Control box temperature control system construction method and control box overheating control method

Abstract

The invention discloses a control box temperature control system construction method and a control box overheating control method.The control box temperature control system construction method comprises the steps that a temperature field simulation model of a control box is constructed, and temperature field distribution in the control box is determined based on the simulation analysis result of the temperature field simulation model; determining an installation area of the temperature sensor according to the temperature field distribution, wherein the temperature gradient of the installation area is smaller than a preset temperature gradient; based on the installation area, carrying out system calibration on the temperature sensor so as to establish a compensation model of the measured value of the temperature sensor; and configuring the compensation model in the temperature control device, and establishing a communication connection relationship between the temperature control device and the temperature sensor and the active cooler so as to construct the temperature control system. The area with the relatively stable temperature gradient is selected as the installation area of the temperature sensor, and the temperature change trend in the control box is reflected more accurately.

Description

Technical Field

[0001] This invention relates to the field of electronic equipment technology, and in particular to a method for constructing a temperature control system for a control box and a method for controlling overheating of a control box. Background Technology

[0002] In related technologies, the temperature varies greatly at different points inside the control box. If the sensor is installed arbitrarily in a non-representative location, the sensor measurement value may be far lower than the actual highest temperature inside the control box, causing the temperature control system to misjudge the temperature as normal, when in fact the critical electronic components have overheated and been damaged. Summary of the Invention

[0003] This invention aims to at least solve one of the technical problems existing in the prior art. Therefore, one objective of this invention is to propose a method for constructing a temperature control system for a control box, selecting a region with a relatively stable temperature gradient as the installation area for the temperature sensor. This allows the monitored values ​​of the temperature sensor to more accurately reflect the temperature change trend inside the control box, reducing the risk of overheating damage caused by false alarms.

[0004] This invention also proposes a method for controlling overheating of the control box.

[0005] This invention provides a method for constructing a control box temperature control system, which includes the following steps:

[0006] Step S1: Construct a temperature field simulation model of the control box, and determine the temperature field distribution inside the control box based on the simulation analysis results of the temperature field simulation model;

[0007] Step S2: Determine the installation area of ​​the temperature sensor based on the temperature field distribution, wherein the temperature gradient of the installation area is less than a preset temperature gradient;

[0008] Step S3: Based on the installation area, perform system calibration on the temperature sensor to establish a compensation model for the measured value of the temperature sensor;

[0009] Step S4: Configure the compensation model in the temperature control device and establish a communication connection between the temperature control device, the temperature sensor, and the active cooler to construct a temperature control system.

[0010] Furthermore, step S1 has the following sub-steps:

[0011] Step S11: Construct the geometric model of the control box;

[0012] Step S12: Based on the geometric model, input the thermodynamic parameters of the control box and define the heat source inside the control box into the temperature field simulation model to construct the temperature field simulation model of the control box;

[0013] Step S13: Run the temperature field simulation model to obtain the temperature field distribution;

[0014] Step S14: Identify the region with a temperature gradient lower than the preset temperature gradient based on the temperature field distribution as the installation region.

[0015] Furthermore, the thermodynamic parameters include the thermal conductivity coefficient on the surface of the control box.

[0016] Furthermore, the surface of the control box is covered with a heat-resistant radiation and heat convection-resistant coating;

[0017] The thermodynamic parameters include the thermal conductivity coefficient of the heat-resistant radiation and heat convection coating.

[0018] Furthermore, the temperature field simulation model is established based on the steady-state heat conduction physical process, and its governing equation is:

[0019] ;

[0020] Where k is the thermal conductivity, T is the temperature field function, and Q is the heat source intensity inside the control box.

[0021] Furthermore, step S3 has the following sub-steps:

[0022] Step S31: Place the inside of the control box in a controlled temperature field established by a standard temperature source, and record the measured values ​​of the temperature sensors and calculate the measurement deviation values ​​at multiple preset standard temperature values.

[0023] , To measure the deviation value, To preset the standard temperature value, These are measured values;

[0024] Step S32: Construct a compensation model between the measured value and the compensated temperature value using the least squares method.

[0025] Furthermore, the compensation model is a linear model or a polynomial model.

