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

Abstract

The invention provides a zone-controlled intelligent charging pile double-cooling heat dissipation system and a control method, and belongs to the technical field of charging pile heat dissipation. Comprising an area division acquisition module used for monitoring the temperature generated by a function module in each thermal control area and the temperature generated by heat dissipation equipment in each thermal control area in real time and constructing a first data set and a second data set, and an early warning analysis module used for constructing an in-pile thermal risk coefficient Rheat and an environment thermal interference coefficient Renv, and the evaluation optimization module is used for constructing a comprehensive temperature control adjustment coefficient Rtotal. According to the system, the heating temperature of the function module is accurately monitored in a zoning manner, heat dissipation is quickly performed on the function module, the temperature change of the function module can be predicted in advance, the power consumption of equipment is reduced, and the heat dissipation efficiency of the equipment is improved.

Description

Technical Field

[0001] The present invention relates to the field of charging pile heat dissipation technology, and in particular to a zone-controlled intelligent charging pile dual cooling and heat dissipation system and a control method. Background Art

[0002] With the rapid adoption of new energy vehicles, high-power charging piles are becoming increasingly common, serving as essential equipment for meeting the demand for fast charging. However, due to the varying charging powers, charging piles in fast and slow charging modes generate significantly different heat loads. If the cooling system is inadequate or the heat load is unevenly distributed, localized overheating can occur, impacting charging efficiency and even causing power module overheating, performance degradation, and shortened equipment life. Therefore, ensuring the efficiency and reliability of the cooling system has become a key technology in the design of high-power charging piles.

[0003] Private new energy vehicle charging stations are often installed in underground garages, some even close to the walls. In practice, due to space utilization and wiring convenience, private smart charging stations are often installed in relatively enclosed locations like underground garages, often placed close to the walls. This type of placement close to the wall presents significant thermal management challenges: the wall absorbs and retains heat, creating a backflow due to convection. This in turn forces some hot air back into the charging station, creating additional heat load and further increasing the temperature inside the station. Most existing smart charging stations utilize a single air-cooled or passive heat dissipation structure, failing to fully account for the uneven heat load caused by heat backflow in enclosed spaces and against the wall. This results in inefficient localized heat dissipation, which can easily trigger device overheating protection, leading to unstable operation and even overtemperature shutdown. 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 deployment environments. Summary of the Invention

[0004] In order to make up for the above shortcomings, the present invention provides a partition-controlled intelligent charging pile dual cooling and heat dissipation system and control method that overcomes the above technical problems or at least partially solves the above problems.

[0005] The present invention is achieved in that:

[0006] The present invention provides a zone-controlled intelligent charging pile dual cooling and heat dissipation system, which includes a zone division acquisition module, a warning analysis module, and an evaluation and optimization module;

[0007] The region division acquisition module is configured to divide a target intelligent charging pile adjacent to a wall of an underground parking garage into a plurality of thermal control regions, and set dynamic temperature monitoring points in each thermal control region, so as to monitor the temperature generated by a functional module in each thermal control region and the temperature generated by a heat dissipation device in each thermal control region in real time according to the dynamic temperature monitoring points, and monitor the backflow temperature formed by the external wall due to thermal convection when the target intelligent charging pile is arranged close to the wall, and enter the target intelligent charging pile as additional heat load, and construct a first data set and a second data set respectively.

[0008] The early warning analysis module is configured to construct a pile-internal thermal risk coefficient R heat according to the first data set, construct an environmental thermal interference coefficient R env according to the second data set, 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 optimization module is configured to associate the pile-internal thermal risk coefficient and the environmental thermal interference coefficient, construct a comprehensive temperature control adjustment coefficient R total , and generate a third evaluation instruction, and generate a corresponding third strategy.

[0010] In a preferred scheme, 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.

[0011] The region division unit is configured to divide the target intelligent charging pile into a plurality of regions, and construct a three-dimensional coordinate system to obtain the coordinates x, y, and z of the i th functional module.

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

[0013] The functional module temperature value acquisition unit is further configured to acquire the heat generation temperature value of the m th functional module adjacent to the i th functional module, to obtain the heat generation temperature R m of the m th functional module.

[0014] The heat dissipation device temperature value acquisition unit is configured to acquire the temperature released by the heat dissipation device arranged in the target intelligent charging pile, to obtain the heat generation temperature S of the heat dissipation device.

[0015] The first data set is constructed based on the heat release amount R i of the i th functional module, the heat generation temperature R m of the m th functional module, and the heat generation temperature S of the heat dissipation device.

[0016] In a preferred scheme, the environmental interference acquisition unit is configured to set a wind speed sensor and an infrared temperature sensor outside the target intelligent charging pile to collect the wind speed and temperature near the target intelligent charging pile, and obtain the wind speed V and the temperature C;

[0017] The environmental interference acquisition unit is configured to set a distance detection sensor on the target intelligent charging pile, detect the distance between the target intelligent charging pile and the wall of the underground garage based on the distance sensor, obtain the distance d between the target intelligent charging pile and the wall, set a plurality of temperature collection points distributed in the height direction based on the distance, collect the temperatures of the collection points by using the temperature sensor, monitor the temperature gradient change value AT in real time, obtain the material of the underground garage according to the construction requirements of the underground garage, obtain the thermal conductivity k of the wall by looking up a table, obtain the wall heat backflow intensity factor Q, and construct a second data set.

