Partition control intelligent charging pile double-cooling heat dissipation system and control method

Abstract

This invention provides a zoned control intelligent charging pile dual cooling heat dissipation system and control method, belonging to the field of charging pile heat dissipation technology. It includes a zone division and acquisition module for real-time monitoring of the temperature generated by functional modules and heat dissipation equipment in each heat control zone, constructing a first dataset and a second dataset; and an early warning analysis module for constructing the internal thermal risk coefficient R of the charging pile. heat and construct the environmental thermal interference coefficient R env The evaluation and optimization module is used to construct the comprehensive temperature control adjustment coefficient R. total This system accurately monitors the heat generation temperature of functional modules by partitioning them, quickly dissipates heat, and can predict temperature changes of functional modules in advance, thereby reducing equipment power consumption and improving equipment heat dissipation efficiency.

Description

Technical Field

[0001] This invention relates to the field of charging pile heat dissipation technology, and more specifically, to a dual cooling heat dissipation system and control method for intelligent charging piles with zoned control. Background Technology

[0002] With the rapid popularization of new energy vehicles, high-power charging piles, as important equipment to meet the fast charging needs of vehicles, are being used more and more widely. However, charging piles generate significantly different heat loads in fast and slow charging modes due to the different charging power. If the heat dissipation system is not responsive enough or the heat load is unevenly distributed, it will lead to excessively high local temperatures, affecting charging efficiency, and even causing problems such as overheating of power modules, performance degradation, and shortened equipment lifespan. Therefore, the efficiency and reliability of the heat dissipation system has become one of the key technologies in the design of high-power charging piles.

[0003] Private new energy vehicle charging stations are frequently installed in underground parking garages, with some even close to the garage walls. In practice, due to space utilization and wiring convenience, private smart charging stations are often installed in relatively enclosed spaces like underground garages, frequently placed close to walls. This wall-mounted placement presents significant thermal management challenges: the wall surface absorbs and retains heat, creating a backflow of heat under convection, causing some hot air to enter the charging station's interior, adding an additional heat load and further exacerbating the internal temperature rise. Most existing smart charging stations employ a single air-cooled or passive cooling structure, failing to adequately consider the non-uniform heat load caused by wall-mounted placement and heat backflow in enclosed spaces. This results in low localized heat dissipation efficiency, easily triggering overheat protection mechanisms and even causing operational instability and over-temperature shutdowns. Furthermore, the lack of differentiated heat dissipation control for different heat source areas limits the overall system's ability to optimize heat dissipation in complex installation environments. Summary of the Invention

[0004] To overcome the above deficiencies, the present invention provides a dual cooling and heat dissipation system and control method for a smart charging pile with zoned control, which overcomes or at least partially solves the above technical problems.

[0005] This invention is implemented as follows:

[0006] This invention provides a zoned control intelligent charging pile dual cooling and heat dissipation system, including a zone division and acquisition module, an early warning and analysis module, and an evaluation and optimization module;

[0007] The area division and acquisition module is used to divide the target smart charging pile in the wall adjacent to the underground parking garage into several thermal control zones, and to set dynamic temperature monitoring points in each thermal control zone. Based on the dynamic temperature monitoring points, it is used to monitor the temperature generated by the functional modules in each thermal control zone and the temperature generated by the heat dissipation equipment in each thermal control zone in real time. It is also used to monitor the additional heat load that enters the target smart charging pile from the external wall due to heat convection when the target smart charging pile is deployed close to the wall, and to construct the first dataset and the second dataset respectively.

[0008] The early warning analysis module is used to construct the internal thermal risk coefficient R of the pile based on the first dataset. heat The environmental thermal disturbance coefficient R is constructed based on the second dataset. env And generate a first evaluation instruction and a second evaluation instruction respectively, and generate a corresponding first strategy and a second strategy;

[0009] The evaluation and optimization module is used to correlate the internal thermal risk coefficient of the pile with the environmental thermal interference coefficient to construct a comprehensive temperature control adjustment coefficient R. total It then generates a third evaluation instruction and a corresponding third strategy.

[0010] In a preferred embodiment, the area division acquisition module includes an area division unit, a functional module temperature value acquisition unit, a heat dissipation device temperature value acquisition unit, and an environmental interference acquisition unit.

[0011] The region division unit is used to divide the target smart charging pile into several regions and construct a three-dimensional coordinate system to obtain the coordinate system x, y, z of the i-th functional module;

[0012] The functional module temperature value acquisition unit is used to install a temperature sensor on the outer surface of each thermal control zone functional module, and acquire the temperature value generated by the functional module in each thermal control zone based on the temperature sensor to obtain the heat release R of the i-th functional module. i ;

[0013] The functional module temperature value acquisition unit is also used to acquire the heating temperature value of the m-th functional module adjacent to the i-th functional module, so as to obtain the heating temperature R of the m-th functional module. m ;

[0014] The heat dissipation equipment temperature value acquisition unit is used to acquire the temperature released by the heat dissipation equipment installed in the target smart charging pile in order to obtain the heat dissipation equipment heating temperature S.

[0015] Based on the heat release R of the i-th functional module i The heating temperature R of the m-th functional module m The first dataset is constructed based on the heat dissipation temperature S of the heat dissipation device.

[0016] In a preferred embodiment, the environmental interference acquisition unit is used to install a wind speed sensor and an infrared temperature sensor outside the target smart charging pile to acquire wind speed and temperature near the target smart charging pile, and obtain wind speed V and temperature C.

[0017] The environmental interference acquisition unit is used to set a distance detection sensor at the target smart charging pile, detect the distance between the target smart charging pile and the underground garage wall based on the distance sensor, the distance d between the target smart charging pile and the wall, and set several temperature acquisition points distributed along the height direction based on the distance. The temperature sensor is used to collect the temperature at the acquisition points, monitor the temperature gradient change value ΔT in real time, and obtain the underground garage material according to the underground garage construction requirements. The thermal conductivity k of the wall is obtained by looking up a table to obtain the wall heat return intensity factor Q, and a second dataset is constructed.

