A high-thermal-conductivity epoxy-encapsulated coil low-stress forming method

Abstract

This application discloses a low-stress molding method for high thermal conductivity epoxy-sealed coils, relating to the field of power equipment processing technology. The method includes: predicting the temperature response during the sealing and curing process to obtain a first predicted temperature sequence; constructing a parameter inversion objective function based on the first predicted temperature sequence and the corresponding first measured temperature; identifying a set of kinetic parameters based on the inversion objective function; predicting the temperature response during subsequent sealing and curing processes based on the set of kinetic parameters to obtain a second predicted temperature sequence; and dynamically adjusting the process parameters during the sealing and curing process based on the second predicted temperature sequence and the corresponding second measured temperature. This application, by inverting and identifying the temperature rise and exothermic behavior during the curing process and dynamically adjusting the curing process parameters, controls the curing reaction rate and exothermic peak, thereby reducing residual stress during curing and preventing cracking of the epoxy sealing layer.

Description

Technical Field

[0001] This application relates to the field of power equipment processing technology, and in particular to a low-stress forming method for high thermal conductivity epoxy-sealed coils. Background Technology

[0002] High thermal conductivity epoxy-sealed coils are widely used in electrical equipment such as dry-type transformers and reactors. Introducing a high proportion of thermally conductive fillers into the epoxy resin can significantly improve the heat dissipation capacity of the windings, but it also significantly alters the curing reaction characteristics of the epoxy system. In actual sealing and curing processes, high thermal conductivity epoxy systems typically exhibit characteristics such as high exothermic peaks, fast reaction rates, and narrow curing windows, easily forming localized high-temperature zones and large temperature gradients within the sealed body.

[0003] As the curing reaction proceeds, the material's elastic modulus increases rapidly. The mismatch between curing shrinkage and the constraints of the winding structure makes it difficult to release residual stress, especially at coil ends, corners, areas of abrupt thickness changes, and around slotted or perforated structures. This can easily lead to stress concentration and cracking of the seal layer, severely affecting insulation reliability and service life. Existing molding processes often use fixed heating rates and fixed holding times for curing control, typically based on empirical experiments to determine the process curve. However, in high thermal conductivity filler systems, different material batches, different seal volumes, and different heat dissipation conditions can all cause significant changes in curing kinetics. Fixed process curves are difficult to adapt to the actual curing process, resulting in insufficient molding reliability. Summary of the Invention

[0004] The main objective of this application is to propose a low-stress molding method for high thermal conductivity epoxy-sealed coils, which identifies and controls the curing process based on actual curing behavior.

[0005] To achieve the above objectives, this application proposes a low-stress molding method for high thermal conductivity epoxy-sealed coils, the method comprising the following steps: The temperature response during the sealing and curing process is predicted to obtain the first predicted temperature sequence. Construct a parameter inversion objective function based on the first predicted temperature sequence and the corresponding first measured temperature; The set of dynamic parameters is identified based on the inversion objective function; Based on the set of kinetic parameters, the temperature response during the subsequent sealing and curing process is predicted to obtain a second predicted temperature sequence. The process parameters during the sealing and curing process are dynamically adjusted based on the second predicted temperature sequence and the corresponding second measured temperature.

[0006] In some embodiments, predicting the temperature response during the sealing and curing process to obtain a first predicted temperature sequence includes the following steps: Acquire temperature and time data at monitoring points of the solidified body and ambient temperature during the solidification and curing process; A curing exothermic model was constructed based on the temperature and time data to characterize the curing exothermic effect and the temperature rise of the encapsulated body. A curing kinetic model was constructed to characterize the rate change characteristics of the curing reaction at different stages; Based on the ambient temperature, the curing exothermic model, and the curing kinetic model, the temperature response during the sealing and curing process is predicted to obtain the first predicted temperature sequence.

[0007] In some embodiments, constructing a curing exothermic model based on the temperature and time data to characterize the curing exothermic effect and the temperature rise of the encapsulated body includes the following steps: The curing exothermic model is constructed as follows: ; in, C eq The equivalent heat capacity of the solidified body; T ( t The measured temperature of the solidified body at the monitoring point is denoted as . T env ( t The ambient temperature outside the solidified body is described as ). h eq Equivalent heat dissipation parameters; m r The equivalent mass of epoxy resin participating in the curing reaction; Δ H The total exothermic reaction of the epoxy system per unit mass during curing; α ( t () represents the degree of curing.

[0008] In some embodiments, constructing a curing kinetic model to characterize the rate change characteristics of the curing reaction at different stages includes the following steps: The autocatalytic curing kinetic model is constructed as follows: ; Where, d α ( t ) / d t This represents the curing reaction rate; k 1 represents the rate constant for non-autocatalytic reactions; k 2 represents the rate constant of the autocatalytic reaction; m , n The reaction order is [number]. Reaction rate constant k 1. k 2. The following relationship is satisfied as temperature changes: ; ; in, A 1. A 2 is the preceding factor; E 1. E 2 represents the apparent activation energy; R It is the gas constant; T This is the curing reaction temperature.

