Charging map determination method and device, equipment and storage medium

Abstract

The embodiment of the invention provides a charging map determination method and device, equipment and a storage medium. The method comprises the steps that charging state information corresponding to a plurality of historical charging vehicles is obtained firstly, the charging state information of each historical charging vehicle is used for indicating time data, position data and charging data of the historical charging vehicles in the charging state within a preset duration, and then according to a preset filtering condition, the charging state information of each historical charging vehicle is obtained; filtering the multiple pieces of charging state information to obtain multiple pieces of target position data, the filtering condition being determined based on a preset charging duration and a preset charging position error, and finally determining a charging map suitable for vehicle charging according to the multiple pieces of target position data and the charging data corresponding to the multiple pieces of target position data. According to the method, the charging map suitable for vehicle charging is determined, and the charging failure rate of the vehicle is effectively reduced.

Description

Technical Field

[0001] The present application relates to the field of vehicle charging technology, and in particular to a method, apparatus, device, and storage medium for determining a charging map. Background Art

[0002] With the transformation of energy structures, electric heavy-duty trucks have become a key vehicle for emissions reduction. However, their large-scale deployment is severely constrained by a lack of charging infrastructure. Firstly, this infrastructure limits vehicle height and high power requirements, resulting in only a small number of public charging stations suitable for electric heavy-duty trucks. Secondly, an unbalanced layout of charging facilities and a lack of information lead to inefficient operations. For some electric heavy-duty trucks, finding available charging stations takes a long time, resulting in inefficient charging.

[0003] Existing charging maps are mainly based on the historical charging data of electric vehicles. By obtaining the location coordinates of the basic charging facilities recorded in the historical charging data, these basic charging facilities are marked on the map to generate a charging map marked with basic charging facilities. In addition, the charging map can also be directly marked based on the installation location information of the basic charging facilities.

[0004] However, the existing charging map cannot meet the charging needs of electric heavy trucks and is prone to a high charging failure rate. Summary of the Invention

[0005] The embodiments of the present application provide a method, apparatus, device, and storage medium for determining a charging map, so as to reduce the charging failure rate of electric heavy trucks.

[0006] In a first aspect, an embodiment of the present application provides a method for determining a charging map, including:

[0007] Obtaining charging status information corresponding to a plurality of historically charged vehicles, wherein the charging status information of each historically charged vehicle indicates time data, location data, and charging data of the historically charged vehicle in the charging state within a preset time period;

[0008] Filtering the plurality of charging status information according to a preset filtering condition to obtain a plurality of target position data, wherein the filtering condition is determined based on a preset charging duration and a preset charging position error;

[0009] A charging map suitable for vehicle charging is determined based on the plurality of target location data and the charging data corresponding to the plurality of target location data.

[0010] In one or more embodiments, determining a charging map suitable for vehicle charging based on the plurality of target location data and the charging data corresponding to the plurality of target location data includes:

[0011] Determine the spatial similarity corresponding to each two target position data and the text similarity corresponding to each two target position data;

[0012] A charging map suitable for vehicle charging is determined according to the spatial similarity corresponding to every two target location data, the text similarity corresponding to every two target location data, and the charging data corresponding to the plurality of target location data.

[0013] In one or more embodiments, determining a charging map suitable for vehicle charging based on the spatial similarity corresponding to each two target location data, the text similarity corresponding to each two target location data, and the charging data corresponding to the plurality of target location data includes:

[0014] Determine the similarity and value of the spatial similarity and text similarity corresponding to each two target position data;

[0015] Determine two target position data whose similarity sum value is greater than a first similarity threshold as the same first target position data;

[0016] determining two target position data whose similarity sum value is less than or equal to the first similarity threshold as different second target position data;

[0017] A charging map suitable for vehicle charging is determined based on all first target location data, all second target location data, charging data corresponding to all first target location data, and charging data corresponding to all second target location data.