[0018] In a preferred embodiment, the early warning analysis module includes a first extraction unit, a first calculation unit, and a first evaluation unit;

[0019] The first extraction unit is used to extract the heat release amount R of the i-th functional module based on the first dataset. i The heating temperature R of the m-th functional module m and the heating temperature S of the heat dissipation equipment;

[0020] The first calculation unit is used to calculate the internal thermal risk coefficient R of the pile based on the data extracted by the first extraction unit. heat .

[0021] In a preferred embodiment, the first assessment unit is used to preset the pile internal risk threshold E, and to compare the preset pile internal risk threshold E with the pile internal thermal risk coefficient R. heat A comparison is performed to generate the first evaluation instruction, including:

[0022] When R heat When ≥E, it indicates that the heat dissipation inside the target smart charging pile is abnormal, and the first strategy is generated, which includes improving the heat dissipation efficiency of the i-th functional module by 32%-50% with the dual cooling equipment, and also improving the heat dissipation efficiency of the m-th functional module adjacent to the i-th functional module by 30%-40% by increasing the fan speed in the air cooling by 10%-20% and the liquid cooling circulation flow by 25%-34%.

[0023] When R heat When the value is <E, it indicates that the heat dissipation inside the target smart charging pile is normal. Maintain the set speed and circulation flow rate of the dual-cooling equipment for the heat dissipation of the functional modules, and continue testing.

[0024] In a preferred embodiment, the early warning analysis module further includes a second extraction unit, a second calculation unit, and a second evaluation unit;

[0025] The second extraction unit is used to extract the wind speed V, temperature C, and wall heat return intensity factor Q from the second dataset;

[0026] The second calculation unit is used to calculate the environmental thermal interference coefficient R based on the data extracted from the second data by the second extraction unit. env .

[0027] In a preferred embodiment, the second evaluation unit is used to preset an environmental interference threshold T and to compare the environmental interference threshold T with the environmental thermal interference coefficient R. env A comparison is made, and a second evaluation instruction is generated, including:

[0028] When R env When T ≥ T, it indicates that the external environmental factors of the target smart charging pile are causing abnormal heat dissipation of the charging pile. A second strategy is generated, which includes increasing the fan speed of the air-cooled equipment by 20%-40% and the circulation speed of the liquid cooling by 15%-25%. In terms of cooling resource allocation, 38%-60% of the heat dissipation power is allocated to the functional modules that are abnormally affected by environmental heat interference. The underground garage fan is started to increase the underground garage wind speed by 10%-35%, thereby reducing the temperature inside the underground garage by 3℃-5℃. The air outlet angle of the target smart charging pile is adjusted upward by 15°-30°.

[0029] When R env When T < T, it indicates that the external environmental factors of the target smart charging pile have a normal impact on the heat dissipation of the charging pile, and monitoring should continue.

[0030] In a preferred embodiment, the evaluation and optimization module includes an associated unit and a third evaluation unit;

[0031] The associated unit is used to determine the internal thermal risk factor R of the pile. heat With environmental thermal interference coefficient R env Correlatedly, the comprehensive temperature control adjustment coefficient R is obtained through calculation. total .

[0032] In a preferred embodiment, the third evaluation unit is used to preset the temperature control adjustment threshold Y and to compare the temperature control adjustment threshold Y with the comprehensive temperature control adjustment coefficient R. total A comparison is made, and a third evaluation instruction is generated, including:

[0033] When R totalWhen ≥Y, it indicates that the target smart charging pile has abnormal heat dissipation. A third strategy is generated, which includes increasing the power of the air-cooled equipment by 20%-40%, increasing the circulation flow rate of the liquid-cooled equipment by 33%-50%, dynamically adjusting the allocation ratio of cooling resources of the dual-cooling equipment to the heat control zone, increasing the cooling resources for functional modules with abnormal heat release by 30%-60%, increasing the wind speed of the underground garage fan by 22%-35%, and adjusting the angle of the heat dissipation port of the target smart charging pile by 10%-15%.

[0034] When R total When <Y, it indicates that the target smart charging pile has normal heat dissipation. It will continue to dissipate heat in the set heat dissipation mode and monitor it in real time.

[0035] A dual-cooling heat dissipation control method for smart charging piles with zoned control includes:

[0036] Step 1: First, the target smart charging pile in the underground parking garage adjacent to the wall is divided into several thermal control zones. The temperature generated by the functional module and the temperature generated by the heat dissipation equipment in each thermal control zone are collected in real time. The additional heat load entering the target smart charging pile from the external wall due to heat convection when the target smart charging pile is deployed close to the wall is also monitored.

[0037] Step Two: Next, construct the internal thermal risk coefficient R of the pile based on the data collected in Step One. heat and environmental thermal interference coefficient R env ;

[0038] Step 3: Finally, calculate the internal thermal risk factor R of the pile. heat and environmental thermal interference coefficient R env Integration to construct a comprehensive temperature control regulation coefficient R total And conduct evaluation and optimization.

[0039] The present invention provides a dual-cooling heat dissipation system and control method for a smart charging pile with zoned control, the beneficial effects of which include:

[0040] 1. By dividing the internal thermal control zone of the charging pile and setting dynamic temperature monitoring points, it is possible to achieve refined collection of the temperature release of each functional module. Combined with the heat output monitoring of the heat dissipation equipment itself, a comprehensive temperature monitoring model is constructed, which improves the accuracy of temperature monitoring. At the same time, by collecting the heat return load caused by heat convection in the external environment when the charging pile is close to the wall, an environmental thermal interference coefficient is constructed, which realizes the effective identification and quantitative analysis of the external thermal impact in complex layout environments such as underground garages, reducing power consumption and improving heat dissipation efficiency.

[0041] 2. When the thermal risk coefficient or interference coefficient exceeds the set threshold, the system automatically generates heat dissipation enhancement strategies, such as increasing the heat dissipation efficiency of the corresponding area by 10% to 50%, adjusting the heat dissipation direction or air duct angle, etc., to effectively prevent heat accumulation, predict temperature changes, and improve the reliability and safety of the charging pile's heat dissipation. Attached Figure Description

[0042] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0043] Figure 1 This is a system block diagram of the present invention;

[0044] Figure 2 This is a flowchart of the method in this invention. Detailed Implementation

[0045] The embodiments of the technical solution of the present invention will now be described in detail with reference to the accompanying drawings. These embodiments are merely illustrative of the technical solution of the present invention and are therefore intended to limit the scope of protection of the present invention.