[0009] In some embodiments, predicting the temperature response during the sealing and curing process based on the ambient temperature, the curing exothermic model, and the curing kinetic model to obtain the first predicted temperature sequence includes the following steps: Based on the ambient temperature, the curing exothermic model, and the curing kinetics model, the first predicted temperature sequence is obtained by solving the fourth-order Runge-Kutta method. The calculation formula for the fourth-order Runge-Kutta method includes: ; Discretize the time interval into a time-synchronous long-duration sequence: ; where Δ t For time step; Initial conditions are met: ; At any moment t i , degree of solidification α ( t Numerical updates: ; Among them, the function f α satisfy: ; The degree of curing will then be updated in the next time step as follows: ; Within the same time step, the temperature is also updated using the fourth-order Runge-Kutta method: ; Among them, the function f T satisfy: ; The temperature will be updated in the next time step as follows: ; For the multiple monitoring points set up, a corresponding energy balance equation is established for each monitoring point, and the fourth-order Runge-Kutta method is used to solve it simultaneously, thereby obtaining the first predicted temperature sequence for each monitoring point.T pred ( t ; i ).

[0010] In some embodiments, the step of constructing a parameter inversion objective function based on the first predicted temperature sequence and the corresponding first measured temperature includes the following steps: The objective function for parameter inversion is constructed as follows: ; in, i * These are the predicted values ​​for the set of dynamic parameters; i The actual values ​​of the set of dynamic parameters. i =[ A 1, E 1, A 2, E 2, m , n ]; N The number of sampling points participating in the inversion calculation; T means ( t i ) for in t i The measured temperature is collected at any time.

[0011] In some embodiments, the dynamic adjustment of process parameters during the sealing and curing process based on the second predicted temperature sequence and the corresponding second measured temperature includes the following steps: Determine whether the temperature peak of the second predicted temperature sequence exceeds a first preset threshold; Determine whether the temperature gradient between different temperature monitoring points exceeds a second preset threshold. An evaluation function is constructed to adjust process parameters to evaluate the impact of the peak temperature and the temperature gradient on the risk of curing stress. The evaluation function is: ; in, J The objective function value for adjusting process parameters; T core ( t ) is the monitoring point for the thermal center of the solidified body at time t The predicted temperature; T edge ( t ) for monitoring points on the surface or edge of the solidified body at time t The predicted temperature; l 1. l 2 represents the weighting coefficient; When generating the process profile, the following physical constraints are applied simultaneously: ; ; ; ; in, α ( t end () represents the degree of cure at the end of the curing process. α req The preset minimum degree of curing threshold, T max Δ is the maximum permissible curing temperature threshold. T max The maximum allowable temperature difference threshold, d T env ( t ) / d t For heating rate, u max This represents the maximum permissible heating rate.

[0012] In some embodiments, the method further includes the following steps: The second measured temperature is compared with the second predicted temperature sequence to achieve online correction; wherein, the deviation between the second measured temperature and the second predicted temperature sequence is defined as: ; in, For the aforementioned deviation, for t i The second measured temperature at time [time]. Based on the set of dynamic parameters Predicted t i The second predicted temperature sequence at time; When satisfied At that time, the online correction mechanism is triggered; in, e th To set the maximum allowable prediction error threshold, the online correction mechanism includes: re-executing the kinetic parameter inversion and updating the kinetic parameter set; reducing the subsequent heating rate and extending the slow heating phase; and adjusting the temperature of the insulation platform or extending the insulation time.

[0013] The embodiments of this application include at least the following beneficial effects: This application provides a low-stress molding method for high thermal conductivity epoxy-sealed coils. The method involves predicting the temperature response during the sealing and curing process to obtain a first predicted temperature sequence; constructing a parameter inversion objective function based on the first predicted temperature sequence and the corresponding first measured temperature; identifying a set of kinetic parameters based on the inversion objective function; predicting the temperature response during subsequent sealing and curing processes based on the set of kinetic parameters to obtain a second predicted temperature sequence; and dynamically adjusting the process parameters during sealing and curing based on the second predicted temperature sequence and the corresponding second measured temperature. By inverting and identifying the temperature rise and exothermic behavior during the curing process and dynamically adjusting the curing process parameters, this application controls the curing reaction rate and exothermic peak, thereby reducing residual stress during curing and preventing cracking of the epoxy sealant layer. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 A schematic flowchart illustrating a low-stress molding method for a high thermal conductivity epoxy-sealed coil provided in this application embodiment; Figure 2 This is a structural diagram of a high thermal conductivity epoxy-sealed coil provided in an embodiment of this application; Figure 3 A physical image of cracking in the seal layer of a high thermal conductivity epoxy-sealed coil provided in an embodiment of this application; Figure 4 This is a schematic flowchart of a low-stress molding method for high thermal conductivity epoxy-sealed coils based on curing kinetics inversion, provided in an embodiment of this application.