[0018] In a preferred scheme, 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 configured to take out the heat release amount R i , the heat generation temperature R m of the mth functional module and the heat generation temperature S of the heat dissipation equipment based on the first data set.

[0020] The first calculation unit is configured to obtain the in-pile thermal risk coefficient R heat by calculation according to the data extracted by the first extraction unit.

[0021] In a preferred scheme, the first evaluation unit is configured to preset an in-pile risk threshold E, compare the in-pile risk threshold E with the in-pile thermal risk coefficient R heat , and generate a first evaluation instruction, including:

[0022] When R heat ≥ E, it indicates that the heat dissipation in the target intelligent charging pile is abnormal, a first strategy is generated, including increasing the heat dissipation efficiency of the double-cooling equipment on the ith functional module by 32%-50%, and also increasing the heat dissipation efficiency of the mth functional module adjacent to the ith functional module by 30%-40%, by increasing the fan speed of the air cooling by 10%-20% and increasing the circulation flow of the liquid cooling by 25%-34%;

[0023] When R heat <E, it indicates that the heat dissipation in the target intelligent charging pile is normal, the heat dissipation setting speed and circulation flow of the double-cooling equipment on the functional module are maintained, and the detection is continued.

[0024] In a preferred scheme, 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 recirculation intensity factor Q from the second data set;

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

[0027] In a preferred solution, the second evaluation unit is used to preset an environmental interference threshold T and compare the environmental interference threshold T with the environmental thermal interference coefficient R env Perform a comparison and generate a second evaluation instruction, including:

[0028] When R env When ≥T, it indicates that the external environmental factors of the target smart charging pile have an abnormal heat dissipation effect on the charging pile. The second strategy is generated, including increasing the fan speed of the air-cooling equipment by 20%-40% and the circulation flow rate of the liquid cooling by 15%-25%. The cooling resources are allocated, and 38%-60% of the heat dissipation power of the heat dissipation resources is allocated to the functional modules affected by the abnormal environmental thermal interference. The underground garage fan is started, and the wind speed in the underground garage is increased by 10%-35%, thereby reducing the temperature in the underground garage by 3℃-5℃. The air outlet angle of the target smart charging pile is increased by 15°-30°.

[0029] When R env When <T, it means 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 continues.

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

[0031] The associated unit is used to convert the heat risk coefficient R heat Thermal interference coefficient with the environment R env The comprehensive temperature control adjustment coefficient R is obtained by calculation total .

[0032] In a preferred solution, the third evaluation unit is used to preset the temperature control adjustment threshold value Y and compare the temperature control adjustment threshold value Y with the comprehensive temperature control adjustment coefficient R total Perform a comparison and generate a third evaluation instruction, including:

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

[0034] When R total When <Y, it indicates that the heat dissipation of the target smart charging pile is normal, and the set heat dissipation method is maintained for heat dissipation and real-time monitoring is performed.

[0035] A dual-cooling heat dissipation control method for a zone-controlled intelligent charging pile, comprising:

[0036] Step 1: First, the target smart charging pile adjacent to the wall of the underground parking garage is divided into several thermal control zones. The temperature generated by the functional modules and the temperature generated by the heat dissipation devices in each thermal control zone are collected in real time. The target smart charging pile is also monitored. When the target smart charging pile is placed close to the wall, the return flow temperature generated by heat convection from the external wall enters the target smart charging pile, which adds additional heat load.

[0037] Step 2: Secondly, construct the pile thermal risk coefficient R according to the data collected in step 1. heat and the ambient thermal interference coefficient R env ;

[0038] Step 3: Finally, the heat risk factor R heat and the ambient thermal interference coefficient R env Integration, build comprehensive temperature control adjustment coefficient R total , and conduct evaluation and optimization.

[0039] The present invention provides a zone-controlled intelligent charging pile dual cooling and heat dissipation system and control method, which has the following beneficial effects:

[0040] 1. By dividing the internal thermal control area of ​​the charging pile and setting dynamic temperature monitoring points, it is possible to achieve refined collection of the temperature release conditions of each functional module. Combined with the heat output monitoring of the heat dissipation device itself, a comprehensive temperature monitoring model is constructed to improve 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, the environmental thermal interference coefficient is constructed, which realizes the effective identification and quantitative analysis of external thermal influences in complex layout environments such as underground garages, reducing power consumption and improving heat dissipation efficiency.

[0041] 2. By automatically generating heat dissipation enhancement strategies when the heat risk coefficient or the interference coefficient exceeds the set threshold, such as increasing the heat dissipation efficiency of the corresponding area by 10%-50%, adjusting the heat dissipation direction or air duct angle, etc., effectively preventing heat accumulation, predicting temperature changes, and improving the reliability and safety of the charging pile heat dissipation. BRIEF DESCRIPTION OF DRAWINGS

[0042] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the drawings needed in the specific embodiments or prior art description will be briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, each element or part is not necessarily drawn according to the actual scale.

[0043] Figure 1 is a system block diagram in the present application;

[0044] Figure 2 is a method flowchart in the present application. DETAILED DESCRIPTION

[0045] The embodiments of the technical solutions of the present application will be described in detail below with reference to the drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present application, and therefore only serve as examples, but cannot limit the protection scope of the present application.