[0046] Example 1, referring to Figure 1 The present invention provides a technical solution: a zone-controlled intelligent charging pile dual cooling heat dissipation system, including a zone division acquisition module, an early warning analysis module, and an evaluation and optimization module;

[0047] The area division and acquisition module is used to divide the target smart charging pile in the wall adjacent to the underground parking garage into several thermal control zones, and to set dynamic temperature monitoring points in each thermal control zone. Based on the dynamic temperature monitoring points, it is used to monitor the temperature generated by the functional modules in each thermal control zone and the temperature generated by the heat dissipation equipment in each thermal control zone in real time. It is also used to monitor the additional heat load that enters the target smart charging pile from the external wall due to heat convection when the target smart charging pile is deployed close to the wall, and to construct the first dataset and the second dataset respectively.

[0048] The early warning analysis module is used to construct the internal thermal risk coefficient R of the pile based on the first dataset. heat The environmental thermal disturbance coefficient R is constructed based on the second dataset. env And generate a first evaluation instruction and a second evaluation instruction respectively, and generate a corresponding first strategy and a second strategy;

[0049] The evaluation and optimization module is used to correlate the internal thermal risk coefficient of the pile with the environmental thermal interference coefficient to construct a comprehensive temperature control adjustment coefficient R. totalIt then generates a third evaluation instruction and a corresponding third strategy.

[0050] In this embodiment, by dividing the interior of the charging pile into thermal control zones and setting dynamic temperature monitoring points, it is possible to achieve refined collection of temperature release data for each functional module. Combined with the heat output monitoring of the heat dissipation equipment itself, a comprehensive temperature monitoring model is constructed, improving the accuracy of temperature monitoring. Simultaneously, by collecting the heat load caused by heat convection in the external environment when the charging pile is near a wall, an environmental thermal interference coefficient is constructed, enabling effective identification and quantitative analysis of external thermal impacts in complex environments such as underground parking garages. Furthermore, by combining the internal thermal risk coefficient, the evaluation and optimization module can form a comprehensive temperature control adjustment coefficient, and based on this coefficient, a control strategy is generated to achieve dynamic adjustment and zoned optimization control of the cooling system.

[0051] When the thermal risk coefficient or interference coefficient exceeds a set threshold, the system can automatically generate heat dissipation enhancement strategies, such as increasing the heat dissipation efficiency of the corresponding area by 10% to 50%, adjusting the heat dissipation direction or air duct angle, etc., to effectively prevent heat accumulation and improve the reliability and safety of the charging pile's heat dissipation.

[0052] Example 2 is an explanation of Example 1; please refer to it. Figure 1 Specifically, the area division acquisition module includes an area division unit, a functional module temperature value acquisition unit, a heat dissipation equipment temperature value acquisition unit, and an environmental interference acquisition unit;

[0053] The region division unit is used to divide the target smart charging pile into several regions and construct a three-dimensional coordinate system to obtain the coordinate system x, y, z of the i-th functional module;

[0054] The functional module temperature value acquisition unit is used to install a temperature sensor on the outer surface of each thermal control zone functional module, and acquire the temperature value generated by the functional module in each thermal control zone based on the temperature sensor to obtain the heat release R of the i-th functional module. i The functional modules include a main control module, a rectifier module, and a charging module;

[0055] The functional module temperature value acquisition unit is also used to acquire the heating temperature value of the m-th functional module adjacent to the i-th functional module, so as to obtain the heating temperature R of the m-th functional module. m ;

[0056] The heat dissipation equipment temperature value acquisition unit is used to acquire the temperature released by the heat dissipation equipment installed in the target smart charging pile in order to obtain the heat dissipation equipment heating temperature S.

[0057] Based on the heat release R of the i-th functional module i The heating temperature R of the m-th functional modulem The first dataset is constructed based on the heat dissipation temperature S of the heat dissipation device.

[0058] In this embodiment, the region division acquisition module provided by the present invention introduces a region division unit, a functional module temperature value acquisition unit, a heat dissipation equipment temperature value acquisition unit, and an environmental interference acquisition unit to achieve refined identification of the internal thermal environment of the smart charging pile and acquisition of multi-dimensional temperature data. Among them, the region division unit divides the internal thermal control area of ​​the charging pile based on a three-dimensional coordinate system and obtains the spatial positioning coordinates (x, y, z) of each functional module, providing a spatial reference for subsequent temperature analysis and control, thereby realizing the modeling and analysis basis of the heat diffusion path.

[0059] The functional module temperature value acquisition unit is equipped with a temperature sensor on the outer surface of each functional module to realize real-time acquisition of heat release during module operation. It further acquires the heat release of the adjacent m-th functional module, thereby constructing a temperature spatial coupling relationship and effectively identifying the risk of heat accumulation. The heat dissipation equipment temperature value acquisition unit performs quantitative analysis on the temperature released or transferred by the heat dissipation device itself during operation, realizing the calculability and control basis of heat dissipation load. It works in conjunction with the heat release of functional modules to construct the first dataset, providing accurate and dynamic thermal data support for the judgment of thermal risks within the pile.

[0060] Example 3 is an explanation of Example 1; please refer to the provided text. Figure 1 Specifically, the environmental interference acquisition unit is used to set up a wind speed sensor and an infrared temperature sensor outside the target smart charging pile to collect wind speed and temperature near the target smart charging pile and obtain wind speed V and temperature C.

[0061] The environmental interference acquisition unit is used to set a distance detection sensor at the target smart charging pile, detect the distance between the target smart charging pile and the underground garage wall based on the distance sensor, the distance d between the target smart charging pile and the wall, and set several temperature acquisition points distributed along the height direction based on the distance. The temperature sensor is used to collect the temperature at the acquisition points, monitor the temperature gradient change value ΔT in real time, and obtain the underground garage material according to the underground garage construction requirements. The thermal conductivity k of the wall is obtained by looking up a table to obtain the wall heat return intensity factor Q, and a second dataset is constructed.