[0026] Furthermore, when the deviation value changes linearly with the preset standard temperature value, the compensation model is a linear model:

[0027] ;

[0028] in, The temperature value is the compensated value. a and b are the temperature compensation coefficients calculated by linear regression. a represents the proportional correction coefficient and b represents the bias correction coefficient.

[0029] When the deviation value changes nonlinearly with the preset standard temperature value, the compensation model is a polynomial model, and polynomial coefficients are extracted from the polynomial model. The polynomial coefficients are the temperature compensation coefficients.

[0030] This invention provides a method for controlling overheating of a control box, applied to a temperature control system configured by the above-described control box temperature control system construction method, and executed by a temperature control device in the temperature control system, comprising the following steps:

[0031] Step S51: Receive the real-time temperature data collected by the temperature sensor inside the control box and generate the measured temperature value of the temperature sensor; call the compensation model stored in the sensor to process the measured temperature value of the temperature sensor to obtain the calibrated temperature value inside the control box.

[0032] Step S52: Compare the calibrated internal temperature value of the control box with the high temperature threshold and the low temperature threshold;

[0033] Step S53: When the internal temperature of the control box reaches or exceeds the high temperature threshold, the temperature control device controls the active cooler to start based on a preset control algorithm and continuously adjusts it at a preset rate to increase the cooling power and heat dissipation intensity.

[0034] When the temperature value drops to or below the low temperature threshold, the temperature control device controls the active cooler to continuously adjust at a preset rate to reduce the cooling power and heat dissipation intensity until it stops.

[0035] Furthermore, the control algorithm is configured as a PID control algorithm.

[0036] As can be seen from the technical solution, the embodiments provided by the present invention have the following advantages:

[0037] (1) By constructing a temperature field simulation model, temperature sensors are installed in areas with small temperature gradients to avoid measurement errors caused by local temperature fluctuations. At the same time, a compensation model is established through system calibration to further correct the measured values ​​of the temperature sensors. The measured values ​​of the temperature sensors can more realistically reflect the overall thermal state inside the control box.

[0038] (2) The temperature control device performs more precise start-up, shutdown and power adjustment of the active cooler based on the calibrated temperature value, preset threshold and control algorithm. This avoids the problems of over-cooling or under-cooling that are common in traditional temperature control, thereby saving energy, reducing operating costs and extending the service life of the active cooler. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 This is a flowchart illustrating the steps of constructing the temperature control system for the control box according to the present invention.

[0041] Figure 2 This is a cross-sectional schematic diagram of the control box body of the present invention;

[0042] Figure 3 This is a schematic diagram of the assembly structure of the control box and the active cooling device of the present invention. Detailed Implementation

[0043] Embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0044] The main function of the automatic control box is remote monitoring and control. It primarily houses electronic modules such as control modules, communication modules, power modules, and sensors. It can collect real-time data to achieve remote monitoring and control of power distribution lines and equipment. Through the communication module, it transmits operational data, such as current, voltage, and power factor, to the power distribution network dispatch center, enabling real-time load monitoring and providing a basis for power grid dispatch. Furthermore, in the event of a line fault, the automatic control box can automatically detect the fault signal and notify the control center, shortening fault handling time. It plays a crucial role in the operation of the power distribution network and is an important device for ensuring the safe operation of the power grid. The control box is typically installed outdoors on distribution poles, directly exposed to the natural environment, facing the effects of direct sunlight and high temperatures. The outer shell of the box is made of all-iron, and a fully sealed structure is used to protect it from small animals. The box lacks any insulation or heat dissipation features; in southern regions, the highest temperature measured inside the box has reached 60℃. Currently, common heat dissipation methods mainly include natural heat dissipation and simple fan cooling. Natural heat dissipation utilizes the natural convection between the control box and the surrounding air to dissipate some heat. This method is simple in structure, requires no additional power equipment, and is relatively inexpensive. Simple fan cooling, on the other hand, involves installing ordinary cooling fans on the surface of the box. The operation of the fans accelerates airflow, carrying away heat from inside the control box. Compared to natural heat dissipation, this method can improve heat dissipation efficiency to some extent.

