Charging pile oil immersion type temperature uniformity heat dissipation regulation method and system

Abstract

The present application relates to the technical field of process control, in particular to a charging pile oil-immersed uniform temperature heat dissipation regulation method and system, comprising the following steps: collecting the temperature and corresponding coordinates of each detection point of the power device and identifying the hot spot area, determining the main heat diffusion direction according to the temperature difference between the hot spot and the adjacent point, judging the expansion state by combining the area change of the previous and subsequent periods, outputting the corresponding adjustment voltage according to the diffusion direction and peripheral distribution, and then performing driving control after judging the consistency of the continuous period direction, realizing the directional regulation and balanced heat dissipation of the internal heat of the charging pile. In the present application, the hot spot area and diffusion direction are identified by associating temperature and coordinates, and the expansion trend is judged by combining the period area difference, the cooling medium in the microchannel is guided to flow to the key area preferentially according to the heat diffusion direction, and the short-term fluctuation misadjustment is inhibited by combining the peripheral bias adjustment, realizing the local heat containment and balanced diffusion, and improving the stability and response consistency of the heat management.

Description

Technical Field

[0001] This invention relates to the field of process control technology, and in particular to a method and system for regulating oil-immersed uniform temperature heat dissipation in charging piles. Background Technology

[0002] The field of process control technology mainly involves the real-time detection, comparative analysis, and closed-loop regulation of continuous or discrete process parameters such as temperature, pressure, flow rate, liquid level, current, voltage, and operating status. Core aspects include modeling the controlled object, acquiring sensor parameters, setting control laws, adjusting mechanisms, and managing the stability of the operating process. It is commonly used in scenarios such as thermal management of power electronic equipment, operation regulation of industrial equipment, and status control of new energy facilities. Its focus is on the continuous adjustment and coordinated control of key variables in the process based on changes in monitored parameters.

[0003] Among them, the traditional oil-immersed uniform temperature heat dissipation control method and system for charging piles refers to the temperature control solution for the heat generated by the rectifier module, power devices, transformer unit and connecting busbar inside the charging pile during high load operation. The technical issues it addresses are uneven heat source distribution inside the charging pile, continuous local temperature rise and adjustment of cooling medium circulation state. It usually involves immersing the power devices in insulating cooling oil, collecting the oil inlet temperature, outlet temperature and surface temperature of key heat-generating elements through temperature sensors, and combining the circulation pump speed adjustment, flow distribution of the guide channel, heat exchanger heat exchange process and controller preset temperature threshold comparison steps to continuously adjust the oil circulation path, flow rate and heat exchange rhythm to complete the temperature control of the uniform temperature heat dissipation process inside the charging pile.

[0004] Traditional oil-immersed uniform heat dissipation relies on a small number of temperature measurement points and comparison with fixed thresholds. The adjustment is based on the inlet and outlet temperatures and local surface temperatures. It lacks the ability to characterize spatial distribution and cannot reflect the diffusion path and evolution trend of heat inside the structure. The circulation pump speed and flow distribution are mostly adjusted according to the overall state. The identification of local hot spots is lagging. Cooling resources are easily consumed in non-critical areas while the supply in critical areas is insufficient. There is a coupling deviation between heat exchange rhythm and load fluctuation, which aggravates temperature field fluctuations, causes local temperature rise to accumulate continuously, increases the thermal stress of the device and affects the operational stability. Summary of the Invention

[0005] To address the technical problems existing in the prior art, this invention provides a method for regulating the uniform temperature dissipation of a charging pile using an oil-immersed system, comprising the following steps: S1: Collect the temperature and location coordinates of multiple detection points of the power device of the charging pile and perform correlation mapping, extract the location coordinates of detection points whose temperature exceeds the preset temperature threshold, and generate a hot spot region set; S2: Extract the temperature of multiple detection points and adjacent detection points in the hot spot region and calculate the difference. Extract the spatial connection direction of multiple detection points corresponding to the maximum temperature difference to generate the main diffusion direction. S3: Based on the hot spot region set, extract the position coordinates of non-hot spot region points and count the total number, calculate the current period area and the previous period area and determine the positive or negative sign of the difference, and generate expansion state features; S4: Based on the expansion state characteristics, obtain the spatial orientation coordinates of the charging pile microchannel oil circuit, output a positive control voltage to the microchannel that is consistent with the main diffusion direction, output a positive bias control voltage to the microchannel located outside the hot spot area set, and generate a solenoid valve adjustment command. S5: Perform time series consistency determination on the main diffusion direction for multiple consecutive time periods. When the direction is determined to be consistent, extract the solenoid valve adjustment command and apply the driving voltage to the charging pile electromagnetic proportional control valve pin to generate thermal control result.

[0006] As a further embodiment of the present invention, the hot spot region set includes temperature anomaly detection points, detection point location coordinates, and hot spot boundary information; the main diffusion direction includes the maximum temperature difference line, direction vector, and spatial orientation; the expansion state characteristics include the number of non-hot spot region points, the current period area, and the area change sign; the solenoid valve adjustment command includes the microchannel positive voltage, the peripheral microchannel bias voltage, and the control direction coordinates; and the thermal regulation result includes the time series consistency judgment result, the electromagnetic proportional control valve drive state, and the thermal regulation effect.

[0007] As a further aspect of the present invention, the specific steps of S1 are as follows: S101: Collect the output temperature of the surface temperature sensor array of the power device of the charging pile and the coordinates of multiple detection points, align the index numbers, match the temperature with the corresponding spatial coordinates, and perform attribute binding verification on the temperature field and the coordinate field to obtain the temperature coordinate set. S102: Based on the temperature field in the temperature coordinate set, a preset temperature threshold is called to perform item-by-item comparison calculation, identify the record item whose temperature value exceeds the temperature threshold, extract the corresponding spatial coordinate field of the record item that meets the condition and perform set recombination to obtain the over-threshold coordinate sequence. S103: Based on the spatial distribution relationship of multiple coordinate points in the super-threshold coordinate sequence, perform neighborhood distance determination calculation, cluster and merge coordinate points whose distance does not reach the preset spatial adjacency threshold, encode the merged multi-coordinate clusters by region number, and generate hot spot region set.

[0008] As a further aspect of the present invention, the temperature threshold is obtained by collecting the factory rated operating parameters of the charging pile power device and the real-time ambient temperature value, extracting the extreme tolerance temperature from the rated operating parameters as the benchmark upper limit, performing difference calculation between the real-time ambient temperature value and the standard ambient benchmark value to obtain the ambient temperature deviation, converting the ambient temperature deviation into a temperature compensation factor according to a preset proportional coefficient, and then linearly superimposing the temperature compensation factor and the benchmark upper limit to determine the temperature threshold.

[0009] As a further aspect of the present invention, the specific steps of S2 are as follows: S201: Extract the location coordinates of multiple detection points and the temperature of adjacent detection points within the hot spot region set; perform a pairwise difference operation on the temperature value of each detection point and the temperature value of adjacent detection points; pair and map the location coordinates of multiple detection points with multiple temperature difference items to obtain the neighboring point temperature difference set. S202: Perform amplitude comparison operation based on the multi-element values ​​of the adjacent point temperature difference set, sort the values ​​according to their size and locate the index position corresponding to the maximum difference, combine the index position with the reverse mapping to the set of detection point numbers, lock the corresponding two detection point numbers, and obtain the index of the extreme difference point pair. S203: Based on the extreme point index, call the position coordinates of the corresponding two detection points, perform coordinate difference operation to obtain the spatial displacement vector, normalize the direction of the spatial displacement vector and retain the direction component, and generate the main diffusion direction.

