Fan speed regulation method and device, electronic equipment and storage medium

Abstract

The application is suitable for the technical field of motor control, and provides a fan speed regulation method and device, electronic equipment and storage medium. The method comprises the following steps: acquiring a discrete relationship between an input quantity and a fan duty ratio and real-time data of a charging pile; the input quantity comprises an ambient temperature, a load rate of the charging pile and an output voltage; according to the real-time data, relevant input quantity data and relevant fan duty ratio data in the discrete relationship are determined; in turn, each input quantity is taken as an independent variable, the fan duty ratio is taken as a dependent variable, linear fitting is performed according to the corresponding relevant input quantity data and relevant fan duty ratio data, and a fitting relationship is obtained; and finally, the fan speed is controlled based on the fitting relationship to obtain the final fan duty ratio. The application can improve the fitting accuracy, accurately obtain the final fan duty ratio related to the real-time data, regulate the fan speed, improve the continuity and effect of the fan speed regulation, and better realize the demand of reducing noise on the premise of meeting the cooling demand of the charging pile.

Description

Technical Field

[0001] This application relates to the field of motor control technology, specifically to a fan speed regulation method, device, electronic equipment, and storage medium. Background Technology

[0002] Charging stations generate significant heat during electric vehicle charging, impacting charging efficiency, the lifespan of internal components, and posing safety hazards. Therefore, fans are typically used for cooling. However, these fans produce noise, which increases with fan speed, affecting people's health and well-being. To achieve a low-noise environment for charging stations, fan speed must be reduced while still meeting cooling requirements, minimizing noise. Fan speed is usually controlled based on the fan's duty cycle.

[0003] In related technologies, when adjusting the speed of the fan, the fan duty cycle is usually determined based on the linear relationship between the charging pile's relevant parameters and the fan's duty cycle. However, due to the non-linear output of the fan duty cycle and the difficulty in determining the linear relationship between the relevant parameters and the fan duty cycle, the above method results in poor continuity and unsatisfactory effect in fan speed adjustment, failing to meet the requirement of reducing fan speed to lower noise while still meeting the heat dissipation and cooling needs of the charging pile. Summary of the Invention

[0004] In view of this, embodiments of this application provide a fan speed regulation method, device, electronic device and storage medium to solve the technical problem that the related fan speed regulation methods have poor continuity and unsatisfactory effect, and cannot achieve the requirement of reducing fan speed to reduce noise while meeting the heat dissipation and cooling requirements of charging piles.

[0005] In a first aspect, embodiments of this application provide a method for regulating the speed of a wind turbine, comprising: acquiring the discrete relationship between an input quantity and the duty cycle of the wind turbine and real-time data of a charging pile; the input quantity includes ambient temperature, the load rate of the charging pile and the output voltage of the charging pile, and the real-time data includes real-time ambient temperature, the real-time load rate of the charging pile and the real-time output voltage of the charging pile;

[0006] Based on the real-time data, relevant input data and relevant wind turbine duty cycle data are determined in the discrete relationship;

[0007] Using the first, second, and third input quantities as independent variables and the fan duty cycle as the dependent variable, linear fitting is performed on the corresponding relevant input quantity data and the corresponding relevant fan duty cycle data to obtain the fitting relationship; wherein, the input quantities include the first, second, and third input quantities, and the first, second, and third input quantities are any one of ambient temperature, load rate, and output voltage, respectively;

[0008] Based on the fitting relationship, the final fan duty cycle is obtained, and the fan speed is controlled according to the final fan duty cycle.

[0009] In one possible implementation of the first aspect, the relevant input data includes a lower limit and an upper limit of relevant inputs; determining the relevant input data and the relevant wind turbine duty cycle data in the discrete relationship based on the real-time data includes: determining the input data that is closest to the real-time data and is less than or equal to the real-time data as the lower limit of relevant inputs, and determining the input data that is closest to the real-time data and is greater than or equal to the real-time data as the upper limit of relevant inputs; and determining the wind turbine duty cycle data corresponding to the lower limit and / or the upper limit of relevant inputs as the relevant wind turbine duty cycle data.

[0010] In one possible implementation of the first aspect, the fitting relationship includes a first fitting relationship, a second fitting relationship, and a third fitting relationship, and the relevant input data includes a lower limit and an upper limit of the relevant input data; the step of sequentially using the first, second, and third inputs as independent variables and the wind turbine duty cycle as the dependent variable, and performing linear fitting based on the corresponding relevant input data and the corresponding relevant wind turbine duty cycle data to obtain the fitting relationship includes:

[0011] Using a first input quantity as the independent variable and the fan duty cycle as the dependent variable, a linear fit is performed based on the upper and lower limits of the relevant input quantities corresponding to the first input quantity and the relevant fan duty cycle data corresponding to the fan duty cycle to obtain a first fitting relationship; the real-time data corresponding to the first input quantity is substituted into the first fitting relationship to obtain a first fan duty cycle; using a second input quantity as the independent variable and the fan duty cycle as the dependent variable, a linear fit is performed based on the upper and lower limits of the relevant input quantities corresponding to the second input quantity and the first fan duty cycle to obtain a second fitting relationship; the real-time data corresponding to the second input quantity is substituted into the second fitting relationship to obtain a second fan duty cycle; using a third input quantity as the independent variable and the fan duty cycle as the dependent variable, a linear fit is performed based on the upper and lower limits of the relevant input quantities corresponding to the third input quantity and the second fan duty cycle to obtain a third fitting relationship.

