Mobile charging pile scheduling method and system based on user use behavior analysis

Abstract

The invention discloses a mobile charging pile scheduling method and system based on user use behavior analysis, and belongs to the field of intelligent charging piles. By analyzing the use behavior of the user, the effect of adjusting the scheduling logic according to the charging use frequency of the site socket of the station is achieved, for the socket with the high use frequency, the priority of the charging pile carried to other positions for charging is reduced, and finally, the charging efficiency is improved. The effect that the charging piles are distributed in different sockets in the station according to the use frequency of the user is achieved, the possibility that the charging piles need to be carried is reduced to the maximum extent, the call charging waiting time of the user is shortened, and the service life of equipment is prolonged while the user experience is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent charging piles, and in particular to a mobile charging pile scheduling method and system based on user usage behavior analysis. Background Art

[0002] In the new energy smart shared charging station, some parking spaces have become hot spots frequently used by users because of their superior geographical location or proximity to the main entrances and exits. The high utilization rate of these parking spaces has brought a series of problems. First, due to the continued high demand for these parking spaces, the dispatching system of the charging station has to frequently dispatch these parking spaces to meet the ever-changing needs of users. This frequent dispatching not only increases the burden on the system, but may also lead to a decrease in dispatching efficiency. Secondly, for charging piles equipped with automatic retractable cable functions, frequent use means that the charging cable needs to be constantly released and retracted. Such repetitive operations not only increase the wear and tear of the charging equipment and shorten the service life of the equipment, but may also lead to safety hazards during the charging process, such as line damage or poor contact.

[0003] In addition, this high frequency of use and scheduling may also affect the user experience. Users may feel inconvenienced by waiting for charging parking spaces, especially during peak hours, when the wait may become even longer. At the same time, frequent scheduling and line retraction and release operations may also complicate the traffic flow within the charging station, increasing the difficulty of user navigation within the station. Summary of the invention

[0004] The present invention provides a mobile charging pile scheduling method and system based on user usage behavior analysis, which can minimize the possibility of moving charging piles according to user usage frequency, reduce user call charging waiting time, and improve user experience.

[0005] The first aspect of the present invention provides a method for scheduling a mobile charging pile based on user usage behavior analysis, comprising the following steps:

[0006] Obtaining a user charging request, and extracting a user parking location in the user charging request;

[0007] Calculate the walking distance required for the dispatching robot to carry each idle charging pile to the user's parking position according to the user's parking position, the position of the idle charging pile and the position of the dispatching robot;

[0008] The charging frequency factor of the socket corresponding to the idle charging pile within a preset time period is calculated according to the user's usage behavior, and the charging frequency factor is multiplied by the corresponding walking distance to obtain multiple transportation coefficients. The idle charging pile corresponding to the minimum value of the transportation coefficients is selected as the charging pile requested by the user, and the scheduling robot is used to schedule the charging pile for the user.

[0009] Optionally, in one embodiment of the present invention, the charging frequency factor of the socket corresponding to the idle charging pile within a preset time period is calculated according to the user's usage behavior, including:

[0010] The number of times all sockets are used for charging within a preset time period is counted and normalized to obtain the charging frequency factor.

[0011] Optionally, in one embodiment of the present invention, when the charging frequency factor of the socket is less than a preset value within a preset time period, the charging frequency factor of the socket is set to a fixed value.

[0012] The second aspect of the present invention provides a mobile charging pile scheduling system based on user usage behavior analysis, including:

[0013] An acquisition module, used to acquire a user charging request and extract a user parking location in the user charging request;

[0014] A calculation module, used to calculate the walking distance that the dispatching robot needs to carry each idle charging pile to the user's parking position according to the user's parking position, the position of the idle charging pile and the position of the dispatching robot;

[0015] The scheduling module is used to calculate the charging frequency factor of the socket corresponding to the idle charging pile within a preset time period according to the user's usage behavior, multiply the charging frequency factor by the corresponding walking distance to obtain multiple transportation coefficients, select the idle charging pile corresponding to the minimum value of the transportation coefficient as the charging pile requested by the user, and use the scheduling robot to schedule the charging pile for the user.

