] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings, but the scope of protection of the present invention is not limited to the following description.

[0021] In the embodiments of this disclosure, the terms "first," "second," "first," "second," etc., are used only to distinguish different components or objects and do not indicate their order, priority, or importance, nor do they constitute any limitation on these components or objects. For example, "first user equipment" and "second user equipment" are used only to refer to two different user equipments, both belonging to the same category of user equipment. It is understood that such naming is arbitrary. A first component may be called a second component, and vice versa, without changing its essential function or technical meaning within the scope of this disclosure.

[0022] It should be clarified that the specific details described below are intended to aid in a comprehensive understanding of the exemplary embodiments of this disclosure, but are not essential for implementing these embodiments. Those skilled in the art will understand that the embodiments can still be implemented even with some or all of these details missing. For example, a system may be illustrated in block diagram form to avoid redundant details affecting the clear presentation of the overall solution; in other cases, unnecessary details of processes, structures, or technologies known in the art may be omitted to highlight core content.

[0023] like Figure 1 As shown, a thermal protection method for a magnetic levitation motor in a high-temperature environment includes: Obtain the armature winding loss, excitation winding loss, and core loss of the magnetic levitation motor under rated operating conditions; Based on the losses of each component and their corresponding volumes, the heat generation rate of each component is calculated, and a mathematical model of the temperature field including thermal conductivity and convective heat transfer coefficient is established. Based on the temperature field mathematical model, the set of node temperatures across the entire magnetic levitation motor is determined, and the set of node temperatures is divided into temperature ranges to obtain several temperature bins. By combining the aforementioned temperature bins, a first thermal risk zone and a second thermal risk zone are determined, wherein the temperature of the first thermal risk zone is higher than that of the second thermal risk zone. Cooling channels are arranged in the first thermal risk area to form an integrated cooling system; Temperature field simulation was performed on the magnetic levitation motor integrated with the aforementioned cooling system to obtain its maximum temperature. When the maximum temperature exceeds the preset safety threshold, the arrangement parameters of the cooling channel are adjusted, and the simulation and adjustment are repeated until the maximum temperature drops below the preset safety threshold, thus completing the thermal protection.

[0024] In a preferred embodiment, to prevent the cooling system from failing due to medium vaporization under extreme operating conditions, this invention introduces a critical early warning implementation for cooling medium phase change during the temperature field simulation stage. In high-temperature environments or regions with high heat flux density, if the temperature of the inner wall of the cooling channel is too high, the local cooling medium (such as deionized water) may approach its saturation state, inducing nucleus boiling or even film boiling, resulting in heat transfer deterioration, flow oscillation, or burn-out failure. Therefore, after obtaining the solid-liquid coupled temperature field, the simulation is performed on any position of the cooling channel. Verify the following phase transition safety constraints: In the formula, The temperature of the inner wall of the cooling channel (obtained by interpolation from the temperature field of the solid domain) is expressed in °C. The average temperature of the main fluid within the cooling channel (obtained from fluid domain simulation) is expressed in °C. This is the saturation temperature (boiling point) of the cooling medium at the current system operating pressure, in °C. This is the phase transition safety margin coefficient, dimensionless, with a range of values ​​of [value range missing]. .

[0025] The above constraints limit the wall superheat ( The temperature difference must not exceed the "residual temperature difference to the boiling point" ( Divide by the safety factor. When the inequality does not hold, it indicates a risk of nucleate boiling initiation (ONB), requiring immediate adjustment of cooling parameters. For example, increase the inlet flow rate, decrease the inlet temperature, or add microfins, turbulence columns, or other heat transfer enhancement structures in this region to ensure the system always operates within the single-phase forced convection safety range.

[0026] In a preferred embodiment, to prevent structural failure caused by high temperatures, the present invention also introduces a safety constraint coupled with thermal stress and temperature rise. In high-temperature environments, magnetic levitation motors not only face the risk of insulation failure, but their key structural components (such as the stator core and rotor sheath) also experience significant thermal stress due to non-uniform temperature rise, which may lead to microcracks or even mechanical failure. Therefore, the coupling limitation between temperature rise and structural strength should be considered simultaneously in the thermal protection design. To this end, after completing the preliminary design of the cooling system and obtaining the temperature field simulation results, the thermal stress level of key structural points is further verified, and its safety constraint expression is as follows: In the formula, This refers to the elastic modulus of the material, expressed in Pa. is the coefficient of linear expansion of the material, expressed in 1 / °C; The local temperature at the key structural points (obtained from temperature field simulation) is expressed in °C. For assembly reference temperature, it is usually taken as The unit is ; The allowable stress of the material at the operating temperature, in units of . ; For the safety factor, the value range is: .