[0012] In one possible implementation of the first aspect, obtaining the final wind turbine duty cycle based on the fitting relationship includes: substituting the real-time data corresponding to the third input quantity into the third fitting relationship to obtain the final wind turbine duty cycle.

[0013] In one possible implementation of the first aspect, in the discrete relationship between the input quantity and the fan duty cycle, the range and granularity of different input quantities are different, and the granularity of the same input quantity is determined according to the rate of change of the fan duty cycle.

[0014] In one possible implementation of the first aspect, the method further includes: acquiring the output current and rated power of the charging pile; and determining the load rate based on the output voltage, output current, and rated power.

[0015] In one possible implementation of the first aspect, the lower limit of the relevant input quantity includes an ambient temperature lower limit, a load rate lower limit, and an output voltage lower limit, and the upper limit of the relevant input quantity includes an ambient temperature upper limit, a load rate upper limit, and an output voltage upper limit; the discrete relationship will be the one closest to the real-time data. ， Input data that is less than or equal to the real-time data is determined as the relevant lower limit of input volume, and input data that is closest to the real-time data and greater than or equal to the real-time data is determined as the relevant upper limit of input volume, including:

[0016] In the discrete relationship, the one closest to the real-time ambient temperature will be selected. ， Input data that is less than or equal to the real-time ambient temperature is determined as the lower limit of the ambient temperature, and the data closest to the real-time ambient temperature is selected. ， Input data that is greater than or equal to the real-time ambient temperature is determined as the upper limit of the ambient temperature; in the discrete relationship, the value closest to the real-time load rate is selected. ， Input data that is less than or equal to the real-time load rate is determined as the lower limit of the load rate, and input data that is closest to the real-time load rate and is greater than or equal to the real-time load rate is determined as the upper limit of the load rate; in the discrete relationship, input data that is closest to the real-time output voltage and is less than or equal to the real-time output voltage is determined as the lower limit of the output voltage, and input data that is closest to the real-time output voltage and is greater than or equal to the real-time output voltage is determined as the upper limit of the output voltage.

[0017] Secondly, embodiments of this application provide a fan speed regulating device, comprising:

[0018] The acquisition module is used to acquire the discrete relationship between the input quantity and the wind turbine duty cycle and the real-time data of the charging pile; the input quantity includes the ambient temperature, the load rate of the charging pile and the output voltage of the charging pile, and the real-time data includes the real-time ambient temperature, the real-time load rate of the charging pile and the real-time output voltage of the charging pile.

[0019] The determination module is used to determine, based on the real-time data, the relevant input data and the relevant wind turbine duty cycle data in the discrete relationship;

[0020] The fitting module is used to sequentially use the first input quantity, the second input quantity, and the third input quantity as independent variables, and the fan duty cycle as the dependent variable, and perform linear fitting based on the corresponding relevant input quantity data and the corresponding relevant fan duty cycle data to obtain the fitting relationship; wherein, the input quantity includes the first input quantity, the second input quantity, and the third input quantity, which are any one of ambient temperature, load rate, and output voltage, respectively;

[0021] The control module is used to obtain the final fan duty cycle based on the fitting relationship, and to control the fan speed according to the final fan duty cycle.

[0022] Thirdly, embodiments of this application provide an electronic device, including a memory and a processor. The memory stores a computer program that can run on the processor. When the processor executes the computer program, it implements the fan speed regulation method as described in any of the first aspects.

[0023] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the fan speed regulation method as described in any of the first aspects.

[0024] Fifthly, embodiments of this application provide a computer program product that, when run on an electronic device, causes the electronic device to execute the fan speed regulation method described in any of the first aspects above.

[0025] It is understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here.

[0026] The wind turbine speed regulation method, device, electronic equipment, and storage medium provided in this application determine the relevant input quantity data and relevant wind turbine duty cycle data in the discrete relationship between the input quantity and the wind turbine duty cycle based on the real-time data of the charging pile. The input quantity includes the ambient temperature, the load rate of the charging pile, and the output voltage of the charging pile. The method uses each input quantity as the independent variable and the wind turbine duty cycle as the dependent variable to perform linear fitting to obtain the fitting relationship, thereby determining the final wind turbine duty cycle. In this embodiment, by considering multiple dimensions and simultaneously setting the ambient temperature, the output voltage of the charging pile, and the load rate as inputs, and based on the most relevant input data within a small range determined from the discrete relationship, linear fitting is performed sequentially with each input as an independent variable. This improves the accuracy of the fitting, thereby obtaining a precise fitting relationship between the input and the fan duty cycle. Furthermore, the final fan duty cycle related to the real-time data is determined, so that the fan speed is adjusted according to the final fan duty cycle. This improves the continuity and effectiveness of fan speed adjustment, and better achieves the goal of reducing fan speed to reduce noise while meeting the heat dissipation and cooling requirements of the charging pile.