[0018] In one or more embodiments, determining the spatial similarity corresponding to each two target position data includes:

[0019] Determine the linear distance and spherical distance corresponding to each two target position data based on the latitude and longitude information in each two target position data;

[0020] The spatial similarity corresponding to each two target location data is determined based on the straight-line distance and spherical distance corresponding to each two target location data, as well as the clustering radius, wherein the clustering radius is determined based on the physical area type in which each two target location data are located and the longitude information in all target location data.

[0021] In one or more embodiments, determining the text similarity corresponding to each two target location data includes:

[0022] Determine the address description information corresponding to each two target location data according to the latitude and longitude information in each two target location data;

[0023] Determine the edit distance between each two target location data according to the address description information corresponding to each two target location data;

[0024] The text similarity corresponding to each two target location data is determined according to the edit distance corresponding to each two target location data and the address description information corresponding to each two target location data.

[0025] In one or more embodiments, determining a charging map suitable for vehicle charging based on all first target location data, all second target location data, charging data corresponding to all first target location data, and charging data corresponding to all second target location data includes:

[0026] Determining the locations of a plurality of charging piles in the charging map according to all the first target location data and all the second target location data;

[0027] According to the charging data corresponding to all the first target location data and the charging data corresponding to all the second target location data, the maximum power data of the plurality of charging piles in the charging map and the type of historical charging vehicle corresponding to each maximum power data are determined.

[0028] In one or more embodiments, filtering the plurality of charging status information according to a preset filtering condition to obtain a plurality of target location data includes:

[0029] For the plurality of charging status information, removing the charging status information whose time data is less than the charging duration, to obtain a plurality of first charging status information;

[0030] For the plurality of first charging status information, removing the first charging status information whose position data is outside the charging position error, to obtain a plurality of second charging status information;

[0031] The position data in the plurality of second charging state information are determined as the plurality of target position data.

[0032] In a second aspect, an embodiment of the present application provides a device for determining a charging map, including:

[0033] An acquisition module is configured to acquire charging status information corresponding to a plurality of historically charged vehicles, wherein the charging status information of each historically charged vehicle indicates time data, location data, and charging data of the historically charged vehicle during a preset time period when the vehicle was in a charging state;

[0034] a filtering module, configured to filter the plurality of charging status information according to a preset filtering condition to obtain a plurality of target position data, wherein the filtering condition is determined based on a preset charging duration and a preset charging position error;

[0035] The determining module is configured to determine a charging map suitable for vehicle charging based on the plurality of target location data and the charging data corresponding to the plurality of target location data.

[0036] In one or more embodiments, the determining module is specifically configured to:

[0037] Determine the spatial similarity corresponding to each two target position data and the text similarity corresponding to each two target position data;

[0038] A charging map suitable for vehicle charging is determined according to the spatial similarity corresponding to every two target location data, the text similarity corresponding to every two target location data, and the charging data corresponding to the plurality of target location data.

[0039] In one or more embodiments, the determining module is configured to determine a charging map suitable for vehicle charging based on the spatial similarity corresponding to each two target location data, the text similarity corresponding to each two target location data, and the charging data corresponding to the plurality of target location data. The determining module is configured to:

[0040] Determine the similarity and value of the spatial similarity and text similarity corresponding to each two target position data;

[0041] Determine two target position data whose similarity sum value is greater than a first similarity threshold as the same first target position data;

[0042] determining two target position data whose similarity sum value is less than or equal to the first similarity threshold as different second target position data;

[0043] A charging map suitable for vehicle charging is determined based on all first target location data, all second target location data, charging data corresponding to all first target location data, and charging data corresponding to all second target location data.

[0044] In one or more embodiments, the determining module for determining the spatial similarity corresponding to each two target position data is specifically configured to:

[0045] Determine the linear distance and spherical distance corresponding to each two target position data based on the latitude and longitude information in each two target position data;

[0046] The spatial similarity corresponding to each two target location data is determined based on the straight-line distance and spherical distance corresponding to each two target location data, as well as the clustering radius, wherein the clustering radius is determined based on the physical area type in which each two target location data are located and the longitude information in all target location data.