[0016] Figure reference numerals: 1-High thermal conductivity epoxy sealant; 2-Coil body; 3-Cracks formed under the action of residual stress during curing. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of methods consistent with the embodiments of this application as detailed in the appended claims.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0019] Reference Figure 1 This application provides a low-stress molding method for high thermal conductivity epoxy-sealed coils. This method may include, but is not limited to, steps S100 to S140, as detailed below: S100: Predict the temperature response during the sealing and curing process to obtain the first predicted temperature sequence; S110: Construct a parameter inversion objective function based on the first predicted temperature sequence and the corresponding first measured temperature; S120: The set of dynamic parameters is identified based on the inversion objective function; S130: Based on the set of kinetic parameters, predict the temperature response during the subsequent sealing and curing process to obtain a second predicted temperature sequence; S140: Dynamically adjust the process parameters during the sealing and curing process based on the second predicted temperature sequence and the corresponding second measured temperature.

[0020] Optionally, predicting the temperature response during the sealing and curing process to obtain a first predicted temperature sequence includes the following steps: Acquire temperature and time data at monitoring points of the solidified body and ambient temperature during the solidification and curing process; A curing exothermic model was constructed based on the temperature and time data to characterize the curing exothermic effect and the temperature rise of the encapsulated body. A curing kinetic model was constructed to characterize the rate change characteristics of the curing reaction at different stages; Based on the ambient temperature, the curing exothermic model, and the curing kinetic model, the temperature response during the sealing and curing process is predicted to obtain the first predicted temperature sequence.

[0021] Optionally, the step of constructing a curing exothermic model based on the temperature and time data to characterize the curing exothermic effect and the temperature rise of the encapsulated body includes the following steps: The curing exothermic model is constructed as follows: ; in, C eq The equivalent heat capacity of the solidified body; T ( t The measured temperature of the solidified body at the monitoring point is denoted as . T env ( tThe ambient temperature outside the solidified body is described as ). h eq Equivalent heat dissipation parameters; m r The equivalent mass of epoxy resin participating in the curing reaction; Δ H The total exothermic reaction of the epoxy system per unit mass during curing; α ( t () represents the degree of curing.

[0022] Optionally, the construction of a curing kinetic model to characterize the rate change characteristics of the curing reaction at different stages includes the following steps: The autocatalytic curing kinetic model is constructed as follows: ; Where, d α ( t ) / d t This represents the curing reaction rate; k 1 represents the rate constant for non-autocatalytic reactions; k 2 represents the rate constant of the autocatalytic reaction; m , n The reaction order is [number]. Reaction rate constant k 1. k 2. The following relationship is satisfied as temperature changes: ; ; in, A 1. A 2 is the preceding factor; E 1. E 2 represents the apparent activation energy; R It is the gas constant; T This is the curing reaction temperature.

[0023] Optionally, the step of predicting the temperature response during the sealing and curing process based on the ambient temperature, the curing exothermic model, and the curing kinetic model to obtain the first predicted temperature sequence includes the following steps: Based on the ambient temperature, the curing exothermic model, and the curing kinetics model, the first predicted temperature sequence is obtained by solving the fourth-order Runge-Kutta method. The calculation formula for the fourth-order Runge-Kutta method includes: ; Discretize the time interval into a time-synchronous long-duration sequence: ; where Δ t For time step; Initial conditions are met: ; At any moment t i , degree of solidification α ( t Numerical updates: ; Among them, the function f α satisfy: ; The degree of curing will then be updated in the next time step as follows: ; Within the same time step, the temperature is also updated using the fourth-order Runge-Kutta method: ; Among them, the function f T satisfy: ; The temperature will be updated in the next time step as follows: ; For the multiple monitoring points set up, a corresponding energy balance equation is established for each monitoring point, and the fourth-order Runge-Kutta method is used to solve it simultaneously, thereby obtaining the first predicted temperature sequence for each monitoring point. T pred ( t ; i ).

[0024] Optionally, the step of constructing the parameter inversion objective function based on the first predicted temperature sequence and the corresponding first measured temperature includes the following steps: The objective function for parameter inversion is constructed as follows: ; in, i * These are the predicted values ​​for the set of dynamic parameters; i The actual values ​​of the set of dynamic parameters. i =[ A 1, E 1, A 2, E 2, m , n ]; N The number of sampling points participating in the inversion calculation; T means ( t i ) for in t iThe measured temperature is collected at any time.