[0062] In this embodiment, by setting wind speed sensors and infrared temperature sensors outside the smart charging pile, the wind speed V and temperature C in the vicinity of the charging pile can be collected in real time. This enables dynamic acquisition of external air flow and environmental heat load, providing basic data support for environmental thermal interference modeling. The environmental interference acquisition unit further uses distance sensors to measure the distance between the charging pile and the wall. Combined with the structural layout conditions, multiple temperature acquisition points are set along the vertical height direction on the side close to the wall. The thermal gradient change value is obtained through temperature sensors, and the wall heat return intensity factor Q is derived. This method not only considers the wall heat storage effect and heat convection path characteristics, but also realizes the spatial distribution perception of heat return, effectively identifying the potential impact of wall-mounted layout on heat dissipation efficiency.

[0063] All external environmental factors are uniformly constructed into a second dataset and used as input indicators in the calculation of the environmental thermal interference coefficient, which enhances the system's adaptability to unstructured environmental impacts and improves the comprehensiveness and dynamic control capability of the thermal management strategy.

[0064] Example 4 is an explanation of Example 1; please refer to the provided text. Figure 1 Specifically, the early warning analysis module includes a first extraction unit, a first calculation unit, and a first evaluation unit;

[0065] The first extraction unit is used to extract the heat release amount R of the i-th functional module based on the first dataset. i The heating temperature R of the m-th functional module m and the heating temperature S of the heat dissipation equipment;

[0066] The first calculation unit is used to perform dimensionless processing on the data extracted by the first extraction unit, and calculate the internal thermal risk coefficient R of the pile using the following formula. heat ;

[0067]

[0068] In the formula, α1, α2, and α3 are weighting coefficients, and R ref To obtain the reference heat release (the temperature values ​​generated by different functional modules may vary greatly, and direct addition or weighting is not conducive to unified measurement. By dividing by a benchmark value, such as the maximum allowable temperature in the design or the standard reference temperature, the value is "scaled" to a dimensionless ratio or percentage range), the reference heat release R is obtained from the heat load benchmark value specified in the industry-recognized standard. refThe parameters α1 = 0.5, α2 = 0.3, and α3 = 0.2 are preset. A large amount of data collected during actual operation, including heat release from functional modules, thermal interference from neighboring modules, and heat release from cooling equipment, is processed. Combined with actual heat dissipation anomaly assessment results, the data is fitted and analyzed to obtain the parameter combination that best reflects the thermal risk trend. This combination is used to obtain the values ​​of α1, α2, and α3. R0 ref =30℃;

[0069] The following is the pile internal thermal risk coefficient R. heat Example table, see Table 1:

[0070]

[0071]

[0072] In this embodiment, the first extraction unit extracts the heat release of the i-th functional module, the m-th neighboring functional module, and the heat dissipation device in the first dataset. This enables the system to refine the risk source and locate the specific heat source unit based on the temperature distribution relationship between different modules, avoiding misjudgment and response delay caused by large-scale and coarse evaluation. The first calculation unit performs dimensionless processing on the heat release data. By normalizing each temperature with the preset reference heat release (such as industry standards or the maximum value of equipment design), the interference of the difference in the magnitude of thermal parameters of different modules on the evaluation results is avoided, and equivalent comparison and unified measurement of different heat sources are realized under the same evaluation scale.

[0073] Based on the processed normalized temperature index, a thermal risk coefficient within the pile is constructed and used as the core criterion for triggering early warning. Compared with traditional methods that rely on absolute temperature or equipment alarms, this method is more real-time, forward-looking, and systematic, enabling dynamic intervention before thermal runaway occurs.

[0074] Example 5 is an explanation of Example 1; please refer to it. Figure 1 Specifically, the first assessment unit is used to preset the risk threshold E within the pile;

[0075] The distribution of thermal risk coefficients within piles is statistically analyzed from a large amount of normal operation data. Historical abnormal situations or thermal failure case data are used to analyze the distribution range of thermal risk coefficients under these conditions, and the inflection point interval between normal and abnormal situations is identified, which serves as the basis for threshold setting.

[0076] Under normal operation, the thermal risk coefficient of most piles is 0.1-0.3. However, once it exceeds 0.3, the system heat dissipation efficiency is insufficient or the temperature rise is abnormal. In this case, the risk threshold E = 0.30 can be used as the initial safety limit.

[0077] The preset risk threshold E in the pile and the thermal risk coefficient R in the pile are then used to determine the risk threshold E in the pile. heatCompare to generate the first evaluation instruction, including:

[0078] When R heat ≥ E, it indicates that the heat dissipation in the target intelligent charging pile is abnormal, and a first strategy is generated, including increasing the heat dissipation efficiency of the dual-cooling device for the i-th functional module by 32%-50%, and successively increasing the heat dissipation efficiency of the m-th functional module adjacent to the i-th functional module by 30%-40%, by increasing the fan speed of the air-cooling by 10%-20% and increasing the liquid-cooling circulation flow by 25%-34%;

[0079] When R heat < E, it indicates that the heat dissipation in the target intelligent charging pile is normal, and the heat dissipation set speed and circulation flow of the dual-cooling device for the functional module are maintained, and the detection continues.

[0080] Combine the charging pile sample serial number in Table 1 to compare the in-pile risk threshold E with the in-pile heat risk coefficient R heat The comparison example table is shown in Table 2;

[0081]

[0082] In this embodiment, by comparing the in-pile heat risk coefficient with the preset threshold E, the abnormal heat dissipation situation can be effectively identified, and the real-time evaluation and hierarchical early warning mechanism of the heat state of the charging pile can be realized, avoiding the decline or even failure of the equipment performance caused by heat accumulation. When it is detected that R heat ≥ E, the system generates a first strategy to differentially enhance the heat dissipation of the target functional module and its adjacent modules respectively. When the detection result is R heat < E, the system keeps the existing fan speed and liquid-cooling flow unchanged, maintains the equipment heat dissipation setting, avoids the risk of energy waste or local condensation caused by excessive cooling, and realizes the goal of energy conservation and consumption reduction.

[0083] Based on the dynamic risk assessment result to adjust the heat dissipation strategy, the dynamic balance between the heat dissipation performance and the energy consumption control can be realized, greatly reducing the hidden danger of thermal runaway, improving the operation stability of the system, and prolonging the service life of the equipment.

