Site selection planning method for electric vehicle battery swap station

Abstract

The invention discloses a site selection method for a battery swap station, and aims to provide a site selection planning method for an electric automobile battery swap station, which is used for site selection planning of the electric automobile battery swap station on the basis of real geographical location information and multi-dimensional consideration factor thermodynamic diagram data. The method has the advantages that regional characteristics are subjected to block research, research efficiency and accuracy are high, thermodynamic diagram data of different dimensions such as permanent resident population, the number of online users of a mobile communication operator base station, road traffic flow and the like are overlaid on a gridded map, and data of the region can be visually displayed; according to the method, the data weight in each grid area can be judged through the thermodynamic diagram data, the number of the needed battery swap stations in the grid areas can be conveniently calculated, the difficulty of transformer substation distribution and site selection is reduced, the data accuracy is improved, and the method is suitable for the technical field of site selection planning of the electric vehicle battery swap stations.

Description

Technical Field

[0001] The present invention relates to the technical field of site selection and planning of electric vehicle battery replacement stations, and more specifically, to a site selection and planning method for electric vehicle battery replacement stations. Background Art

[0002] In recent years, the new energy vehicle market has shown a rapid growth trend. Compared with the charging mode, the battery swap mode uses centralized charging stations to centrally store, charge, and uniformly distribute a large number of batteries, and provides battery replacement services for electric vehicles at the battery swap station. It has the following advantages: high energy replenishment efficiency, battery swap time is less than five minutes, which is faster than all fast charging speeds; battery loss is small, and the battery swap batteries are collected and collected for low-power slow charging after replacement, which helps to extend the battery life; small space occupation area, no need to occupy public parking spaces; improving power grid efficiency, also helps to alleviate the pressure of power grid expansion. In the past few years, the battery swap model has developed slowly due to factors such as high construction costs of battery swaps, lack of a suitable business model, and inconsistent battery standards. However, with the support of policies and the continuous maturity of technology, the battery swap market has ushered in development opportunities.

[0003] The problem of site selection and planning for electric vehicle battery swap stations is to minimize the distance for users to swap batteries and maximize the operating profit of the battery swap stations under the premise of satisfying the needs of users as much as possible. Site selection and planning for electric vehicle battery swap stations is an important long-term decision. The quality of site selection directly affects many factors such as service mode, service quality, service efficiency, and service cost. Although some studies have adopted different intelligent algorithms to solve the problem of site selection and planning for charging stations or battery swap stations, the final results of different algorithms are also very different, and there are still certain limitations in the accuracy of the results and decision support. Summary of the invention

[0004] In view of the shortcomings of the prior art, the purpose of the present invention is to provide a site selection and planning method for electric vehicle battery swap stations based on real geographical location information and multi-dimensional consideration factor heat map data.

[0005] To achieve the above object, the present invention provides the following technical solution: a site selection and planning method for an electric vehicle battery swap station, comprising the following steps:

[0006] S1. Preliminarily divide the areas that electric vehicle battery swap stations need to cover, grid the areas to be planned with a distance of N kilometers, and study the regional characteristics within each grid;

[0007] S2. Assign values ​​to the areas within the grid based on the proportion of the map area in the grid space;

[0008] S3. Calculation of heat map data and determination of the number of battery swap stations within the gridded area. Calculation of heat map data within the grid area by using the regional attributes within the area, and integration of heat map data of multiple dimensions to determine the data weight of each large grid. At the same time, according to the total number of battery swap stations planned to be built, the number of battery swap stations in each large grid is calculated according to the data weight of each large grid.

[0009] S4, subdivide the grid and mark the inaccessible areas on the map. In each grid space, further subdivide each large grid into small grids, and use the small grid as the smallest unit to mark the large inaccessible areas;

[0010] S5. Minimum path planning for the location of the battery swap station. The intersection of the small grid lines is used as the potential location of the battery swap station and the user location. The path combination from the user to the location of the battery swap station is traversed to find the minimum path sum. The minimum path sum is the optimal location point.

[0011] S6. Fine-tune and optimize the site selection of the battery swap station. According to the actual on-site conditions of the battery swap station construction site, fine-tune and optimize the site selection to make the battery swap station address meet the optimal constraints.

[0012] Preferably, in step S2, the value assignment method is to assign a value between 0 and 1 based on the area ratio of the map area within the grid.

