A charging pile charging module fan control method, system, device and storage medium

Abstract

The present invention discloses a fan control method, system, device and storage medium for a charging module of a charging pile, including the following processes: S1, setting the initial integral value, proportional value and differential value of the PID controller, and then calculating the initial output of the PID controller; S2, obtaining the temperature difference of the charging module after the output adjustment of the PID controller, and calculating the current optimal integral value, proportional value and differential value of the PID controller through a neural network controller; S3, the PID controller uses the current optimal integral value, proportional value and differential value to perform a new round of output calculation, and returns to S2. The fan speed can be adjusted in real time according to the temperature detection value of the charging module, reducing the power consumption of the charger while meeting the heat dissipation requirements of the whole machine.

Description

Technical Field

[0001] The present invention belongs to the field of charging piles, and relates to a method, system, device and storage medium for controlling a fan of a charging module of a charging pile. Background Art

[0002] With the development of the charging pile industry, intelligence has been increasingly valued in the industry, and smart charging piles have become an important development direction for charging piles in the future. At present, the heat dissipation methods of charging piles are mainly divided into fan cooling and liquid cooling. Liquid cooling has high cost, and the market mostly uses fan cooling. A major disadvantage of fan cooling is that the noise is relatively loud when running at full speed, which will disturb the rest of the surrounding residents. The noise can be reduced when not running at full speed, but when not running at full speed, the temperature of the charging module is difficult to control, which can easily cause the temperature of the charging module to be too high or too low. Summary of the invention

[0003] The purpose of the present invention is to overcome the shortcomings of the above-mentioned prior art and provide a charging pile charging module fan control method, system, device and storage medium, which can adjust the fan speed in real time according to the temperature detection value of the charging module, reduce the power consumption of the charger while meeting the heat dissipation requirements of the whole machine.

[0004] In order to achieve the above object, the present invention adopts the following technical solutions: A method for controlling a fan of a charging module of a charging pile includes the following steps: S1, set the initial integral value, proportional value and differential value of the PID controller, and then calculate the initial output of the PID controller; S2, obtaining the temperature difference of the charging module after the PID controller output adjustment, and calculating the current optimal integral value, proportional value and differential value of the PID controller through the neural network controller; S3, the PID controller uses the current optimal integral value, proportional value and differential value to perform a new round of output calculation and returns to S2.

[0005] Preferably, in S1, the initial integral value, proportional value and differential value of the PID controller are obtained by trial and error.

[0006] Furthermore, the trial and error method process is: first, by changing the integral value, until it is determined that the temperature deviation of the charging module is in a decreasing state, a preliminary integral value is obtained; then, by changing the proportional value, it is determined that the temperature deviation of the charging module continues to be in a decreasing state, and a preliminary proportional value is obtained; finally, by changing the differential value, until it is determined that the temperature deviation of the charging module is in a decreasing state, a preliminary differential value is obtained.

[0007] Preferably, in S2, the neural network controller adopts a BP neural network, including an input layer, a hidden layer and an output layer. The charging module temperature difference and the charging module temperature primary deviation are inputs to the BP neural network. The hidden layer has three outputs, which are intermediate transition values. The BP neural network output layer has three outputs, which represent the integral value, proportional value and differential value of the PID controller.

[0008] Furthermore, a Sigmoid activation function is used to calculate the hidden layer output value and the output layer output value.

[0009] Furthermore, after the BP neural network obtains the output value of the output layer, it calculates the objective function value of the detected temperature difference and determines whether the temperature deviation is within the range of the objective function value. If it is within the range, the output value of the output layer is sent to the PID controller. If it is outside the range, the weights and thresholds of the BP neural network are adjusted and the BP neural network calculation is performed again.

[0010] Preferably, when the PID controller calculates a new round of output, the current optimal integral value, proportional value and differential value are used, combined with the charging module temperature difference, the charging module temperature primary deviation and the charging module temperature secondary deviation for calculation.

[0011] A charging pile charging module fan control system, comprising: The initial output module is used to set the initial integral value, proportional value and differential value of the PID controller, and then calculate the initial output of the PID controller; A neural network module is used to obtain the temperature difference of the charging module after the initial output adjustment of the PID controller, and calculate the current optimal integral value, proportional value and differential value of the PID controller through the neural network controller; The output module is updated so that the PID controller uses the current optimal integral value, proportional value and differential value to perform a new round of output calculation and returns to the neural network module.

[0012] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method for controlling a fan of a charging module of a charging pile when executing the computer program.

[0013] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the charging pile charging module fan control method are implemented.