[0025] Optionally, the step of dynamically adjusting the process parameters during the sealing and curing process based on the second predicted temperature sequence and the corresponding second measured temperature includes the following steps: Determine whether the temperature peak of the second predicted temperature sequence exceeds a first preset threshold; Determine whether the temperature gradient between different temperature monitoring points exceeds a second preset threshold. An evaluation function is constructed to adjust process parameters to evaluate the impact of the peak temperature and the temperature gradient on the risk of curing stress. The evaluation function is: ; in, J The objective function value for adjusting process parameters; T core ( t ) is the monitoring point for the thermal center of the solidified body at time t The predicted temperature; T edge ( t ) for monitoring points on the surface or edge of the solidified body at time t The predicted temperature; l 1. l 2 represents the weighting coefficient; When generating the process profile, the following physical constraints are applied simultaneously: ; ; ; ; in, α ( t end () represents the degree of cure at the end of the curing process. α req The preset minimum degree of curing threshold, T max Δ is the maximum permissible curing temperature threshold. T max The maximum allowable temperature difference threshold, d T env ( t ) / d t For heating rate, u max This represents the maximum permissible heating rate.

[0026] Optionally, the method further includes the following steps: The second measured temperature is compared with the second predicted temperature sequence to achieve online correction; wherein, the deviation between the second measured temperature and the second predicted temperature sequence is defined as: ; in, For the aforementioned deviation, for t i The second measured temperature at time [time]. Based on the set of dynamic parameters Predicted t i The second predicted temperature sequence at time; When satisfied At that time, the online correction mechanism is triggered; in, e th To set the maximum allowable prediction error threshold, the online correction mechanism includes: re-executing the kinetic parameter inversion and updating the kinetic parameter set; reducing the subsequent heating rate and extending the slow heating phase; and adjusting the temperature of the insulation platform or extending the insulation time.

[0027] The following sections will provide a detailed description and explanation of some optional embodiments of this application, using specific application examples.

[0028] This embodiment relates to the field of electrical equipment insulation manufacturing and molding technology, specifically to a low-stress molding method for high thermal conductivity epoxy-sealed coils based on curing kinetics inversion. It is applicable to electrical equipment such as dry-type transformers and reactors that use high thermal conductivity epoxy materials for sealing and molding.

[0029] To address the issues of high thermal conductivity epoxy systems exhibiting strong exothermic activity, rapid temperature rise, and significant curing shrinkage during the curing process, which can easily lead to residual stress and cracking of the sealant layer under the constraint of the winding structure, this embodiment collects temperature-time data at key locations of the coil during the curing and early curing stages. A curing exothermic and temperature rise response model is established, and the curing kinetics under the specific curing conditions are identified through parameter inversion. Based on this, the heating rate, holding temperature, and holding time are dynamically adjusted to control the curing reaction rate and exothermic peak, limiting the temperature peak and temperature gradient, thereby reducing residual stress and suppressing cracking. This embodiment achieves low-stress and reliable molding of high thermal conductivity epoxy-sealed coils without changing the epoxy material formulation.

[0030] Specifically, this embodiment provides a low-stress molding method for high thermal conductivity epoxy-encapsulated coils based on curing kinetics inversion, used to control the encapsulation and curing process of high thermal conductivity epoxy-encapsulated coils, including the following steps: (1) Arrange at least two temperature monitoring points at key locations of the high thermal conductivity epoxy-sealed coil, and collect temperature-time data at each temperature monitoring point during the sealing and curing process, while also collecting ambient temperature data. (2) Based on the collected temperature-time data, a curing exothermic model is established to characterize the curing exothermics and the temperature rise of the solidified body, and the temperature change behavior of the solidified body during the curing process is described in combination with the curing kinetic model. (3) Based on the model, the curing kinetic parameters are inverted and identified to obtain the kinetic parameters that characterize the actual curing behavior of the high thermal conductivity epoxy system under the current sealing conditions; (4) Based on the kinetic parameters obtained by inversion, predict the temperature response in the subsequent curing process, and determine whether the predicted temperature peak and / or the temperature gradient between different temperature monitoring points exceed the preset threshold. (5) When the judgment result exceeds the preset threshold, adjust the heating rate, heat preservation temperature and / or heat preservation time in the solidification process, and return to step (4) to re-predict the temperature response. (6) When the judgment result does not exceed the preset threshold and the degree of curing reaches the preset requirement, the curing process is completed, and the solidified coil is cooled and demolded in a controlled manner to obtain a high thermal conductivity epoxy solidified coil with low stress forming. Among them, the temperature prediction and process adjustment in steps (4) and (5) are used to generate or correct the curing process control parameters of the heating equipment in the actual solidification production process.

[0031] Furthermore, the temperature monitoring points include at least the thermal center monitoring point located inside the solid enclosure, and the monitoring point located on the surface or edge area of ​​the solid enclosure.

[0032] Furthermore, the model relating curing heat release to the temperature rise of the solidified body is established based on the energy balance relationship and is used to describe the effect of curing heat release on the temperature change of the solidified body.

[0033] Furthermore, the curing kinetic model is a kinetic model used to describe the relationship between the degree of curing and time, preferably an autocatalytic curing kinetic model.

[0034] Furthermore, temperature response prediction and / or curing kinetic parameter inversion are achieved through numerical integration, numerical iteration, or table lookup.