[0013] Preferably, the regional attributes in step S3 are heat map data of different dimensions including permanent population, number of online users of mobile communication operator base stations, and road traffic flow. A heat map data is synthesized by assigning weight values ​​to the data of the time period. The synthesis formula is as follows:

[0014]

[0015] Among them, Z represents the thermal data in the grid area, J represents the sum of weighted values ​​in the grid area, and Q represents the sum of weights in the grid area.

[0016] At the same time, the thermal data are combined into a comprehensive thermal map, and the number of battery swap stations in the grid is allocated according to the total number of battery swap stations that need to be built. The calculation formula is as follows:

[0017]

[0018] Among them, D represents the number of battery swap stations that need to be built in the grid area, R represents the thermal data in the grid area, W represents the sum of the thermal data of all grids, H represents the total number of battery swap stations that need to be built, and the number of battery swap stations that need to be built in the grid area is rounded off.

[0019] Preferably, in step S4, the spacing of the large grid is divided into M parts, that is, the distance between each grid is N / M kilometers, and the intersection of the grid lines is set as the site selection point of the battery swap station and the demand point for battery swap, and the inaccessible area includes mountains and rivers on the map.

[0020] Preferably, the site selection and planning of the battery swap station in step S5 includes the following steps:

[0021] S5-1, setting a combination of battery swap station site selection points and battery swap demand points within the grid area;

[0022] S5-2. Without moving the battery swap station site combination, find the minimum distance from each other small grid line intersection to the battery swap station, add these minimum distances together, and find the minimum distance under the current battery swap station site combination;

[0023] S5-3, the site selection point of the mobile battery swap station, change the site selection combination of the battery swap station to find the minimum distance from the battery swap user to the battery swap station;

[0024] S5-4. After traversing and calculating all the combinations, the combination of battery swap stations with the minimum distance from the battery swap user to the battery swap station is taken as the site selection location for the battery swap station in the grid area.

[0025] By adopting the above technical solution, the area is divided into grids and the regional characteristics are studied in blocks, so the research efficiency and accuracy are high. At the same time, the heat map data of different dimensions such as permanent population, number of online users of mobile communication operators' base stations, road traffic flow, etc. are superimposed on the gridded map to intuitively display the data of the area. The data weight in each grid area can be judged by the heat map data, which is convenient for calculating the number of power stations required in the grid area, reducing the difficulty of substation allocation and site selection, and increasing the accuracy of the data.

[0026] At the same time, by highlighting large insurmountable areas such as mountains and rivers in small grids within the region, it has high accuracy and can effectively prevent mistakes in setting up substations. It can also facilitate the subsequent calculation of the minimum distance for the battery swap station site selection combination, while ensuring the cost of battery swap station construction and operation while meeting user needs, reducing the difficulty in site selection for battery swap stations. At the same time, in the site selection of battery swap stations, it meets the constraints of the lowest land price and the most convenient transportation, reduces the later maintenance cost of the battery swap station, and improves the economic benefits of the battery swap station. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 A flowchart of an embodiment of a method for site selection and planning of an electric vehicle battery swap station according to the present invention;

[0028] Figure 2A preliminary gridded and valued regional map of an embodiment of a site selection and planning method for an electric vehicle battery swap station of the present invention;

[0029] Figure 3 Thermal data of road traffic flow characteristics of regional road traffic flow in an embodiment of a site selection and planning method for an electric vehicle battery swap station of the present invention;

[0030] Figure 4 The synthesized thermal data and thermal data diagram of an embodiment of a site selection and planning method for an electric vehicle battery swap station of the present invention;

[0031] Figure 5 A distribution diagram of the number of battery swap stations in an embodiment of a site selection and planning method for an electric vehicle battery swap station of the present invention

[0032] Figure 6 A subdivided grid and annotated regional map of an embodiment of a site selection and planning method for an electric vehicle battery swap station of the present invention;

[0033] Figure 7 This is an example diagram of calculating the minimum distance sum in an embodiment of a site selection planning method for an electric vehicle battery swap station of the present invention. DETAILED DESCRIPTION

[0034] Reference Figures 1 to 7 An embodiment of a site selection planning method for an electric vehicle battery swap station of the present invention is further described.

[0035] For ease of explanation, spatial relative terms such as "upper", "lower", "left", "right" and the like are used in the embodiments to illustrate the relationship of one element or feature shown in the figure relative to another element or feature. It should be understood that, in addition to the orientation shown in the figure, the spatial terms are intended to include different orientations of the device in use or operation. For example, if the device in the figure is inverted, the element described as being "under" other elements or features will be positioned "on" other elements or features. Therefore, the exemplary term "under" can include both upper and lower orientations. The device can be positioned in other ways (rotated 90 degrees or in other orientations), and the spatial relative descriptions used here can be interpreted accordingly.