[0045] Existing heat dissipation methods have many shortcomings. Natural heat dissipation is greatly affected by ambient temperature and airflow speed. In hot summers or environments with poor air circulation, its heat dissipation effect is extremely limited and cannot meet the heat dissipation requirements of the control box. While simple fan cooling can improve the heat dissipation effect to some extent, ordinary fans have relatively low heat dissipation efficiency and are easily affected by dust, oil, and other impurities. In outdoor environments, these impurities can easily enter the control box and adhere to the fan blades and the surface of electronic components. This not only affects the normal operation of the fan and reduces heat dissipation efficiency but may also lead to short circuits and corrosion of electronic components, further affecting the normal operation of the control box. Therefore, there is an urgent need for a more efficient and reliable overheat control method to solve the overheating problem of the automated control box on the distribution pole.

[0046] The following is for reference. Figures 1-3 A method for controlling overheating of a control box according to an embodiment of the present invention is described.

[0047] like Figure 1 As shown, this embodiment of the invention provides a method for constructing a control box temperature control system, which includes the following steps:

[0048] Step S1: Construct a temperature field simulation model of the control box, and determine the temperature field distribution inside the control box based on the simulation analysis results of the temperature field simulation model.

[0049] Specifically, step S1 has the following sub-steps:

[0050] Step S11: Construct the geometric model of the control box;

[0051] Step S12: Based on the geometric model, input the thermodynamic parameters of the control box and define the heat source inside the control box into the temperature field simulation model to construct the temperature field simulation model of the control box;

[0052] Step S13: Run the temperature field simulation model to obtain the temperature field distribution;

[0053] Step S14: Identify the area where the temperature gradient is lower than the preset temperature gradient based on the temperature field distribution as the installation area.

[0054] Thermodynamic parameters include the thermal conductivity coefficient on the surface of the control box.

[0055] When the surface of the control box is covered with a heat-resistant radiation and heat-convection coating, the thermodynamic parameters also include the thermal conductivity coefficient of the heat-resistant radiation and heat-convection coating.

[0056] The temperature field simulation model is based on the steady-state heat conduction physical process, and its governing equations are:

[0057] ;

[0058] Where k is the thermal conductivity, T is the temperature field function, and Q is the heat source intensity inside the control box.

[0059] In a specific example, a temperature field simulation model of the control box is established using thermal analysis software to facilitate the rational placement of sensors. First, a geometric model is constructed based on the actual structural dimensions of the control box, accurately defining the material properties of the control box shell and the heat sources of internal components. If the surface of the control box is covered with a heat-resistant radiation and convection coating (such as a nano-ceramic coating), then the thermodynamic parameters of the control box surface need to be replaced with the thermal conductivity coefficient k and surface emissivity ε of the nano-ceramic coating. These values ​​are obtained through material testing; typically, k is between 0.2 and 0.8 W / (m·K), and ε is higher than 0.85 to reflect its strong infrared reflectivity. After establishing the temperature field simulation model, a thermal simulation of the control box is performed under typical summer conditions, setting the ambient temperature to 40℃ and the solar radiation intensity to 800 W / m², simulating external heat sources caused by direct sunlight.

[0060] This means that the heat source includes the heat source of the internal components of the control box and the heat source of the external components of the control box. The heat source of the internal components is the heat source generated when the internal components of the control box are running, and the heat source of the external components is solar radiation.

[0061] The heat conduction process within the enclosure follows the steady-state heat conduction control equation:

[0062] ;

[0063] Where k represents the thermal conductivity of each material region, T is the temperature field function, and Q is the internal heat source intensity per unit volume. The temperature field simulation model takes into account the thermal radiation and convection exchange on the surface of the control box and the heating of internal components during the solution process. Through multiple iterations, the spatial distribution of the temperature field within the box is solved, and a temperature contour map is output.