[0047] In one or more embodiments, the determining module for determining the text similarity corresponding to each two target location data is specifically configured to:

[0048] Determine the address description information corresponding to each two target location data according to the latitude and longitude information in each two target location data;

[0049] Determine the edit distance between each two target location data according to the address description information corresponding to each two target location data;

[0050] The text similarity corresponding to each two target location data is determined according to the edit distance corresponding to each two target location data and the address description information corresponding to each two target location data.

[0051] In one or more embodiments, the determining module is configured to determine a charging map suitable for vehicle charging based on all first target location data, all second target location data, the charging data corresponding to all first target location data, and the charging data corresponding to all second target location data. The determining module is configured to:

[0052] Determining the locations of a plurality of charging piles in the charging map according to all the first target location data and all the second target location data;

[0053] According to the charging data corresponding to all the first target location data and the charging data corresponding to all the second target location data, the maximum power data of the plurality of charging piles in the charging map and the type of historical charging vehicle corresponding to each maximum power data are determined.

[0054] In one or more embodiments, the filtering module is specifically configured to:

[0055] For the plurality of charging status information, removing the charging status information whose time data is less than the charging duration, to obtain a plurality of first charging status information;

[0056] For the plurality of first charging status information, removing the first charging status information whose position data is outside the charging position error, to obtain a plurality of second charging status information;

[0057] The position data in the plurality of second charging state information are determined as the plurality of target position data.

[0058] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a memory, a processor;

[0059] The memory stores computer-executable instructions;

[0060] The processor executes the computer-executable instructions stored in the memory, so that the processor is used to implement the method described in the first aspect and any one of the embodiments when executing.

[0061] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the method described in the first aspect and any one of the embodiments above.

[0062] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, is used to implement the method for determining a charging map as described in the first aspect and various possible implementations of the first aspect.

[0063] The present application provides a method, apparatus, device, and storage medium for determining a charging map. The method first obtains charging status information corresponding to multiple historically charged vehicles. For each historically charged vehicle, the charging status information indicates the time data, location data, and charging data during which the historically charged vehicle was in a charging state within a preset duration. The method then filters the multiple charging status information based on preset filtering conditions to obtain multiple target location data, wherein the filtering conditions are determined based on a preset charging duration and a preset charging location error. Finally, a charging map suitable for vehicle charging is determined based on the multiple target location data and the charging data corresponding to the multiple target location data. In the above method, by obtaining the charging status information of multiple historical charging vehicles, the time data, position data, and charging data of the historical charging vehicles in the charging state within the preset time period can be accurately grasped; by pre-setting filtering conditions, according to the preset charging time and the preset charging position error, the multiple charging status information can be filtered to obtain multiple target position data suitable for vehicle charging, reducing the impact of invalid data, thereby ensuring the accuracy and reliability of the obtained multiple target position data; by combining the multiple target position data and the charging data corresponding to the multiple target position data, the multiple target position data and the corresponding charging data can be determined to determine a charging map suitable for vehicle charging, which can help the vehicle efficiently select a suitable charging pile in the charging map, reduce the failure rate of vehicle charging, and improve the charging efficiency of the vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0065] Figure 1 Schematic diagram of the process of determining the charging map provided in the embodiment of the present application Figure 1 ;

[0066] Figure 2 Schematic diagram of the process of determining the charging map provided in the embodiment of the present application Figure 2 ;

[0067] Figure 3 Schematic diagram of the process of determining the charging map provided in the embodiment of the present application Figure 3 ;

[0068] Figure 4 A schematic diagram of the structure of a device for determining a charging map provided in an embodiment of the present application;

[0069] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0070] The above drawings illustrate specific embodiments of the present application, which will be described in more detail below. These drawings and the textual description are not intended to limit the scope of the present application in any way, but rather to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0071] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0072] Before introducing the embodiments of the present application, the application background of the embodiments of the present application is first explained:

[0073] With the transformation of energy structures, electric heavy-duty trucks have become a key vehicle for emissions reduction. However, their large-scale deployment is severely constrained by a lack of charging infrastructure. Firstly, this infrastructure limits vehicle height and high power requirements, resulting in only a small number of public charging stations suitable for electric heavy-duty trucks. Secondly, an unbalanced layout of charging facilities and a lack of information lead to inefficient operations. For some electric heavy-duty trucks, finding available charging stations takes a long time, resulting in inefficient charging.