[0036] Furthermore, relational terms such as “first” and “second” and the like are merely used to distinguish one component from another having the same name, but do not necessarily require or imply any such actual relationship or order between these components.

[0037] A site selection and planning method for an electric vehicle battery swap station comprises the following steps:

[0038] S1. Preliminarily divide the areas that electric vehicle battery swap stations need to cover, grid the areas to be planned with a distance of N kilometers, and study the regional characteristics within each grid;

[0039] S2. Assign values ​​to the areas within the grid based on the proportion of the map area in the grid space;

[0040] S3. Calculation of heat map data and determination of the number of battery swap stations within the gridded area. Calculation of heat map data within the grid area by using the regional attributes within the area, and integration of heat map data of multiple dimensions to determine the data weight of each large grid. At the same time, according to the total number of battery swap stations planned to be built, the number of battery swap stations in each large grid is calculated according to the data weight of each large grid.

[0041] S4, subdivide the grid and mark the inaccessible areas on the map. In each grid space, further subdivide each large grid into small grids, and use the small grid as the smallest unit to mark the large inaccessible areas;

[0042] S5. Minimum path planning for the location of the battery swap station. The intersection of the small grid lines is used as the potential location of the battery swap station and the user location. The path combination from the user to the location of the battery swap station is traversed to find the minimum path sum. The minimum path sum is the optimal location point.

[0043] S6. Fine-tune and optimize the site selection of the battery swap station. According to the actual on-site conditions of the battery swap station construction site, fine-tune and optimize the site selection to make the battery swap station address meet the optimal constraints.

[0044] Reference Figure 2 In step S2, the value assignment method is to assign a value between 0 and 1 based on the area ratio of the map area in the grid.

[0045] Reference Figure 3 to Figure 4 The regional attributes in step S3 are heat map data of different dimensions, such as permanent population, number of online users of mobile communication operator base stations, and road traffic flow. A heat map data is synthesized by assigning weight values ​​to the data of the time period. The synthesis formula is as follows:

[0046]

[0047] Among them, Z represents the thermal data in the grid area, J represents the sum of weighted values ​​in the grid area, and Q represents the sum of weights in the grid area. Among the regional attributes, the permanent population heat map data is data that does not change frequently, and there may be only one permanent population heat map; and for data with time period characteristics such as the number of online users of base stations of mobile communication operators and road traffic flow, multiple heat map data can be obtained according to the time period, and a heat map data is synthesized by assigning weight values ​​to the data in the time period to facilitate subsequent calculations. By setting 1 hour as the time interval, a total of 24 heat map data of road traffic flow in the regional range for one day are obtained, and there are corresponding values ​​in each large grid. Weights are assigned to each heat map data according to the time period, and the data in each corresponding grid on the 24 heat map data are multiplied by the weight value and then summed. Finally, the sum divided by the weight value is the final available heat map data for the consideration factor of this dimension. For example, the grid values ​​and weights assigned to a large grid in a 24-hour period of a day on a regional map are shown in the following table. The grid value of each time period is multiplied by the weight value assigned to the time period to obtain the weighted value. The sum of the weighted values ​​J is divided by the sum of the weights Q to obtain the comprehensive value Z of the grid. The comprehensive values ​​of other large grids on the map are calculated in the same way. For example, the grid values ​​and weights assigned to a large grid in a 24-hour period of a day on a regional map are shown in the following table. Figure 3 As shown, the grid value of each time period is multiplied by the weight value assigned to the time period to obtain the weighted value, and the sum of the weighted values ​​41004 is divided by the weight sum 72 to obtain the comprehensive value of the grid, which is 569.5. In this way, a road traffic flow heat map that can comprehensively reflect the characteristics of road traffic flow in the area is obtained from 24 road traffic flow heat maps of different time periods. After obtaining the heat map data of multi-dimensional consideration factors that have been comprehensively processed, it is necessary to calculate the final heat map data based on the weight of each consideration factor. For example, considering the three dimensions of permanent population, number of online users of mobile communication operators' base stations and road traffic flow, the three data and weight values ​​of the same position in the large grid are as follows: Figure 4 As shown, the final heat map value of the large grid is the total weighted value 20038.8 divided by the total weighted value 10, which is equal to 2003.88 and the total number of battery swap stations built according to needs.