[0027] The safety constraint expression is based on a simplified uniaxial thermal stress model and is used to estimate the upper limit of the equivalent thermal stress caused by temperature rise. When the local temperature obtained from the simulation causes the estimated stress to exceed the limit on the right, even if the motor temperature does not exceed the insulation safety threshold, the cooling channel layout needs to be readjusted (e.g., increasing the local cooling density in the high temperature gradient region or optimizing the flow channel direction) to achieve thermal synergistic protection and ensure structural integrity.

[0028] In a preferred embodiment, the step of dividing the node temperature set into temperature ranges to obtain several temperature bins includes: Determine the maximum and minimum temperatures in the set of node temperatures. Set the number of temperature-controlled bins. And calculate the width of each temperature bin. ; temperature range Divided into The first continuous temperature bin, the first The range of each temperature bin is: ,in .

[0029] In a preferred embodiment, the step of determining the first thermal risk zone and the second thermal risk zone by combining several temperature bins includes: Count the number of nodes in each temperature bin to obtain the node count sequence. from Begin traversing forward, calculating the ratio of the decrease in the number of nodes in adjacent buckets. When there exists a certain condition that makes When the preset mutation threshold is , and ), the first To the The physical areas corresponding to the temperature bins are defined as the first thermal risk area; the first to the second... The physical area corresponding to each temperature bin is determined as the second thermal risk area.

[0030] In a preferred embodiment, arranging cooling channels in the first thermal risk zone includes: Obtain the set of spatial coordinates of the first thermal risk area. ; Within the structurally permissible area of ​​the magnetic levitation motor, determine all areas where pipes can be installed; calculate... and intersection ;exist Cooling channels are arranged along the direction of maximum local temperature gradient, ensuring that the angle between the centerline of the cooling channels and the direction of this local temperature gradient is less than 1. A cooling medium is introduced into the cooling channel to form the integrated cooling system.

[0031] In a preferred embodiment, to further improve the scientific nature and energy efficiency of cooling channel layout, this invention proposes a cooling channel topology optimization objective function based on a trade-off between heat removal benefits and fluid transport costs, which guides the cooling channels within the permissible pipe layout area. Intelligent path planning within the area. Defining spatial location. Comprehensive benefit indicators of the site as follows: In the formula, It is a location Priority indicators for the layout of cooling channels at the location; For position The local heat flux density at a given location is calculated from the temperature field gradient. The unit is W / m 2 ; The maximum heat flux density over the entire area, expressed in W / m³. 2 ; From the cooling inlet to the location The estimated cumulative fluid pressure drop to be overcome, in Pa; The maximum allowable total pressure drop of the cooling system (determined by pump power limitations), in Pa; This is the priority weighting coefficient for hot removal, and its value range is... .

[0032] Pressure drop estimation method: The following formula can be used to estimate: in, The coefficient of friction, The cumulative flow path length (m) The hydraulic diameter (m) The density of the cooling medium (kg / m³) 3 ), The velocity is (m / s). During the channel path generation process, a graph search algorithm (such as the improved Dijkstra's algorithm) or a level set method is used to maximize the velocity along the path. The cumulative integral value is used as the target to automatically generate a cooling channel topology that balances efficient heat dissipation and low flow resistance. This example breaks through the limitations of traditional "hot spot" experience-based layout and realizes intelligent allocation of cooling resources and synergistic optimization of system energy efficiency.

[0033] In a preferred embodiment, the calculation of the heat generation rate of each component is performed using the following formula: in, Heat generation rate, unit: W / m 3 ; Component wear and tear, measured in W; The volume of the component is expressed in meters (m). 3 .

[0034] When establishing a temperature field model, it is necessary to know the heat generated per unit volume within each component of the motor, also known as the "heat generation rate." This value reflects the density of heat generation within the material and is a crucial input parameter in thermal simulation. During motor operation, copper losses occur due to current flowing through the windings, and iron losses occur in the iron core under an alternating magnetic field; these losses are ultimately released as heat. To convert these total losses into a distributed heat source suitable for use in the heat conduction equation, the total power loss of each component must be divided by its actual volume. In other words, the total heat generated by the entire component is "averaged" across its occupied space, thus obtaining how many watts of heat are generated per cubic meter of material per second. After this processing, components of different sizes and with different losses can be accurately described in a unified thermal model, providing a reliable heat source basis for subsequent solutions to temperature distribution.