[0016] Optionally, in one embodiment of the present invention, the calculation module is further used to count the number of times all sockets are used for charging within a preset time period, and perform normalization to obtain the charging frequency factor.

[0017] Optionally, in one embodiment of the present invention, when the charging frequency factor of the socket is less than a preset value within a preset time period, the charging frequency factor of the socket is set to a fixed value.

[0018] A third aspect of the present invention provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to execute the mobile charging pile scheduling method based on user usage behavior analysis as described in the above embodiment.

[0019] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which is executed by a processor to execute the mobile charging pile scheduling method based on user usage behavior analysis as described in the above embodiment.

[0020] The mobile charging pile scheduling method and system based on user usage behavior analysis of the embodiments of the present invention achieves the effect of adjusting the scheduling logic according to the frequency of use of charging sockets at the station site by analyzing the user usage behavior. For sockets with higher usage frequency, the priority of the charging piles at this location to be moved to other locations for charging is reduced. Ultimately, the charging piles are distributed in different sockets in the station according to the frequency of user use, thereby minimizing the possibility of needing to move the charging piles, reducing the waiting time for users to call for charging, and improving the user experience while extending the service life of the equipment.

[0021] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0023] Figure 1 A flowchart of a mobile charging pile scheduling method based on user usage behavior analysis provided according to an embodiment of the present invention;

[0024] Figure 2 A schematic diagram of a usage scenario of an embodiment of the present invention;

[0025] Figure 3 This is an example diagram of a mobile charging pile scheduling system based on user usage behavior analysis according to an embodiment of the present invention;

[0026] Figure 4 A schematic diagram of the structure of an electronic device provided by an embodiment of the invention. DETAILED DESCRIPTION

[0027] 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 intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0028] Figure 1 The present invention provides a flowchart of a mobile charging pile scheduling method based on user usage behavior analysis according to an embodiment of the present invention.

[0029] like Figure 1 As shown, the mobile charging pile scheduling method based on user usage behavior analysis includes the following steps:

[0030] In step S101, a user charging request is obtained, and the user parking location in the user charging request is extracted.

[0031] It is understandable that after the user parks the car, he can use a terminal (such as a mobile phone or a charging pile device, etc.) to send a charging request including the user's parking location to the charging system. In addition, the charging request may also include information such as charging time, which is not limited.

[0032] In step S102, the walking distance required by the dispatching robot to carry each idle charging pile to the user's parking position is calculated according to the user's parking position, the position of the idle charging pile and the position of the dispatching robot.

[0033] In an embodiment of the present invention, Figure 2 As shown, the sockets in the new energy smart shared charging station are fixed, and the charging piles are plugged into the sockets. When in use, the dispatching robot drives the charging piles to move to the sockets that need charging.

[0034] After obtaining the user's parking position, first calculate the walking distance of the dispatching robot from the current position to each charging pile and carry the charging pile to the user's parking position. In this way, the walking distance d of the robot carrying each charging pile can be obtained. 1 ,d 2 ,...d n .

[0035] In step S103, the charging frequency factor of the socket corresponding to the idle charging pile within the preset time period is calculated according to the user's usage behavior, and the charging frequency factor is multiplied by the corresponding walking distance to obtain multiple transportation coefficients. The idle charging pile corresponding to the minimum value of the transportation coefficient is selected as the charging pile requested by the user, and the scheduling robot is used to schedule the charging pile for the user.

[0036] If all walking distances are sorted from small to large, the charging pile corresponding to the smallest distance is the one needed for this charging. For sockets with high usage frequency, frequent charging pile scheduling increases the burden on the system, resulting in a decrease in scheduling efficiency, increased wear of the charging pile, and shortened service life of the charging pile. Therefore, the embodiments of the present invention take into account user usage behavior and optimize the charging pile scheduling scheme according to the user usage behavior.