[0074] Existing charging maps are mainly based on the historical charging data of electric vehicles. By obtaining the location coordinates of the basic charging facilities recorded in the historical charging data, these basic charging facilities are marked on the map to generate a charging map marked with basic charging facilities. In addition, the charging map can also be directly marked based on the installation location information of the basic charging facilities.

[0075] However, the existing charging map cannot meet the charging needs of electric heavy trucks and is prone to a high charging failure rate.

[0076] The present application provides a method for determining a charging map, which aims to solve the above technical problems of the prior art. The inventive concept of the present application is as follows: Traditional charging maps are determined by directly marking the locations of all basic charging facilities. The charging piles determined based on the traditional charging map may have poor spatial compatibility or low charging power, resulting in a high charging failure rate for electric heavy trucks. If the charging status information of the vehicle can be analyzed, the target location data and the charging data corresponding to the target location data can be determined by considering the time data, location data, and charging data of the historical charging vehicle in the charging status information. Then, a charging map suitable for vehicle charging can be determined. Therefore, the present application determines a preset filtering condition based on a preset charging time and a preset charging location error. According to the preset filtering condition, multiple charging status information are filtered to obtain multiple target location data to ensure the accuracy and reliability of the data. Then, based on the multiple target location data and the charging data corresponding to the multiple target location data, a charging map suitable for vehicle charging is determined. The charging data corresponding to the multiple target location data in the charging map can help the vehicle efficiently select a suitable charging pile in the charging map, thereby reducing the failure rate of vehicle charging.

[0077] The execution subject of the embodiments of the present application is an electronic device, which can be a terminal device, such as a laptop computer, a desktop computer, a tablet computer, etc., or a server. In actual applications, whether the electronic device is a terminal device or a server can be determined based on actual conditions and is not specifically limited to this.

[0078] The following specific embodiments describe in detail the technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0079] Figure 1 Schematic diagram of the process of determining the charging map provided in the embodiment of the present application Figure 1 .like Figure 1 As shown, the method for determining the charging map includes the following steps:

[0080] S110, obtaining charging status information corresponding to a plurality of historically charged vehicles;

[0081] The charging status information of each historically charged vehicle is used to indicate time data, location data, and charging data of the historically charged vehicle in the charging state within a preset time period.

[0082] In this step, for the charging status information of each historical charging vehicle, the charging status information is used to indicate the time data, location data, and charging data of the historical charging vehicle in the charging state within a preset time period. The charging status information corresponding to multiple historical charging vehicles can be obtained, thereby clarifying the time data, location data, and charging data of multiple historical charging vehicles in the charging state.

[0083] For example, the time data may be the time interval during which the historical charging vehicle was in the charging state within a preset time period, the location data may be the latitude and longitude data when the historical charging vehicle was in the charging state, and the charging data may be the current and voltage when the historical charging vehicle was in the charging state.

[0084] In one possible implementation, the charging status information of each historically charged vehicle includes multiple charging statuses corresponding to multiple time points within a preset time period. The time data of the historically charged vehicle in the charging status, that is, the time interval during which the historically charged vehicle was in the charging status, can be determined based on the multiple charging statuses corresponding to multiple time points within the preset time period.

[0085] For example, assuming that the charging state sequence corresponding to multiple time points is {S i}, S i represents the charging state at the i-th time point, S i =1 indicates charging state, S i ≠1 indicates a non-charging state. The start time index list of the charging state is α, and the end time index list of the charging state is β.