[0035] In a preferred embodiment, establishing a mathematical model of the temperature field including thermal conductivity and convective heat transfer coefficient includes: The thermal conductivity of each component of the magnetic levitation motor is determined based on the material type and empirical formula. The convective heat transfer coefficient of its outer shell surface is calculated by computational fluid dynamics simulation of the external flow field and combined with the Nusselt number correlation. The heat generation rate, thermal conductivity, and convective heat transfer coefficient of each component are used as boundary conditions. These are then substituted into the steady-state heat conduction differential equation to obtain the mathematical model of the temperature field.

[0036] To accurately predict the temperature distribution of a magnetic levitation motor during operation, a mathematical model of the temperature field, incorporating both thermal conductivity and convective heat transfer characteristics, needs to be established. First, based on the materials used in each component of the motor (such as copper windings, silicon steel sheets, and aluminum alloy casing) and their physical properties, combined with empirical engineering formulas, the thermal conductivity of each material is determined. This reflects the ability of heat to be conducted within a solid. Second, regarding the heat exchange between the motor casing and the surrounding air, computational fluid dynamics (CFD) simulations of the external flow field are used to obtain the fluid flow state. Combined with the classic Nusselt number correlation, the convective heat transfer coefficient on the casing surface is calculated, which characterizes the efficiency of heat removal by the external air. Finally, the heat generation rate of each component due to electromagnetic losses is taken as the internal heat source. Simultaneously, the aforementioned thermal conductivity and convective heat transfer coefficients are used as key physical property parameters and boundary conditions, substituted into the steady-state thermal conduction control equation for solution, thus obtaining the temperature field distribution of the entire motor under thermal equilibrium. This process achieves a systematic integration from material properties and external cooling conditions to internal heating mechanisms, providing a reliable theoretical basis for motor thermal management design.

[0037] When establishing the mathematical model of its temperature field, the thermal conductivity of each component of the motor is first determined based on its material. For example, the stator core is made of silicon steel sheets, with a thermal conductivity of 30 W / (m·K); the windings are made of copper, with a thermal conductivity of 398 W / (m·K); and the outer casing is made of aluminum alloy, with a thermal conductivity of 205 W / (m·K). Next, computational fluid dynamics (CFD) software is used to simulate the external airflow field, simulating the flow state of the motor under natural convection or forced air cooling conditions. Combined with classic Nusselt number empirical correlations (such as formulas applicable to the outer surface of a cylinder), the convective heat transfer coefficients of different regions of the outer casing are calculated; for example, the side surface is approximately 15 W / (m·K). 2 ·K), the top is slightly higher due to the rising effect of hot air, take 20W / (m 2 Finally, the winding copper loss and core loss obtained from the electromagnetic simulation are converted into volumetric heat generation rate, which, together with the aforementioned thermal conductivity and convective heat transfer coefficient, are used as input parameters and substituted into the steady-state heat conduction equation (a classical equation in heat transfer). , Thermal conductivity, For temperature field, The temperature distribution of the entire machine can be obtained by solving the problem using finite element software (where the volume heat generation rate is used). The results show that the highest temperature of the winding is 98℃, which exceeds the preset safety threshold set by the system. This indicates that the current cooling scheme is insufficient to meet the thermal management requirements, and further measures such as enhancing air cooling, optimizing the structure, or reducing the load are needed to suppress the temperature rise.

[0038] In a preferred embodiment, the temperature field simulation of the magnetic levitation motor integrated with the cooling system includes: Set the inlet flow rate and inlet temperature of the cooling medium; The standard k-ε turbulence model and standard wall function are selected; By coupling electromagnetic and thermofluid multiphysics fields, the temperature field distribution across the entire motor domain and the pressure field distribution within the cooling channel are obtained.