[0064] Step S2: Determine the installation area of ​​the temperature sensor based on the temperature distribution field, and the temperature gradient of the installation area is less than the preset temperature gradient;

[0065] The analysis focused on the temperature gradient variation within the enclosure, particularly in areas far from heat sources but sensitive to overall thermal changes. Avoiding corner areas and areas directly around heat sources, the analysis selected regions with relatively stable temperature gradients as installation sites for temperature sensors. This ensured that the sensor readings more accurately reflected the temperature trends within the control enclosure. Finally, based on the thermal field distribution results, the selected areas were converted into specific coordinate points, creating a sensor deployment parameter table to guide subsequent installation.

[0066] The preset temperature gradient here refers to the maximum temperature change rate threshold preset by those skilled in the art based on the specific technical requirements, thermal design objectives and safety margins of the control box, which can be 0.5℃ / cm.

[0067] When the heat-resistant radiation and convection coating is a nano-ceramic coating, the thermodynamic parameters of the coating need to be input into the temperature field simulation model. These parameters include the nano-ceramic coating having a thermal conductivity ≤0.3 W / (m·K), a solar radiation absorptivity ≤0.25, a Q235 steel outer shell material with a thermal conductivity of 45 W / (m·K), and external environmental parameters: ambient temperature -20℃ to 60℃, and solar radiation intensity 800 W / m². The heat flux density distribution on the inner and outer surfaces of the enclosure is calculated using finite element analysis to determine that the temperature gradient error at the sensor installation location is ≤5%. This invention uses a nano-ceramic coating, which has a low thermal conductivity ≤0.3 W / (m·K) and low solar radiation absorptivity, effectively blocking the temperature rise of the enclosure from external heat sources. Simultaneously, an active cooling system is installed, consisting of a TEC1-12706 semiconductor cooling chip, a specific specification aluminum alloy heat sink, and a cooling fan. Four sets of these cooling systems are evenly installed on the four sides of the enclosure to ensure uniform heat dissipation and significantly improve heat dissipation efficiency.

[0068] When the heat radiation and convection protection coating is an aerogel coating, a nozzle with a diameter of 1.5-2.0 mm should be used, larger than that used for nano-ceramic coatings. The spray gun pressure should be adjusted to 0.2-0.3 MPa. Since aerogel is relatively lightweight, this avoids coating splattering due to high pressure. The spray gun should be 20-30 cm away from the outer surface, with a moving speed of 5-10 cm / s. A cross-spraying method should be used to ensure uniform coating thickness. The aerogel coating thickness should be appropriately reduced to 0.3-1.5 mm, and the coating needs to be applied in 2-3 coats, with each coat not exceeding 0.5 mm in thickness, and each coat spaced at least 1 hour apart. The curing environment for the aerogel coating should have a relative humidity ≤60% to avoid moisture absorption affecting performance; the temperature should be maintained at 15-25℃, and the curing time extended to 24-48 hours. When establishing a temperature field simulation model using thermal analysis software, the thermal conductivity parameters (thermal conductivity, emissivity, etc.) of the aerogel coating and the structural parameters of the enclosure should be accurately input. Different operating conditions should be set, such as direct sunlight, high-temperature environments, and internal heat sources, to simulate the temperature distribution inside the enclosure. Based on the simulation results, areas where the coating's thermal resistance is significantly affected, such as corners of the housing or near heat sources, are avoided to determine the optimal installation location for the temperature sensor and generate precise sensor installation coordinate parameters.

[0069] Step S3: Based on the installation area, perform system calibration on the temperature sensor to establish a compensation model for the measured values ​​of the temperature sensor;

[0070] Step S31: Place the inside of the control box in a controlled temperature field established by a standard temperature source, and record the measured values ​​of the temperature sensors at multiple preset standard temperature values, and calculate the measurement deviation value.

[0071] , To measure the deviation value, To preset the standard temperature value, These are measured values;

[0072] The temperature sensor can be a PT100 thermocouple. Temperature sensor calibration should be performed at more than 3 temperature points (e.g., 30℃, 45℃, 60℃), and the measured value of the temperature sensor should be recorded after each temperature point has stabilized for 30 minutes.

[0073] The 30-minute temperature stability here means that, within 30 minutes, the actual temperature change threshold of the temperature point is ≤ ±0.05°C, as monitored by a data acquisition device with an accuracy ≥ 0.1°C.