[0010] As a further aspect of the present invention, the specific steps of S3 are as follows: S301: Based on the hot spot region set, extract the position coordinates of the critical points of non-hot spot regions in the surrounding eight neighborhood space and count the total number of position coordinates. Serialize and arrange the position coordinates of multiple critical points according to the raster index sequence, and perform a counting and accumulation operation on the serialized coordinates to obtain the critical coordinate counting result. S302: Determine the hot spot boundary grid range based on the critical coordinate counting result, call the pixel area corresponding to the boundary grid range, perform area accumulation and addition operations on the current period grid number and the previous period grid number respectively, and perform difference subtraction operation on the two period area values ​​to obtain the period area difference result; S303: Based on the periodic area difference result, perform sign bit determination operation, compare the difference value with the zero reference value for sign and perform state marking encoding, map the sign marking result to the state feature encoding table, and generate extended state features.

[0011] As a further aspect of the present invention, the specific steps of S4 are as follows: S401: Obtain the spatial orientation coordinates of the microchannel oil path of the charging pile, calculate the cosine value of the angle between the multi-microchannel coordinate vector and the main diffusion direction, determine the sign of the cosine based on the zero reference value, extract the same-direction vector index and the opposite-direction vector index, and obtain the spatial orientation index set. S402: Based on the spatial orientation index set, call the expansion state feature, extract the expansion state identifier bit and compare it with the preset state judgment bit, output the state judgment Boolean value, and combine the hot spot region set coordinate boundary data to determine the regional membership of the microchannel to obtain the expansion periphery distribution sequence. S403: Based on the spatial orientation index set and the extended peripheral distribution sequence, assign positive control voltage parameters to the same-direction index and negative control voltage parameters to the opposite-direction index respectively, and when the state determination Boolean value is true, superimpose positive bias control voltage on the elements of the distribution sequence to generate a solenoid valve adjustment command.

[0012] As a further aspect of the present invention, the specific steps of S5 are as follows: S501: Obtain the main diffusion direction for three consecutive time periods, identify and record the direction value of the main diffusion direction for each time period, compare the direction values ​​in the sequence item by item, filter the direction items that meet the direction consistency judgment rules, and generate the time series direction consistency result. S502: Based on the time series direction consistency results, perform direction stability judgment on the consistency judgment results, compare each direction consistency value with a preset stability threshold, identify the direction items that meet the preset stability threshold, filter the direction index set corresponding to the driveable signal, and establish a stable direction index set. S503: Call the stable direction index set, extract the corresponding solenoid valve adjustment command, apply the driving voltage to the pin of the charging pile electromagnetic proportional control valve, switch the open or closed state of the microchannel electromagnetic proportional control valve according to the applied voltage, and generate thermal regulation results.

[0013] As a further aspect of the present invention, the stability threshold is determined by extracting the reference thermal diffusion offset angle under the rated operating conditions of the charging pile as the initial parameter, collecting the calibration error value of the temperature sensor, converting the calibration error value into the angle tolerance equivalent, and summing the reference thermal diffusion offset angle with the angle tolerance equivalent to obtain the directional tolerance compensation amount, and superimposing and correcting the initial parameter and the directional tolerance compensation amount.

[0014] The charging pile oil-immersed uniform temperature heat dissipation and control system includes: The temperature mapping module collects the temperature and location coordinates of multiple detection points of the charging pile power device and performs correlation mapping. It extracts the location coordinates of detection points whose temperature exceeds the preset temperature threshold, generates a hot spot region set, and transmits it to the gradient analysis module. The gradient analysis module extracts the temperature of multiple detection points and adjacent detection points in the hot spot region and calculates the difference. It extracts the spatial connection direction of multiple detection points corresponding to the maximum temperature difference, generates the main diffusion direction, and transmits it to the expansion evaluation module. The expansion assessment module extracts the position coordinates of non-hot spot points based on the hot spot region set and counts the total number, calculates the current cycle area and the previous cycle area and determines the positive or negative sign of the difference, generates expansion state features and transmits them to the valve control generation module. The valve control generation module obtains the spatial orientation coordinates of the charging pile microchannel oil circuit based on the expansion state characteristics, outputs a positive control voltage to the microchannel that is consistent with the main diffusion direction, outputs a positive bias control voltage to the microchannel located outside the hot spot area set, generates a solenoid valve adjustment command and transmits it to the drive execution module. The drive execution module performs time series consistency determination on the main diffusion direction for multiple consecutive time periods. When the direction is determined to be consistent, the module extracts the solenoid valve adjustment command and applies a drive voltage to the charging pile electromagnetic proportional control valve pin to generate thermal control results.

[0015] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In this invention, a spatial heat distribution is constructed by correlating temperature with location coordinates and hot spot region sets are extracted. The main diffusion direction is determined by combining the temperature difference between adjacent points. At the same time, the expansion state is determined based on the periodic area difference, forming a continuous characterization of the heat diffusion trend. On this basis, the microchannel is directionally driven according to the diffusion direction and a bias adjustment is applied to the periphery to promote the cooling medium to flow preferentially along the critical path. The continuous periodic direction consistency determination suppresses misadjustment caused by short-term fluctuations, thereby achieving rapid containment and balanced diffusion control of local hot spots, reducing temperature field inhomogeneity and fluctuation amplitude, and improving the overall thermal management stability and response consistency. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention, 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 the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the steps of the present invention; Figure 2 This is a detailed schematic diagram of S1 of the present invention; Figure 3 This is a detailed schematic diagram of S2 of the present invention; Figure 4 This is a detailed schematic diagram of S3 of the present invention; Figure 5 This is a detailed schematic diagram of S4 of the present invention; Figure 6 This is a detailed schematic diagram of S5 of the present invention; Figure 7 This is a system module diagram of the present invention. Detailed Implementation

[0018] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0019] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0020] Please see Figure 1 This invention provides a method for regulating the uniform temperature and heat dissipation of an oil-immersed charging pile, comprising the following steps: S1: Collect the temperature and location coordinates of multiple detection points of the power device of the charging pile and perform correlation mapping, extract the location coordinates of detection points whose temperature exceeds the preset temperature threshold, and generate a hot spot region set; S2: Extract the temperature of multiple detection points and adjacent detection points in the hot spot area and calculate the difference. Extract the spatial line direction of multiple detection points corresponding to the maximum temperature difference to generate the main diffusion direction. S3: Extract the location coordinates of non-hot spot points based on the hot spot region set and count the total number, calculate the current period area and the previous period area and determine the positive or negative sign of the difference, and generate expansion state features; S4: Based on the expansion state characteristics, obtain the spatial orientation coordinates of the charging pile microchannel oil circuit, output positive control voltage for the microchannel that is consistent with the main diffusion direction, output positive bias control voltage for the microchannel located on the periphery of the hot spot area set, and generate solenoid valve adjustment command. S5: Perform time series consistency determination on the main diffusion direction for multiple consecutive time periods. When the direction is determined to be consistent, extract the solenoid valve adjustment command and apply the driving voltage to the pin of the charging pile electromagnetic proportional control valve to generate thermal control results.

[0021] The hot spot region set includes temperature anomaly detection points, detection point location coordinates, and hot spot boundary information. The main diffusion direction includes the line connecting the maximum temperature difference, the direction vector, and the spatial orientation. The expansion state characteristics include the number of non-hot spot region points, the current period area, and the sign of area change. The solenoid valve adjustment command includes the microchannel positive voltage, the peripheral microchannel bias voltage, and the control direction coordinates. The thermal regulation results include the time series consistency judgment results, the electromagnetic proportional control valve drive status, and the thermal regulation effect.