[0086] For any time point i, if the charging state S at the i-th time point i =1 and (i=0 or the charging state S at the i-1th time point i-1 ≠1), then add the time point i to the starting time index list α of the charging state.

[0087] If the charging state S at the i-th time point i =1 and (i=N-1 or the charging state S at the i+1th time point i+1 ≠1), then add i to the end time index list β of the charging state, where N is the length of the charging state sequence.

[0088] For example, taking the charging state sequence as {1,1,1,1,0,0} and time point i=0,1,2,3,4,5 as an example, for time point i=0, S0=1, then add time point i=0 to the starting time index list α of the charging state; for time point i=1, S1=1, and S i-1 =S0=1,

[0089] S i+1 =S2=1, then there is no need to add the time point i=1 to the start time index list α of the charging state or the end time index list β of the charging state; for the time point i=3, S3=1, and S i+1 =S4≠1, then the time point i=3 is added to the end time index list β of the charging state.

[0090] In a possible implementation, the charging state start time index list α and the charging state end time index list β are combined to obtain the time interval ε of the historical charging vehicle in the charging state = {[s k ,e k ]}, where s k and e k They respectively represent the start time index and end time index of the kth time interval in the charging state.

[0091] If the end time index e of the kth time interval in the charging state k With the start time index s k The difference between k -s k If is 0, the kth time interval in the charging state is deleted from the historical time intervals ε in which the charging vehicle is in the charging state.

[0092] In addition, the merging condition of the time interval is set as follows: the starting time index s of the k+1th time interval in the charging state k+1 The end time index e of the kth time interval in the charging state k If the difference is less than the preset merging threshold, the adjacent time intervals that meet the merging conditions in the time interval ε of the historical charging vehicle in the charging state can be merged, avoiding the problem of time interval fragmentation caused by charging state information noise or state switching.

[0093] S120, filtering the plurality of charging status information according to a preset filtering condition to obtain a plurality of target location data;

[0094] The filtering condition is determined based on a preset charging time and a preset charging position error.

[0095] In this step, filtering conditions can be determined based on a preset charging time and a preset charging position error. According to the preset filtering conditions, multiple charging status information are filtered, and multiple target position data are obtained based on the position data in the filtered multiple charging status information.

[0096] In one possible implementation, multiple charging status information are filtered according to preset filtering conditions. The filtering may be based on a preset charging time and the time data in the multiple charging status information, and the charging status information with time data less than the preset charging time is deleted. Thereafter, the filtering is based on a preset charging position error and the position data in the multiple charging status information, and the charging status information with position data outside the charging position error is deleted. Then, multiple target position data are obtained based on the position data in the filtered multiple charging status information.

[0097] S130 : Determine a charging map suitable for vehicle charging based on the plurality of target location data and the charging data corresponding to the plurality of target location data.

[0098] In this step, a charging map annotated with the plurality of target location data and the corresponding charging data is determined based on the plurality of target location data and the charging data corresponding to the plurality of target location data, and is used as a charging map suitable for vehicle charging.

[0099] For example, the charging data corresponding to the target location data may be the maximum charging power of the vehicle in a historical charging state.

[0100] In one possible implementation, the charging data corresponding to the multiple target location data can be determined based on the charging data in the multiple charging status information, and the charging data in the charging status information of each historical charging vehicle includes the current and voltage corresponding to multiple time points within a preset time period.

[0101] Based on the current and voltage corresponding to multiple time points within the preset time period, multiple charging powers corresponding to the multiple time points can be obtained, and the maximum charging power among the multiple charging powers is used as the charging data corresponding to the target position data.

[0102] In one possible implementation, each historically charged vehicle may include a vehicle type identifier, and the vehicle types include heavy truck type vehicles and light truck type vehicles. Multiple target location data may carry the vehicle type identifier. Then, when determining a charging map suitable for vehicle charging based on the multiple target location data and the charging data corresponding to the multiple target location data, the vehicle type identifiers carried by the multiple target location data may be marked on the charging map.