[0084] Example 6. This example is an explanatory note in Example 1. Please refer to Figure 1 , specifically, the early warning analysis module further includes a second extraction unit, a second calculation unit and a second evaluation unit;

[0085] The second extraction unit is used to extract the wind speed V and temperature C in the second data set, and extract the distance d between the target intelligent charging pile and the wall, the wall thermal conductivity k and the temperature gradient change value ΔT, for obtaining the wall heat reflux intensity factor Q;

[0086] Among them, the wall heat reflux intensity factor Q is obtained through the following calculation formula;

[0087]

[0088] The table below shows the reference value for the wall thermal conductivity k.

[0089] The thermal conductivity of the rough concrete surface is 1.4 (W / m·K);

[0090] Marble veneer... is 2.0 (W / m·K);

[0091] The galvanized sheet is rated at 50 (W / m·K).

[0092] Table 3 shows an example of calculating the wall heat return intensity factor Q based on the charging pile sample serial number in Table 2.

[0093]

[0094]

[0095] The second calculation unit is used to calculate the environmental thermal interference coefficient R based on the data extracted from the second data by the second extraction unit, after dimensionless processing, using the following formula. env ;

[0096]

[0097] In the formula, ω1, ω2, and ω3 represent weighting coefficients, and satisfy ω1 + ω2 + ω3 = 1, V ref This represents the industry benchmark value for wind speed. According to the General Code for Design of Civil Buildings, the natural ventilation speed for underground parking garages is typically 0.25 m / s to 0.5 m / s. (C) ref This is expressed as an industry benchmark value for temperature. According to the Technical Specifications for Electrical Safety of Electric Vehicle Charging Facilities, the upper limit for safe operation is set at 25℃ or 40℃. Q ref This is expressed as the industry benchmark value for wall heat return intensity, based on reference values;

[0098] The underground parking garage walls are made of rough, unfinished material, with a distance of 30cm or less from the car, and a heat return intensity reference value of 10W / m. 2 -25W / m 2 When the distance from the car is greater than 30cm, the reference value for heat reflow intensity is 5W / m. 2 -9W / m 2 ;

[0099] The underground parking garage walls are made of smooth marble or ceramic tile, with a distance of 10cm or less from the car, and a heat return intensity reference value of 5W / m. 2 -15W / m 2 When the distance from the car is greater than 10cm, the reference value for heat reflow intensity is 2W / m. 2-4W / m 2 ;

[0100] The underground parking garage walls are made of galvanized steel or aluminum sheet, with a distance of 5cm or less from the car, and a heat return strength reference value of 15W / m. 2 -35W / m 2 When the distance from the car is greater than 5cm, the reference value for heat reflow intensity is 8W / m. 2 -14W / m 2 .

[0101] The additional heat load entering the target smart charging pile due to the return temperature formed by heat convection from the external wall is caused by poor air circulation in the underground garage environment, making it difficult for the temperature to dissipate. The wall may absorb and store the heat, forming a heat "reflection zone" or "heat return zone". The smart charging pile itself generates heat, and if it is close to the wall, it will cause heat accumulation. The wall material (such as concrete) has poor thermal conductivity, and after absorbing heat, it is not easy to dissipate it. Instead, it will radiate or convection back to the equipment. Therefore, monitoring the heat return intensity Q measures the intensity of heat "returning" to the charging pile caused by heat reflection or conduction from the wall. This provides a key variable for calculating the "environmental thermal interference coefficient", and then determines whether to activate secondary heat dissipation strategies (such as increasing air volume, liquid cooling distribution, etc.), improve the foresight of heat dissipation control, reduce the probability of extreme temperature rise or critical alarm, and protect critical functional modules.

[0102] Preset ω1 = 0.3, ω2 = 0.4, and ω3 = 0.3, V ref =0.25, C ref =35, Q ref =100, under multiple environmental conditions (wind speed, temperature, wall material, etc.), the heat dissipation efficiency or temperature rise response of the charging pile is monitored. Multivariate sensitivity analysis is used to determine the influence coefficient of each factor on thermal interference. Based on the analysis results, ω1, ω2 and ω3 are inferred.

[0103] Based on the sample serial number of the charging pile in Table 3, the environmental thermal interference coefficient R is calculated. env Example table, see Table 4.

[0104]

[0105] In this embodiment, the second extraction unit collects the external wind speed V, temperature C, and heat return intensity factor Q formed near the wall of the target smart charging pile. This allows for accurate perception of the interference effect of the local environment in the underground parking lot on the charging pile thermal management system, achieving dynamic correlation identification between the charging pile and the surrounding thermal environment. The second calculation unit performs dimensionless processing on the V, C, and Q data and combines them with weighting coefficients ω1, ω2, and ω3, satisfying ω1+ω2+ω3=1, to perform unified scaling and comprehensive calculation on the three types of thermal interference factors, thereby obtaining the environmental thermal interference coefficient R. envThis will enhance the scientific rigor and stability of assessments of external heat sources.

[0106] This mechanism can quickly identify and issue early warnings for phenomena such as decreased heat dissipation efficiency caused by reduced wind speed, increased local temperature, or enhanced wall heat reflection in underground parking garages. This ensures the charging pile's thermal control system can respond quickly to micro-environmental fluctuations. The calculated R... env It can provide reliable input for subsequent comprehensive temperature control and regulation of the system, and provide quantitative reference for the formulation of strategies such as heat dissipation parameter optimization and load adjustment, thereby enhancing the adaptability and synergy of heat dissipation strategies.

[0107] Example 7 is an explanation of Example 1; please refer to it. Figure 1 Specifically, the second evaluation unit is used to preset the environmental interference threshold T;

[0108] By collecting a large amount of measured data under different environmental scenarios, we analyzed the range distribution of the environmental thermal interference coefficient when the heat dissipation performance was normal and the range distribution when the heat dissipation performance decreased or an alarm was triggered.

[0109] By cross-analyzing these two types of data, a value that "best distinguishes between normal and abnormal" is selected as the threshold.