[0022] Please see Figure 2 The specific steps of S1 are as follows: S101: Collect the output temperature of the surface temperature sensor array of the power device of the charging pile and the coordinates of multiple detection points, align the index numbers, match the temperature with the corresponding spatial coordinates, and perform attribute binding verification on the temperature field and the coordinate field to obtain the temperature coordinate set. A 16x16 array of platinum resistance thermometers deployed on the surface of the charging pile's insulated gate bipolar transistor continuously acquires real-time surface temperature data from 256 detection points at a sampling frequency of 10 Hz. The device's factory-calibrated three-dimensional spatial coordinate matrix is ​​retrieved via a data interface to extract the lateral, longitudinal, and depth position data for each detection point. A moving average filtering noise reduction operation is performed on the acquired real-time surface temperature data. The sampled data is divided into a sliding window containing five consecutive time points, and the average temperature value within each window is used to replace the original value at the center point, filtering out abrupt spikes and noise. The timestamp and sensor physical number of the real-time surface temperature data are extracted, and the spatial node number of the coordinate data is extracted simultaneously. Quantization is performed on non-numerical numbering information. The character combinations in the sensor physical number are extracted, converted to decimal values ​​according to the American Standard Code Interchange (ACS) code lookup table, and concatenated to generate a numerical reference index value. For example, if the sensor physical number contains the string "T1A", after conversion, the letter "T" is converted to 84, the number "1" to 49, and the letter "A" to 65, generating the reference index value 844965. Spatial node numbers are converted to be identical, generating index values ​​to be calibrated. An attribute binding verification operation is performed by comparing the baseline index value and the index value to be calibrated. If they are equal, a value of 1 is assigned; otherwise, a value of 0 is assigned. The ratio of the total number of values ​​assigned to 0 to the total number of nodes is calculated to obtain the coordinate matching error rate. If the coordinate matching error rate is lower than the preset fault tolerance baseline value, the verification passes. The preset fault tolerance baseline value is determined based on 1000 sensor anti-interference test data. The highest communication interruption rate obtained from the test is 1.5%, and an anti-interference margin of 0.5% is added, resulting in a preset fault tolerance baseline value of 2%. The actual total number of collected nodes is 256, and the total number of values ​​assigned to 0 is 3. Dividing 3 by 256 yields a coordinate matching error rate of 1.17%. A comparison is performed between 1.17% and 2%. Since 1.17% is lower than 2%, the attribute binding verification is considered passed. The 253 valid temperature fields that passed verification are then concatenated row-by-row with their corresponding three-dimensional spatial position data to generate a temperature coordinate set.

[0023] S102: Based on the temperature field in the temperature coordinate set, call the preset temperature threshold to perform item-by-item comparison calculation, identify the record item whose temperature value exceeds the temperature threshold, extract the corresponding spatial coordinate field of the record item that meets the condition and perform set recombination to obtain the over-threshold coordinate sequence. Extract all specific records from the temperature coordinate set and separate independent temperature fields containing real-time temperature information. Obtain the preset temperature threshold for the charging pile power devices. This preset temperature threshold depends on the upper limit of the factory rated operating temperature parameter and the experimental safety margin coefficient of the power devices. The upper limit of the factory rated operating temperature parameter is directly read from the device technical parameter manual. The experimental safety margin coefficient is determined by conducting extreme thermal fatigue failure tests on sampled devices from the same batch. Place 50 sample devices in an ambient temperature chamber and perform 500 rapid temperature rise and fall cycles at an ambient temperature of 40°C to 85°C. Record the percentage of devices whose junction temperature rises to the critical point where a significant surge in leakage current occurs. Obtain the average percentage point of thermodynamic failure as 85%. Lower the percentage by 5% as a safety buffer and determine the experimental safety margin coefficient as 80%. Obtain the upper limit of the factory rated operating temperature parameter as 120°C. Multiply 120°C by the experimental safety margin coefficient of 80% to obtain the preset temperature threshold of 96°C. The 253 independent temperature field values ​​extracted from the aforementioned temperature coordinate set were compared item by item with the predetermined preset temperature threshold of 96 degrees Celsius. During the traversal comparison process, when a record with a temperature value of 98.5 degrees Celsius was read, since 98.5 degrees Celsius is greater than 96 degrees Celsius, this record was marked as exceeding the high temperature limit and added to the pending processing sequence. For records that met the high temperature limit condition after all traversal comparisons, their internally bound horizontal position data, vertical position data, and depth position data were extracted. These extracted three-dimensional spatial position data were then sorted and reassembled according to their horizontal position values ​​in ascending order, forming a continuously stored over-threshold coordinate sequence. Some typical data from the aforementioned over-threshold coordinate sequence were organized to form the corresponding implementation test record information, as shown in Table 1.

[0024] Table 1. Detailed list of coordinate sequences exceeding the threshold 15 mm 20 mm 5 mm 98.5 degrees Celsius 18 mm 24 mm 5 mm 97.2 degrees Celsius 22 mm 21 mm 5 mm 96.8 degrees Celsius As shown in Table 1, the detailed parameters of the coordinates of each spatial point after extraction and recombination, as well as the recorded temperature values, all exceeded the preset temperature threshold.

[0025] S103: Based on the spatial distribution relationship of multiple coordinate points in the over-threshold coordinate sequence, perform neighborhood distance determination calculation, cluster and merge coordinate points whose distance does not reach the preset spatial adjacency threshold, encode the merged multi-coordinate clusters by region number, and generate hot spot region set; The system reads the lateral, longitudinal, and depth position data of each point in the generated over-threshold coordinate sequence one by one, and performs a neighborhood distance determination operation based on the spatial distribution relationship of multiple coordinate points. It extracts any first and second measured coordinate points from the sequence, and calculates the numerical differences between the two points in the lateral, longitudinal, and depth dimensions. The resulting differences in each of the three dimensions are squared, and the summation and square root operations are performed to obtain the actual physical straight-line distance between the first and second measured coordinate points. A preset spatial adjacency threshold parameter is set as the comparison basis for distance determination. This preset spatial adjacency threshold parameter is determined by actually measuring the average spacing of the microchannel structure inside the heat sink substrate of the power device. Physical slice measurements show that the average spacing of the microchannels is 5 mm. The preset spatial adjacency threshold is set to 1.5 times this average spacing. Multiplying 5 mm by 1.5 yields 7.5 mm, which is used as the discrimination benchmark value. The first coordinate point in the aforementioned over-threshold coordinate sequence details table, with a horizontal position of 15 mm, a vertical position of 20 mm, and a depth of 5 mm, is taken as the first measured coordinate point. The second coordinate point, with a horizontal position of 18 mm, a vertical position of 24 mm, and a depth of 5 mm, is taken as the second measured coordinate point. The horizontal difference between 18 mm and 15 mm is calculated to be 3 mm, the vertical difference between 24 mm and 20 mm is calculated to be 4 mm, and the depth difference between 5 mm and 5 mm is calculated to be 0 mm. The squares of 3, 4, and 0 are obtained as 9, 16, and 0, respectively. The sum of 9, 16, and 0 is obtained as 25. The square root of 25 is then taken to obtain the actual physical straight-line distance as 5 mm. The actual physical straight-line distance of 5 mm is compared with the preset spatial adjacency threshold of 7.5 mm. Since 5 mm is less than 7.5 mm, it meets the condition that the distance does not reach the preset spatial adjacency threshold. For multiple coordinate points that meet the condition, a clustering and merging operation is performed to mark their actual physical attributes as the same local high-heat connected region. After performing this calculation and determination on all points in the sequence, multiple independent high-thermal-connectivity multi-coordinate clusters are formed. The total number of coordinate points contained in each multi-coordinate cluster is counted, and each multi-coordinate cluster is assigned an integer region number code starting from the number 1 in descending order of the total number of coordinate points, generating a set of hotspot regions with clear location boundaries and unique numerical identifiers.