[0027] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this specification. Attached Figure Description

[0028] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0029] Figure 1 This is a schematic flowchart of a fan speed regulation method provided in an embodiment of this application;

[0030] Figure 2 This is a schematic diagram of the structure of a fan speed regulating device provided in an embodiment of this application;

[0031] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0032] The present application will be described more clearly below with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the function of the present application, but do not limit the present application in any way. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the present application. These all fall within the protection scope of the present application.

[0033] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0034] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0035] In the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0036] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0037] Furthermore, the term "multiple" mentioned in the embodiments of this application should be interpreted as two or more.

[0038] Charging stations generate significant heat when charging electric vehicles, typically using fans to dissipate and cool them. In related technologies, fan speed adjustment is usually determined based on the linear relationship between charging station parameters and the fan's duty cycle. However, due to the non-linearity of the fan's duty cycle output and the difficulty in determining the linear relationship between relevant parameters and the fan's duty cycle, the above methods suffer from poor continuity in fan speed adjustment and are ineffective. They fail to meet the cooling requirements of the charging station while simultaneously reducing fan speed to decrease noise.

[0039] Based on the above problems, the inventors discovered through research that by considering multiple dimensions and simultaneously setting the output voltage, load rate, and ambient temperature of the charging pile as input quantities, and obtaining the discrete relationship between the input quantities and the wind turbine duty cycle, and then using the most relevant input quantity data within the smallest range determined from the discrete relationship as the most relevant to the real-time data, linear fitting can be performed sequentially with each input quantity as the independent variable. This can improve the accuracy of the fitting and obtain an accurate fitting relationship between the input quantity and the wind turbine duty cycle, thereby determining the final wind turbine duty cycle related to the real-time data.

[0040] Figure 1 This is a schematic flowchart of a fan speed regulation method provided in an embodiment of this application. Figure 1 As shown, the method in the embodiments of this application may include:

[0041] Step 101: Obtain the discrete relationship between the input quantity and the wind turbine duty cycle, and the real-time data of the charging pile.

[0042] The input parameters include ambient temperature, charging pile load rate, and charging pile output voltage. The real-time data includes real-time ambient temperature, real-time charging pile load rate, and real-time charging pile output voltage.

[0043] For example, in this embodiment, the discrete relationship between the input quantity and the fan duty cycle can be represented by a table, matrix, or array. For instance, Table 1 shows the discrete relationship between the input quantity and the fan duty cycle. For ease of understanding and description, this embodiment uses a table to illustrate the discrete relationship.

[0044] Optionally, in this embodiment, the range and granularity of different input quantities in the discrete relationship between the input quantity and the wind turbine duty cycle are different. Specifically, the range of ambient temperature and output voltage among the input quantities can be set according to the actual operating conditions of the charging pile, while the range of load rate is set to 0–1. Simultaneously, to ensure that the data corresponding to the wind turbine duty cycle changes as uniformly as possible in the discrete relationship, thereby guaranteeing the accuracy and effectiveness of subsequent fitting, the granularity of the same input quantity in the discrete relationship is determined based on the rate of change of the wind turbine duty cycle. When the rate of change of the wind turbine duty cycle is fast, the granularity can be appropriately reduced; conversely, when the rate of change of the wind turbine duty cycle is slow, the granularity can be appropriately increased to make the data corresponding to the wind turbine duty cycle as uniform as possible.

[0045] Referring to Table 1, when the ambient temperature is 25℃, the output voltage is 260V, and the load rate is in the range of 0 to 0.5, the rate of change of the fan duty cycle is relatively slow; therefore, the numerical granularity of the load rate is 0.25. However, when the ambient temperature and output voltage remain constant, and the load rate is above 0.5, the rate of change of the fan duty cycle is relatively fast. Therefore, the numerical granularity of the load rate in the range of 0.5 to 1 is reduced to 0.125 to ensure the uniformity of the data corresponding to the fan duty cycle.

[0046] Optionally, in this embodiment, when obtaining the load rate, the output current and rated power of the charging pile can be obtained, and the load rate can be determined based on the output voltage, output current, and rated power. For example, when obtaining the real-time load rate, the real-time output current and rated power of the charging pile can be obtained, and the real-time load rate can be determined based on the real-time output voltage, real-time output current, and rated power.

[0047] It should be noted that when the charging pile includes two charging modules that can be switched between series and parallel, when the charging pile is working in the low-voltage charging mode, the two charging modules are connected in parallel, and the output voltage of the charging module is the original output voltage detected at the output terminal of the charging pile. When the charging pile is working in the high-voltage charging mode, the two charging modules are connected in series, and the output voltage of the charging module is half of the original output voltage detected at the output terminal of the charging pile.

[0048] In this embodiment, both output voltage and load rate are selected as input quantities, i.e., as relevant parameters of the charging pile, because both output voltage and load rate affect the wind turbine duty cycle. With the same load rate, different output voltages result in different wind turbine duty cycles. For example, at half-load power (with the same output current), output voltages of 300V and 500V correspond to wind turbine duty cycles of 40% and 80%, respectively. Therefore, selecting both output voltage and load rate, which both affect the wind turbine duty cycle, as input quantities allows for a multi-dimensional consideration of the correlation between the charging pile's relevant parameters and the wind turbine duty cycle, i.e., the impact on the wind turbine duty cycle. This leads to a more accurate fitting relationship with the wind turbine duty cycle and a more accurate calculation of the final wind turbine duty cycle based on real-time data.