[0110] The environmental interference threshold T and the environmental thermal interference coefficient R are then compared. env A comparison is made, and a second evaluation instruction is generated, including:

[0111] When R env When T ≥ T, it indicates that the external environmental factors of the target smart charging pile are causing abnormal heat dissipation of the charging pile. A second strategy is generated, which includes increasing the fan speed of the air-cooled equipment by 20%-40% and the circulation speed of the liquid cooling by 15%-25%. In terms of cooling resource allocation, 38%-60% of the heat dissipation power is allocated to the functional modules that are abnormally affected by environmental heat interference. The underground garage fan is started to increase the underground garage wind speed by 10%-35%, thereby reducing the temperature inside the underground garage by 3℃-5℃. The air outlet angle of the target smart charging pile is adjusted upward by 15°-30°.

[0112] When R env When T < T, it indicates that the external environmental factors of the target smart charging pile have a normal impact on the heat dissipation of the charging pile, and monitoring should continue.

[0113] Based on the charging pile sample serial number in Table 4, the environmental interference threshold T and the environmental thermal interference coefficient R were calculated. env For comparison, see Table 5.

[0114]

[0115]

[0116] In this embodiment, by comparing the environmental thermal interference coefficient with a preset threshold T, the system can accurately identify abnormal external heat dissipation caused by factors such as reduced wind speed, increased temperature, or enhanced heat return from the wall. This enables intelligent early warning and strategy linkage for the complex microclimate environment of the underground garage. When the environmental thermal interference coefficient is ≥ T, the system automatically generates a second strategy. The second strategy further controls the operation of the underground garage fan, increasing the garage wind speed by 10%-35%, forming a forced convection ventilation effect, effectively driving away heat accumulation air masses, reducing the overall temperature of the garage by 3℃-5℃, improving the heat exchange conditions around the smart charging pile, and realizing an environmental-assisted cooling collaborative mechanism.

[0117] The system adjusts the heat dissipation vent of the target smart charging pile upward by 15°-30° to change the direction of hot air exhaust, avoid the hot air from flowing back into the wall and causing heat accumulation, and reduce the reverse interference of the wall surface heat return effect on the system.

[0118] Example 8 is an explanation of Example 1; please refer to it. Figure 1 Specifically, the evaluation and optimization module includes an associated unit and a third evaluation unit;

[0119] The associated unit is used to determine the internal thermal risk factor R of the pile. heat With environmental thermal interference coefficient R env Correlated, dimensionless processing is performed, and the comprehensive temperature control adjustment coefficient R is calculated using the following formula. total ;

[0120] R total =ρ1×R heat +ρ2×R env ;

[0121] In the formula, ρ1 and ρ2 are weighting coefficients, and ρ1+ρ2=1.

[0122] With preset values ​​of ρ1 = 0.6 and ρ2 = 0.4, and based on actual system operation and historical data experience, combined with industry-standard criteria, the importance of each indicator to the heat dissipation system is assessed, and corresponding weights are assigned. For example, the internal thermal risk coefficient often more directly reflects the heat generation of the equipment itself, and therefore has a larger weight. The environmental thermal interference coefficient has a smaller weight.

[0123] Based on the charging pile sample serial number in Table 5, the comprehensive temperature control adjustment coefficient R is calculated. total An example table is shown in Table 6;

[0124]

[0125] In this embodiment, the internal thermal risk coefficient R of the pile is linked through the "associated unit". heat With environmental thermal interference coefficient R envWeighted fusion is performed to construct a unified comprehensive temperature control regulation coefficient R. total This system enhances its ability to identify the combined effects of "internal thermal load" and "external environmental thermal interference," enabling unified evaluation and modeling of multi-source thermal factors. The system performs dimensionless normalization on the two types of heterogeneous thermal risk parameters, using industry reference heat release, wind speed, temperature, and regeneration intensity as benchmarks to make different physical quantities comparable, thereby enhancing the stability and generalization of the model. It is applicable to various deployment scenarios and smart charging pile systems of different specifications.

[0126] The comprehensive temperature control adjustment coefficient serves as a unified basis for judging the internal and external thermal states of the pile, providing quantitative decision-making support for the third evaluation unit to generate a comprehensive strategy. Compared with relying solely on a single heat source, the strategy triggering is more scientific, resource allocation is more precise, and the control efficiency and system response stability are significantly improved.

[0127] Example 9, this example is an explanation of Example 1, please refer to it. Figure 1 Specifically, the third evaluation unit is used to preset the temperature control adjustment threshold Y;

[0128] By collecting and analyzing the comprehensive temperature control adjustment coefficient of a large number of charging piles in actual operating environment, the distribution of the comprehensive adjustment coefficient when the system heat dissipation is normal and abnormal is statistically analyzed. For example, by comparing the distribution of the comprehensive adjustment coefficient that shows normal operation in historical data with the distribution of the coefficient that has experienced abnormal heat dissipation events, a dividing point is found. This dividing point is used as a threshold, so that when the comprehensive adjustment coefficient is greater than or equal to Y, the system is judged to be in a state of abnormal heat dissipation, and when it is lower than Y, it is judged to be in a state of normal operation.

[0129] The temperature control threshold Y and the comprehensive temperature control coefficient R are then combined. total A comparison is made, and a third evaluation instruction is generated, including:

[0130] When R total When ≥Y, it indicates that the target smart charging pile has abnormal heat dissipation. A third strategy is generated, which includes increasing the power of the air-cooled equipment by 20%-40%, increasing the circulation flow rate of the liquid-cooled equipment by 33%-50%, dynamically adjusting the allocation ratio of cooling resources of the dual-cooling equipment to the heat control zone, increasing the cooling resources for functional modules with abnormal heat release by 30%-60%, increasing the wind speed of the underground garage fan by 22%-35%, and adjusting the angle of the heat dissipation port of the target smart charging pile by 10%-15%.

[0131] When R total When <Y, it indicates that the target smart charging pile has normal heat dissipation. It will continue to dissipate heat in the set heat dissipation mode and monitor it in real time.

[0132] Based on the charging pile sample serial number in Table 6, the temperature control adjustment threshold Y and the comprehensive temperature control adjustment coefficient R are calculated. totalFor comparison, see Table 7.