[0046] Example 1, refer to Figure 1 The present application provides a technical solution: a partition-controlled intelligent charging pile double-cooling heat dissipation system, comprising a region division acquisition module, a early warning analysis module and an evaluation optimization module;

[0047] The region division acquisition module is used for dividing the target intelligent charging pile adjacent to the wall of the underground parking garage into a plurality of thermal control regions, and setting dynamic temperature monitoring points in each thermal control region, for monitoring the temperature generated by the functional modules in each thermal control region and the temperature generated by the heat dissipation equipment of each thermal control region according to the dynamic temperature monitoring points, and also for monitoring the additional heat load of the target intelligent charging pile caused by the backflow temperature from the external wall due to thermal convection when the target intelligent charging pile is arranged close to the wall, and constructing a first data set and a second data set respectively;

[0048] The early warning analysis module is used for constructing a pile heat risk coefficient R heat according to the first data set, constructing an environmental heat interference coefficient R env according to the second data set, and generating a first evaluation instruction and a second evaluation instruction respectively, and generating a corresponding first strategy and a second strategy;

[0049] The evaluation optimization module is used for associating the pile heat risk coefficient and the environmental heat interference coefficient, and constructing a comprehensive temperature control adjustment coefficient R totalAnd generate a third evaluation instruction, and generate a corresponding third strategy.

[0050] In this embodiment, by dividing the internal charging pile into heat control regions and setting dynamic temperature monitoring points, the temperature release of each functional module can be collected in detail. Combined with the heat output monitoring of the heat dissipation equipment, a comprehensive temperature monitoring model is constructed, which improves the accuracy of temperature monitoring. At the same time, by collecting the heat load caused by external heat convection when the charging pile is close to the wall, the environmental heat interference coefficient is constructed, and the effective identification and quantitative analysis of external heat influence in complex environments such as underground garages are realized. Further, combined with the heat risk coefficient in the pile, the evaluation optimization module can form a comprehensive temperature control adjustment coefficient, and generate a control strategy according to the coefficient to realize dynamic adjustment and partition optimization control of the cooling system.

[0051] When the heat risk coefficient or the interference coefficient exceeds the set threshold, the system can automatically generate a heat dissipation enhancement strategy, such as increasing the heat dissipation efficiency of the corresponding region 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 heat dissipation.

[0052] Embodiment 2, this embodiment is an explanation and description in embodiment 1, please refer to Figure 1 Specifically, the region division and collection module includes a region division unit, a functional module temperature value collection unit, a heat dissipation equipment temperature value collection unit, and an environmental interference collection unit.

[0053] The region division unit is configured to divide the target intelligent charging pile into a plurality of regions, and construct a three-dimensional coordinate system to obtain the coordinates x, y, and z of the i-th functional module.

[0054] The functional module temperature value collection unit is configured to set temperature sensors on the outer surfaces of the functional modules in each heat control region, and collect the temperature values generated by the functional modules in each heat control region based on the temperature sensors to obtain the heat release amount R i of the i-th functional module.

[0055] The functional module temperature value collection unit is further configured to collect the heat generation temperature R m of the m-th functional module adjacent to the i-th functional module to obtain the heat generation temperature R m of the m-th functional module.

[0056] The heat dissipation equipment temperature value collection unit is configured to collect the temperature released by the heat dissipation equipment set in the target intelligent charging pile to obtain the heat generation temperature S of the heat dissipation equipment.

[0057] Based on the heat release amount R i of the i-th functional module and the heat generation temperature R m of the m-th functional module, the evaluation optimization module is configured to generate a third evaluation instruction, and generate a corresponding third strategy.m and the heating temperature S of the heat dissipation device to construct a first data set.

[0058] In this embodiment, the area division and acquisition module provided by the present invention realizes the refined identification of the internal thermal environment of the smart charging pile and the acquisition of multi-dimensional temperature data by introducing the area division unit, the functional module temperature value acquisition unit, the heat dissipation device temperature value acquisition unit and the environmental interference acquisition unit. Among them, the area division unit divides the thermal control area inside the charging pile based on the three-dimensional coordinate system, and obtains the positioning coordinates (x, y, z) of each functional module in space, providing a spatial reference basis 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, and further acquires the heat release amount of the adjacent m-th functional module, thereby constructing a temperature-space coupling relationship and effectively identifying the risk of heat accumulation. The heat dissipation device temperature value acquisition unit quantitatively analyzes the temperature released or transferred by the heat dissipation device itself during operation, realizing the calculability and regulation basis of the heat dissipation load, and coordinating with the heat release amount of the functional module to construct the first data set, providing accurate and dynamic thermal data support for the judgment of heat risk in the pile.

[0060] Example 3, this example is the explanation in Example 1, please refer to Figure 1 Specifically, the environmental interference collection unit is used to set a wind speed sensor and an infrared temperature sensor outside the target smart charging pile to collect the wind speed and temperature near the target smart charging pile to obtain the wind speed V and temperature C;

[0061] The environmental interference collection unit is used to set a distance detection sensor on the target smart charging pile, detect the distance between the target smart charging pile and the underground garage wall based on the distance sensor, and the distance d between the target smart charging pile and the wall. Based on the distance, several temperature collection points distributed along the height direction are set, and the temperature sensor is used to collect the temperature of the collection points, and the temperature gradient change value ΔT is monitored in real time. In combination with the construction requirements of the underground garage, the underground garage material is obtained, and the wall thermal conductivity k is obtained by table lookup to obtain the wall heat reflow intensity factor Q, and construct a second data set.