[0049] Table 1

[0050]

[0051]

[0052] Step 102: Based on real-time data, determine the relevant input data and the relevant wind turbine duty cycle data in the discrete relationship.

[0053] In one possible implementation, the relevant input data includes a lower limit and an upper limit of the relevant input data. In this embodiment, when determining the relevant input data and the relevant wind turbine duty cycle data, A1 to A2 may be included.

[0054] A1. In discrete relations, the input data that is closest to the real-time data and is less than or equal to the real-time data is determined as the lower limit of the relevant input data, and the input data that is closest to the real-time data and is greater than or equal to the real-time data is determined as the upper limit of the relevant input data.

[0055] A2. Determine the fan duty cycle data corresponding to the lower limit and / or upper limit of the relevant input quantity as the relevant fan duty cycle data.

[0056] Optionally, this embodiment may employ a step-by-step search method or other methods to sequentially determine the upper and lower limits of the relevant input quantities for real-time data. There are no specific restrictions on the order in which the upper and lower limits of the relevant input quantities for real-time data are determined.

[0057] For example, in this embodiment, the real-time ambient temperature is 38°C, the real-time output voltage is 320V, and the real-time load rate is 0.64 (wherein, the real-time output current is 80A and the rated power is 40000W).

[0058] In some embodiments, the relevant input lower limit includes an ambient temperature lower limit, a load rate lower limit, and an output voltage lower limit; the relevant input upper limit includes an ambient temperature upper limit, a load rate upper limit, and an output voltage upper limit. Step A1 may include:

[0059] In the discrete relation, the input data that is closest to, and less than or equal to, the real-time ambient temperature is determined as the lower limit of the ambient temperature, and the input data that is closest to, and greater than or equal to, the real-time ambient temperature is determined as the upper limit of the ambient temperature. In this embodiment, the real-time ambient temperature is 38℃. Referring to Table 1, the lower limit of the ambient temperature can be determined as 35℃, and the upper limit of the ambient temperature as 40℃.

[0060] In discrete relationships, the input data that is closest to the real-time load rate and is less than or equal to the real-time load rate is determined as the lower limit of the load rate, and the input data that is closest to the real-time load rate and is greater than or equal to the real-time load rate is determined as the upper limit of the load rate. In this embodiment, the real-time load rate is 0.64. Referring to Table 1, the lower limit of the load rate can be determined as 0.625, and the upper limit of the load rate is 0.75.

[0061] In discrete relationships, the input data that is closest to, but less than or equal to, the real-time output voltage is determined as the lower limit of the output voltage, and the input data that is closest to, but greater than or equal to, the real-time output voltage is determined as the upper limit of the output voltage. In this embodiment, the real-time output voltage is 320V. Referring to Table 1, the lower limit of the output voltage can be determined to be 300V, and the upper limit of the output voltage is 350V.

[0062] Furthermore, based on the determined lower limits of ambient temperature, load rate, and output voltage, and the upper limits of ambient temperature, load rate, and output voltage, this embodiment can determine 2×2×2=8 relevant fan duty cycle data. The determined relevant input data and relevant fan duty cycle data are shown in Table 2. Referring to Table 2, the relevant input data are represented in bold, and the relevant fan duty cycle data are represented in italic bold.

[0063] Table 2

[0064]

[0065] In this embodiment, based on the acquired real-time data, the relevant input data most correlated with the real-time data is determined in the discrete relationship between ambient temperature, load rate, output voltage, and fan duty cycle. This narrows the fitting range, so that in the subsequent linear fitting, a more accurate fitting can be performed based on the relevant input data within a smaller range, thereby obtaining a more accurate fitting relationship between the input and the fan duty cycle.

[0066] Step 103: Using the first, second, and third input quantities as independent variables and the fan duty cycle as the dependent variable, perform linear fitting based on the corresponding relevant input quantity data and the corresponding relevant fan duty cycle data to obtain the fitting relationship.

[0067] The input quantities include a first input quantity, a second input quantity, and a third input quantity, wherein the first input quantity, the second input quantity, and the third input quantity are any one of ambient temperature, load rate, and output voltage, respectively.

[0068] For example, this embodiment uses output voltage as the first input, load rate as the second input, and ambient temperature as the third input for ease of understanding and description. However, in actual applications, the first, second, and third inputs can be any one of ambient temperature, load rate, and output voltage, without any specific limitations.

[0069] In one possible implementation, the fitting relationship includes a first fitting relationship, a second fitting relationship, and a third fitting relationship. As mentioned above, the relevant input data includes a lower limit of the relevant input and an upper limit of the relevant input. In this embodiment, when performing linear fitting to obtain the fitting relationship, it may include B1 to B3.

[0070] B1. Using the first input quantity as the independent variable and the fan duty cycle as the dependent variable, perform linear fitting based on the upper limit and lower limit of the relevant input quantity corresponding to the first input quantity, and the relevant fan duty cycle data corresponding to the fan duty cycle, to obtain the first fitting relationship; substitute the real-time data corresponding to the first input quantity into the first fitting relationship to obtain the first fan duty cycle.