[0035] Furthermore, the preset threshold includes at least one of the following: (a) The maximum permissible temperature threshold for the thermal center of the solid seal; (b) The maximum allowable temperature difference threshold between different temperature monitoring points.

[0036] Furthermore, during the curing process, the predicted temperature is continuously compared with the measured temperature. When the deviation between the two exceeds the preset error threshold, the curing kinetic parameters are re-executed and the subsequent curing process is corrected.

[0037] Specifically, this embodiment can be implemented through the following methods: (1) Monitoring point layout and data collection.

[0038] At least two temperature monitoring points are set at key locations within the sealant of the high thermal conductivity epoxy-sealed coil to collect temperature change information in different areas of the sealant during the sealing and curing process. The key locations can be selected based on the structure and geometry of the sealant coil, preferably including but not limited to the thermal center region inside the sealant, the surface or edge region of the sealant, and areas prone to stress concentration such as coil ends, corners, and edges of slotted or perforated structures.

[0039] During the sealing and curing process, temperature-time data at each monitoring point are collected in real time. T ( t (and simultaneously record the ambient temperature) T env ( t ).

[0040] (2) Inversion model.

[0041] The effect of curing exothermics on the temperature rise of the encapsulated body satisfies the following curing exothermic model: (1) In the formula, C eq The equivalent heat capacity of the solidified body characterizes the combined heat capacity of the epoxy resin, thermally conductive filler, winding structure, and mold, expressed in J / K. T ( t The measured temperature of the epoxy sealant at the monitoring point is expressed in °C. T env ( t () represents the external environment of the solidified body or the temperature of the heating furnace, in °C; h eq Equivalent heat dissipation parameters characterize the overall heat exchange capacity between the solid enclosure and the external environment, and are expressed in W / K. m r The equivalent mass of epoxy resin participating in the curing reaction is expressed in kg; Δ H The total exothermic reaction of the epoxy system per unit mass during curing is expressed in J / kg. α ( t ) represents the degree of curing, which characterizes the extent of the curing reaction in an epoxy system, and its value ranges from 0 to 1.

[0042] Curing degreeα ( t The evolution over time can be described using a curing kinetic model, preferably an autocatalytic curing kinetic model, to characterize the rate change characteristics of the curing reaction at different stages. One embodiment of this model is expressed as follows: (2) In the formula, d α ( t ) / d t The term represents the curing reaction rate, measured in seconds (s). -1 ; k 1 represents the rate constant for non-autocatalytic reactions, in units of s. -1 ; k 2 represents the autocatalytic reaction rate constant, in seconds. -1 ; m , n The reaction order describes the rate change characteristics of the curing reaction at different stages. The reaction rate constant. k 1. k 2. The temperature variation satisfies the Arrhenius relation: (3) (4) In the formula, A 1. A 2 is the pre-factor, characterizing the frequency response, with units of s. -1 ; E 1. E 2 represents the apparent activation energy, which characterizes the sensitivity of the reaction to temperature, and is expressed in J / mol. R The gas constant is 8.314 J / (mol·K); T This is the curing reaction temperature, expressed in Kelvin (K).

[0043] Based on temperature-time data measured at each monitoring point T ( t ), and ambient temperature T env ( t The set of dynamic parameters can be expressed as: i =[ A 1, E 1, A 2, E 2, m , n Based on the curing exothermic model and curing kinetic model, the temperature response during the curing process can be predicted using numerical integration methods. One feasible approach is to use the fourth-order Runge-Kutta method (RK4) for numerical solution. (5) Discretize the time interval into a time-synchronous long-duration sequence: (6) In the formula, Δ t Let be the time step. Initial conditions are satisfied: (7) At any moment t i , degree of solidification α ( t Numerical updates: (8) Where the function f α satisfy: (9) The degree of curing will then be updated in the next time step as follows: (10) Within the same time step, the temperature update also uses the fourth-order Runge-Kutta (RK4) method: (11) Where the function f T satisfy: (12) The temperature will be updated in the next time step as follows: (13) For cases with multiple temperature monitoring points, a corresponding energy balance equation is established for each monitoring point, and the fourth-order Runge-Kutta (RK4) integration process is used to solve it simultaneously, thereby obtaining the predicted temperature response for each monitoring point. T pred ( t ; i ).

[0044] The predicted temperature sequence obtained from equations (10)-(13) T pred ( t ; i ), and the measured temperature T means ( t i Together, they constitute the objective function for parameter inversion, used to identify the set of dynamic parameters. i * : (14) In the formula, i* This is the set of kinetic parameters obtained from the inversion, used to characterize the true curing kinetics of the high thermal conductivity epoxy system under the current sealing conditions; N The number of sampling points participating in the inversion calculation; T means ( t i ) for in t i The measured temperature is collected at any time.

[0045] (3) Dynamic adjustment of process based on inversion results.