[0039] When simulating the temperature field of a magnetic levitation motor in an integrated cooling system, the inlet conditions of the cooling medium (such as cooling water) must first be set, including flow velocity and temperature, which determine the initial cooling capacity and heat exchange potential. Next, in the numerical simulation, the standard k-ε turbulence model (a widely used numerical method that simulates the average flow characteristics and energy dissipation behavior of fluids in turbulent conditions by solving the transport equations of turbulent kinetic energy (k) and its dissipation rate (ε)) is used in conjunction with standard wall functions to describe the flow state of the fluid within the cooling channel. This is because cooling water flow is typically in a turbulent state, and this model can effectively capture the velocity distribution, energy dissipation, and heat transfer characteristics between the fluid and the wall in complex channels, while also considering computational efficiency and accuracy. Based on this, the simulation further couples the electromagnetic field, thermal field, and fluid field into a multiphysics field: the heat generated by electromagnetic losses during motor operation acts as a heat source, transferring to the structural materials and heating the cooling channel walls, while the flowing cooling medium continuously carries away this heat, and its flow is also affected by the channel geometry and pressure distribution. By jointly solving these interacting physical processes, a detailed temperature distribution inside the entire motor and the pressure field within the cooling channels can be obtained, thereby comprehensively evaluating the cooling effect, identifying potential hot spots, and providing a basis for subsequent structural optimization.

[0040] In a preferred embodiment, see Figure 2 Adjusting the layout parameters of the cooling channels, including: When the pressure difference between the inlet and outlet of the cooling channel obtained from the simulation exceeds the pump power limit, increase the channel cross-sectional area or reduce the number of bends. If the maximum temperature is still higher than the preset safety threshold, increase the flow rate of the cooling medium or reduce the inlet temperature.

[0041] In the design of a cooling system, simulation can be used to evaluate the performance of the cooling channels. If the simulation results show that the pressure difference between the inlet and outlet of the cooling channel is too large, exceeding the power limit provided by the pump, it indicates that the fluid flow resistance is too high. In this case, the channel structure needs to be optimized to reduce the pressure drop. A common approach is to appropriately increase the cross-sectional area of ​​the channel or reduce the number of bends. A larger flow cross-section reduces flow velocity and friction loss, while fewer bends reduce local resistance, thus maintaining the required flow rate without increasing pump power. On the other hand, if the highest temperature inside the motor is still higher than the set safety threshold after the above adjustments, it indicates that the current cooling capacity is insufficient to effectively remove heat. In this case, it is necessary to enhance the cooling effect: this can be achieved by increasing the flow rate of the cooling medium to accelerate heat transport, or by reducing the inlet temperature of the cooling water to increase the temperature difference between the cooling water and the heat-generating components, thereby improving heat exchange efficiency. These two strategies address the issue from the perspectives of "enhancing convection" and "increasing driving force," respectively. While meeting pump power constraints, they ensure that the temperature in critical areas remains within a safe range, ultimately achieving synergistic optimization of the cooling system structure and thermal control performance.

[0042] In a preferred embodiment, the operation of the cooling system needs to meet the energy consumption and temperature drop synergistic optimization constraint; The energy consumption and temperature drop collaborative optimization constraint is expressed by the following formula: in, This represents the pressure difference between the inlet and outlet of the cooling system, expressed in Pa. This refers to the volumetric flow rate of cooling water, in cubic meters per second (m³). 3 / s; This refers to the density of cooling water, expressed in kg / m³. 3 ; This refers to the specific heat capacity of cooling water at constant pressure, expressed in J / (kg·℃). and These are the inlet and outlet temperatures of the cooling water, respectively, in °C. The system energy efficiency coefficient is, and .

[0043] The operation of the cooling system must not only effectively remove the heat generated by the magnetic levitation motor, but also consider energy consumption. Therefore, a "coordinated optimization constraint of energy consumption and temperature drop" is introduced. The pump work consumed by the system (determined by the cooling water flow rate and pipeline pressure difference) cannot exceed the theoretical energy consumption limit corresponding to its actual heat exchange capacity. Specifically, the cooling water absorbs heat when flowing through the motor cooling channel, causing the outlet temperature to rise. This temperature rise reflects the system's heat dissipation effect; the energy required to drive the cooling water flow is proportional to the flow rate and pressure difference. To achieve high efficiency and energy saving, the mechanical work used to drive the cooling water per unit time must be minimized while ensuring sufficient temperature drop capacity. To this end, an energy efficiency coefficient greater than 1 is introduced as an adjustment factor to set a reasonable energy efficiency boundary. The cooling scheme is considered feasible only when the actual input pump work can be effectively converted into heat exchange benefits and the efficiency is not lower than this boundary. This avoids energy waste caused by excessive pressurization or excessive flow rate, and ensures that the cooling performance meets the temperature control requirements, thereby achieving a balance between heat dissipation effect and operating energy consumption, and realizing the efficient and economical operation of the cooling system.

[0044] In a preferred embodiment, such as Figure 3 As shown, after completing thermal protection, it also includes: Infrared images of the surface of the magnetic levitation motor during actual operation were acquired using an infrared thermal imager. The infrared image is subjected to median filtering to eliminate random noise, resulting in a denoised two-dimensional surface temperature distribution map.