[0026] Please see Figure 3 The specific steps of S2 are as follows: S201: Extract the location coordinates of multiple detection points and the temperature of adjacent detection points within the hot spot region set. Perform a pairwise difference operation on the temperature value of each detection point and the temperature value of adjacent detection points. Pair and map the location coordinates of multiple detection points with multiple temperature difference items to obtain the neighboring point temperature difference set. From the generated hot spot regions, extract the local high-thermal connectivity region coded as region 1, and retrieve the three-dimensional spatial coordinates and corresponding real-time surface temperature data of multiple detection points contained within this region. For any extracted central detection point, define the physical distance neighborhood based on the previously calculated preset spatial adjacency threshold of 7.5 mm, and traverse and search all adjacent detection points within this physical distance neighborhood. Extract the real-time surface temperature value of the central detection point, and simultaneously extract the real-time surface temperature values ​​of each of the retrieved adjacent detection points, performing a pairwise difference operation. Specifically, subtract the temperature value of the central detection point from the temperature value of each adjacent detection point, and calculate the absolute value of the subtraction result to obtain multiple corresponding temperature difference items. For example, the real-time surface temperature of the central detection point at a horizontal position of 15 mm, a vertical position of 20 mm, and a depth of 5 mm is 98.5 degrees Celsius. Simultaneously, the real-time surface temperature of its adjacent detection point at a horizontal position of 18 mm, a vertical position of 24 mm, and a depth of 5 mm is found to be 97.2 degrees Celsius. Substituting 98.5 degrees Celsius and 97.2 degrees Celsius into the equation and performing a subtraction operation to obtain the absolute value, the specific temperature difference is 1.3 degrees Celsius. After calculating the differences between all central detection points and their corresponding adjacent detection points within this high-heat connectivity region, the horizontal, vertical, and depth data of the central detection points, as well as the three-dimensional coordinate data of each adjacent detection point, are combined with the calculated temperature difference of 1.3 degrees Celsius to establish a one-to-one pairing mapping relationship. This process is repeated for all local high-heat connectivity regions within the hotspot region set, involving neighborhood range searching, temperature difference calculation, and coordinate mapping combination operations, ultimately generating a neighboring point temperature difference set containing all position pairing relationships and specific temperature difference items.

[0027] S202: Perform amplitude comparison operation based on multi-element values ​​of temperature difference set of neighboring points, sort the values ​​according to their size and locate the index position corresponding to the maximum difference, combine the index position to back-map to the set of detection point numbers, lock the corresponding two detection point numbers, and obtain the index of the extreme difference point pair; Read all temperature difference items from the generated neighbor temperature difference set, extract these multi-element values, and perform amplitude comparison operations. Compare the extracted first and second temperature difference items, retaining the larger difference as the current temporary maximum value. Then, iterate through and compare this temporary maximum value with each subsequent temperature difference item in the sequence, continuously updating the temporary maximum value in each comparison, until all element values ​​in the neighbor temperature difference set have been traversed. Reorganize all records in the neighbor temperature difference set according to the descending order of temperature difference values, generating a complete descending sequence. Extract the first record from the descending sequence, read its corresponding row number in the data table, and determine it as the index position of the maximum difference. For example, substitute the previously calculated temperature difference item 1.3 degrees Celsius, and simultaneously obtain other temperature difference items in the set, such as 0.8 degrees Celsius and 1.1 degrees Celsius. The values ​​of 1.3 degrees Celsius are compared sequentially with 0.8 degrees Celsius and 1.1 degrees Celsius. 1.3 degrees Celsius is determined to be the maximum value in the current set, and its data entry is moved to the beginning of the sequence. The first row containing this value is designated as the index position corresponding to the maximum difference. The coordinates of the center detection point and adjacent detection points within this index position are extracted. A pre-defined spatial node number lookup table is retrieved from the equipment's manufacturing process. Using the extracted coordinate values, a reverse lookup and cross-matching operation is performed to retrieve the original node identifier codes corresponding to these two coordinates from the lookup table, thus accurately locating the two corresponding detection point numbers. The locked center detection point number and adjacent detection point numbers are concatenated to generate a range point index that uniquely identifies the physical location of the extreme temperature difference.

[0028] S203: Based on the extreme point index, call the coordinates of the corresponding two detection points, perform coordinate difference operation to obtain the spatial displacement vector, normalize the direction of the spatial displacement vector and retain the direction component, and generate the main diffusion direction; The generated extreme point pair index is extracted and used to initiate a data retrieval command to the spatial coordinate database, reading the lateral, longitudinal, and depth position data corresponding to the precisely locked center detection point and its adjacent detection points. Coordinate difference operations are performed on the two sets of acquired three-dimensional spatial coordinates, subtracting the lateral, longitudinal, and depth position values ​​of the center detection point from the values ​​of the adjacent detection points, respectively, to obtain the physical displacement differences in the three spatial coordinate dimensions. These calculated displacement differences are combined into a three-dimensional floating-point array to construct a spatial displacement vector representing the direction of heat transfer. For example, using the previously locked center detection point coordinates of 15 mm lateral, 20 mm longitudinal, and 5 mm depth, and the adjacent detection point coordinates of 18 mm lateral, 24 mm longitudinal, and 5 mm depth, subtracting 15 mm from 18 mm yields a lateral displacement difference of 3 mm, subtracting 20 mm from 24 mm yields a longitudinal displacement difference of 4 mm, and subtracting 5 mm from 5 mm yields a depth displacement difference of 0 mm, resulting in a spatial displacement vector of 3, 4, and 0. The differences in the three dimensions of the spatial displacement vector are extracted, squared, and then summed. Specifically, the squares of 3 (9), 4 (16), and 0 (0) are summed to obtain a value of 25. The square root of 25 yields the actual modulus of the vector as 5. Direction normalization is then performed on the spatial displacement vector. The lateral, longitudinal, and depth displacement differences are divided by the calculated actual modulus to obtain the directional components retained after removing distance factors. Dividing 3 by 5 gives 0.6, 4 by 5 gives 0.8, and 0 by 5 gives 0, ultimately generating a standard unit vector consisting of 0.6, 0.8, and 0, which is set as the main diffusion direction.