[0048] At the same time, the number of battery swap stations in the grid is allocated according to the total number of battery swap stations that need to be built. The calculation formula is as follows:

[0049]

[0050] Among them, D represents the number of battery swap stations that need to be built in the grid area, R represents the thermal data in the grid area, W represents the sum of the thermal data of all grids, H represents the total number of battery swap stations that need to be built, and the number of battery swap stations that need to be built in the grid area is rounded off. For example, it is planned to build about 600 battery swap stations in the map area. Then, according to the final thermal map data, the number of battery swap stations is evenly distributed according to the proportion of the value of each large grid to the total value of the grid. For example, the final thermal value of a large grid is 6135, and the sum of all grid values ​​is 1866004. Then the number of battery swap stations that can be allocated in the grid area is 6135 / 1866004*600≈1.97. According to the principle of rounding off, 2 battery swap stations need to be built in the grid in the end. The other grids evenly distribute the number of battery swap stations according to the same algorithm, and finally obtain the number of battery swap stations that need to be built in each large grid in the entire area. By dividing the area into grids and superimposing heat map data of different dimensions such as permanent population, number of online users of mobile communication operators' base stations, and road traffic flow on the gridded map, the data of the area can be displayed intuitively. The validity of the personnel data in the area can be determined through the heat map data, which reduces the difficulty of substation allocation and site selection and increases the accuracy of the data.

[0051] Reference Figure 5 to Figure 6 In step S4, the spacing of the large grid is divided into M parts, even if the distance between each grid is N / M kilometers, for example, let M=8, that is, the spacing of each side of the large grid is divided into 8 parts, and the spacing between each small grid is 4 kilometers / 8=0.5 kilometers. At the same time, the intersection of the grid lines is set as the site selection point of the power exchange station and the demand point of power exchange, and the inaccessible area includes mountains and rivers on the map. By highlighting large areas such as mountains and rivers that cannot be crossed in the area, it is effective to prevent mistakes in the setting of the substation, and at the same time, it is convenient to calculate the minimum distance of the subsequent site selection combination of the power exchange station, and the cost of construction and operation of the power exchange station is guaranteed on the premise of meeting user needs, and the difficulty of site selection of the power exchange station is reduced.

[0052] The site selection and planning of the battery swap station in step S5 includes the following steps:

[0053] S5-1, setting a combination of battery swap station site selection points and battery swap demand points within the grid area;

[0054] S5-2. Without moving the battery swap station site combination, find the minimum distance from each other small grid line intersection to the battery swap station, add these minimum distances together, and find the minimum distance under the current battery swap station site combination;

[0055] S5-3, the site selection point of the mobile battery swap station, change the site selection combination of the battery swap station to find the minimum distance from the battery swap user to the battery swap station;

[0056] S5-4. After traversing and calculating all the combinations, the combination of battery swap stations with the minimum distance from the battery swap user to the battery swap station is taken as the site selection location for the battery swap station in the grid area.

[0057] By highlighting large insurmountable areas such as mountains and rivers in the region, errors in substation installation can be effectively prevented. At the same time, it can facilitate the subsequent calculation of the minimum distance for the battery swap station site selection combination, ensuring the cost of battery swap station construction and operation while meeting user needs, reducing the difficulty of battery swap station site selection, and at the same time, meeting the constraints of the lowest land price and the most convenient transportation in the site selection of the battery swap station, reducing the later maintenance cost of the battery swap station and improving the economic benefits of the battery swap station.

[0058] exist Figure 7 The method of selecting a site for a battery swap station in step S5 is specifically shown in FIG. 2. From the image, it is observed that within the large grid area, two battery swap stations S A and S B , there are 7 small grids marked as insurmountable areas within the large grid. In addition to the marked areas, the intersection of the small grid lines is the potential location of two battery swap stations S A and S B The site selection location and the demand point C where users who need to swap batteries go to swap batteries.

[0059] Traverse all possible combinations of battery swap station locations and user demand points, and find the minimum distance and DS from the starting point of the battery swap user at the intersection of all other small grid lines to the battery swap station under the same battery swap station location scheme. K =∑D ij The subscript K represents the site selection combination scheme of the battery swap station, which can be named according to the coordinates of the battery swap station, and the subscript ij is the coordinate of the starting demand point of the battery swap user.