[0071] Optionally, in this embodiment, under the same load rate and ambient temperature, with output voltage as the independent variable and fan duty cycle as the dependent variable, linear fitting is performed based on the upper and lower limits of output voltage corresponding to the output voltage and the relevant fan duty cycle data corresponding to the fan duty cycle to obtain a first fitting relationship. There are four first fitting relationships. Referring to Table 2, under the same load rate of 0.625 and ambient temperature of 35℃, linear fitting is performed on (300, 0.39) and (350, 0.37) to obtain a first fitting relationship Y. 11 = -0.0004*X 11 +0.51. Similarly, under the same load factor of 0.75 and ambient temperature of 35°C, linear fitting was performed on (300, 0.52) and (350, 0.5) to obtain another first fitting relationship Y. 12 = -0.0004*X 12 +0.64; Under the same load factor of 0.625 and ambient temperature of 40℃, linear fitting was performed on (300,0.45) and (350,0.42) to obtain another first fitting relationship Y. 13 = -0.0006*X 13 +0.63; Under the same load factor of 0.75 and ambient temperature of 40℃, linear fitting was performed on (300,0.55) and (350,0.55) to obtain the first fitting relationship Y. 14 =0.55.

[0072] Furthermore, in this embodiment, the real-time output voltage of 320V is substituted into the four first fitting relationships to obtain the four first fan duty cycles. For example, substituting the real-time output voltage of 320V into Y... 11 = -0.0004*X 11 Adding 0.51, we get a duty cycle of 0.382 for the first wind turbine. Similarly, we get duty cycles of 0.512, 0.438, and 0.55 for the other three first wind turbines.

[0073] Optionally, in this embodiment, after obtaining the first fan duty cycle based on the first fitting relationship, Table 2 can be updated according to the real-time output voltage and the first fan duty cycle to obtain Table 3, facilitating subsequent linear fitting to obtain the second fitting relationship. It should be noted that only Table 2 is updated here, not Table 1. That is, when adjusting the fan speed again to determine the final fan duty cycle, linear fitting is still performed based on the discrete relationship between the input quantity and the fan duty cycle (Table 1) to obtain the fitting relationship.

[0074] Table 3

[0075]

[0076] B2. Using the second input quantity as the independent variable and the fan duty cycle as the dependent variable, perform linear fitting based on the upper limit and lower limit of the relevant input quantity corresponding to the second input quantity, as well as the first fan duty cycle, to obtain the second fitting relationship; substitute the real-time data corresponding to the second input quantity into the second fitting relationship to obtain the second fan duty cycle.

[0077] Optionally, in this embodiment, under the same output voltage and ambient temperature, with load rate as the independent variable and fan duty cycle as the dependent variable, linear fitting is performed based on the upper and lower limits of load rate corresponding to the load rate and the relevant fan duty cycle data corresponding to the fan duty cycle to obtain a second fitting relationship. There are two second fitting relationships. Referring to Table 3, under the same output voltage of 320V and ambient temperature of 35℃, linear fitting is performed on (0.625, 0.382) and (0.75, 0.512) to obtain a second fitting relationship Y. 21 =1.04*X 21 -0.268. Similarly, at an output voltage of 320V and an ambient temperature of 40℃, linear fitting was performed on (0.625, 0.438) and (0.75, 0.55) to obtain another second fitting relationship Y. 22 =0.896*X 22 -0.122.

[0078] Furthermore, in this embodiment, the real-time load factor of 0.64 is substituted into the two second fitting relationships to obtain the two second fan duty cycles. For example, substituting the real-time load factor of 0.64 into Y... 21 =1.04*X 21 -0.268 yields a second fan duty cycle of 0.3976. Substituting the real-time load factor of 0.64 into Y... 22 =0.896*X 22 -0.122, yielding a duty cycle of 0.4514 for the second wind turbine.

[0079] Similarly, in this embodiment, after obtaining the second fan duty cycle based on the second fitting relationship, Table 3 can be updated according to the real-time load rate and the second fan duty cycle to obtain Table 4, which facilitates subsequent linear fitting to obtain the third fitting relationship. It should be noted that only Table 3 is updated here, not Table 1.

[0080] Table 4

[0081] Ambient temperature (°C) 0.64 35 320 0.3976 40 320 0.4514

[0082] B3. Using the third input quantity as the independent variable and the fan duty cycle as the dependent variable, perform linear fitting based on the upper limit and lower limit of the relevant input quantity corresponding to the third input quantity, as well as the second fan duty cycle, to obtain the third fitting relationship.

[0083] Optionally, in this embodiment, under the same output voltage and load rate, with ambient temperature as the independent variable and fan duty cycle as the dependent variable, a third fitting relationship is obtained by performing linear fitting based on the upper and lower limits of ambient temperature and the relevant fan duty cycle data. Referring to Table 4, under the same output voltage of 320V and load rate of 0.64, linear fitting is performed on (35, 0.3976) and (40, 0.4514) to obtain the third fitting relationship Y3 = 0.0108*X3 + 0.021.

[0084] In this embodiment, based on the relevant input data within a defined small range, three linear fits are performed sequentially with three input quantities as independent variables and the fan duty cycle as the dependent variable. The next fit is performed based on the results of each linear fit, which allows for a more accurate fit. This results in a more precise fitting relationship between the input quantities and the fan duty cycle, and ultimately, the final fan duty cycle related to the real-time data is obtained.