[0029] Please see Figure 4 The specific steps of S3 are as follows: S301: Based on the hot spot region set, extract the position coordinates of the critical points of non-hot spot regions in the surrounding eight neighborhood space and count the total number of position coordinates. Serialize and arrange the position coordinates of multiple critical points according to the raster index sequence, and perform a counting and accumulation operation on the serialized coordinates to obtain the critical coordinate count result. The generated hotspot region set is directly extracted to obtain the set of edge coordinate points with a center position of 15 mm horizontally, 20 mm vertically, and 5 mm deep. The local spatial search range is set to the 8-neighborhood space surrounding the corresponding coordinate point. Using a two-dimensional planar coordinate offset rule—increasing or decreasing the spatial resolution step size by one for both the horizontal and vertical positions—the 8 adjacent peripheral coordinate points are retrieved. The spatial resolution step size, defined in the previous steps, is 3 mm, resulting in a horizontal offset range of 12 mm to 18 mm and a vertical offset range of 17 mm to 23 mm. These retrieved peripheral coordinate points are iterated through, and the corresponding real-time surface temperature values ​​are retrieved for each point. These real-time temperature values ​​are compared one by one with the previously set preset temperature threshold of 96 degrees Celsius. If the real-time temperature value of a peripheral coordinate point is lower than 96 degrees Celsius, that point is determined to be a non-hotspot region critical point. After executing the above judgment logic, the location coordinates of three non-hotspot region critical points that meet the conditions are selected from the 8-neighbor space: 12 mm horizontally and 20 mm vertically, 15 mm horizontally and 17 mm vertically, and 18 mm horizontally and 17 mm vertically. The obtained multi-critical point location coordinates are counted and statistically analyzed, confirming a total of three location coordinates. Based on the preset absolute physical grid division rules of the equipment measurement, the physical grid number information corresponding to each critical point location coordinate is extracted, generating a digital grid index sequence. Following the grid index sequence in ascending order, the horizontal value is used as the first sorting parameter, and the vertical value as the second sorting parameter, to serialize and arrange the above three multi-critical point location coordinates. Based on the sorted sequence, a count register variable with an initial value of 0 is established. Each coordinate point after serialization is read sequentially, and an addition operation incrementing by 1 is performed on the count register variable for each read coordinate point. After performing this addition operation on the three coordinate points in the sequence sequentially, the final critical coordinate count result is 3.

[0030] S302: Determine the hot spot boundary grid range based on the critical coordinate counting results, call the pixel area corresponding to the boundary grid range, perform area accumulation and addition operations on the current period grid number and the previous period grid number respectively, and perform difference subtraction operation on the two period area values ​​to obtain the period area difference result; The critical coordinate count result with a calculated value of 3 is obtained. This critical coordinate count result is used as a spatial contour expansion parameter. Combined with the boundary point set data recorded in the previous detection cycle, the hot spot boundary grid range of the current cycle is determined. The pixel area corresponding to each smallest physical grid contained in this boundary grid range is retrieved from the internal storage space. This corresponding pixel area is obtained by performing a square operation on the spatial resolution step size parameter. The previously obtained spatial resolution step size is 3 mm. Multiplying 3 mm by 3 mm yields a pixel area of ​​9 square millimeters for a single grid. The number of grids in the current cycle boundary grid range is found to be 12. Simultaneously, the hot spot boundary grid range corresponding to the previous detection cycle recorded in the historical data is retrieved, yielding a number of 8 grids in the previous cycle. Multiplying the current cycle grid count of 12 by the pixel area of ​​9 square millimeters for a single grid yields a total pixel area of ​​108 square millimeters for the current cycle. Similarly, multiplying the previous cycle grid count of 8 by the pixel area of ​​9 square millimeters for a single grid yields a total pixel area of ​​72 square millimeters for the previous cycle. Substituting the total pixel area of ​​the current period (108 square millimeters) and the total pixel area of ​​the previous period (72 square millimeters) into the differential subtraction operation, the total pixel area of ​​the current period is used as the minuend, and the total pixel area of ​​the previous period is used as the subtrahend. That is, subtracting 72 square millimeters from 108 square millimeters yields a difference of 36 square millimeters. This 36 square millimeters is taken as the final period area difference result. Integrating the key data indicators in the aforementioned period area calculation process, a period area difference calculation table is formed as shown in Table 2.

[0031] Table 2. Periodic Area Difference Calculation Table Previous testing cycle 8 9 square millimeters 72 square millimeters 0 square millimeters Current testing cycle 12 9 square millimeters 108 square millimeters 36 square millimeters As shown in Table 2, the area increment results were obtained by introducing fixed physical area parameters and performing time-series difference comparison operations.

[0032] S303: Perform sign bit determination operation based on periodic area difference results, compare the difference value with the zero reference value for sign and perform state marking encoding, map the sign marking result to the state feature encoding table, and generate extended state features; The calculated periodic area difference result of 36 square millimeters is extracted, and the zero reference value pre-recorded in the internal memory is retrieved. This zero reference value is set based on the ideal static equilibrium state of heat transfer, i.e., when there is no physical diffusion or area change in the heat radiation range between two adjacent detection cycles, the area difference between the two observations is theoretically equal to absolute zero. Therefore, this zero reference value is set to 0 square millimeters. A sign-bit determination operation is performed between the periodic area difference result of 36 square millimeters and the zero reference value of 0 square millimeters. The polarity of the difference is determined by comparing their numerical values. Since 36 square millimeters is greater than 0 square millimeters, the sign polarity of the difference value is determined to be positive. According to the preset numerical state conversion rules, this positive polarity determination state is processed by state labeling and encoded with the identifier number 1. If the comparison finds that the difference value is equal to 0 square millimeters, it is assigned the identifier number 0; if the difference value is less than 0 square millimeters, it is assigned the identifier number 2. In this comparison operation, the state labeling result generated based on the positive polarity is the number 1. The system invokes a pre-defined state feature encoding table within the data verification space. This table is pre-written and fixed by the equipment during the factory manufacturing process based on over 5000 historical thermodynamic experiments. The table clearly defines the mapping relationship between each identifier number and its corresponding physical evolution state. Based on the established data association channel, the obtained symbolic label result, number 1, is mapped to this state feature encoding table for precise retrieval. Through cross-referencing row and column conditions, it is confirmed that the physical evolution attribute corresponding to number 1 is a positive area expansion trend. The associated expansion period text description field under this mapping entry is extracted and used to generate an expansion state feature characterizing the current dynamic evolution trend of the hotspot.

[0033] Please see Figure 5 The specific steps of S4 are as follows: S401: Obtain the spatial orientation coordinates of the microchannel oil path of the charging pile, calculate the cosine value of the angle between the multi-microchannel coordinate vector and the main diffusion direction, determine the sign of the cosine based on the zero reference value, extract the same-direction vector index and the opposite-direction vector index, and obtain the spatial orientation index set. The physical spatial layout of the microchannel oil circuit is read from the structural design database inside the charging pile via the communication data bus, and the three-dimensional spatial coordinate data of the fluid initiation and termination points of each microchannel are extracted. The fluid initiation point of the first microchannel is obtained with a horizontal coordinate of 20 mm, a vertical coordinate of 30 mm, and a depth coordinate of 10 mm; the fluid termination point has a horizontal coordinate of 25 mm, a vertical coordinate of 38 mm, and a depth coordinate of 10 mm. The corresponding dimension values ​​of the initiation point coordinates are subtracted from the termination point coordinates: 25 mm minus 20 mm yields a horizontal component of 5 mm, 38 mm minus 30 mm yields a vertical component of 8 mm, and 10 mm minus 10 mm yields a depth component of 0 mm. These are combined to obtain the microchannel coordinate vector with a horizontal component of 5, a vertical component of 8, and a depth component of 0. The previously generated main diffusion direction (horizontal component 0.6, vertical component 0.8, depth component 0) is then used to calculate the cosine of the angle between the microchannel coordinate vector and the main diffusion direction. The horizontal, vertical, and depth components of both vectors are multiplied: 5 * 0.6 = 3, 8 * 0.8 = 6.4, 0 * 0 = 0. The sum of 3, 6.4, and 0 yields a dot product of 9.4. The actual magnitudes of the two vectors are calculated. The main diffusion direction is a standard unit vector with an actual magnitude of 1. The actual magnitude of the microchannel coordinate vector is obtained by taking the square root of the sum of the squares of its components: 5² = 25 + 8² = 64 = 89. Taking the square root of 89 gives an approximate magnitude of 9.43. The dot product of 9.43 (microchannel vector magnitude 9.43) and 1 (main diffusion direction magnitude 1) yields a cosine of the included angle of 0.996. A pre-set zero reference value of 0 is retrieved to distinguish the relative orientation of the vectors. The cosine of the included angle of 0.996 is compared with this zero reference value. Since 0.996 is greater than 0, the microchannel is determined to be in the same direction. For microchannels determined to be in the same direction, assign the identifier number 1 as the same-direction vector index; if the cosine of the included angle is less than 0, assign the identifier number 2 as the opposite-direction vector index. This calculation and determination operation is performed by traversing all microchannels. The generated multiple same-direction vector indices and opposite-direction vector indices are then sequentially combined according to their physical arrangement to construct a spatial orientation index set.