[0037] Specifically, count the number of times all sockets are used for charging within a preset time period T. 1 ,f 2 ,...f n , further normalized Get the charging frequency factor f 1 ',f 2 ',...f n'. Multiply the walking distance d and the charging frequency factor f' to adjust the walking distance according to the user's charging frequency information to obtain the handling selection coefficient w of each charging pile. 1 ,w 2 ,...w n , where w i =d i ×f i '. Sort all the transport selection coefficients from small to large, and the charging pile corresponding to the smallest value is the one that needs to be used for this charging.

[0038] It is understandable that for sockets with high usage frequency, the larger the charging frequency factor is, the larger the handling selection coefficient becomes after multiplying it by the walking distance, thereby reducing the scheduling of charging piles for sockets with high usage frequency.

[0039] Furthermore, when the charging frequency factor of the socket is less than a preset value within a preset time period, the charging frequency factor of the socket is set to a fixed value. When the socket is used too rarely, a fixed value is used. Perform calculations to avoid values ​​being 0.

[0040] According to the mobile charging pile scheduling method based on user usage behavior analysis proposed in an embodiment of the present invention, by analyzing user usage behavior, the scheduling logic is adjusted according to the frequency of use of charging sockets at the station site. For sockets with higher usage frequency, the priority of the charging piles at this location to be moved to other locations for charging is reduced. Ultimately, the charging piles are distributed in different sockets in the station according to the frequency of user use, thereby minimizing the possibility of needing to move the charging piles, reducing the waiting time for users to call for charging, and improving the user experience while extending the service life of the equipment.

[0041] Next, a mobile charging pile scheduling system based on user usage behavior analysis proposed in accordance with an embodiment of the present invention will be described with reference to the accompanying drawings.

[0042] Figure 3 This is an example diagram of a mobile charging pile scheduling system based on user usage behavior analysis according to an embodiment of the present invention.

[0043] like Figure 3 As shown, the mobile charging pile scheduling system 10 based on user usage behavior analysis includes: an acquisition module 100, a calculation module 200 and a scheduling module 300.

[0044] The acquisition module 100 is used to obtain the user's charging request and extract the user's parking position in the user's charging request. The calculation module 200 is used to calculate the walking distance that the dispatching robot needs to carry each idle charging pile to the user's parking position based on the user's parking position, the position of the idle charging pile and the position of the dispatching robot. The scheduling module 300 is used to calculate the charging frequency factor of the socket corresponding to the idle charging pile within a preset time period based on the user's usage behavior, multiply the charging frequency factor by the corresponding walking distance to obtain multiple transportation coefficients, select the idle charging pile corresponding to the minimum value of the transportation coefficient as the charging pile for the user's charging request, and use the dispatching robot to schedule the charging pile for the user.

[0045] Optionally, in one embodiment of the present invention, the calculation module is further used to count the number of times all sockets are used for charging within a preset time period, and perform normalization to obtain a charging frequency factor.

[0046] Optionally, in one embodiment of the present invention, when the charging frequency factor of the socket is less than a preset value within a preset time period, the charging frequency factor of the socket is set to a fixed value.

[0047] It should be noted that the aforementioned explanation of the embodiment of the mobile charging pile scheduling method based on user usage behavior analysis is also applicable to the mobile charging pile scheduling system based on user usage behavior analysis of this embodiment, and will not be repeated here.

[0048] According to the mobile charging pile scheduling system based on user usage behavior analysis proposed in the embodiment of the present invention, by analyzing the user usage behavior, the scheduling logic is adjusted according to the usage frequency of the charging sockets at the station site. For sockets with higher usage frequency, the priority of the charging piles at this location to be moved to other locations for charging is reduced. Ultimately, the charging piles are distributed in different sockets in the station according to the user usage frequency, thereby minimizing the possibility of needing to move the charging piles, reducing the waiting time for users to call for charging, and improving the user experience while extending the service life of the equipment.