[0103] Exemplarily, a charging map suitable for vehicle charging is marked with a plurality of target location data, a maximum charging power corresponding to the plurality of target location data, and a vehicle type identifier carried by the plurality of target location data.

[0104] The method for determining a charging map provided in an embodiment of the present application first obtains charging status information corresponding to multiple historically charged vehicles. For each historically charged vehicle, the charging status information is used to indicate time data, location data, and charging data of the historically charged vehicle in the charging state within a preset time period. Then, according to a preset filtering condition, the multiple charging status information is filtered to obtain multiple target location data, wherein the filtering condition is determined based on a preset charging time period and a preset charging location error. Finally, a charging map suitable for vehicle charging is determined based on the multiple target location data and the charging data corresponding to the multiple target location data. In this embodiment, by acquiring the charging status information of multiple historical charging vehicles, the time data, location data, and charging data of the historical charging vehicles in the charging state within the preset time period can be accurately grasped; by pre-setting filtering conditions, according to the preset charging time and the preset charging position error, the multiple charging status information can be filtered to obtain multiple target location data suitable for vehicle charging, reducing the impact of invalid data, thereby ensuring the accuracy and reliability of the obtained multiple target location data; by combining the multiple target location data and the charging data corresponding to the multiple target location data, the multiple target location data and the corresponding charging data can be determined to determine a charging map suitable for vehicle charging, which can help the vehicle efficiently select a suitable charging pile in the charging map, reduce the failure rate of vehicle charging, and improve the charging efficiency of the vehicle.

[0105] Based on the above embodiments, Figure 2 Schematic diagram of the process of determining the charging map provided in the embodiment of the present application Figure 2 .like Figure 2 As shown, a possible implementation of the above step S130 further includes the following steps:

[0106] S210: Determine the spatial similarity corresponding to every two target position data and the text similarity corresponding to every two target position data.

[0107] In this step, the target location data includes spatial location data and descriptive text corresponding to the spatial location data. Based on the spatial location data of each two target location data, the spatial similarity corresponding to each two target location data is determined. Based on the descriptive text corresponding to the spatial location data of each two target location data, the text similarity corresponding to each two target location data is determined.

[0108] Exemplarily, the spatial location data represents the longitude and latitude information in the target location data, and the description text corresponding to the spatial location data represents the address description information corresponding to the longitude and latitude information in the target location data.

[0109] In a possible implementation, determining the spatial similarity corresponding to each pair of target location data further includes the following steps:

[0110] Step 1: Determine the straight-line distance and spherical distance corresponding to each two target location data based on the latitude and longitude information in each two target location data.

[0111] Illustratively, the latitude and longitude information includes longitude data and latitude data.

[0112] In a possible implementation, according to the longitude and latitude information in each pair of target location data, including the longitude data and the latitude data, the straight-line distance corresponding to each pair of target location data can be calculated by the following formula:

[0113]

[0114] in, is the straight-line distance between the target position data p and the target position data q, and are the longitude data corresponding to the target position data p and the target position data q respectively, and They are the latitude data corresponding to the target position data p and the target position data q respectively.

[0115] The spherical distance corresponding to each two target position data can be calculated by the following formula:

[0116]

[0117] in, is the spherical distance corresponding to the target position data p and the target position data q, is the absolute value of the latitude data difference between the target position data p and the target position data q, is the absolute value of the difference in longitude data between the target position data p and the target position data q, and R is the radius of the earth, which is usually taken as R=6371km.

[0118] Step 2: Determine the spatial similarity between each two target location data based on the linear distance, spherical distance, and cluster radius corresponding to each two target location data;

[0119] The clustering radius is determined based on the physical area type where every two target location data are located and the longitude information of all target location data.

[0120] Exemplarily, the physical area type where every two target location data are located may include an urban area type and a suburban area type. A smaller clustering radius may be set in the urban area, and a larger clustering radius may be set in the suburban area to adapt to the charging pile density distribution in different physical areas.