[0085] Step 104: Based on the fitting relationship, obtain the final fan duty cycle, and control the fan speed according to the final fan duty cycle.

[0086] In one possible implementation, when obtaining the final wind turbine duty cycle based on the fitting relationship, the real-time data corresponding to the third input quantity can be substituted into the third fitting relationship to obtain the final wind turbine duty cycle.

[0087] For example, in this embodiment, the real-time ambient temperature of 38℃ is substituted into the third fitting relationship Y3=0.0108*X3+0.021 to obtain the final fan duty cycle of 0.4314. Then, the fan speed is adjusted according to the final fan duty cycle of 0.4314.

[0088] The fan speed regulation method provided in this application determines the relevant input data and relevant fan duty cycle data in the discrete relationship between input quantities and fan duty cycle based on the real-time data of the charging pile. The input quantities include ambient temperature, charging pile load rate, and charging pile output voltage. Linear fitting is performed sequentially with each input quantity as the independent variable and the fan duty cycle as the dependent variable to obtain a fitting relationship, thereby determining the final fan duty cycle. By considering multiple dimensions and simultaneously setting ambient temperature, charging pile output voltage, and load rate as input quantities, and by performing linear fitting sequentially with each input quantity as the independent variable based on the most relevant and smallest range of input quantity data determined from the discrete relationship, the accuracy of the fitting can be improved, thus obtaining an accurate fitting relationship between the input quantities and the fan duty cycle. This allows for the determination of the final fan duty cycle related to the real-time data, enabling fan speed regulation based on the final fan duty cycle. This improves the continuity and effectiveness of fan speed regulation, better achieving the goal of reducing fan speed and noise while meeting the heat dissipation and cooling requirements of the charging pile.

[0089] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0090] Figure 2 This is a schematic diagram of the structure of a fan speed regulating device provided in one embodiment of this application. Figure 2 As shown, the fan speed control device provided in this embodiment may include: an acquisition module 201, a determination module 202, a fitting module 203, and a control module 204.

[0091] The acquisition module 201 is used to acquire the discrete relationship between the input quantity and the wind turbine duty cycle and the real-time data of the charging pile; the input quantity includes the ambient temperature, the load rate of the charging pile and the output voltage of the charging pile, and the real-time data includes the real-time ambient temperature, the real-time load rate of the charging pile and the real-time output voltage of the charging pile.

[0092] The determination module 202 is used to determine the relevant input data and the relevant wind turbine duty cycle data in the discrete relationship based on the real-time data.

[0093] The fitting module 203 is used to sequentially use the first input quantity, the second input quantity, and the third input quantity as independent variables, and the fan duty cycle as the dependent variable, and perform linear fitting based on the corresponding relevant input quantity data and the corresponding relevant fan duty cycle data to obtain the fitting relationship; wherein, the input quantity includes the first input quantity, the second input quantity, and the third input quantity, and the first input quantity, the second input quantity, and the third input quantity are any one of ambient temperature, load rate, and output voltage, respectively.

[0094] The control module 204 is used to obtain the final fan duty cycle based on the fitting relationship, and control the fan speed according to the final fan duty cycle.

[0095] Optionally, the relevant input data includes a lower limit and an upper limit of relevant inputs; the determining module 202 is specifically used to: in the discrete relationship, determine the input data that is closest to the real-time data and is less than or equal to the real-time data as the lower limit of relevant inputs, and determine the input data that is closest to the real-time data and is greater than or equal to the real-time data as the upper limit of relevant inputs; determine the wind turbine duty cycle data corresponding to the lower limit and / or the upper limit of relevant inputs as the relevant wind turbine duty cycle data.

[0096] Optionally, the fitting relationship includes a first fitting relationship, a second fitting relationship, and a third fitting relationship, and the relevant input data includes a lower limit and an upper limit of the relevant input data; the fitting module 203 is specifically used to: take the first input as the independent variable and the fan duty cycle as the dependent variable, perform linear fitting based on the upper limit and lower limit of the relevant input corresponding to the first input, and the relevant fan duty cycle data corresponding to the fan duty cycle, to obtain a first fitting relationship; substitute the real-time data corresponding to the first input into the first fitting relationship to obtain a first fan duty cycle;

[0097] Using the second input quantity as the independent variable and the fan duty cycle as the dependent variable, a linear fit is performed based on the upper and lower limits of the relevant input quantities corresponding to the second input quantity, as well as the first fan duty cycle, to obtain a second fitting relationship; the real-time data corresponding to the second input quantity is substituted into the second fitting relationship to obtain the second fan duty cycle;

[0098] Using the third input quantity as the independent variable and the fan duty cycle as the dependent variable, a linear fit is performed based on the upper limit and lower limit of the relevant input quantity corresponding to the third input quantity, as well as the second fan duty cycle, to obtain the third fitting relationship.

[0099] Optionally, the control module 204 is specifically used to: substitute the real-time data corresponding to the third input quantity into the third fitting relationship to obtain the final wind turbine duty cycle.

[0100] Optionally, the acquisition module 201 is further specifically used to: acquire the output current and rated power of the charging pile; and determine the load rate based on the output voltage, output current and rated power.