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

[0063] All external environmental factors are uniformly constructed into a second data set and used as input indicators in the calculation of the environmental thermal interference coefficient, which enhances the system's adaptability to non-structural environmental influences and improves the comprehensiveness and dynamic control capabilities of the thermal management strategy.

[0064] Example 4: This example is an explanation of Example 1. Please refer to 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 data set. i , heating temperature R of the mth functional module m and the heat dissipation temperature S of the heat dissipation device;

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

[0067]

[0068] In the formula, α1, α2 and α3 are weight coefficients, R ref To obtain the reference heat release (the temperature values ​​generated by each functional module may vary greatly, and direct addition or weighting is not conducive to a unified measurement. By dividing by a reference 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 heat load reference value specified in the industry-recognized standard is used to obtain the reference heat release R ref. The preset a1=0.5, a2=0.3 and a3=0.2, by sorting a large number of heat release of functional modules, adjacent module heat interference and heat dissipation equipment heat release and other data collected in actual operation, combined with actual heat dissipation abnormal judgment result, the data is fitted and analyzed, the parameter combination that can best reflect the heat risk trend is obtained, which is used to obtain the values of a1, a2 and a3, R ref = 30℃;

[0069] The following is the in-pile thermal risk coefficient R heat The example table is shown in Table 1:

[0070]

[0071]

[0072] In this embodiment, the heat release of the i-th functional module, the m-th adjacent functional module and the heat dissipation equipment in the first data set is extracted by the first extraction unit, so that the system can locate the risk source to the specific heat source unit based on the temperature distribution relationship between different modules, avoid misjudgment and response delay caused by large-scale and extensive evaluation, and the first calculation unit carries out dimensionless processing on the heat release data. By normalizing each temperature with the preset reference heat release (such as industry standard, maximum value of equipment design), the influence of the difference in the order of magnitude of the thermal parameters of different modules on the evaluation result is avoided, and equivalent comparison and unified measurement of different heat sources under the same evaluation scale are realized.

[0073] Based on the processed normalized temperature index, the in-pile thermal risk coefficient is constructed, and is used as the core criterion for early warning triggering. Compared with the traditional method of relying on absolute temperature or device alarm, this method is more real-time, forward-looking and systematic, and can realize dynamic intervention before thermal runaway occurs.

[0074] Embodiment 5, this embodiment is an explanation and description in embodiment 1, please refer to Figure 1 Specifically, the first evaluation unit is configured to preset an in-pile risk threshold E.

[0075] The distribution of the in-pile thermal risk coefficient is counted in a large number of normal operation data, the distribution range of the thermal risk coefficient under these conditions is analyzed by using historical abnormal situation or thermal failure case data, and the inflection point interval between normal and abnormal is found out, which is used as the threshold setting basis;

[0076] Under normal operation, most of the in-pile thermal risk coefficients are 0.1-0.3, but once it exceeds 0.3, the system heat dissipation efficiency is insufficient or the temperature rise is abnormal, and then the risk threshold E=0.30 can be used as the initial safety limit value.

[0077] And the preset in-pile risk threshold E and the in-pile thermal risk coefficient R heatThe comparison is made 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 double-cooling device to the i-th functional module by 32%-50%, and also 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 setting speed and circulation flow of the double-cooling device to the functional module are maintained, and the detection continues.

[0080] In combination with Table 1, the pile risk threshold E and the pile heat risk coefficient R heat The comparison example table is shown in Table 2;

[0081]

[0082] In this embodiment, by comparing the pile heat risk coefficient with the preset threshold E, the heat dissipation abnormality can be effectively identified, the real-time evaluation and grading early warning mechanism of the charging pile heat state can be realized, and the performance degradation or even failure of the equipment caused by heat accumulation can be avoided. When R heat ≥ E, the system generates a first strategy to differentially enhance the heat dissipation of the target functional module and its adjacent module, and when the detection result is R heat <E, the system maintains the existing fan speed and liquid cooling flow, maintains the equipment heat dissipation setting, avoids excessive cooling to cause energy waste or local condensation risk, and realizes the energy saving and consumption reduction target.

[0083] Based on the dynamic risk evaluation result, the heat dissipation strategy is adjusted, the dynamic balance between the heat dissipation performance and the energy consumption control can be realized, the heat runaway hidden danger is greatly reduced, the system operation stability is improved, and the equipment service life is prolonged.

[0084] Embodiment 6, this embodiment is an explanation and description in Embodiment 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 configured to extract the wind speed V and the 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, to obtain the wall heat backflow intensity factor Q.

[0086] The wall heat backflow intensity factor Q is obtained by the following calculation formula:

[0087]

[0088] The look-up table of wall thermal conductivity k is shown as follows:

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

[0090] The thermal conductivity of the marble veneer is 2.0 (W / m·K);

[0091] The thermal conductivity of the galvanized sheet is 50 (W / m·K);

[0092] The calculation example table of wall thermal backflow intensity factor Q in combination with the charging pile sample serial number in Table 2 is shown in Table 3.