[0060] The lower left corner intersection of each large grid is taken as the origin, and the distance of each small grid is set to unit 1. A , S B The combination scheme K can be marked as "A33B62". The minimum distance from the starting demand point C of the battery swap user to the battery swap station is D17 = 8, because the distance from the user to the battery swap station S A The minimum distance is 8, and the distance to the exchange station S B The minimum distance is 10, so we choose the minimum distance 8. Similarly, D 60 =2. In this way, without moving the combination of the battery swap station site selection, find the minimum distance from each other small grid line intersection to the battery swap station, add these minimum distances, and find the minimum distance and DS under the current battery swap station site selection combination. A33B62Then, we move the location of the battery swap station and change the location combination of the battery swap station to find the minimum distance and DS between the battery swap user and the battery swap station. K After all combinations are calculated, the minimum DS K The battery swap station site selection combination with the highest value is the site selection location for the battery swap station under the large grid.

[0061] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Common changes and substitutions made by those skilled in the art within the scope of the technical solution of the present invention should be included in the protection scope of the present invention.

Claims

1. A site selection and planning method for electric vehicle battery swap stations. It is characterized in that The following steps are involved: S1. Preliminarily divide the areas that electric vehicle battery swap stations need to cover, grid the areas to be planned with a distance of N kilometers, and study the regional characteristics within each grid; S2. Assign values ​​to the areas within the grid, and assign values ​​to each grid based on the proportion of the map area in the grid space; S3. Calculate the heat map data and determine the number of battery swap stations within the grid area. Integrate the heat map data of multiple dimensions to determine the data weight of each large grid. At the same time, according to the total number of battery swap stations planned to be built, calculate the number of battery swap stations in each large grid according to the data weight of each large grid. S4, subdivide the grid and mark the inaccessible areas on the map. In each grid space, further subdivide each large grid into small grids, and use the small grid as the smallest unit to mark the large inaccessible areas; S5. Minimum path planning for the location of the battery swap station. The intersection of the small grid lines is used as the potential location of the battery swap station and the user location. The path combination from the user to the location of the battery swap station is traversed to find the minimum path sum. The minimum path sum is the optimal location point. S6. Fine-tune and optimize the site selection of the battery swap station. According to the actual on-site conditions of the battery swap station construction site, fine-tune and optimize the site selection to make the battery swap station address meet the optimal constraints.

2. A site selection and planning method for an electric vehicle battery swap station according to claim 1, It is characterized in that In step S2, the value assignment method is to assign a value between 0 and 1 based on the area ratio of the map area within the grid.

3. A site selection and planning method for an electric vehicle battery swap station according to claim 1, It is characterized in that In step S3, the heat map data is the sum of heat map data of different dimensions including permanent population, number of online users of base stations of mobile communication operators, and road traffic flow.

4. A site selection and planning method for an electric vehicle battery swap station according to claim 3, It is characterized in that The heat map data of the number of online users of base stations of mobile communication operators and road traffic flow includes the sum of heat map data in different time periods within a regional range.

5. A site selection and planning method for an electric vehicle battery swap station according to claim 3, It is characterized in that In step S3, determining the number of battery swap stations includes the following steps: S3-1. Determine the number of battery swap stations that need to be built in the region; S3-2. Calculate the number of battery swap stations that need to be built in the grid by calculating the thermal data in the grid / the overall thermal data of the region×the number of battery swap stations that need to be built in the region, and round the result to the nearest integer. S3-3. According to step S3-2, the number of battery swap stations that need to be built in all grids is calculated in sequence.

6. A method for site selection and planning of an electric vehicle battery swap station according to claim 1, It is characterized in that In step S5, the site selection planning of the battery swap station includes the following steps: S5-1. Set a combination of battery swap station site selection points and battery swap demand points within the grid area; S5-2. Without moving the battery swap station site combination, find the minimum distance from each other small grid line intersection to the battery swap station, add these minimum distances together, and find the minimum distance under the current battery swap station site combination; S5-3, the site selection point of the mobile battery swap station, change the site selection combination of the battery swap station to find the minimum distance from the battery swap user to the battery swap station; S5-4. After traversing and calculating all the combinations, the combination of battery swap stations with the minimum distance from the battery swap user to the battery swap station is taken as the site selection location for the battery swap station in the grid area.

7. A method for site selection and planning of an electric vehicle battery swap station according to claim 1, It is characterized in that In step S6, the optimal constraint conditions include land price and traffic conditions in the area.

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