[0014] Compared with the prior art, the present invention has the following beneficial effects: The present invention combines a PID controller with a neural network algorithm, takes the temperature difference of the charging module and the primary temperature deviation of the charging module as input values ​​of the neural network algorithm, updates the integral value, proportional value and differential value of the PID controller through the neural network algorithm, thereby performing PID control on the fan and adjusting the fan speed in real time, with higher control accuracy and faster response, reducing the power consumption of the charger while meeting the heat dissipation requirements of the entire machine. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a schematic diagram of the fan control principle of the charging module of the charging pile of the present invention; Figure 2 This is a diagram of the neural network architecture of the present invention. DETAILED DESCRIPTION

[0016] The embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0017] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first" and "second" are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by technicians in the technical field to which the present invention belongs. The terms "installed", "connected", and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection, an electrical connection, or can communicate with each other; it can be directly connected or indirectly connected through an intermediate medium, and it can be the internal connection of two elements or the interaction relationship between two elements. The term "and / or" used in this article includes any and all combinations of one or more related listed items. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0019] In the present invention, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may include that the first and second features are in direct contact, or may include that the first and second features are not in direct contact but are in contact through another feature between them. Moreover, a first feature being "above", "above" and "above" a second feature includes that the first feature is directly above and obliquely above the second feature, or simply indicates that the first feature is higher in level than the second feature. A first feature being "below", "below" and "below" a second feature includes that the first feature is directly below and obliquely below the second feature, or simply indicates that the first feature is lower in level than the second feature.

[0020] The disclosure below provides many different embodiments or examples to realize different structures of the present invention. In order to simplify the disclosure of the present invention, the parts and settings of specific examples are described below. Of course, they are only examples, and the purpose is not to limit the present invention. In addition, the present invention can repeat reference numbers and / or reference letters in different examples, and this repetition is for the purpose of simplicity and clarity, which itself does not indicate the relationship between the various embodiments and / or settings discussed. In addition, the present invention provides various specific examples of processes and materials, but those of ordinary skill in the art can be aware of the application of other processes and / or the use of other materials.

[0021] like Figure 1 As shown in the figure, the charging pile charging module fan control method of the present invention is described, in which BP is the BP neural network algorithm, Gn(s) is the charging module temperature-fan speed mathematical model (the charging module temperature-fan speed model can be obtained by the manufacturer based on the charging module output current, charging time, charging power, etc. as variables, and tested in different environments to obtain test data), r is the charging module temperature setting value, and y is the actual detection value of the charging module temperature. , and They are the optimal proportional constant, integral constant and differential constant values ​​inferred by the BP neural network algorithm.

[0022] The control process includes the following steps: Step 1: Set the initial startup parameters of the PID controller , and , calculate the initial output of the PID controller (fan speed).

[0023] (1) In the formula, e is the temperature difference detected at the current charging module of the PID controller, u is the fan speed input value output by the PID controller, , and They are the three parameters of the PID controller: proportional constant, integral constant and differential constant; e , and They represent the charging module temperature difference, the charging module temperature primary deviation and the charging module temperature secondary deviation respectively. , and The calculation formula is: e y(2) (3) (4) In the formula, k , k -1 and k -2 represents the current moment, one moment in the past, and two moments in the past. r is the temperature setting value of the charging module, It is the actual detection value of the charging module temperature.

[0024] The temperature difference of the charging module is a positive deviation or a negative deviation. If the temperature difference of the charging module is a positive deviation, the fan speed is increased through the PID controller. If the temperature difference of the charging module is a negative deviation, the fan electronic controller is adjusted through the PID controller to reduce the fan speed. The detected temperature difference of the charging module is adjusted in 5°C increments. The minimum fan speed is 0. The temperature difference is reduced or increased by one order of magnitude at 0-5°C, reduced or increased by two orders of magnitude at 5-10°C, reduced or increased by three orders of magnitude at 10-15°C, and so on.

[0025] PID controller related parameters , and The initial startup parameters can be obtained by trial and error, that is, by changing the integral value until it is determined that the temperature deviation of the charging module is decreasing, the initial integral value can be obtained. ; Then, by changing the ratio value, it is determined that the temperature deviation of the charging module continues to decrease, and the initial ratio value can be obtained. ; Finally, by changing the differential value until it is determined that the temperature deviation of the charging module is decreasing, the initial differential value can be obtained. The three preliminary values ​​are determined in this way, and after the whole machine starts charging, the optimal integral value, proportional value and differential value are obtained through the neural network algorithm calculation in step 2.