[0074] Step S32: Construct a compensation model between the measured value and the compensated temperature value using the least squares method.

[0075] Furthermore, the compensation model can be a linear model or a polynomial model; when the deviation value changes linearly with the preset standard temperature value, the compensation model is a linear model.

[0076] ;

[0077] in, The temperature value is the compensated value. a and b are the temperature compensation coefficients calculated by linear regression. a represents the proportional correction coefficient and b represents the bias correction coefficient.

[0078] When the deviation value changes nonlinearly with the preset standard temperature value, the compensation model is a polynomial model, and the polynomial coefficients are extracted from the polynomial model. The polynomial coefficients are the temperature compensation coefficients.

[0079] Step S33: Construct a two-dimensional dataset with a preset standard temperature value on the x-axis and a measurement deviation value ΔT on the y-axis; divide the entire temperature range of the temperature sensor into several fitting segments according to whether the absolute value of the measurement deviation value exceeds a first preset error threshold; wherein, when the absolute value of the measurement deviation value exceeds the first preset error threshold, the corresponding temperature range is divided into a fine fitting segment; when the absolute value of the measurement deviation value does not exceed the first preset error threshold, the corresponding temperature range is divided into a regular fitting segment;

[0080] Step S34: Calculate the residual δ based on the compensated temperature value from the compensation model and the preset standard temperature value. - , where δ is the residual;

[0081] Step S35: When N consecutive residuals in the fine fitting segment or the regular fitting segment exceed the second preset residual value, at least M temperature samples in thermal equilibrium are re-collected within the temperature range of the corresponding fitting segment. The compensation model of the segment is re-fitted using the least squares method, and the corresponding temperature compensation coefficient is updated. N≥3, M≥7.

[0082] Specifically, a first partitioning interval is configured for the fine-fit segment, and a second partitioning interval is configured for the regular-fit segment, with the first partitioning interval being smaller than the second partitioning interval.

[0083] In a specific example, before the control box is put into operation, the temperature sensor needs to be installed in the corresponding position inside the box based on the installation area obtained from the temperature field simulation model. After installation, to ensure the accuracy and stability of the temperature control system response, the sensor needs to be calibrated. The calibration process uses a standard temperature source to generate airflow at a preset standard temperature, which is then uniformly injected into the control box through a duct to maintain a stable and uniform reference temperature inside the control box.

[0084] Set multiple preset standard temperature values, and record the actual value measured by the temperature sensor at each preset standard temperature value. Compared with the preset standard temperature value And calculate the deviation value ΔT between the two. After collecting the measurement deviation values ​​corresponding to all preset standard temperature values, a compensation fitting model is constructed using the least squares method based on the measurement deviation values. If the measurement deviation values ​​change linearly, a first-order linear interpolation method is used.

[0085] ;

[0086] The temperature value is the compensated value. a and b are the temperature compensation coefficients calculated by linear regression. a represents the proportional correction coefficient and b represents the bias correction coefficient.

[0087] If the measurement deviation changes nonlinearly, a polynomial fitting model is used, such as a cubic polynomial:

[0088] ;

[0089] Where a, b, c...d are the polynomial coefficients obtained from the fitting. A complete temperature compensation coefficient table is generated based on the fitted model and written into the temperature control device, which then corrects the data collected by the temperature sensor in real time.

[0090] Then, the compensation effect of the temperature sensor under multiple preset standard temperature values ​​is verified. The absolute value of the residual between the temperature value after compensation model calibration and the preset standard temperature value should not be greater than 1℃ to meet the high-precision temperature monitoring requirements of the system.

[0091] To further improve the accuracy of temperature sensor monitoring data and avoid boundary errors caused by traditional piecewise fitting of fixed temperature ranges, especially abrupt error changes at phase transition points and high-temperature ranges, sensor calibration and compensation model optimization steps are set up based on the above-mentioned temperature sensor compensation model, as follows:

[0092] Error distribution pre-analysis (pre-calibration stage): Within the full range of the temperature sensor, such as -40℃ to 150℃, collect raw data for 30 minutes at 1℃ intervals after stabilization, and calculate the error ΔT at each temperature point, where ΔT = raw value - standard value;

[0093] Dynamic interval division: The K-means clustering algorithm is used to cluster the error data. The intervals where the ΔT fluctuation exceeds ±0.03℃ (the first preset error threshold) (the error peak area) are automatically divided into fine fitting segments. For example, -10~5℃ is the dew condensation error area, divided at 5℃ intervals. Within this segment, a calibration temperature point is set every 5℃. The error stability area ΔT≤±0.03℃ is divided into regular fitting segments, divided at 20℃ intervals. Within this segment, a calibration temperature point is set every 20℃. This solves the boundary error problem caused by traditional fixed segmentation.