[0093]

[0094]

[0095] The second calculation unit is configured to calculate an environmental thermal interference coefficient R according to the data extracted from the second data by the second extraction unit, through dimensionless processing, and through the following formula env ;

[0096]

[0097] In the formula, ω1, ω2 and ω3 represent weight coefficients, and satisfy ω1+ω2+ω3=1, V ref represents a wind speed industry reference value, and according to the General Rules for Civil Building Design, the natural ventilation of an underground garage is usually 0.25 m / s-0.5 m / s, ref represents a temperature industry reference value, and according to the Electrical Safety Technical Specifications for Electric Vehicle Charging Facilities, the upper limit of safe operation is set to 25℃ or 40℃, ref represents a wall thermal backflow intensity industry reference value, and is based on a reference value;

[0098] The underground garage wall surface material is rough and not veneered, and the distance from the car is less than or equal to 30 cm, and the thermal backflow intensity reference value is 10 W / m 2 -25 W / m 2 The distance from the car is greater than 30 cm, and the thermal backflow intensity reference value is 5 W / m 2 -9 W / m 2 ;

[0099] The underground garage wall surface material is smooth marble or ceramic tile, and the distance from the car is less than or equal to 10 cm, and the thermal backflow intensity reference value is 5 W / m 2 -15 W / m 2 The distance from the car is greater than 10 cm, and the thermal backflow intensity reference value is 2 W / m 2-4W / m 2 ;

[0100] The wall surface material of the underground garage is galvanized sheet or aluminum sheet, and the distance from the car is less than or equal to 5 cm, and the reference value of the heat reflux intensity is 15W / m 2 -35W / m 2 , and the distance from the car is greater than 5 cm, and the reference value of the heat reflux intensity is 8W / m 2 -14W / m 2 .

[0101] The heat reflux temperature formed by the heat convection of the external wall enters the additional heat load of the target intelligent charging pile. Due to the poor air circulation in the underground garage environment, the temperature is not easy to dissipate, the wall may absorb and store the temperature, form a heat "reflection area" or "heat reflux area", and the intelligent charging pile itself generates heat. If it is close to the wall, it will cause heat accumulation. The wall surface material (such as concrete) has poor heat conduction performance, and after absorbing heat, it is not easy to dissipate, but it is instead radiated or convected to the equipment; therefore, the heat reflux intensity Q is monitored, and the heat reflux intensity Q is monitored. The strength of the heat "reflux" to the charging pile caused by the heat reflection or heat conduction of the wall is measured, which provides a key variable for the calculation of the "environmental heat interference coefficient", and then determines whether the secondary heat dissipation strategy (such as increasing the air volume, liquid cooling distribution, etc.) needs to be started. The forward-looking of heat dissipation control is improved, the probability of extreme temperature rise or critical alarm is reduced, and the key function modules are protected.

[0102] The preset ω1=0.3, ω2=0.4 and ω3=0.3, V ref =0.25, C ref =35, Q ref =100, through multiple sets of environmental conditions (wind speed, temperature, wall surface material, etc.), the heat dissipation efficiency or temperature rise response of the charging pile is monitored, the influence coefficient of each factor on the heat interference is determined by using multivariate sensitivity analysis, and ω1, ω2 and ω3 are back calculated according to the analysis result;

[0103] The environmental heat interference coefficient R env is shown in Table 4

[0104]

[0105] In this embodiment, the second extraction unit can accurately perceive the interference of the local environment in the underground parking lot to the heat management system of the charging pile by collecting the external wind speed V, temperature C and heat reflux intensity factor Q formed by the wall close to the target intelligent charging pile. The dynamic correlation identification of the charging pile and the surrounding thermal environment is realized. The second calculation unit carries out dimensionless processing on the V, C and Q data, and combines the weight coefficients ω1, ω2 and ω3, satisfies ω1+ω2+ω3=1, and carries out unified scale comprehensive calculation on the three types of heat interference elements, so as to obtain the environmental heat interference coefficient R env, improving the scientificity and stability of the assessment of external interference heat sources.

[0106] This mechanism can quickly identify and issue early warnings for phenomena such as reduced heat dissipation efficiency caused by reduced wind speed in underground garages, increased local temperature, or enhanced wall heat reflection, ensuring the rapid response of the charging pile thermal control system to microenvironmental fluctuations. env It can provide reliable input for the subsequent comprehensive temperature control adjustment of the system, provide a quantitative reference basis for the formulation of strategies such as cooling parameter tuning and load adjustment, and enhance the adaptability and coordination of cooling strategies.

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

[0108] By collecting a large amount of measured data in different environmental scenarios, we analyze the distribution of the ambient thermal interference coefficient when the heat dissipation performance is normal and when the heat dissipation performance degrades or an alarm occurs.

[0109] Through cross-analysis of these two types of data, a value that "best distinguishes normal from abnormal" is selected as the threshold;

[0110] The environmental interference threshold T and the environmental thermal interference coefficient R env Perform a comparison and generate a second evaluation instruction, including:

[0111] When R env When ≥T, it indicates that the external environmental factors of the target smart charging pile have an abnormal heat dissipation effect on the charging pile. The second strategy is generated, including increasing the fan speed of the air-cooling equipment by 20%-40% and the circulation flow rate of the liquid cooling by 15%-25%. The cooling resources are allocated, and 38%-60% of the heat dissipation power of the heat dissipation resources is allocated to the functional modules affected by the abnormal environmental thermal interference. The underground garage fan is started, and the wind speed in the underground garage is increased by 10%-35%, thereby reducing the temperature in the underground garage by 3℃-5℃. The air outlet angle of the target smart charging pile is increased by 15°-30°.

[0112] When R env When <T, it means 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 continues.