[0046] Based on the kinetic parameters obtained from the inversion, the temperature response during the subsequent curing process is predicted, and it is determined whether the predicted temperature peak and / or the temperature gradient between different temperature monitoring points exceed a preset threshold. The preset threshold can be set according to material properties and process requirements. To facilitate the evaluation of the impact of temperature peak and temperature gradient on curing stress risk, an evaluation function for process adjustment reference can be constructed, one embodiment of which can be expressed as: (15) In the formula, J The objective function value for process adjustment is used to evaluate the unfavorable effect of the temperature field during the curing process; T core ( t ) is the monitoring point for the thermal center of the solidified body at time t The predicted temperature, in °C; T edge ( t ) for monitoring points on the surface or edge of the solidified body at time t The predicted temperature, in °C; l 1. l 2 is a weighting coefficient used to balance the influence of peak temperature and temperature gradient on curing stress. The objective function is used to constrain the peak temperature at the thermal center and the temperature difference between different locations, thereby indirectly limiting the superposition of thermal stress and curing shrinkage stress.

[0047] In addition, the following physical constraints are applied simultaneously when generating the process profile: (16) (17) (18) (19) In the formula, α ( t end () represents the degree of cure at the end of the curing process. α reqThe preset minimum degree of curing threshold, T max Δ is the maximum permissible curing temperature threshold. T max The maximum allowable temperature difference threshold, d T env ( t ) / d t For heating rate, u max This represents the maximum permissible heating rate.

[0048] (4) Online calibration.

[0049] During the curing process, measured temperature data from various temperature monitoring points are continuously collected and compared with data based on inversion parameters. i * The predicted temperature response is compared to the measured temperature to achieve online correction. The deviation between the predicted temperature and the measured temperature is defined as: (20) The current process curve is considered to deviate significantly from the actual curing behavior when the following conditions are met: (twenty one) In the formula, e th This is the maximum allowable prediction error threshold. When equation (21) is satisfied, the inversion prediction error is large, triggering an online correction mechanism: Re-execute the dynamic parameter inversion and update the parameter set; The subsequent heating rate was lowered to prolong the gradual heating phase; Adjust the temperature of the insulation platform or extend the insulation time to ensure complete curing.

[0050] For example, this embodiment provides an optional implementation method as follows: Figure 2 This is a structural diagram of a high thermal conductivity epoxy-encapsulated coil. The high thermal conductivity epoxy-encapsulated coil includes a high thermal conductivity epoxy encapsulation layer 1 and an encapsulated coil body 2; after encapsulation, the coil body 2 is wrapped by the high thermal conductivity epoxy encapsulation layer 1.

[0051] Figure 3 The photograph shows a cracking defect that occurs during the curing process of a high thermal conductivity epoxy-sealed coil, illustrating the technical problem to be solved in this embodiment. Obvious cracks 3 can be observed in the pore structure, groove structure, or geometric abrupt regions of the high thermal conductivity epoxy sealant layer 1.

[0052] In actual production, high thermal conductivity epoxy systems, due to their high filler content and concentrated heat release, are prone to rapid localized temperature increases during the curing reaction. Simultaneously, as the curing reaction proceeds, the material's elastic modulus increases rapidly, and the curing shrinkage is constrained by the structure of the coil body 2, making it difficult to release, resulting in significant residual stress within the sealing layer 1. When this residual stress accumulates in stress concentration areas such as the edges of hole or groove structures and exceeds the material's strength limit, cracks 3 will form in these areas, leading to epoxy sealing failure. This embodiment addresses the problem of high thermal conductivity epoxy sealed coils easily generating cracks 3 in localized areas during curing by proposing a low-stress molding method based on curing kinetics inversion.

[0053] Figure 4 This is a schematic diagram of the low-stress molding method for high thermal conductivity epoxy-encapsulated coils based on curing kinetics inversion in this embodiment. The steps are explained as follows: 21-Fixing and Layout of Monitoring Points; 22-Temperature-Time Data Acquisition; 23-Establishment of a curing exothermic-temperature rise model; 24-Inversion of curing kinetic parameters; 25-Temperature response prediction; 26. Whether the peak temperature or temperature gradient exceeds the limit; 27-Process parameter adjustment; 28 - Has the degree of curing met the requirements? 29 - Curing complete and demolding.

[0054] Specifically, the method includes the following steps: First, perform step 21 to complete the sealing operation of the high thermal conductivity epoxy-sealed coil, and arrange temperature monitoring points at key locations of the sealed body. The monitoring points include at least the thermal center monitoring point and the surface or edge monitoring points of the sealed body.

[0055] Subsequently, step 22 is executed, during the solidification and early curing stages, temperature-time data of each monitoring point are collected in real time, and heating furnace or ambient temperature data are collected simultaneously.

[0056] Next, step 23 is executed, establishing a curing exothermic-temperature rise coupled model based on the collected temperature data, and combining it with the curing kinetic model to describe the temperature change behavior during the curing process.