[0094] Fitting segments and coefficients are dynamically updated: A residual feedback trigger mechanism is set up—after each calibration, the residual of the compensation model is calculated (residual = compensated value - standard value). If the residuals of 5 consecutive samples in a fitting segment all exceed ±0.02℃ (the second preset residual value can be set based on the accuracy requirements of the scheme), the secondary fitting of the segment is automatically triggered: 10 high-precision stable samples in the segment are re-collected, and the fitting coefficients of the segment are updated using the least squares method. No full-range recalibration is required, which improves maintenance efficiency.

[0095] It should be noted that when the temperature control device monitors the internal temperature of the control box in real time, it determines the fitting segment to which the temperature sensor belongs based on the actual measured value, calls the compensation coefficient corresponding to the fitting segment, calculates and processes the actual measured value, and obtains the calibrated internal temperature value of the temperature box.

[0096] Step S4: Configure the compensation model in the temperature control device and establish a communication connection between the temperature control device, the temperature sensor, and the active cooler to build a temperature control system.

[0097] like Figure 3As shown, in a specific example, the active cooling unit includes a thermoelectric cooler, a heat sink, and a cooling fan. The heat sink has multiple parallel-arranged fins with a spacing of 2-4 mm and a height of 30-50 mm. The thermoelectric cooler is a TEC1-12706 model. The cooling fan operates at 2000-3000 rpm with an airflow of 50-80 cubic meters per hour. During installation, the cold side of the thermoelectric cooler is pressed against the outer casing, and the hot side is connected to the heat sink. The fan is fixed to the heat sink. One set is installed on each of the four sides of the control box to ensure uniform heat dissipation. The active cooling unit can be magnetically attached to the heat dissipation areas of the casing. After evenly applying thermal grease to the cold side of the TEC1-12706 thermoelectric cooler, it is tightly adhered to the area of ​​the casing requiring heat dissipation, ensuring good contact to improve heat transfer efficiency. Then, the aluminum alloy heat sink is installed on the hot side of the thermoelectric cooler and secured firmly with screws or clips. Finally, install the cooling fan on the heatsink, connect the power cord, and ensure the cooling fan is functioning properly. Evenly install four sets of active cooling units on the four sides of the case, using neodymium iron boron magnets for magnetic connection, ensuring a secure connection with each magnet having an attraction force of ≥50N.

[0098] Retrofitting existing control boxes is difficult, live-line work is costly, and power outage work affects power supply reliability. This solution uses a magnetic attraction method for the active cooling unit. The neodymium iron boron magnets have a residual magnetism ≥1.2T and a single magnet attraction force ≥50N. They connect to the outer shell of the control box, making installation convenient. Furthermore, the overall retrofit process does not require large-scale structural changes to the control box, avoiding complex and costly disassembly and assembly work, and reducing installation and maintenance costs.

[0099] This invention also provides a control box overheat control method, applied to a temperature control system configured by the above-described control box temperature control system construction method, executed by a temperature control device in the temperature control system, and comprising the following steps:

[0100] Step S51: The temperature control device receives the real-time temperature data of the control box from the temperature sensor and generates the measured value of the temperature sensor; it calls the compensation model stored in its internal memory to process the measured value of the temperature sensor and obtain the calibrated temperature value of the control box.

[0101] Step S52: The temperature control device compares the calibrated internal temperature value of the control box with the high temperature threshold and the low temperature threshold;

[0102] Step S53: When the internal temperature of the control box reaches or exceeds the high temperature threshold, the temperature control device controls the active cooler to start based on the preset control algorithm and gradually increases the cooling power and heat dissipation intensity.