[0101] Optionally, the lower limit of the relevant input quantity includes the lower limit of ambient temperature, the lower limit of load rate, and the lower limit of output voltage; the upper limit of the relevant input quantity includes the upper limit of ambient temperature, the upper limit of load rate, and the upper limit of output voltage; the determining module 202 is further specifically used to: in the discrete relationship, select the value closest to the real-time ambient temperature. ， Input data that is less than or equal to the real-time ambient temperature is determined as the lower limit of the ambient temperature, and the data closest to the real-time ambient temperature is selected. ， The input data that is greater than or equal to the real-time ambient temperature is determined as the upper limit of the ambient temperature.

[0102] In the discrete relationship, the one closest to the real-time load rate will be selected. ， Input data that is less than or equal to the real-time load rate is determined as the lower limit of the load rate, and the data closest to the real-time load rate is selected. ， Input data that is greater than or equal to the real-time load rate is determined as the upper limit of the load rate;

[0103] In the discrete relationship, the one closest to the real-time output voltage will be selected. ， Input data that is less than or equal to the real-time output voltage is determined as the lower limit of the output voltage, and the input data that is closest to the real-time output voltage is selected. ， The input data that is greater than or equal to the real-time output voltage is determined as the upper limit of the output voltage.

[0104] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0105] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. For example... Figure 3 As shown, the electronic device 300 of this embodiment includes a processor 310 and a memory 320, wherein the memory 320 stores a computer program 321 that can run on the processor 310. When the processor 310 executes the computer program 321, it implements the steps in any of the above-described method embodiments, for example... Figure 1 Steps 101 to 104 are shown. Alternatively, when processor 310 executes computer program 321, it implements the functions of each module / unit in the above-described device embodiments, for example... Figure 2 The functions of modules 201 to 204 are shown.

[0106] For example, computer program 321 may be divided into one or more modules / units, one or more of which are stored in memory 320 and executed by processor 310 to complete this application. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of computer program 321 in electronic device 300.

[0107] Those skilled in the art will understand that Figure 3 This is merely an example of an electronic device and does not constitute a limitation on the electronic device. It may include more or fewer components than shown, or combinations of certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0108] The processor 310 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0109] The memory 320 can be an internal storage unit of the electronic device, such as a hard drive or memory, or an external storage device, such as a plug-in hard drive, SmartMedia Card (SMC), Secure Digital (SD) card, or Flash Card. The memory 320 can also include both internal and external storage units. The memory 320 is used to store computer programs and other programs and data required by the electronic device. The memory 320 can also be used to temporarily store data that has been output or will be output.

[0110] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0111] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0112] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0113] In the embodiments provided by this invention, it should be understood that the disclosed devices / electronic devices and methods can be implemented in other ways. For example, the device / electronic device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0114] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0115] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0116] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0117] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. 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 of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for regulating the speed of a fan, characterized in that, include: The discrete relationship between the input quantity and the wind turbine duty cycle and the real-time data of the charging pile are obtained; the input quantity includes ambient temperature, the load rate of the charging pile and the output voltage of the charging pile, and the real-time data includes real-time ambient temperature, real-time load rate of the charging pile and real-time output voltage of the charging pile. Based on the real-time data, relevant input data and relevant wind turbine duty cycle data are determined in the discrete relationship; Using the first, second, and third input quantities as independent variables and the fan duty cycle as the dependent variable, linear fitting is performed on the corresponding relevant input quantity data and the corresponding relevant fan duty cycle data to obtain the fitting relationship; wherein, the input quantities include the first, second, and third input quantities, and the first, second, and third input quantities are any one of ambient temperature, load rate, and output voltage, respectively; Based on the fitting relationship, the final fan duty cycle is obtained, and the fan speed is controlled according to the final fan duty cycle; The fitting relationship includes a first fitting relationship, a second fitting relationship, and a third fitting relationship, and the relevant input data includes a lower limit and an upper limit of the relevant input data. The process involves sequentially using the first, second, and third input quantities as independent variables and the wind turbine duty cycle as the dependent variable. Linear fitting is performed based on the corresponding relevant input quantity data and the corresponding relevant wind turbine duty cycle data to obtain the fitting relationship, including: Using the first input quantity as the independent variable and the fan duty cycle as the dependent variable, a linear fit is performed based on the upper limit and lower limit of the relevant input quantity corresponding to the first input quantity, and the relevant fan duty cycle data corresponding to the fan duty cycle, to obtain the first fitting relationship; the real-time data corresponding to the first input quantity is substituted into the first fitting relationship to obtain the first fan duty cycle. Using the second input quantity as the independent variable and the fan duty cycle as the dependent variable, a linear fit is performed based on the upper and lower limits of the relevant input quantities corresponding to the second input quantity, as well as the first fan duty cycle, to obtain a second fitting relationship; the real-time data corresponding to the second input quantity is substituted into the second fitting relationship to obtain the second fan duty cycle; Using the third input quantity as the independent variable and the fan duty cycle as the dependent variable, a linear fit is performed based on the upper limit and lower limit of the relevant input quantity corresponding to the third input quantity, as well as the second fan duty cycle, to obtain the third fitting relationship; The process of obtaining the final wind turbine duty cycle based on the fitted relationship includes: Substitute the real-time data corresponding to the third input quantity into the third fitting relationship to obtain the final wind turbine duty cycle.