[0034] S402: Based on the spatial orientation index set, call the expansion state features, extract the expansion state identifier bit and compare it with the preset state judgment bit, output the state judgment Boolean value, combine the hot spot region set coordinate boundary data to determine the regional membership of the microchannel, and obtain the expansion periphery distribution sequence. The generated spatial orientation index set is obtained, and the expansion state feature representing a positive expansion trend generated in the aforementioned process is read through data retrieval instructions. From the underlying data structure corresponding to this expansion state feature, the expansion state flag bit at a specific byte position is extracted, and the extracted actual flag bit value is the number 1. A preset state judgment bit, pre-written in the internal memory and fixed to the number 1 during device initialization, is retrieved, indicating that the charging pile is currently in a dangerous expansion phase of accelerated heat accumulation. The extracted expansion state flag bit (number 1) and the preset state judgment bit (number 1) are compared. A numerical consistency check confirms that they are completely equal, and a Boolean value indicating a true state judgment is output according to Boolean logic rules. Simultaneously, the coordinate point set corresponding to the hot spot boundary grid range obtained in the aforementioned process is read as the hot spot region set coordinate boundary data. The specific position coordinates of each microchannel in the spatial orientation index set are extracted, and the geometric position membership degree is determined between the microchannel position coordinates and the hot spot region set coordinate boundary data. The shortest physical distance between the center coordinates of each microchannel and the boundary coordinates of the nearest hotspot is calculated. A warning perimeter distance threshold of 15 mm is set. This threshold is determined through statistical analysis of 500 thermal runaway propagation experiments. The physical region within 15 mm of the heat source is considered a high-risk zone for the first wave of heat impact. When the shortest physical distance from the center coordinates of a microchannel to the hotspot boundary is 10 mm, it is determined that this 10 mm is less than the warning perimeter distance threshold of 15 mm, confirming that the microchannel is within the perimeter distribution range and assigning it a strong membership identifier of 1. After completing the distance assessment and membership identifier assignment for all microchannels, the numbers of all microchannels assigned a strong membership identifier of 1 are sequentially arranged to generate an extended perimeter distribution sequence for precise positioning.

[0035] S403: Based on the spatial orientation index set and the extended peripheral distribution sequence, positive control voltage parameters are assigned to the same-direction index and negative control voltage parameters are assigned to the opposite-direction index. When the state judgment Boolean value is true, a positive bias control voltage is superimposed on the elements of the distribution sequence to generate a solenoid valve adjustment command. The generated spatial orientation index set and the extended peripheral distribution sequence are read. Electrical parameter allocation is performed on each vector index contained in the spatial orientation index set. The index set is traversed. When a previously assigned vector index with an identifier of 1 is encountered, the corresponding positive drive voltage rule is retrieved, assigning a positive control voltage parameter of 12 volts to the control node of the corresponding microchannel. When a reverse vector index with an identifier of 2 is encountered, the reverse drive voltage rule is retrieved, assigning a negative control voltage parameter of -5 volts to the control node of the corresponding microchannel. The baseline values ​​of these voltage parameters are determined based on the fluid dynamics conduction response curve manual, ensuring a linear mapping between the valve opening angle and the voltage amplitude. The aforementioned output state judgment Boolean value is received. If the Boolean value is detected as true, the voltage bias compensation mechanism is activated. For each microchannel element node existing in the extended peripheral distribution sequence, its currently assigned basic control voltage parameter is extracted, and a positive bias control voltage of 2.5 volts is uniformly superimposed on its value. The positive control voltage parameter of 12 volts for the microchannels identified as being in the same direction and belonging to the peripheral distribution sequence is summed with the 2.5 volt positive bias control voltage to obtain the final corrected drive voltage parameter of 14.5 volts. The calculated final corrected drive voltage parameters for each microchannel are converted into a standard digital-to-analog converter signal format. This data packet is then concatenated with the physical hardware address encoding of each microchannel to generate a solenoid valve adjustment command that can be directly sent to the hardware execution layer. This solenoid valve adjustment command is transmitted to the corresponding micro-hydraulic solenoid valve controller via a communication cable, completing the dynamic electrical intervention of the microchannel oil flow.

[0036] Please see Figure 6 The specific steps of S5 are as follows: S501: Obtain the main diffusion direction for three consecutive time periods, identify the main diffusion direction for each time period and record the direction value, compare the direction values ​​in the sequence item by item, filter the direction items that meet the direction consistency judgment rules, and generate the time series direction consistency result. Extract the main diffusion direction data for three consecutive time periods. The calculated main diffusion direction is used as the baseline data for the first period, with a horizontal component of 0.6, a vertical component of 0.8, and a depth component of 0. The main diffusion direction for the second period is simultaneously acquired, with a horizontal component of 0.65, a vertical component of 0.75, and a depth component of 0. The main diffusion direction for the third period is acquired, with a horizontal component of 0.58, a vertical component of 0.81, and a depth component of 0. For each time period, perform attribution identification and direction value recording operations on the main diffusion direction. Convert the three-dimensional vector into a two-dimensional plane angle value using arctangent geometry. Perform division operations with the vertical component as the numerator and the horizontal component as the denominator. For the first period, the vertical component 0.8 divided by the horizontal component 0.6 yields an arctangent angle of 53.13 degrees. For the second period, the vertical component 0.75 divided by the horizontal component 0.65 yields an arctangent angle of 49.08 degrees. For the third period, the vertical component 0.81 divided by the horizontal component 0.58 yields an arctangent angle of 54.39 degrees. The three angle values ​​calculated above are persistently stored as sequence direction values ​​to generate a complete historical direction sequence. For adjacent time nodes in the sequence, a subtraction operation is performed sequentially: 53.13 degrees in the first period is subtracted from 49.08 degrees in the second period, yielding an absolute difference of 4.05 degrees. Similarly, 54.39 degrees in the third period is subtracted from 49.08 degrees in the second period, yielding an absolute difference of 5.31 degrees. A pre-generated direction offset tolerance threshold of 10 degrees is retrieved based on 100 flow field boundary tests. The calculated values ​​of 4.05 degrees and 5.31 degrees are compared with the 10-degree tolerance threshold. Since 4.05 degrees and 5.31 degrees are both less than 10 degrees, the deviations in each period are confirmed to meet the direction consistency judgment rule. All direction items that meet the consistency judgment rule are integrated, and the time series direction consistency result with an internal Boolean value of "true" is output. The advantage of this operational logic is that by calculating the absolute value of the angle deviation over multiple consecutive cycles, it eliminates the interference of single measurement errors on the judgment of the overall diffusion trend.