[0103] When the temperature drops to or below the low temperature threshold, the temperature control device controls the active cooler to gradually reduce the cooling power and heat dissipation intensity until it stops.

[0104] Furthermore, the control algorithm is configured as a PID control algorithm.

[0105] The temperature control device is connected to the active cooler. The temperature sensor collects the temperature inside the box in real time and generates the measured value of the temperature sensor, which is then transmitted to the temperature control device. The temperature control device calls the compensation model stored in it to process the measured value of the temperature sensor and obtain the calibrated temperature value inside the control box.

[0106] The high-temperature threshold was set to 55℃ and the low-temperature threshold to 45℃. When the internal temperature of the calibrated control box reached the high-temperature threshold, the temperature control device, based on the PID control algorithm, gradually increased the cooling power of the semiconductor refrigeration chip (maximum not exceeding 80% of the rated power) and the cooling fan speed (maximum 3000 rpm) at a rate of 0.5-1℃ / minute. When the temperature dropped to the low-temperature threshold, the cooling power and fan speed were gradually reduced at the same rate until they stopped. During the debugging process, more than three temperature fluctuation cycles were simulated to verify the accuracy and timeliness of the temperature control device's response.

[0107] The proportional coefficient Kp of the PID control algorithm is set to 0.8-1.2, the integral coefficient Ki is set to 0.1-0.3, and the derivative coefficient Kd is set to 0.05-0.1. The cooling power and fan speed are dynamically adjusted according to the rate of temperature change inside the chamber, so that the temperature control accuracy reaches ±1.5℃, while reducing the energy consumption of the cooler by more than 30%.

[0108] like Figure 2 As shown in the example, before applying the heat radiation and heat convection protection coating, under normal power distribution working conditions, maintenance personnel use a special cleaning agent (neutral detergent) and cleaning tools (soft brush, clean cloth) to slowly wipe along the surface of the control box housing to remove dust, oil, and other impurities, making the housing surface smooth and clean. After cleaning, apply a rust-preventive paint with a thickness of 0.1-0.3 mm within 24 hours to prevent the housing from rusting. After the rust-preventive paint has fully dried, it is ready for subsequent coating work.

[0109] In the case of power distribution control boxes installed on outdoor poles, construction personnel apply the nano-ceramic coating evenly to the pre-treated box shell surface using spraying or brushing methods. During spraying, the spray gun should be 15-25 cm away from the shell and moved at a stable speed to control the coating thickness at 0.5-2 mm. Before coating, the box shell should be sandblasted for 5-10 minutes with sand particles of 0.5-1.5 mm in diameter and a pressure of 0.4-0.6 MPa to increase surface roughness, improve coating adhesion, and effectively block the temperature rise of the box from external heat sources.

[0110] Then, a heat-resistant radiation and heat convection-resistant coating is applied to the outside of the sandblasted layer.

[0111] In this invention, the distribution box is precisely modeled using thermal analysis software, taking into account various thermophysical parameters such as nano-ceramic coatings. The sensor installation position is determined through finite element analysis to ensure that the temperature gradient error is ≤5%. After the temperature sensor is installed, it is calibrated. A compensation fitting model is constructed based on data collected at different temperature points to generate a temperature compensation coefficient table for real-time data correction. The temperature control device adopts a PID control algorithm with reasonable settings for the proportional coefficient Kp, integral coefficient Ki, and derivative coefficient Kd, which can achieve a temperature control accuracy of ±1.5℃, thus realizing precise temperature control.

[0112] As can be seen from the technical solution, the embodiments provided by the present invention have the following advantages:

[0113] (1) By constructing a temperature field simulation model, temperature sensors are installed in areas with small temperature gradients to avoid measurement errors caused by local temperature fluctuations. At the same time, a compensation model is established through system calibration to further correct the measured values ​​of the temperature sensors. The measured values ​​of the temperature sensors can more realistically reflect the overall thermal state inside the control box.