[0026] Step 2: Obtain the temperature difference of the charging module after the initial output adjustment of the PID controller, and input it into the neural network controller to calculate the current optimal integral value, proportional value and differential value of the PID controller.

[0027] like Figure 2 As shown, in this embodiment, the neural network controller adopts a BP neural network, including an input layer, a hidden layer and an output layer (control layer). are the inputs of the BP neural network, representing e(k) and △e(k), i.e., the temperature difference of the charging module and the primary temperature deviation of the charging module; x1', x2' and x3' are the three outputs of the hidden layer, i.e., the intermediate transition values ​​of the algorithm, which are used to determine the weights and thresholds; y1, y2 and y3 are the three outputs of the BP neural network output layer (control layer), representing the three parameters of the PID controller respectively. , and , The input layer Unit to hidden layer The weights between units, The hidden layer Unit to output layer The weights between units.

[0028] The calculation process of the neural network controller is: (1) Calculate the output value of each neuron in the hidden layer and output layer of BP neural network 1. The calculation method of each neuron in the hidden layer and output layer is as follows: (5) (6) in, (*) is the activation function. The activation function adopted in this paper is the Sigmoid function. The sigmoid function is strictly incremental and has a good balance in the transition process from linear to nonlinear. i is the coefficient adjustment value in the hidden layer output activation function. In this paper, the initial moment ai Set to 0.001; b i It is the coefficient adjustment value in the control layer output activation function. In this paper, the initial moment b i Set to 0.003, and the coefficient adjustment value will be adjusted accordingly at different times.

[0029] (7) In the formula, is the tilt parameter of the sigmoid function, where .

[0030] The digital value of the temperature difference detected at the current charging module is expressed as e(k).

[0031] (2) Calculate the objective function value of the detected temperature difference , and make a judgment. (8) like If the condition holds, execute step (4) to adjust the weights and thresholds of the BP neural network until the value is within the objective function range. If it is not true, it means that the temperature deviation has reached the target value range (that is, the default convergence state). The adjustment of the BP neural network can be ended, and the output value of the output layer is sent to the PID controller.

[0032] (3) Adjust the weights and thresholds of the BP neural network. Weights and thresholds of the output layer: (9) (10) Where b i (k) is the coefficient adjustment value in the output activation function of the output layer at time k, b i (k+1) is the coefficient adjustment value in the output activation function of the output layer at time k+1.

[0033] Hidden layer weights and thresholds: (11) (13) a i (k) is the coefficient adjustment value in the hidden layer output activation function at time k, a i (k+1) is the coefficient adjustment value in the hidden layer output activation function at time k+1.

[0034] , return to step (1).

[0035] Step 3: The PID controller uses the current optimal integral value, proportional value and differential value to perform a new round of output calculation and returns to step 2.

[0036] The following are device embodiments of the present invention, which can be used to perform method embodiments of the present invention. For details not disclosed in the device embodiments, please refer to the method embodiments of the present invention.

[0037] In another embodiment of the present invention, a charging pile charging module fan control system is provided, and the charging pile charging module fan control system can be used to implement the above-mentioned charging pile charging module fan control method. Specifically, the charging pile charging module fan control system includes an initial output module, a neural network module and an update output module.

[0038] Among them, the initial output module is used to set the initial integral value, proportional value and differential value of the PID controller, and then calculate the initial output of the PID controller.

[0039] The neural network module is used to obtain the temperature difference of the charging module after the initial output adjustment of the PID controller, and calculate the current optimal integral value, proportional value and differential value of the PID controller through the neural network controller.

[0040] The updated output module is used for the PID controller to use the current optimal integral value, proportional value and differential value to perform a new round of output calculations and return to the neural network module.

[0041] In yet another embodiment of the present invention, a terminal device is provided. The terminal device includes a processor and a memory, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions to implement the corresponding method flow or corresponding function; the processor described in the embodiment of the present invention can be used for the operation of the fan control method of the charging pile charging module, including: S1, setting the initial integral value, proportional value and differential value of the PID controller, and then calculating the initial output of the PID controller; S2, obtaining the temperature difference of the charging module after the output adjustment of the PID controller, and calculating the current optimal integral value, proportional value and differential value of the PID controller through the neural network controller; S3, the PID controller uses the current optimal integral value, proportional value and differential value to perform a new round of output calculation, and returns to S2.

[0042] In another embodiment, the present invention further provides a computer-readable storage medium (Memory), which is a memory device in a terminal device for storing programs and data. It is understandable that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and the extended storage medium supported by the terminal device. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory.