[0057] Then, step 24 is performed to invert and identify the curing kinetic parameters based on numerical methods, thereby obtaining a set of kinetic parameters characterizing the actual curing behavior of the high thermal conductivity epoxy system under the current sealing conditions.

[0058] Based on this, step 25 is performed to predict the temperature response of the subsequent curing process based on the kinetic parameters obtained by inversion, and the predicted temperature curve is obtained.

[0059] Then, step 26 is executed to determine whether the predicted peak temperature of the thermal center or the temperature gradient between different monitoring points exceeds the preset threshold. When the judgment result is yes, proceed to step 27 to adjust the heating rate, holding temperature or holding time to weaken the curing exothermic peak or reduce the temperature gradient, and return to step 25 to continue temperature prediction, forming a closed-loop process of inversion and adjustment. If the judgment result of step 26 is negative, and the prediction result meets the temperature peak and temperature gradient constraint requirements, proceed to step 28 to determine whether the degree of curing has reached the preset requirements; if it has not reached the preset requirements, continue to execute step 25; if it has reached the preset requirements, execute step 29 to complete the curing process, and perform controlled cooling and demolding on the solidified coil to finally obtain a low-stress-molded high thermal conductivity epoxy solidified coil.

[0060] The inversion-prediction-adjustment closed-loop control process formed through the above steps can effectively suppress sudden temperature rises and stress concentrations during the curing process, thereby avoiding phenomena such as... Figure 3 The epoxy sealant cracking defect shown is illustrated.

[0061] This embodiment has at least the following beneficial effects: (1) Adaptive adjustment of process based on curing kinetics inversion.

[0062] In this embodiment, during the solidification and early curing stages, temperature-time data at key locations of the epoxy solidified body are collected to invert and identify curing kinetic parameters. This allows for the characterization of the true curing reaction rate and exothermic characteristics of the high thermal conductivity epoxy system under the solidification conditions, avoiding the failure of traditional fixed process curves due to batch differences in materials, changes in solidification volume, or changes in heat dissipation conditions.

[0063] (2) Effectively limit the heat release peak and temperature gradient, and reduce the residual stress after curing.

[0064] By dynamically adjusting the heating rate, holding temperature, and holding time based on the inversion results, this embodiment can effectively limit the peak temperature of the thermal center of the solidified body and the temperature gradient between different locations while ensuring that the degree of curing meets the standard, thereby reducing the residual stress level caused by the superposition of thermal expansion mismatch and curing shrinkage.

[0065] (3) Significantly reduces the risk of cracking in complex structural regions.

[0066] For stress-sensitive areas such as coil ends, corners, slotted or hole structures, this embodiment uses multi-monitoring temperature constraints and dynamic process adjustment to suppress local temperature rises and stress concentration, effectively preventing cracking defects in the epoxy sealant layer in the above areas, and solving the engineering problem of easy cracking of high thermal conductivity epoxy sealant coils.

[0067] (4) No need to change the material formula, and it has strong engineering applicability.

[0068] This embodiment achieves low-stress molding through process control, without relying on adjustments to the epoxy resin or thermally conductive filler formulation. It is easy to implement on existing dry-type transformer and related electrical equipment production lines, and has good engineering feasibility and promotional value.

[0069] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0070] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0071] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0072] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0073] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A low-stress molding method for high thermal conductivity epoxy-sealed coils, characterized in that, The method includes the following steps: The temperature response during the sealing and curing process is predicted to obtain the first predicted temperature sequence. Construct a parameter inversion objective function based on the first predicted temperature sequence and the corresponding first measured temperature; The set of dynamic parameters is identified based on the inversion objective function; Based on the set of kinetic parameters, the temperature response during the subsequent sealing and curing process is predicted to obtain a second predicted temperature sequence. The process parameters during the sealing and curing process are dynamically adjusted based on the second predicted temperature sequence and the corresponding second measured temperature.

2. The low-stress molding method for a high thermal conductivity epoxy-sealed coil according to claim 1, characterized in that, The process of predicting the temperature response during the sealing and curing process to obtain a first predicted temperature sequence includes the following steps: Acquire temperature and time data at monitoring points of the solidified body and ambient temperature during the solidification and curing process; A curing exothermic model was constructed based on the temperature and time data to characterize the curing exothermic effect and the temperature rise of the encapsulated body. A curing kinetic model was constructed to characterize the rate change characteristics of the curing reaction at different stages; Based on the ambient temperature, the curing exothermic model, and the curing kinetic model, the temperature response during the sealing and curing process is predicted to obtain the first predicted temperature sequence.

3. The low-stress molding method for a high thermal conductivity epoxy-sealed coil according to claim 2, characterized in that, The step of constructing a curing exothermic model to characterize the curing exothermics and the temperature rise of the encapsulated body based on the temperature and time data includes the following steps: The curing exothermic model is constructed as follows: ； in, C eq The equivalent heat capacity of the solidified body; T ( t The measured temperature of the solidified body at the monitoring point is denoted as . T env ( t The ambient temperature outside the solidified body is denoted as . h eq Equivalent heat dissipation parameters; m r The equivalent mass of epoxy resin participating in the curing reaction; Δ H The total exothermic reaction of the curing reaction of the epoxy system per unit mass; α ( t () represents the degree of curing.