[0114] (2) The temperature control device performs more precise start-up, shutdown and power adjustment of the active cooler based on the calibrated temperature value, preset threshold and control algorithm. This avoids the problems of over-cooling or under-cooling that are common in traditional temperature control, thereby saving energy, reducing operating costs and extending the service life of the active cooler.

[0115] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0116] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. A method for constructing a temperature control system for a control box, characterized in that, The method comprises the following steps: Step S1: constructing a temperature field simulation model of the control box, determining the temperature field distribution in the control box based on the simulation analysis result of the temperature field simulation model; Step S2: determining the installation area of the temperature sensor according to the temperature field distribution, the temperature gradient of the installation area being less than a preset temperature gradient; Step S3: performing system calibration on the temperature sensor based on the installation area to establish a compensation model of the measured value of the temperature sensor; Step S4: configuring the compensation model in the temperature control device, and establishing the communication connection relationship between the temperature control device and the temperature sensor and the active cooler to construct a temperature control system.

2. The control box temperature control system construction method according to claim 1, wherein, The step S1 has the following sub-steps: Step S11: constructing a geometric model of the control box; Step S12: inputting the thermodynamic parameters of the control box and defining the heat source in the control box into the temperature field simulation model based on the geometric model to construct the temperature field simulation model of the control box; Step S13: running the temperature field simulation model to obtain the temperature field distribution; Step S14: identifying the area with a temperature gradient lower than the preset temperature gradient as the installation area according to the temperature field distribution.

3. The method of claim 2, wherein the control box temperature control system is constructed by, The thermodynamic parameters include the heat conduction coefficient on the surface of the box body of the control box.

4. The method of claim 2, wherein the temperature control system is a control box temperature control system. The surface of the control box is covered with a heat radiation and convection resistant coating; The thermodynamic parameters include the heat conduction coefficient of the heat radiation and convection resistant coating.

5. The method of claim 2, wherein the temperature control system is a control box temperature control system. The temperature field simulation model is established based on the steady-state heat conduction physical process, and the control equation thereof is: ； Wherein, k is the thermal conductivity coefficient, T is the temperature field function, and Q is the heat source intensity in the control box.

6. The method of claim 1, wherein the control box temperature control system is constructed by, The step S3 has the following sub-steps: Step S31: placing the inside of the control box in a controlled temperature field established by a standard temperature source, and recording the measured value of the temperature sensor and calculating the measurement deviation value at a plurality of preset standard temperature values: , To measure the deviation value, To set the standard temperature value, To measure the value; Step S32: constructing a compensation model between the measured value and the compensated temperature value by using the least square method.

7. The method of claim 6, wherein the control box temperature control system is constructed by, The compensation model is a linear model or a polynomial model.

8. The method of claim 7, wherein the control box temperature control system is constructed by, When the deviation value presents a linear change with the preset standard temperature value, the compensation model is a linear model: ； wherein, Tcomp is the compensated temperature value, a and b are temperature compensation coefficients calculated by linear regression, a represents a proportional correction coefficient, and b represents a bias correction coefficient. When the deviation value presents a nonlinear change with the preset standard temperature value, the compensation model is a polynomial model, and a polynomial coefficient is extracted from the polynomial model, the polynomial coefficient being the temperature compensation coefficient.

9. A control method of controlling overheat of a control box, characterized by, Applied to the temperature control system configured by the control box temperature control system construction method in any one of claims 1-8, executed by the temperature control device in the temperature control system, comprising the following steps: Step S51: receiving the temperature sensor real-time collected control box internal temperature and generating the temperature sensor measured value, calling the compensation model stored therein, processing the temperature sensor measured value to obtain the calibrated control box internal temperature value; Step S52: comparing the calibrated control box internal temperature value with the high temperature threshold and the low temperature threshold respectively; Step S53: When the temperature inside the control box reaches or exceeds the high temperature threshold, based on a preset control algorithm, the active cooler is controlled to start and continuously adjust at a preset rate to increase the refrigeration power and heat dissipation intensity. When the temperature value drops to or below the low temperature threshold, the active cooler is controlled to continuously adjust at a preset rate to reduce the refrigeration power and heat dissipation intensity until it stops.

10. The control box overheat control method of claim 9, wherein, The control algorithm is configured as a PID control algorithm.

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