[0043] One or more instructions stored in a computer-readable storage medium can be loaded and executed by the processor to implement the corresponding steps of the charging module fan control method of the charging pile in the above embodiment; one or more instructions in the computer-readable storage medium are loaded by the processor and execute the following steps: S1, set the initial integral value, proportional value and differential value of the PID controller, and then calculate the initial output of the PID controller; S2, obtain the temperature difference of the charging module after the output adjustment of the PID controller, and calculate the current optimal integral value, proportional value and differential value of the PID controller through the neural network controller; S3, the PID controller uses the current optimal integral value, proportional value and differential value to perform a new round of output calculation, and returns to S2.

[0044] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0045] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0046] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0047] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0048] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0049] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0050] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0051] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0052] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

[0053] It should be understood that the above description is for illustration and not for limitation. Many embodiments and many applications beyond the examples provided will be apparent to those skilled in the art upon reading the above description. Therefore, the scope of this patent should not be determined with reference to the above description, but rather with reference to the preceding claims and the full scope of equivalents to which such claims are entitled. For the purpose of comprehensiveness, all articles and references, including disclosures of patent applications and publications, are incorporated herein by reference. The omission of any aspect of the subject matter disclosed herein in the preceding claims is not intended to be a waiver of such subject matter, nor should it be considered that the applicant has not considered such subject matter to be part of the disclosed inventive subject matter.

Claims

1. A method for controlling a fan of a charging pile charging module, characterized in that: The process includes: S1, set the initial integral value, proportional value and differential value of the PID controller, and then calculate the initial output of the PID controller; S2, obtaining the temperature difference of the charging module after the PID controller output adjustment, and calculating the current optimal integral value, proportional value and differential value of the PID controller through the neural network controller; S3, the PID controller uses the current optimal integral value, proportional value and differential value to perform a new round of output calculation and returns to S2.

2. The method for controlling the fan of the charging module of the charging pile according to claim 1, characterized in that: In S1, the initial integral value, proportional value and differential value of the PID controller are obtained by trial and error.

3. The method for controlling the fan of the charging module of the charging pile according to claim 2, characterized in that: The trial and error method process is as follows: first, the integral value is changed until it is determined that the temperature deviation of the charging module is in a decreasing state, and a preliminary integral value is obtained; then, the proportional value is changed to determine that the temperature deviation of the charging module continues to be in a decreasing state, and a preliminary proportional value is obtained; finally, the differential value is changed until it is determined that the temperature deviation of the charging module is in a decreasing state, and a preliminary differential value is obtained.

4. The method for controlling the fan of the charging module of the charging pile according to claim 1, characterized in that: In S2, the neural network controller adopts BP neural network, including input layer, hidden layer and output layer. The temperature difference of charging module and the primary deviation of charging module temperature are inputs of BP neural network. The hidden layer has three outputs, which are intermediate transition values. The output layer of BP neural network has three outputs, which respectively represent the integral value, proportional value and differential value of PID controller.

5. The method for controlling the fan of the charging module of the charging pile according to claim 4, characterized in that: The Sigmoid activation function is used to calculate the hidden layer output value and the output layer output value.

6. The method for controlling the fan of the charging module of the charging pile according to claim 4, characterized in that: After the BP neural network obtains the output value of the output layer, it calculates the objective function value of the detected temperature difference and determines whether the temperature deviation is within the range of the objective function value. If it is within the range, the output value of the output layer is sent to the PID controller. If it is outside the range, the weights and thresholds of the BP neural network are adjusted and the BP neural network calculation is performed again.

7. The method for controlling the fan of a charging pile charging module according to claim 1, characterized in that: When the PID controller calculates a new round of output, the current optimal integral value, proportional value and differential value are used, combined with the charging module temperature difference, the charging module temperature primary deviation and the charging module temperature secondary deviation for calculation.

8. A fan control system for a charging pile charging module, characterized in that: include: The initial output module is used to set the initial integral value, proportional value and differential value of the PID controller, and then calculate the initial output of the PID controller; A neural network module is used to obtain the temperature difference of the charging module after the initial output adjustment of the PID controller, and calculate the current optimal integral value, proportional value and differential value of the PID controller through the neural network controller; The output module is updated so that the PID controller uses the current optimal integral value, proportional value and differential value to perform a new round of output calculation and returns to the neural network module.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the charging pile charging module fan control method as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by the processor, the steps of the charging pile charging module fan control method as described in any one of claims 1 to 7 are implemented.

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