[0121] In one possible implementation, the cluster radius ∈ can be calculated using the following formula:

[0122]

[0123] Among them, ∈ is the cluster radius, ∈0 is the base radius, σ λ is the standard deviation of the longitude data corresponding to the target location data, and τ is the standard deviation threshold.

[0124] The mixed distance corresponding to each two target position data can be determined based on the straight-line distance and spherical distance corresponding to each two target position data. The calculation formula is as follows:

[0125]

[0126] in, is the mixed distance corresponding to the target position data p and the target position data q, is the straight-line distance between the target position data p and the target position data q, is the spherical distance corresponding to the target position data p and the target position data q.

[0127] The spatial similarity corresponding to each two target location data can be calculated by the following formula:

[0128]

[0129] Among them, S geo (p,q) is the spatial similarity between the target position data p and the target position data q, is the mixed distance corresponding to the target position data p and the target position data q, ω(θ) is the compensation weight, and ∈ is the clustering radius.

[0130] In a possible implementation, determining the text similarity corresponding to each two target location data further includes the following steps:

[0131] Step 1: Determine the address description information corresponding to each two target location data based on the latitude and longitude information in each two target location data.

[0132] For example, a geocoding service may be used to perform position conversion on the longitude and latitude data of the longitude and latitude information of each two target location data to obtain address description information corresponding to each two target location data.

[0133] In a possible implementation, the address description information may include description information at different levels, such as a city level, a road level, and a landmark reference level.

[0134] Step 2: Determine the edit distance corresponding to each pair of target location data according to the address description information corresponding to each pair of target location data.

[0135] Exemplarily, the edit distance is used to indicate the degree of difference between two address description information, and represents the minimum number of operations required to convert one address description information into another.

[0136] In a possible implementation, the edit distance corresponding to each pair of target location data can be calculated through the following formula:

[0137]

[0138] where, ED * (p, q) is the edit distance corresponding to target location data p and target location data q, L p is the address description information corresponding to target location data p, L q is the address description information corresponding to target location data q, δ l (L p ) is the content of the l-th layer after splitting the address description information L p by the preset level m, δ l (L p ) is the content of the l-th layer after splitting the address description information L q by the preset level m, ED(δ l (L p ), δ l (L q ) is the edit distance corresponding to the content of the l-th layer of the address description information corresponding to each pair of target location data, is the level weight, indicating the importance of different levels in address matching.

[0139] Step 3: Determine the text similarity corresponding to each pair of target location data according to the edit distance corresponding to each pair of target location data and the address description information corresponding to each pair of target location data.

[0140] In a possible implementation, the text similarity corresponding to each pair of target location data can be calculated through the following formula:

[0141]

[0142] where, S text (p, q) is the text similarity corresponding to target location data p and target location data q, ED * (p, q) is the edit distance corresponding to target location data p and target location data q, |L p | and |L q | are the address description information Lp and address description information L q When the target position data p and target position data q are exactly the same, ED * (p,q)=0,S text (p,q)=1.

[0143] S220 : Determine a charging map suitable for vehicle charging based on the spatial similarity corresponding to every two target location data, the text similarity corresponding to every two target location data, and the charging data corresponding to the plurality of target location data.

[0144] Exemplarily, the spatial similarity and text similarity corresponding to each two target location data can reflect the similarity between each two target location data. When the similarity is too large, the two target location data can be merged into the same target location data to remove redundant target location data.

[0145] In a possible implementation, a possible implementation of step S220 further includes the following steps:

[0146] S1, determining the similarity and value of the spatial similarity and text similarity corresponding to each two target position data.

[0147] Exemplarily, the spatial similarity and text similarity corresponding to two target location data are added together to obtain the similarity sum value corresponding to every two target location data.