4. The low-stress molding method for a high thermal conductivity epoxy-sealed coil according to claim 3, characterized in that, The construction of a curing kinetic model to characterize the rate change characteristics of the curing reaction at different stages includes the following steps: The autocatalytic curing kinetic model is constructed as follows: ； Where, d α ( t ) / d t This represents the curing reaction rate; k 1 represents the rate constant for non-autocatalytic reactions; k 2 represents the rate constant of the autocatalytic reaction; m , n The reaction order is [number]. Reaction rate constant k 1. k 2. The following relationship is satisfied as temperature changes: ； ； in, A 1. A 2 is the preceding factor; E 1. E 2 represents the apparent activation energy; R It is the gas constant; T This is the curing reaction temperature.

5. The low-stress molding method for a high thermal conductivity epoxy-sealed coil according to claim 4, characterized in that, The method of predicting the temperature response during the sealing and curing process based on the ambient temperature, the curing exothermic model, and the curing kinetic model to obtain the first predicted temperature sequence includes the following steps: Based on the ambient temperature, the curing exothermic model, and the curing kinetics model, the first predicted temperature sequence is obtained by solving the fourth-order Runge-Kutta method. The calculation formula for the fourth-order Runge-Kutta method includes: ； Discretize the time interval into a time-synchronous long-duration sequence: ; where Δ t For time step; Initial conditions are met: ; At any moment t i , degree of solidification α ( t Numerical updates for ) ； Among them, the function f α satisfy: ； The degree of curing will then be updated in the next time step as follows: ； Within the same time step, the temperature is also updated using the fourth-order Runge-Kutta method: ； Among them, the function f T satisfy: ； The temperature will be updated in the next time step as follows: ； For the multiple monitoring points set up, a corresponding energy balance equation is established for each monitoring point, and the fourth-order Runge-Kutta method is used to solve it simultaneously, thereby obtaining the first predicted temperature sequence for each monitoring point. T pred ( t ; θ ).

6. The method for low-stress molding of a high thermal conductivity epoxy-sealed coil according to claim 5, characterized in that, The step of constructing the parameter inversion objective function based on the first predicted temperature sequence and the corresponding first measured temperature includes the following steps: The objective function for parameter inversion is constructed as follows: ； in, θ * These are the predicted values ​​for the set of dynamic parameters; θ The actual values ​​of the set of dynamic parameters. θ =[ A 1, E 1, A 2, E 2, m , n ]; N The number of sampling points participating in the inversion calculation; T means ( t i ) for in t i The measured temperature is collected at any time.

7. The method for low-stress molding of a high thermal conductivity epoxy-sealed coil according to claim 1, characterized in that, The dynamic adjustment of process parameters during the sealing and curing process based on the second predicted temperature sequence and the corresponding second measured temperature includes the following steps: Determine whether the temperature peak of the second predicted temperature sequence exceeds a first preset threshold; Determine whether the temperature gradient between different temperature monitoring points exceeds a second preset threshold. An evaluation function is constructed to adjust process parameters to evaluate the impact of the peak temperature and the temperature gradient on the risk of curing stress. The evaluation function is: ； in, J The objective function value for adjusting process parameters; T core ( t ) is the monitoring point for the thermal center of the solidified body at time t The predicted temperature; T edge ( t ) for monitoring points on the surface or edge of the solidified body at time t The predicted temperature; λ 1. λ 2 represents the weighting coefficient; When generating the process profile, the following physical constraints are applied simultaneously: ； ； ； ； in, α ( t end () represents the degree of cure at the end of the curing process. α req The preset minimum degree of curing threshold, T max Δ is the maximum permissible curing temperature threshold. T max The maximum allowable temperature difference threshold, d T env ( t ) / d t For heating rate, u max This represents the maximum permissible heating rate.

8. A low-stress molding method for a high thermal conductivity epoxy-sealed coil according to any one of claims 1 to 7, characterized in that, The method further includes the following steps: The second measured temperature is compared with the second predicted temperature sequence to achieve online correction; wherein, the deviation between the second measured temperature and the second predicted temperature sequence is defined as: ； in, For the aforementioned deviation, for t i The second measured temperature at time [time]. Based on the set of dynamic parameters Predicted t i The second predicted temperature sequence at time; When satisfied At that time, the online correction mechanism is triggered; in, e th To set the maximum allowable prediction error threshold, the online correction mechanism includes: re-executing the kinetic parameter inversion and updating the kinetic parameter set; reducing the subsequent heating rate and extending the slow heating phase; and adjusting the temperature of the insulation platform or extending the insulation time.

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