2. The fan speed regulation method according to claim 1, characterized in that, The relevant input data includes a lower limit and an upper limit for the relevant input; The step of determining relevant input data and relevant wind turbine duty cycle data in the discrete relationship based on the real-time data includes: In the discrete relationship, the input data that is closest to the real-time data and is less than or equal to the real-time data is determined as the lower limit of the relevant input data, and the input data that is closest to the real-time data and is greater than or equal to the real-time data is determined as the upper limit of the relevant input data. The wind turbine duty cycle data corresponding to the lower limit and / or upper limit of the relevant input quantity are determined as the relevant wind turbine duty cycle data.

3. The fan speed regulation method according to claim 1 or 2, characterized in that, In the discrete relationship between the input quantity and the fan duty cycle, the range and granularity of different input quantities are different, and the granularity of the same input quantity is determined according to the rate of change of the fan duty cycle.

4. The fan speed regulation method according to claim 1 or 2, characterized in that, The method further includes: Obtain the output current and rated power of the charging pile; The load factor is determined based on the output voltage, output current, and rated power.

5. The fan speed regulation method according to claim 2, characterized in that, The lower limits of the relevant input quantities include the lower limit of ambient temperature, the lower limit of load rate, and the lower limit of output voltage; the upper limits of the relevant input quantities include the upper limit of ambient temperature, the upper limit of load rate, and the upper limit of output voltage. In the discrete relationship, the input data that is closest to the real-time data and is less than or equal to the real-time data is determined as the lower limit of the relevant input data, and the input data that is closest to the real-time data and is greater than or equal to the real-time data is determined as the upper limit of the relevant input data, including: In the discrete relationship, the input data that is closest to the real-time ambient temperature and is less than or equal to the real-time ambient temperature is determined as the lower limit of the ambient temperature, and the input data that is closest to the real-time ambient temperature and is greater than or equal to the real-time ambient temperature is determined as the upper limit of the ambient temperature. In the discrete relationship, the input data that is closest to the real-time load rate and is less than or equal to the real-time load rate is determined as the lower limit of the load rate, and the input data that is closest to the real-time load rate and is greater than or equal to the real-time load rate is determined as the upper limit of the load rate. In the discrete relationship, the input data that is closest to the real-time output voltage and is less than or equal to the real-time output voltage is determined as the lower limit of the output voltage, and the input data that is closest to the real-time output voltage and is greater than or equal to the real-time output voltage is determined as the upper limit of the output voltage.

6. A fan speed regulating device, characterized in that, include: The acquisition module is used to acquire the discrete relationship between the input quantity and the wind turbine duty cycle and the real-time data of the charging pile; the input quantity includes the ambient temperature, the load rate of the charging pile and the output voltage of the charging pile, and the real-time data includes the real-time ambient temperature, the real-time load rate of the charging pile and the real-time output voltage of the charging pile. The determination module is used to determine, based on the real-time data, the relevant input data and the relevant wind turbine duty cycle data in the discrete relationship; The fitting module is used to sequentially use the first input quantity, the second input quantity, and the third input quantity as independent variables, and the fan duty cycle as the dependent variable, and perform linear fitting based on the corresponding relevant input quantity data and the corresponding relevant fan duty cycle data to obtain the fitting relationship; wherein, the input quantity includes the first input quantity, the second input quantity, and the third input quantity, and the first input quantity, the second input quantity, and the third input quantity are any one of ambient temperature, load rate, and output voltage, respectively; The control module is used to obtain the final fan duty cycle based on the fitting relationship, and control the fan speed according to the final fan duty cycle; The fitting relationship includes a first fitting relationship, a second fitting relationship, and a third fitting relationship. The relevant input data includes a lower limit and an upper limit of the relevant input data. The fitting module is further used to perform linear fitting with the first input data as the independent variable and the fan duty cycle as the dependent variable, based on the upper and lower limits of the relevant input data corresponding to the first input data and the relevant fan duty cycle data corresponding to the fan duty cycle, to obtain the first fitting relationship. The real-time data corresponding to the first input data is then substituted into the first fitting relationship to obtain the first fan duty cycle. Using the second input quantity as the independent variable and the fan duty cycle as the dependent variable, a linear fit is performed based on the upper and lower limits of the relevant input quantities corresponding to the second input quantity, as well as the first fan duty cycle, to obtain a second fitting relationship; the real-time data corresponding to the second input quantity is substituted into the second fitting relationship to obtain the second fan duty cycle; Using the third input quantity as the independent variable and the fan duty cycle as the dependent variable, a linear fit is performed based on the upper limit and lower limit of the relevant input quantity corresponding to the third input quantity, as well as the second fan duty cycle, to obtain the third fitting relationship; The control module is also used to substitute the real-time data corresponding to the third input quantity into the third fitting relationship to obtain the final wind turbine duty cycle.

7. An electronic device comprising a memory and a processor, wherein the memory stores a computer program executable on the processor, characterized in that, When the processor executes the computer program, it implements the fan speed regulation method as described in any one of claims 1 to 5.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the fan speed regulation method as described in any one of claims 1 to 5.

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