[0113] Combined with the charging pile sample number in Table 4, the environmental interference threshold T and the environmental thermal interference coefficient R env The comparison example table is shown in Table 5;

[0114]

[0115]

[0116] In this embodiment, by comparing the environmental thermal interference coefficient with the preset threshold T, the abnormal external heat dissipation situation caused by factors such as weakening of wind speed, temperature rise or enhancement of wall heat backflow can be accurately identified, intelligent early warning and strategy linkage of complex microclimate environment of underground garage are realized, when the environmental thermal interference coefficient is greater than or equal to T, the system automatically generates the second strategy, the second strategy further controls the operation of the underground garage fan, improves the garage wind speed by 10%-35%, forms a forced convection ventilation effect, effectively disperses the heat accumulation air mass, makes the whole garage temperature drop by 3-5℃, improves the heat exchange condition around the intelligent charging pile, and realizes the environmental auxiliary cooling collaborative mechanism.

[0117] The system adjusts the angle of the heat dissipation outlet of the target intelligent charging pile by 15°-30°, changes the direction of hot air discharge, avoids the formation of heat accumulation in the wall backflow, and reduces the reverse interference of the wall backheat effect on the system.

[0118] Embodiment 8, this embodiment is an explanation and description in embodiment 1, please refer to Figure 1 , specifically, the evaluation optimization module comprises an association unit and a third evaluation unit;

[0119] The association unit is used for associating the in-pile thermal risk coefficient R heat with the environmental thermal interference coefficient R env , and obtaining a comprehensive temperature control adjustment coefficient R total through dimensionless processing and the following formula.

[0120] R total = p1 x R heat + p2 x R env ;

[0121] In the formula, p1 and p2 are weight coefficients, and p1+p2=1.

[0122] Pre-set p1=0.6 and p2=0.4, according to the actual operation of the system and historical data experience, combined with industry general standards, the importance of each index on the heat dissipation system is evaluated, and the corresponding weight is given, for example, the in-pile thermal risk coefficient often more directly reflects the heating condition of the equipment itself, and the weight is larger. The weight of the environmental thermal interference coefficient is smaller;

[0123] An example table of the comprehensive temperature control adjustment coefficient R total of the charging pile sample serial number is shown in Table 6 in combination with Table 5;

[0124]

[0125] In this embodiment, the in-pile thermal risk coefficient R heat and the environmental thermal interference coefficient R envThe weighted fusion is performed to construct a unified comprehensive temperature control regulation coefficient R total , improve the identification ability of the system to the cooperative influence of "in-device thermal load" and "environmental external thermal interference", realize unified evaluation modeling of multiple source thermal factors, and perform dimensionless normalization processing on the two types of heterogeneous thermal risk parameters, so that different physical quantities have comparability, the stability and generalization of the model are enhanced, and the model can be applicable to multiple layout scenes and intelligent charging pile systems of different specifications.

[0126] The comprehensive temperature control regulation coefficient is used as a unified judgment basis for the internal and external thermal state of the pile, and provides quantitative decision support for generating a comprehensive strategy for the third evaluation unit. Compared with relying on a single heat source for judgment, the strategy triggering is more scientific, the resource allocation is more accurate, and the regulation efficiency and the stability of the system response are significantly improved.

[0127] Embodiment 9, this embodiment is an explanation and description in embodiment 1, please refer to Figure 1 Specifically, the third evaluation unit is configured to preset a temperature control regulation threshold Y.

[0128] By collecting and analyzing the comprehensive temperature control regulation coefficients of a large number of charging piles in the actual running environment, the distribution of the comprehensive regulation coefficient when the system is normally and abnormally cooled is counted, for example, the distribution of the comprehensive regulation coefficient in the historical data that is normally running is compared with the coefficient distribution of the event of abnormal cooling, and a dividing point is found out, which is used as a threshold, so that when the comprehensive regulation coefficient is greater than or equal to Y, the system determines that the cooling is abnormal, and when it is lower, it is determined to be normal.

[0129] The temperature control regulation threshold Y is compared with the comprehensive temperature control regulation coefficient R total to generate a third evaluation instruction, including:

[0130] When R total ≥ Y, it indicates that the target intelligent charging pile is abnormally cooled, a third strategy is generated, including increasing the power of the air cooling equipment by 20%-40%, and increasing the circulating flow rate of the liquid cooling equipment by 33%-50%, dynamically adjusting the cooling resource allocation ratio of the double-cooling equipment to the thermal control area, increasing 30%-60% of the cooling resources for the function module of the abnormal heat release, and increasing 22%-35% of the underground garage fan speed, and increasing the angle of the target intelligent charging pile cooling port by 10%-15% adjustment ratio.

[0131] When R total < Y, it indicates that the target intelligent charging pile is normally cooled, maintains the set cooling mode for cooling, and performs real-time monitoring.

[0132] The temperature control regulation threshold Y is compared with the comprehensive temperature control regulation coefficient R totalThe comparative example table is shown in Table 7.

[0133]

[0134] In this embodiment, the third evaluation unit evaluates the integrated thermal state after fusing the in-pile thermal risk and external thermal interference based on a preset temperature control adjustment threshold Y, can accurately identify the overall abnormal heat dissipation state, and trigger a coordinated cooling regulation strategy, thereby realizing adaptive temperature control management under a multi-source thermal disturbance scene. When an abnormality is identified, the system dynamically adjusts the power output and circulation flow of the double-cooling equipment (air cooling + liquid cooling) through a partitioning strategy, especially concentrates the cooling resources to the abnormal area functional modules (such as supplying 30%-60% of the cooling resources), effectively improves the cooling efficiency, and avoids resource waste and inefficient regulation.