[0045] After implementing thermal protection measures, the system uses an infrared thermal imager to non-contactly monitor the surface temperature of the magnetic levitation motor under actual operating conditions, acquiring an infrared image of its surface. This image essentially reflects the two-dimensional temperature distribution of the motor casing or visible components. However, due to environmental interference, equipment precision limitations, or electromagnetic noise, the original infrared image usually contains a certain amount of random noise, which may affect the accuracy of subsequent analysis. Therefore, median filtering is required to process the image. This is a commonly used image denoising method. Its basic principle is to select a small neighborhood around each pixel and replace the original pixel value with the median temperature value within that neighborhood, thereby effectively suppressing isolated outliers (such as salt-and-pepper noise) while better preserving edge and detail features in the temperature field. After this processing, a smoother and more reliable two-dimensional surface temperature distribution map is obtained, laying a high-quality data foundation for subsequent region segmentation, feature point extraction, and fusion of internal sensor data.

[0046] In a preferred embodiment, after performing median filtering on the infrared image, the method further includes: Based on the geometry of the magnetic levitation motor, the denoised two-dimensional surface temperature distribution map is divided into several sub-regions; Within each sub-region, pixels with a temperature gradient greater than a preset gradient threshold are selected as candidate feature points. From all candidate feature points, a representative set of feature points that is spatially balanced and covers all key heat-generating areas is selected; After obtaining the representative feature point set, the following is also included: Read the measured temperature data and spatial coordinates of several temperature sensors embedded inside the magnetic levitation motor; The infrared temperature of the representative feature points and the measured temperature of the internal sensor are used together as observation data for subsequent temperature field reconstruction.

[0047] After median filtering and denoising the infrared image, the system divides the entire two-dimensional surface temperature distribution map into several physically meaningful sub-regions, such as key areas like the stator end, rotor outer edge, or near cooling channels, based on the actual geometry of the magnetic levitation motor. This division helps focus on local thermal features and avoids information ambiguity caused by global processing. Next, within each sub-region, the system identifies locations with significant temperature changes by selecting pixels whose temperature gradient exceeds a preset threshold as candidate feature points. These points typically correspond to potential hotspots or heat conduction boundaries, and are highly valuable for reflecting the true thermal state. Subsequently, a set of representative feature points with a balanced spatial distribution that comprehensively covers all key heat-generating areas of the motor is further selected from all candidate points, ensuring that there is no over-concentration in any particular area, nor is any important heat source region overlooked. Based on this, the system also simultaneously reads the measured temperature and its precise spatial coordinates recorded by multiple temperature sensors embedded inside the motor. Finally, these internal sensor data and the infrared surface temperatures corresponding to the aforementioned representative feature points are combined to form a set of fused observation data for subsequent high-precision reconstruction of the three-dimensional temperature field. By using this method of internal and external data collaboration, we can not only utilize infrared images to provide rich information on surface thermal distribution, but also rely on internal sensors to ensure the accuracy of temperature in the core area, thereby significantly improving the reliability and physical consistency of the overall temperature field reconstruction.

[0048] In a preferred embodiment, in order to overcome the systematic errors in the simulation model caused by factors such as material parameter deviations and simplified boundary conditions, the present invention introduces an online self-calibration embodiment based on measured and simulated deviations after completing the initial temperature field reconstruction, thereby realizing the dynamic evolution of the thermal model.

[0049] Definition of the first In the next running cycle, the first The temperature residuals at each observation point (including representative feature points extracted from infrared images and embedded temperature sensors) are: in, For the first Cycle number Temperature residual at a point, in °C; For the first Cycle number The measured temperature at the point, in °C; For the first Cycle number The simulated temperature of the point is expressed in °C.

[0050] Based on the above residuals, the equivalent volumetric heat generation rate for the next cycle is corrected. For any element in the finite element mesh, the correction amount for its heat generation rate is... Calculated according to the following feedback law: In the formula, This is the correction amount to be superimposed on the nominal heat generation rate, in W / m³. 3 ; represents the learning gain coefficient, in units of The value must ensure closed-loop stability (in engineering practice, it is usually taken as...). ); This is the set of indices of all observation points associated with the current cell space; For the first Geometric weights for each observation point (e.g., using inverse distance weights) ,in (where the distance is from the observation point to the center of the cell) satisfies .