[0133]

[0134] In this embodiment, the third evaluation unit evaluates the overall thermal state based on the preset temperature control adjustment threshold Y and the combined thermal state after integrating the internal thermal risk and external thermal interference. It can accurately identify the overall abnormal heat dissipation state and trigger a coordinated cooling control strategy, thereby realizing adaptive temperature control management in multi-source thermal disturbance scenarios. When an anomaly is identified, the system dynamically adjusts the power output and circulation flow of the dual cooling equipment (air cooling + liquid cooling) through a partitioning strategy. In particular, it centrally allocates cooling resources to the functional modules in the abnormal area (such as centrally supplying 30%-60% of the cooling resources), effectively improving cooling efficiency and avoiding resource waste and inefficient adjustment.

[0135] By increasing the power of air-cooled equipment and the flow rate of liquid cooling, and combining it with a 10%-15% intelligent upward adjustment mechanism for the angle of the heat dissipation vents, a three-dimensional heat dissipation regulation system combining "point and surface" is formed. This enhances the cooling speed of hot spots, suppresses heat accumulation, and effectively reduces the risk of thermal runaway and internal overload damage. When the system identifies heat retention caused by environmental thermal interference, the evaluation module can intelligently trigger the garage fan to increase the wind speed by 20%-35%. Through the adjustment of the overall wind speed and flow field in the underground space, it helps to alleviate environmental thermal disturbances and dissipate local hot airflow, thereby improving the adaptability of the cooling system to external conditions.

[0136] Example 10, please refer to Figure 2 Specifically, a dual-cooling heat dissipation control method for smart charging piles with zoned control includes:

[0137] Step 1: First, the target smart charging pile in the underground parking garage adjacent to the wall is divided into several thermal control zones. The temperature generated by the functional module and the temperature generated by the heat dissipation equipment in each thermal control zone are collected in real time. The additional heat load entering the target smart charging pile from the external wall due to heat convection when the target smart charging pile is deployed close to the wall is also monitored.

[0138] Step Two: Next, construct the internal thermal risk coefficient R of the pile based on the data collected in Step One. heat and environmental thermal interference coefficient R env ;

[0139] Step 3: Finally, calculate the internal thermal risk factor R of the pile. heat and environmental thermal interference coefficient R env Integration to construct a comprehensive temperature control regulation coefficient R total And conduct evaluation and optimization.

[0140] In this embodiment, by dividing the interior of the charging pile into multiple thermal control zones and collecting the heat release of functional modules and heat dissipation equipment in each zone in real time, while monitoring the heat return intensity of the wall under wall deployment, the local and overall thermal distribution of the charging pile can be fully restored, providing data support for subsequent temperature control strategies. The heat release of the functional modules themselves and environmental factors such as wall convection heat return and garage wind speed are respectively constructed as the "heat risk coefficient inside the pile" and the "environmental thermal interference coefficient", which effectively solves the limitation of existing technologies that only focus on the heat source of the equipment itself and ignore the environmental impact, and improves the comprehensiveness and accuracy of thermal risk assessment.

[0141] By integrating two types of thermal coefficients to form a "comprehensive temperature control adjustment coefficient," and setting evaluation thresholds for dynamic comparison and strategy distribution, the system can adaptively adjust key parameters such as air-cooled power, liquid-cooled flow rate, and air outlet angle according to different thermal states. This enables dynamic redistribution of cooling resources in different zones, improves the cooling efficiency of key modules, and automatically links the underground garage fans based on the intensity of environmental thermal interference to optimize wind speed and ventilation direction, improve ventilation and heat exchange conditions, avoid heat accumulation, and enhance the environmental adaptability and overall heat dissipation stability of the cooling system.

[0142] The threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by those skilled in the art for each set of sample data; as long as it does not affect the ratio between the parameter and the quantized value, it is acceptable.

[0143] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A dual-cooling and heat dissipation system for a smart charging pile with zoned control, characterized in that, It includes a regional division and data collection module, an early warning and analysis module, and an evaluation and optimization module; The area division and acquisition module is used to divide the target smart charging pile in the wall adjacent to the underground parking garage into several thermal control zones, and to set dynamic temperature monitoring points in each thermal control zone. Based on the dynamic temperature monitoring points, it is used to monitor the temperature generated by the functional modules in each thermal control zone and the temperature generated by the heat dissipation equipment in each thermal control zone in real time. It is also used to monitor the additional heat load that enters the target smart charging pile from the external wall due to heat convection when the target smart charging pile is deployed close to the wall, and to construct the first dataset and the second dataset respectively. The early warning analysis module is used to construct the internal thermal risk coefficient R of the pile based on the first dataset. heat The environmental thermal disturbance coefficient R is constructed based on the second dataset. env And generate a first evaluation instruction and a second evaluation instruction respectively, and generate a corresponding first strategy and a second strategy; The evaluation and optimization module is used to correlate the internal thermal risk coefficient of the pile with the environmental thermal interference coefficient to construct a comprehensive temperature control adjustment coefficient R. total It then generates a third evaluation instruction and a corresponding third strategy.

2. The dual cooling and heat dissipation system for a smart charging pile with zoned control according to claim 1, characterized in that, The region division acquisition module includes a region division unit, a functional module temperature value acquisition unit, a heat dissipation device temperature value acquisition unit, and an environmental interference acquisition unit; The region division unit is used to divide the target smart charging pile into several regions and construct a three-dimensional coordinate system to obtain the coordinate system x, y, z of the i-th functional module; The functional module temperature value acquisition unit is used to install a temperature sensor on the outer surface of each thermal control zone functional module, and acquire the temperature value generated by the functional module in each thermal control zone based on the temperature sensor to obtain the heat release R of the i-th functional module. i ; The functional module temperature value acquisition unit is also used to acquire the heating temperature value of the m-th functional module adjacent to the i-th functional module, so as to obtain the heating temperature R of the m-th functional module. m ; The heat dissipation equipment temperature value acquisition unit is used to acquire the temperature released by the heat dissipation equipment installed in the target smart charging pile in order to obtain the heat dissipation equipment heating temperature S. Based on the heat release R of the i-th functional module i The heating temperature R of the m-th functional module m The first dataset is constructed based on the heat dissipation temperature S of the heat dissipation device.