[0135] By increasing the power of the air cooling equipment and the flow rate of the liquid cooling, and combining a 10%-15% intelligent up-regulation mechanism of the heat dissipation port angle, a "point-surface combined" three-dimensional heat dissipation regulation system is formed, the cooling speed of the hot spot area is strengthened, the heat accumulation is inhibited, the risk of thermal runaway and internal overload damage is effectively reduced, and the evaluation module can intelligently trigger the garage fan to increase the wind speed by 20%-35% when the system identifies that the heat is retained due to environmental thermal interference. Through overall wind speed and flow field adjustment of the underground space, the environmental thermal disturbance is assisted to be relieved and the local hot air flow is dispersed, and the external condition adaptability of the cooling system is improved.

[0136] Embodiment 10, please refer to Figure 2 Specifically, a partitioning-controlled intelligent charging pile double-cooling heat dissipation control method includes;

[0137] Step one: first, the target intelligent charging pile adjacent to the wall of the underground parking garage is divided into several thermal control areas, and the temperature generated by the functional modules in each thermal control area and the temperature generated by the heat dissipation equipment in each thermal control area are collected in real time. The backflow temperature formed by the external wall due to thermal convection when the target intelligent charging pile is arranged close to the wall enters the target intelligent charging pile as additional heat load;

[0138] Step two: secondly, according to the data collected in step one, the in-pile thermal risk coefficient R heat and the environmental thermal interference coefficient R env are constructed respectively;

[0139] Step three: finally, the in-pile thermal risk coefficient R heat and the environmental thermal interference coefficient R env are fused to construct the integrated temperature control adjustment coefficient R total , and evaluation and optimization are performed.

[0140] In this embodiment, by dividing the inside of the charging pile into multiple thermal control areas, collecting the heat release of each area function module and heat dissipation device in real time, and monitoring the wall heat backflow intensity under the wall deployment, the local and overall heat distribution state of the charging pile can be fully restored, providing data support for subsequent temperature control strategies. The heat release of the function module itself, the wall convection heat return, and the garage wind speed are respectively constructed as "pile internal heat risk coefficient" and "environmental heat interference coefficient", effectively solving the problem of ignoring environmental impact in the prior art, and improving the comprehensiveness and accuracy of heat risk assessment.

[0141] The two types of thermal coefficients are fused to form a "comprehensive temperature control adjustment coefficient", and an evaluation threshold is set for dynamic comparison and strategy issuing. According to different thermal states, the key parameters such as air cooling power, liquid cooling flow, air outlet angle, etc. can be adjusted adaptively to realize dynamic partition cooling resource redistribution, improve the cooling efficiency of key modules, automatically link the underground garage fan according to the environmental heat interference intensity, optimize the wind speed and ventilation direction, improve the ventilation and heat exchange conditions, avoid heat accumulation, and improve the environmental adaptability and overall heat dissipation stability of the cooling system.

[0142] The size of the threshold is set for easy comparison. The size of the threshold depends on the amount of sample data and the base number set by the person skilled in the art for each group of sample data; as long as it does not affect the proportional relationship of the parameters and the quantized values.

[0143] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application, and they should be covered in the scope of the claims and the specification of the present application.

Claims

1. A zone-controlled intelligent charging pile dual cooling and heat dissipation system, characterized in that: It includes regional division and collection module, early warning analysis module and evaluation and optimization module; The area division and acquisition module is used to divide the target smart charging pile adjacent to the wall of the underground parking garage into several thermal control areas, and set dynamic temperature monitoring points in each thermal control area. It is used to monitor the temperature generated by the functional modules in each thermal control area and the temperature generated by the heat dissipation equipment in each thermal control area in real time based on the dynamic temperature monitoring points. It is also used to monitor the return temperature generated by heat convection from the external wall when the target smart charging pile is arranged close to the wall and the additional heat load entering the target smart charging pile, thereby constructing a first data set and a second data set respectively; The early warning analysis module is used to construct the pile internal heat risk coefficient R according to the first data set. heat , construct the environmental thermal interference coefficient R based on the second data set env , and respectively generate a first evaluation instruction and a second evaluation instruction, and generate corresponding first strategies and second strategies; The evaluation and optimization module is used to correlate the heat risk coefficient inside the pile with the environmental heat interference coefficient to construct a comprehensive temperature control adjustment coefficient R total , and generate a third evaluation instruction and a corresponding third strategy.

2. The dual cooling and heat dissipation system of a smart charging pile with zone control according to claim 1 is characterized in that: The area division acquisition module includes an area division unit, a function module temperature value acquisition unit, a heat dissipation device temperature value acquisition unit and an environmental interference acquisition unit; The area division unit is used to divide the target smart charging pile into several areas, 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 set a temperature sensor on the outer surface of each thermal control area functional module, and acquire the temperature value generated by the temperature sensor on the functional module of each thermal control area to obtain the heat release amount R of the i-th functional module. i ; The function module temperature value acquisition unit is also used to acquire the heating temperature value of the mth function module adjacent to the i-th function module to obtain the heating temperature R of the mth function module. m ; The heat dissipation device temperature value acquisition unit is used to collect the temperature released by the heat dissipation device set in the target smart charging pile to obtain the heat dissipation device heating temperature S; Based on the heat release R of the i-th functional module i , heating temperature R of the mth functional module m and the heating temperature S of the heat dissipation device to construct a first data set.