[0051] Finally, the total heat generation rate for the next cycle is updated as follows: In the formula, The nominal volumetric heat generation rate of the motor under rated operating conditions (obtained by calculation of electromagnetic losses or by referring to a table), in units of... . For the first The period is used for the corrected total volumetric heat generation rate in temperature field simulation, in units of The corrected total heat generation rate As a heat source term, it is re-inputted into the temperature field solver (i.e., a transient heat conduction simulation module based on the finite element method, such as the COMSOL Multiphysics thermal module) to execute a new round of thermal simulation and thermal risk assessment, thereby dynamically updating cooling control parameters or power scheduling strategies to form adaptive thermal protection commands. This strategy constructs an online learning closed loop of simulation, actual measurement, deviation analysis, model correction, and re-decision, enabling the thermal management system to have adaptive cognitive capabilities, effectively suppressing model uncertainty, and significantly improving temperature control accuracy and protection reliability under long-term operation.

[0052] In a preferred embodiment, the filtering of the representative feature point set includes: Calculate the Euclidean distance between any two candidate feature points; When the minimum distance between a candidate feature point and a selected feature point is less than a preset spacing threshold, the candidate feature point is removed. Repeat the above process until all remaining candidate feature points satisfy the minimum spacing constraint.

[0053] The purpose of selecting a representative feature point set is to choose key points that are evenly distributed and not too close to each other from a large number of candidate points, in order to avoid information redundancy and improve the efficiency and stability of subsequent processing (such as temperature field reconstruction or model fitting). Its working principle is as follows: First, calculate the spatial distance between any two candidate feature points; then, examine each candidate point one by one in a certain order. If the distance between a candidate point and a selected feature point is found to be less than a preset minimum distance threshold, the point is considered too close to an existing representative point, providing highly repetitive information, and is therefore discarded. This process continues, constantly selecting new representative points that meet the minimum distance requirement from the remaining candidate points, while simultaneously eliminating other points that are too close, until the distance between all remaining candidate points is no less than the set threshold. The resulting feature point set is relatively evenly distributed in space, effectively covering key areas while avoiding excessive local density, thus improving computational efficiency while maintaining accuracy.

[0054] In a preferred embodiment, when reconstructing the temperature field using observational data, a temperature field fusion consistency constraint is introduced to ensure that the reconstruction result simultaneously fits the infrared surface data and the internal sensor data; the temperature field fusion consistency constraint is expressed by the following formula: in, Output the three-dimensional temperature field model to be reconstructed; , For the first The location of each internal sensor and the measured temperature; , For the first The location and infrared temperature of a representative feature point; The weighting coefficient has a range of values. ; This is the tolerance threshold.

[0055] When reconstructing the three-dimensional temperature field inside the equipment using observational data, a scheme called "temperature field fusion consistency constraint" is introduced to ensure that the reconstruction results are consistent with both the measured values ​​of the internal sensors and the surface temperature data acquired by the infrared thermal imager. The temperature predicted by the reconstructed temperature field model at the location of the internal sensors should be as close as possible to the actual sensor measurements; simultaneously, in key areas of the surface covered by the infrared image, the model's predicted temperature should also be as close as possible to the infrared measured temperature. To balance the importance of these two types of data, a weighting coefficient is introduced to adjust the influence of infrared data on the overall constraint. Since internal sensors are generally more reliable, the weight of infrared data is set to no more than 1. Furthermore, an allowable error range (i.e., tolerance threshold) is set; as long as the weighted sum of the model's prediction deviations at the two types of locations does not exceed this threshold, the reconstruction result is considered reasonable and consistent. In this way, the reconstructed temperature field reflects both the true internal thermal state and the observed information on surface heat distribution, thereby improving the accuracy and physical reliability of the overall temperature field estimation.

[0056] In a preferred embodiment, the high-temperature environment refers to the operating environment in which the overall temperature of the magnetic levitation motor exceeds the maximum allowable operating temperature of H-class insulation material, which is 180°C, under rated operating conditions; the preset safety threshold does not exceed 80°C.