[0037] S502: Based on the time series direction consistency results, perform direction stability judgment on the consistency judgment results, compare each direction consistency value with the preset stability threshold, identify the direction items that meet the preset stability threshold, filter the direction index set corresponding to the driveable signal, and establish a stable direction index set. Read the generated time series direction consistency results with the internal identifier set to Boolean true, and extract the associated consecutive multi-period absolute difference data. Obtain the first consistency difference of 4.05 degrees between the first and second periods, and the second consistency difference of 5.31 degrees between the third and second periods, calculated above. Perform depth direction stability judgment processing on the above consistency judgment results. Retrieve the preset stability threshold from the preset parameter storage area. The determination process of this preset stability threshold is based on the extreme test of the laminar flow maintenance conditions of the internal coolant of the charging pile. In 50 consecutive thermodynamic impact experiments with different flow rates, the maximum angular change safety boundary that will not cause turbulent disturbance of the internal coolant of the pipe is recorded, and its conservative critical value is set to 6 degrees. Compare the obtained first consistency difference of 4.05 degrees with the preset stability threshold of 6 degrees, and determine that 4.05 degrees is lower than the 6-degree limit. Simultaneously, compare the second consistency difference of 5.31 degrees with the preset stability threshold of 6 degrees, and determine that 5.31 degrees is also lower than the 6-degree limit. By comparing the thresholds of the two consecutive steps mentioned above, it is identified that all current directional changes meet the constraints of the preset stability threshold. After confirming that the conditions are met, the screening mechanism of the underlying control signal is activated. For the spatial orientation index set generated in the previous steps, the microchannel node attribute data contained therein is extracted. From this, directional items with driveable signal attributes are selected. Specifically, the selection logic is to retrieve the microchannel sequence with the same-direction vector index identifier number 1 from the spatial orientation index set. The intersection operation of this microchannel sequence and the aforementioned expansion periphery distribution sequence is performed to extract the microchannel hardware address numbers that must be actively cooled under the stable heat flow expansion state, such as extracting microchannels numbered 3, 7, and 12. These three numbers are arranged into an array to establish a stable direction index set for guiding the precise action of the end electrical components. The advantage of this operation logic is that by introducing a strict stability threshold for secondary comparison, invalid cooling commands during periods of violent directional oscillation are filtered out.

[0038] S503: Call the stable direction index set, extract the corresponding solenoid valve adjustment command, apply the driving voltage to the pin of the charging pile electromagnetic proportional control valve, switch the open or closed state of the microchannel electromagnetic proportional control valve according to the applied voltage, and generate thermal regulation results. The constructed stable direction index set is read, and the specific microchannel hardware address information contained therein is extracted to obtain the microchannel list numbered 3, 7, and 12. Based on the extracted target microchannel number, precise addressing is performed in the control buffer to retrieve the solenoid valve adjustment commands independently generated in the previous steps for these microchannels determined to be in the same direction and belonging to the peripheral distribution sequence. Specific electrical drive parameters are parsed from this command data packet, and the final corrected drive voltage parameter calculated in the previous steps is obtained as 14.5 volts. An electrical connection is established with the end effector via a communication cable, locating the charging pile electromagnetic proportional control valve pins numbered 3, 7, and 12. The parsed 14.5-volt voltage parameter is converted into a pulse width modulation signal, and a continuous drive voltage loading operation is performed on the target electromagnetic proportional control valve pins. The current mechanical opening data of the microchannel electromagnetic proportional control valve is collected to confirm that its initial state is completely closed. The minimum valve opening action voltage reference of 5 volts and the saturation control voltage of 24 volts corresponding to full opening, preset in the hardware specifications, are extracted. It is determined that the applied 14.5-volt voltage exceeds the 5-volt opening reference. Subtracting the opening reference of 5 volts from the applied voltage of 14.5 volts yields the effective driving voltage of 9.5 volts. Subtracting the opening reference of 5 volts from the saturation control voltage of 24 volts yields the maximum driving range of 19 volts. Dividing 9.5 volts by 19 volts calculates the target opening ratio to be 50%. Based on the applied voltage, the internal solenoid coil generates a corresponding electromagnetic thrust to overcome the mechanical spring resistance, causing the microchannel electromagnetic proportional control valve to switch from its original closed state to a 50% opening adjustment state. After confirming the valve displacement is in place, the cooling medium enters the channel to perform heat exchange. The valve opening feedback signal and the flow rate change data from the flow sensor are summarized and packaged to generate a thermal regulation result log representing the intervention of local active cooling. The advantage of this calculation logic is that, through precise application of the solenoid valve pin voltage and switching of the proportional opening state, a precise balance between the cooling medium flow rate and the dynamic distribution of hot spots is achieved.

[0039] Please see Figure 7 The charging pile oil-immersed uniform temperature heat dissipation and control system includes: The temperature mapping module collects the temperature and location coordinates of multiple detection points of the charging pile power device and performs correlation mapping. It extracts the location coordinates of detection points whose temperature exceeds the preset temperature threshold, generates a hot spot region set, and transmits it to the gradient analysis module. The gradient analysis module extracts the temperature of multiple detection points and adjacent detection points in the hot spot region and calculates the difference. It extracts the spatial connection direction of multiple detection points corresponding to the maximum temperature difference, generates the main diffusion direction, and transmits it to the expansion evaluation module. The expansion evaluation module extracts the position coordinates of non-hot spot region points based on the hot spot region set and counts the total number. It calculates the current period area and the previous period area and determines the positive or negative sign of the difference. It generates expansion state features and transmits them to the valve control generation module. The valve control generation module obtains the spatial orientation coordinates of the charging pile microchannel oil circuit based on the expansion state characteristics, outputs a positive control voltage to the microchannel that is consistent with the main diffusion direction, outputs a positive bias control voltage to the microchannel located on the periphery of the hot spot region, generates a solenoid valve adjustment command and transmits it to the drive execution module. The drive execution module performs time series consistency determination on the main diffusion direction for multiple consecutive time periods. When the direction is determined to be consistent, it extracts the solenoid valve adjustment command and applies the drive voltage to the pin of the charging pile electromagnetic proportional control valve to generate thermal regulation results.

[0040] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for regulating the uniform temperature and heat dissipation of an oil-immersed charging pile, characterized in that, Includes the following steps: S1: Collect the temperature and location coordinates of multiple detection points of the power device of the charging pile and perform correlation mapping, extract the location coordinates of detection points whose temperature exceeds the preset temperature threshold, and generate a hot spot region set; S2: Extract the temperature of multiple detection points and adjacent detection points in the hot spot region and calculate the difference. Extract the spatial connection direction of multiple detection points corresponding to the maximum temperature difference to generate the main diffusion direction. S3: Based on the hot spot region set, extract the position coordinates of non-hot spot region points and count the total number, calculate the current period area and the previous period area and determine the positive or negative sign of the difference, and generate expansion state features; S4: Based on the expansion state characteristics, obtain the spatial orientation coordinates of the charging pile microchannel oil circuit, output a positive control voltage to the microchannel that is consistent with the main diffusion direction, output a positive bias control voltage to the microchannel located outside the hot spot area set, and generate a solenoid valve adjustment command. S401: Obtain the spatial orientation coordinates of the microchannel oil path of the charging pile, calculate the cosine value of the angle between the multi-microchannel coordinate vector and the main diffusion direction, determine the sign of the cosine based on the zero reference value, extract the same-direction vector index and the opposite-direction vector index, and obtain the spatial orientation index set. S402: Based on the spatial orientation index set, call the expansion state feature, extract the expansion state identifier bit and compare it with the preset state judgment bit, output the state judgment Boolean value, and combine the hot spot region set coordinate boundary data to determine the regional membership of the microchannel to obtain the expansion periphery distribution sequence. S403: Based on the spatial orientation index set and the extended peripheral distribution sequence, assign positive control voltage parameters to the same-direction index and negative control voltage parameters to the opposite-direction index respectively, and when the state determination Boolean value is true, superimpose positive bias control voltage on the elements of the distribution sequence to generate a solenoid valve adjustment command; S5: Perform time series consistency determination on the main diffusion direction for multiple consecutive time periods. When the direction is determined to be consistent, extract the solenoid valve adjustment command and apply the driving voltage to the charging pile electromagnetic proportional control valve pin to generate thermal control result.