3. The dual cooling and heat dissipation system of a smart charging pile with zone control according to claim 2 is characterized in that: The environmental interference collection unit is used to set a wind speed sensor and an infrared temperature sensor outside the target smart charging pile to collect the wind speed and temperature near the target smart charging pile to obtain the wind speed V and temperature C; The environmental interference collection unit is used to set a distance detection sensor on the target smart charging pile, detect the distance between the target smart charging pile and the underground garage wall based on the distance sensor, and the distance d between the target smart charging pile and the wall. Based on the distance, several temperature collection points distributed along the height direction are set, and the temperature sensor is used to collect the temperature of the collection points, and the temperature gradient change value ΔT is monitored in real time. In combination with the construction requirements of the underground garage, the underground garage material is obtained, and the wall thermal conductivity k is obtained by table lookup to obtain the wall heat reflow intensity factor Q, and construct a second data set.

4. The dual cooling and heat dissipation system for intelligent charging piles with zone control according to claim 3 is 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 data set. i , heating temperature R of the mth functional module m and the heat dissipation temperature S of the heat dissipation device; The first calculation unit is used to obtain the heat risk coefficient R in the pile by calculation based on the data extracted by the first extraction unit. heat .

5. The dual cooling and heat dissipation system of a smart charging pile with zone control according to claim 4 is characterized in that: The first evaluation unit is used to preset the risk threshold E in the pile and compare the preset risk threshold E in the pile with the thermal risk coefficient R in the pile. heat Perform a comparison and generate a first evaluation instruction, including: When R heat When ≥E, it indicates that the heat dissipation in the target smart charging pile is abnormal, and the first strategy is generated, including increasing the heat dissipation efficiency of the dual cooling equipment for the i-th functional module by 32%-50%, and also 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 the liquid cooling circulation flow by 25%-34%; When R heat When <E, it indicates that the heat dissipation in the target smart charging pile is normal. Maintain the set speed and circulation flow of the dual cooling equipment for the heat dissipation of the functional module and continue testing.

6. The dual cooling and heat dissipation system for intelligent charging piles with zone control according to claim 5 is characterized in that: The early warning analysis module further 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 recirculation intensity factor Q from the second data set; The second calculation unit is used to obtain the environmental thermal interference coefficient R by calculation based on the data extracted from the second data by the second extraction unit. env .

7. The dual cooling and heat dissipation system for intelligent charging piles with zone control according to claim 6 is 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 Perform a comparison and generate a second evaluation instruction, including: When R env When ≥T, it indicates that the external environmental factors of the target smart charging pile have an abnormal heat dissipation effect on the charging pile. The second strategy is generated, including increasing the fan speed of the air-cooling equipment by 20%-40% and the circulation flow rate of the liquid cooling by 15%-25%. The cooling resources are allocated, and 38%-60% of the heat dissipation power of the heat dissipation resources is allocated to the functional modules affected by the abnormal environmental thermal interference. The underground garage fan is started, and the wind speed in the underground garage is increased by 10%-35%, thereby reducing the temperature in the underground garage by 3℃-5℃. The air outlet angle of the target smart charging pile is increased by 15°-30°. When R env When <T, it means 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 continues.

8. The dual cooling and heat dissipation system for intelligent charging piles with zone control according to claim 7 is characterized in that: The evaluation and optimization module includes an association unit and a third evaluation unit; The associated unit is used to convert the heat risk coefficient R heat Thermal interference coefficient with the environment R env The comprehensive temperature control adjustment coefficient R is obtained by calculation total .

9. The dual cooling and heat dissipation system for intelligent charging piles with zone control according to claim 8, characterized in that: The third evaluation unit is used to preset the temperature control adjustment threshold Y and compare the temperature control adjustment threshold Y with the comprehensive temperature control adjustment coefficient R total Perform a comparison and generate a third evaluation instruction, including: When R total When ≥Y, it indicates that the target smart charging pile has abnormal heat dissipation, and the third strategy is generated, including increasing the power of the air cooling equipment by 20%-40%, and increasing the circulating flow rate of the liquid cooling equipment by 33%-50%, dynamically adjusting the cooling resource allocation ratio of the dual cooling equipment to the thermal control area, increasing the cooling resources for the functional modules with abnormal heat release by 30%-60%, and increasing the wind speed of the underground garage fan by 22%-35%. The angle of the heat dissipation port of the target smart charging pile is adjusted upward by 10%-15%; When R total When <Y, it indicates that the target smart charging pile is dissipating heat normally, maintaining the set heat dissipation method for heat dissipation and real-time monitoring.

10. A dual cooling and heat dissipation control method for a zone-controlled smart charging pile, applied to a zone-controlled smart charging pile dual cooling and heat dissipation system according to any one of claims 1 to 9, characterized in that: include; Step 1: First, the target smart charging pile adjacent to the wall of the underground parking garage is divided into several thermal control zones. The temperature generated by the functional modules and the temperature generated by the heat dissipation devices in each thermal control zone are collected in real time. The target smart charging pile is also monitored. When the target smart charging pile is placed close to the wall, the return flow temperature generated by heat convection from the external wall enters the target smart charging pile, which adds additional heat load. Step 2: Secondly, the internal heat risk coefficient and the environmental heat interference coefficient are constructed based on the data collected in step 1; Step 3: Finally, the thermal risk coefficient inside the pile and the environmental thermal interference coefficient are integrated to construct a comprehensive temperature control adjustment coefficient, which is then evaluated and optimized.

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