[0057] High-temperature environment refers to the situation where the overall temperature of a magnetic levitation motor exceeds the maximum operating temperature (180℃) that its Class H insulation material can withstand during normal full-load (i.e., rated operating condition) operation. Class H insulation material is a critical material in the motor used to isolate live parts, prevent short circuits, and ensure safety. If the temperature exceeds 180℃ for an extended period, its insulation performance will rapidly deteriorate, potentially leading to motor failure or even damage. Therefore, the system has a preset safety threshold of 80℃, used to monitor and determine whether the motor is in a safe operating state. This 80℃ does not refer to the temperature of the motor's internal windings or core components, but rather to the temperature limit of certain critical external or auxiliary parts (such as bearing housings, housings, or cooling medium outlets), serving as an early warning indicator. By comparing the actual monitored temperature with this safety threshold, the control system can take timely protective measures such as cooling, load reduction, or shutdown before the motor actually approaches dangerously high temperatures, effectively preventing insulation failure and equipment damage caused by overheating, and ensuring the long-term stable operation of the magnetic levitation motor with high reliability.

[0058] In a preferred embodiment, the system energy efficiency coefficient Determine as follows: Obtain the water pump power and heat dissipation of the cooling system; Calculate the theoretical minimum pump power; make It is the ratio of heat dissipation to pump power multiplied by the baseline efficiency coefficient, and This indicates that the system is in a high-efficiency operating range.

[0059] System energy efficiency coefficient Coefficient of performance (COP) is a key indicator used to measure the operating efficiency of a cooling system. Its determination method is based on actual operating data: first, the power currently consumed by the water pump in the cooling system and the actual heat dissipation carried away by the system are obtained; then, using thermodynamic principles, the theoretically minimum pump work required under the current heat dissipation demand is estimated (i.e., the minimum energy consumption necessary to complete the same heat dissipation task under ideal conditions). Based on this, the final COP is obtained by multiplying the ratio of heat dissipation to actual water pump power by a preset baseline efficiency coefficient. This coefficient has a clear physical meaning: when A value greater than 1 indicates that the system's current heat dissipation output is relatively high compared to the water pump's energy consumption, and its operating state is better than the baseline efficiency level, placing it in a high-efficiency operating range; conversely, if... A value less than or equal to 1 indicates that the system may have problems with high energy consumption or low heat dissipation efficiency. Therefore, the value not only reflects the energy efficiency performance of the cooling system, but also serves as an important basis for optimized control (such as adjusting the water pump speed or flow rate), thereby achieving a synergistic improvement in energy saving and thermal management.

[0060] In a preferred embodiment, a thermal protection system for a magnetic levitation motor in a high-temperature environment includes a processor and a memory that communicate with each other. The processor is used to read a computer program from the memory and execute it to implement the above-described thermal protection method for a magnetic levitation motor in a high-temperature environment.

[0061] Although the present invention has been described in conjunction with preferred embodiments, those skilled in the art, upon understanding the core concept of the invention, can make various modifications, adjustments, or substitutions. Therefore, it should be understood that the appended claims are intended to cover the above preferred embodiments, as well as all equivalent forms, modifications, and improvements falling within the spirit and scope of the invention. It should be emphasized that the above description is merely an exemplary embodiment of the present invention and is not intended to limit its scope of protection; any changes, equivalent substitutions, or optimizations made based on the technical essence of the present invention should be included within the protection scope of the present invention.

Claims

1. A thermal protection method for a magnetic levitation motor in a high-temperature environment, characterized in that, The method includes: Obtain the armature winding loss, excitation winding loss, and core loss of the magnetic levitation motor under rated operating conditions; Based on the losses of each component and their corresponding volumes, the heat generation rate of each component is calculated, and a mathematical model of the temperature field including thermal conductivity and convective heat transfer coefficient is established. Based on the temperature field mathematical model, the set of node temperatures across the entire magnetic levitation motor is determined, and the set of node temperatures is divided into temperature ranges to obtain several temperature bins. By combining the aforementioned temperature bins, a first thermal risk zone and a second thermal risk zone are determined, wherein the temperature of the first thermal risk zone is higher than that of the second thermal risk zone. Cooling channels are arranged in the first thermal risk area to form an integrated cooling system; Temperature field simulation was performed on the magnetic levitation motor integrated with the aforementioned cooling system to obtain its maximum temperature. When the maximum temperature exceeds the preset safety threshold, the arrangement parameters of the cooling channel are adjusted, and the simulation and adjustment are repeated until the maximum temperature drops below the preset safety threshold, thus completing the thermal protection.

2. The thermal protection method for a magnetic levitation motor in a high-temperature environment according to claim 1, characterized in that, The node temperature set is divided into temperature ranges, resulting in several temperature bins, including: Determine the maximum temperature in the set of node temperatures. and minimum temperature Set the number of temperature-controlled bins. And calculate the width of each temperature bin. ; temperature range Divided into The first continuous temperature bin, the first The range of each temperature bin is: ,in .