2. The charging pile oil-immersed uniform temperature heat dissipation control method according to claim 1, characterized in that, The hot spot region set includes temperature anomaly detection points, detection point location coordinates, and hot spot boundary information. The main diffusion direction includes the line connecting the maximum temperature difference, the direction vector, and the spatial orientation. The expansion state characteristics include the number of non-hot spot region points, the current period area, and the area change sign. The solenoid valve adjustment command includes the microchannel positive voltage, the peripheral microchannel bias voltage, and the control direction coordinates. The thermal regulation result includes the time series consistency judgment result, the electromagnetic proportional control valve drive state, and the thermal regulation effect.

3. The oil-immersed uniform temperature heat dissipation control method for charging piles according to claim 1, characterized in that, The specific steps of S1 are as follows: S101: Collect the output temperature of the surface temperature sensor array of the power device of the charging pile and the coordinates of multiple detection points, align the index numbers, match the temperature with the corresponding spatial coordinates, and perform attribute binding verification on the temperature field and the coordinate field to obtain the temperature coordinate set. S102: Based on the temperature field in the temperature coordinate set, a preset temperature threshold is called to perform item-by-item comparison calculation, and the record item whose temperature value exceeds the temperature threshold is identified. The corresponding spatial coordinate field of the record item that meets the condition is extracted and reassembled into a set to obtain the over-threshold coordinate sequence. S103: Based on the spatial distribution relationship of multiple coordinate points in the super-threshold coordinate sequence, perform neighborhood distance determination calculation, cluster and merge coordinate points whose distance does not reach the preset spatial adjacency threshold, encode the merged multi-coordinate clusters by region number, and generate hot spot region set.

4. The oil-immersed uniform temperature heat dissipation control method for charging piles according to claim 3, characterized in that, The temperature threshold is determined by collecting the factory-rated operating parameters of the charging pile power devices and the real-time ambient temperature value, extracting the extreme tolerance temperature from the rated operating parameters as the upper limit of the benchmark, calculating the difference between the real-time ambient temperature value and the standard ambient benchmark value to obtain the ambient temperature deviation, converting the ambient temperature deviation into a temperature compensation factor according to a preset proportional coefficient, and then linearly superimposing the temperature compensation factor with the upper limit of the benchmark to determine the threshold.

5. The oil-immersed uniform temperature heat dissipation control method for charging piles according to claim 1, characterized in that, The specific steps of S2 are as follows: S201: Extract the location coordinates of multiple detection points and the temperature of adjacent detection points within the hot spot region set; perform a pairwise difference operation on the temperature value of each detection point and the temperature value of adjacent detection points; pair and map the location coordinates of multiple detection points with multiple temperature difference items to obtain the neighboring point temperature difference set. S202: Perform amplitude comparison operation based on the multi-element values ​​of the adjacent point temperature difference set, sort the values ​​according to their size and locate the index position corresponding to the maximum difference, combine the index position with the reverse mapping to the set of detection point numbers, lock the corresponding two detection point numbers, and obtain the index of the extreme difference point pair. S203: Based on the extreme point index, call the position coordinates of the corresponding two detection points, perform coordinate difference operation to obtain the spatial displacement vector, normalize the direction of the spatial displacement vector and retain the direction component, and generate the main diffusion direction.

6. The oil-immersed uniform temperature heat dissipation control method for charging piles according to claim 1, characterized in that, The specific steps for S3 are as follows: S301: Based on the hot spot region set, extract the position coordinates of the critical points of non-hot spot regions in the surrounding eight neighborhood space and count the total number of position coordinates. Serialize and arrange the position coordinates of multiple critical points according to the raster index sequence, and perform a counting and accumulation operation on the serialized coordinates to obtain the critical coordinate counting result. S302: Determine the hot spot boundary grid range based on the critical coordinate counting result, call the pixel area corresponding to the boundary grid range, perform area accumulation and addition operations on the current period grid number and the previous period grid number respectively, and perform difference subtraction operation on the two period area values ​​to obtain the period area difference result; S303: Based on the periodic area difference result, perform sign bit determination operation, compare the difference value with the zero reference value for sign and perform state marking encoding, map the sign marking result to the state feature encoding table, and generate extended state features.

7. The oil-immersed uniform temperature heat dissipation control method for charging piles according to claim 1, characterized in that, The specific steps of S5 are as follows: S501: Obtain the main diffusion direction for three consecutive time periods, identify and record the direction value of the main diffusion direction for each time period, compare the direction values ​​in the sequence item by item, filter the direction items that meet the direction consistency judgment rules, and generate the time series direction consistency result. S502: Based on the time series direction consistency results, perform direction stability judgment on the consistency judgment results, compare each direction consistency value with a preset stability threshold, identify the direction items that meet the preset stability threshold, filter the direction index set corresponding to the driveable signal, and establish a stable direction index set. S503: Call the stable direction index set, extract the corresponding solenoid valve adjustment command, apply the driving voltage to the pin of the charging pile electromagnetic proportional control valve, switch the open or closed state of the microchannel electromagnetic proportional control valve according to the applied voltage, and generate thermal regulation results.

8. The method for regulating oil-immersed uniform temperature dissipation in charging piles according to claim 7, characterized in that, The stability threshold is determined by extracting the reference thermal diffusion offset angle under the rated operating conditions of the charging pile as the initial parameter, collecting the calibration error value of the temperature sensor, converting the calibration error value into the angle tolerance equivalent, and summing the reference thermal diffusion offset angle and the angle tolerance equivalent to obtain the directional tolerance compensation amount. The initial parameter and the directional tolerance compensation amount are then superimposed and corrected to determine the threshold.

9. A charging pile oil-immersed uniform temperature heat dissipation and control system, characterized in that, The system is used to implement the oil-immersed uniform temperature heat dissipation control method for charging piles according to any one of claims 1-8, the system comprising: The temperature mapping module collects the temperature and location coordinates of multiple detection points of the charging pile power device and performs correlation mapping. It extracts the location coordinates of detection points whose temperature exceeds the preset temperature threshold, generates a hot spot region set, and transmits it to the gradient analysis module. The gradient analysis module extracts the temperature of multiple detection points and adjacent detection points in the hot spot region and calculates the difference. It extracts the spatial connection direction of multiple detection points corresponding to the maximum temperature difference, generates the main diffusion direction, and transmits it to the expansion evaluation module. The expansion assessment module extracts the position coordinates of non-hot spot points based on the hot spot region set and counts the total number, calculates the current cycle area and the previous cycle area and determines the positive or negative sign of the difference, generates expansion state features and transmits them to the valve control generation module. The valve control generation module obtains the spatial orientation coordinates of the charging pile microchannel oil circuit based on the expansion state characteristics, outputs a positive control voltage to the microchannel that is consistent with the main diffusion direction, outputs a positive bias control voltage to the microchannel located outside the hot spot area set, generates a solenoid valve adjustment command and transmits it to the drive execution module. The drive execution module performs time series consistency determination on the main diffusion direction for multiple consecutive time periods. When the direction is determined to be consistent, the module extracts the solenoid valve adjustment command and applies a drive voltage to the charging pile electromagnetic proportional control valve pin to generate thermal control results.

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