[0049] Figure 4 A schematic diagram of the structure of an electronic device provided by an embodiment of the invention. The electronic device may include:

[0050] Memory 401 , processor 402 , and a computer program stored in the memory 401 and executable on the processor 402 .

[0051] When the processor 402 executes the program, the mobile charging pile scheduling method based on user usage behavior analysis provided in the above embodiment is implemented.

[0052] Furthermore, the electronic device further comprises:

[0053] The communication interface 403 is used for communication between the memory 401 and the processor 402 .

[0054] The memory 401 is used to store computer programs that can be executed on the processor 402 .

[0055] The memory 401 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0056] If the memory 401, the processor 402 and the communication interface 403 are implemented independently, the communication interface 403, the memory 401 and the processor 402 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0057] Optionally, in a specific implementation, if the memory 401, the processor 402 and the communication interface 403 are integrated on a chip, the memory 401, the processor 402 and the communication interface 403 can communicate with each other through an internal interface.

[0058] The processor 402 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present invention.

[0059] This embodiment also provides a computer-readable storage medium on which a computer program is stored, characterized in that when the program is executed by a processor, the mobile charging pile scheduling method based on user usage behavior analysis as described above is implemented.

[0060] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0061] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "N" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0062] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present invention belong.

[0063] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0064] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

Claims

1. A mobile charging pile scheduling method based on user usage behavior analysis, characterized in that: The following steps are involved: Obtaining a user charging request, and extracting a user parking location in the user charging request; Calculate the walking distance required for the dispatching robot to carry each idle charging pile to the user's parking position according to the user's parking position, the position of the idle charging pile and the position of the dispatching robot; The charging frequency factor of the socket corresponding to the idle charging pile within a preset time period is calculated according to the user's usage behavior, and the charging frequency factor is multiplied by the corresponding walking distance to obtain multiple transportation coefficients. The idle charging pile corresponding to the minimum value of the transportation coefficients is selected as the charging pile requested by the user, and the scheduling robot is used to schedule the charging pile for the user.

2. The method according to claim 1, characterized in that The charging frequency factor of the corresponding socket of the idle charging pile in the preset time period is calculated based on the user's usage behavior, including: The number of times all sockets are used for charging within a preset time period is counted and normalized to obtain the charging frequency factor.

3. The method according to claim 2, characterized in that When the charging frequency factor of the socket is less than a preset value within a preset time period, the charging frequency factor of the socket is set to a fixed value.

4. A mobile charging pile scheduling system based on user usage behavior analysis, characterized in that: include: An acquisition module, used to acquire a user charging request and extract a user parking location in the user charging request; A calculation module, used to calculate the walking distance that the dispatching robot needs to carry each idle charging pile to the user's parking position according to the user's parking position, the position of the idle charging pile and the position of the dispatching robot; The scheduling module is used to calculate the charging frequency factor of the socket corresponding to the idle charging pile within a preset time period according to the user's usage behavior, multiply the charging frequency factor by the corresponding walking distance to obtain multiple transportation coefficients, select the idle charging pile corresponding to the minimum value of the transportation coefficient as the charging pile requested by the user, and use the scheduling robot to schedule the charging pile for the user.

5. The system according to claim 4, characterized in that The calculation module is further used to count the number of times all sockets are used for charging within a preset time period, and perform normalization to obtain the charging frequency factor.

6. The system according to claim 5, characterized in that When the charging frequency factor of the socket is less than a preset value within a preset time period, the charging frequency factor of the socket is set to a fixed value.

7. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the mobile charging pile scheduling method based on user usage behavior analysis as described in any one of claims 1 to 3.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the mobile charging pile scheduling method based on user usage behavior analysis as described in any one of claims 1 to 3.

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