3. The thermal protection method for a magnetic levitation motor in a high-temperature environment according to claim 2, characterized in that, By combining several temperature bins, the first and second thermal risk zones are determined, including: Count the number of nodes in each temperature bin to obtain the node count sequence. from Begin traversing forward, calculating the ratio of the decrease in the number of nodes in adjacent buckets. When there exists a certain ) makes As a preset mutation threshold, and When ), the first To the The physical areas corresponding to the temperature bins are defined as the first thermal risk area; the first to the second... The physical area corresponding to each temperature bin is determined as the second thermal risk area.

4. The thermal protection method for a magnetic levitation motor in a high-temperature environment according to claim 1, characterized in that, Cooling aisles are arranged in the first heat risk zone, including: Obtain the set of spatial coordinates of the first thermal risk area. ; Within the structurally permissible area of ​​the magnetic levitation motor, all areas where pipes can be installed are identified. ;calculate and intersection ;exist Cooling channels are arranged along the direction of maximum local temperature gradient, ensuring that the angle between the centerline of the cooling channels and the direction of this local temperature gradient is less than 1. A cooling medium is introduced into the cooling channel to form the integrated cooling system.

5. The thermal protection method for a magnetic levitation motor in a high-temperature environment according to claim 1, characterized in that, The temperature field simulation of the magnetic levitation motor integrated with the cooling system includes: Set the inlet flow rate and inlet temperature of the cooling medium; The standard k-ε turbulence model and standard wall function are selected; By coupling electromagnetic and thermofluid multiphysics fields, the temperature field distribution across the entire motor domain and the pressure field distribution within the cooling channel are obtained.

6. The thermal protection method for a magnetic levitation motor in a high-temperature environment according to claim 5, characterized in that, Adjusting the layout parameters of the cooling channels, including: When the pressure difference between the inlet and outlet of the cooling channel obtained from the simulation exceeds the pump power limit, increase the channel cross-sectional area or reduce the number of bends. If the maximum temperature is still higher than the preset safety threshold, increase the flow rate of the cooling medium or reduce the inlet temperature.

7. The thermal protection method for a magnetic levitation motor in a high-temperature environment according to claim 6, characterized in that, The operation of the cooling system must meet the constraint of energy consumption and temperature drop synergistic optimization. The energy consumption and temperature drop collaborative optimization constraint is expressed by the following formula: ,in, This represents the pressure difference between the inlet and outlet of the cooling system, expressed in Pa. This refers to the volumetric flow rate of cooling water, in cubic meters per second (m³). 3 / s; This refers to the density of cooling water, expressed in kg / m³. 3 ; This refers to the specific heat capacity of cooling water at constant pressure, expressed in J / (kg·℃). and These are the inlet and outlet temperatures of the cooling water, respectively, in °C. The system energy efficiency coefficient is, and .

8. The thermal protection method for a magnetic levitation motor in a high-temperature environment according to claim 1, characterized in that, After completing thermal protection, it also includes: Infrared images of the surface of the magnetic levitation motor during actual operation were acquired using an infrared thermal imager. The infrared image is subjected to median filtering to eliminate random noise, resulting in a denoised two-dimensional surface temperature distribution map.

9. A thermal protection method for a magnetic levitation motor in a high-temperature environment according to claim 8, characterized in that, After median filtering of the infrared image, the process also includes: Based on the geometry of the magnetic levitation motor, the denoised two-dimensional surface temperature distribution map is divided into several sub-regions; Within each sub-region, pixels with a temperature gradient greater than a preset gradient threshold are selected as candidate feature points. From all candidate feature points, a representative set of feature points that is spatially balanced and covers all key heat-generating areas is selected; After obtaining the representative feature point set, the following is also included: Read the measured temperature data and spatial coordinates of several temperature sensors embedded inside the magnetic levitation motor; The infrared temperature of the representative feature points and the measured temperature of the internal sensor are used together as observation data for subsequent temperature field reconstruction.

10. A thermal protection method for a magnetic levitation motor in a high-temperature environment according to claim 9, characterized in that, When reconstructing the temperature field using observational data, a temperature field fusion consistency constraint is introduced to ensure that the reconstruction result simultaneously fits both infrared surface data and internal sensor data; the temperature field fusion consistency constraint is expressed by the following formula: ,in, Output the three-dimensional temperature field model to be reconstructed; , For the first The location of each internal sensor and the measured temperature; , For the first The location and infrared temperature of a representative feature point; The weighting coefficient has a range of values. ; This is the tolerance threshold.

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