3. The dual cooling and heat dissipation system for a zoned intelligent charging pile according to claim 2, characterized in that, The environmental interference acquisition unit is used to set up a wind speed sensor and an infrared temperature sensor outside the target smart charging pile to collect wind speed and temperature near the target smart charging pile and obtain wind speed V and temperature C. The environmental interference acquisition unit is used to set a distance detection sensor at the target smart charging pile, detect the distance between the target smart charging pile and the underground garage wall based on the distance sensor, the distance d between the target smart charging pile and the wall, and set several temperature acquisition points distributed along the height direction based on the distance. The temperature sensor is used to collect the temperature at the acquisition points, monitor the temperature gradient change value ΔT in real time, and obtain the underground garage material according to the underground garage construction requirements. The thermal conductivity k of the wall is obtained by looking up a table to obtain the wall heat return intensity factor Q, and a second dataset is constructed.

4. The dual cooling and heat dissipation system for a zoned intelligent charging pile according to claim 3, characterized in that, The early warning analysis module includes a first extraction unit, a first calculation unit, and a first evaluation unit; The first extraction unit is used to extract the heat release amount R of the i-th functional module based on the first dataset. i The heating temperature R of the m-th functional module m and the heating temperature S of the heat dissipation equipment; The first calculation unit is used to calculate the internal thermal risk coefficient R of the pile based on the data extracted by the first extraction unit. heat .

5. The dual cooling and heat dissipation system for a zone-controlled intelligent charging pile according to claim 4, characterized in that, The first assessment unit is used to preset the pile internal risk threshold E and to compare the preset pile internal risk threshold E with the pile internal thermal risk coefficient R. heat A comparison is performed to generate the first evaluation instruction, including: When R heat When ≥E, it indicates that the heat dissipation inside the target smart charging pile is abnormal, and the first strategy is generated, which includes improving the heat dissipation efficiency of the i-th functional module by 32%-50% with the dual cooling equipment, and also improving the heat dissipation efficiency of the m-th functional module adjacent to the i-th functional module by 30%-40% by increasing the fan speed in the air cooling by 10%-20% and the liquid cooling circulation flow by 25%-34%. When R heat When the value is <E, it indicates that the heat dissipation inside the target smart charging pile is normal. Maintain the set speed and circulation flow rate of the dual-cooling equipment for the heat dissipation of the functional modules, and continue testing.

6. The dual cooling and heat dissipation system for a zoned intelligent charging pile according to claim 5, characterized in that, The early warning analysis module also includes a second extraction unit, a second calculation unit, and a second evaluation unit; The second extraction unit is used to extract the wind speed V, temperature C, and wall heat return intensity factor Q from the second dataset; The second calculation unit is used to calculate the environmental thermal interference coefficient R based on the data extracted from the second data by the second extraction unit. env .

7. The dual cooling and heat dissipation system for a zone-controlled intelligent charging pile according to claim 6, characterized in that, The second evaluation unit is used to preset the environmental interference threshold T and compare the environmental interference threshold T with the environmental thermal interference coefficient R. env A comparison is made, and a second evaluation instruction is generated, including: When R env When T ≥ T, it indicates that the external environmental factors of the target smart charging pile are causing abnormal heat dissipation of the charging pile. A second strategy is generated, which includes increasing the fan speed of the air-cooled equipment by 20%-40% and the circulation speed of the liquid cooling by 15%-25%. In terms of cooling resource allocation, 38%-60% of the heat dissipation power is allocated to the functional modules that are abnormally affected by environmental heat interference. The underground garage fan is started to increase the underground garage wind speed by 10%-35%, thereby reducing the temperature inside the underground garage by 3℃-5℃. The air outlet angle of the target smart charging pile is adjusted upward by 15°-30°. When R env When T < T, it indicates that the external environmental factors of the target smart charging pile have a normal impact on the heat dissipation of the charging pile, and monitoring should continue.

8. The dual cooling and heat dissipation system for a zoned intelligent charging pile according to claim 7, characterized in that, The evaluation and optimization module includes an associated unit and a third evaluation unit; The associated unit is used to determine the internal thermal risk factor R of the pile. heat With environmental thermal interference coefficient R env Correlatedly, the comprehensive temperature control adjustment coefficient R is obtained through calculation. total .

9. A dual-cooling heat dissipation system for a smart charging pile with zoned control according to claim 8, characterized in that, The third evaluation unit is used to preset the temperature control adjustment threshold Y and to compare the temperature control adjustment threshold Y with the comprehensive temperature control adjustment coefficient R. total A comparison is made, and a third evaluation instruction is generated, including: When R total When ≥Y, it indicates that the target smart charging pile has abnormal heat dissipation. A third strategy is generated, which includes increasing the power of the air-cooled equipment by 20%-40%, increasing the circulation flow rate of the liquid-cooled equipment by 33%-50%, dynamically adjusting the allocation ratio of cooling resources of the dual-cooling equipment to the heat control zone, increasing the cooling resources for functional modules with abnormal heat release by 30%-60%, increasing the wind speed of the underground garage fan by 22%-35%, and adjusting the angle of the heat dissipation port of the target smart charging pile by 10%-15%. When R total When <Y, it indicates that the target smart charging pile has normal heat dissipation. It will continue to dissipate heat in the set heat dissipation mode and monitor it in real time.

10. A zone-controlled intelligent charging pile dual-cooling heat dissipation control method, applied to the zone-controlled intelligent charging pile dual-cooling heat dissipation system according to any one of claims 1-9, characterized in that, include; Step 1: First, the target smart charging pile in the underground parking garage adjacent to the wall is divided into several thermal control zones. The temperature generated by the functional module and the temperature generated by the heat dissipation equipment in each thermal control zone are collected in real time. The additional heat load entering the target smart charging pile from the external wall due to heat convection when the target smart charging pile is deployed close to the wall is also monitored. Step 2: Next, construct the internal thermal risk coefficient and the environmental thermal interference coefficient based on the data collected in Step 1; Step 3: Finally, the internal thermal risk coefficient and the environmental thermal interference coefficient are integrated to construct a comprehensive temperature control regulation coefficient, which is then evaluated and optimized.

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