[0148] In a possible implementation, the similarity sum value corresponding to each two target position data can be calculated by the following formula:

[0149] S pq =ξ1·S geo (p,q)+ξ2·S text (p,q)

[0150] Among them, S pq is the similarity sum value corresponding to the target position data p and the target position data q, S geo (p,q) is the spatial similarity between the target position data p and the target position data q, S text (p,q) is the text similarity corresponding to the target position data p and the target position data q, ξ1 and ξ2 are the weight coefficients of spatial similarity and text similarity respectively.

[0151] S2: Determine two target position data whose similarity sum value is greater than a first similarity threshold as the same first target position data.

[0152] Exemplarily, the first similarity threshold is used to indicate the maximum value of the similarity sum corresponding to the two target position data. The similarity sum is compared with the first similarity threshold, and the two target position data with a similarity sum greater than the first similarity threshold are determined to be the same first target position data.

[0153] In a possible implementation, when the similarity sum value is greater than the first similarity threshold, it indicates that the latitude and longitude information of the two target location data are adjacent or consistent, and the address description information of the two target location data is highly consistent, then the two target location data can be determined as the same first target location data.

[0154] For example, if the first similarity threshold is 0.8, and the similarity sum value corresponding to the target position data p1 and the target position data q1 is 0.9, which is greater than the first similarity threshold 0.8, then the target position data p1 and the target position data q1 can be determined to be the same first target position data x1.

[0155] S3: Determine two target position data whose similarity sum value is less than or equal to a first similarity threshold as different second target position data.

[0156] Exemplarily, the similarity sum is compared with a first similarity threshold, and two target position data whose similarity sum is less than or equal to the first similarity threshold are determined as different second target position data.

[0157] In one possible implementation, when the similarity sum value is less than or equal to the first similarity threshold, it indicates that the longitude and latitude information of the two target location data are significantly different, and the address description information of the two target location data is inconsistent, then the two target location data can be determined as different second target location data.

[0158] For example, if the first similarity threshold is 0.8, and the similarity sum value corresponding to the target position data p2 and the target position data q2 is 0.7, which is less than the first similarity threshold 0.8, then the target position data p2 and the target position data q2 can be determined as different second target position data y1 and y2.

[0159] S4 , determining a charging map suitable for vehicle charging based on all the first target location data, all the second target location data, the charging data corresponding to all the first target location data, and the charging data corresponding to all the second target location data.

[0160] In one possible implementation, the longitude and latitude coordinates corresponding to all the first target location data and all the second target location data can be determined based on the longitude and latitude information in all the first target location data and all the second target location data. The charging data corresponding to all the first target location data and all the second target location data can be determined based on the charging data corresponding to all the longitude and latitude coordinates. All the longitude and latitude coordinates and all the charging data can be marked on the map to obtain a charging map suitable for vehicle charging.

[0161] In a possible implementation, a possible implementation of step S4 further includes the following steps:

[0162] Step 1: Determine the locations of multiple charging piles in the charging map based on all first target location data and all second target location data.

[0163] For example, based on the longitude and latitude information in all the first target location data and all the second target location data, the longitude and latitude coordinates corresponding to all the first target location data and all the second target location data can be determined. By using all the longitude and latitude coordinates as the longitude and latitude coordinates of multiple charging piles in the charging map, the positions of multiple charging piles in the charging map can be determined.

[0164] Step 2: Determine the maximum power data of multiple charging piles in the charging map and the type of historical charging vehicles corresponding to each maximum power data based on the charging data corresponding to all the first target location data and the charging data corresponding to all the second target location data.

[0165] Exemplarily, the charging data corresponding to the target location data includes maximum power data, and the target location data carries a vehicle type identifier.

[0166] In a possible implementation, the maximum power data in the charging data corresponding to all the first target location data and the maximum power data in the charging data corresponding to all the second target location data are respectively used as the maximum power data of multiple charging piles in the charging map.

[0167] According to the vehicle type identifiers carried in all the first target location data and all the second target location data, determine the types of historical charging vehicles corresponding to the maximum power data in the charging data corresponding to all the first target location data and the charging data corresponding to all the second target location data, and use the types of historical charging vehicles corresponding to the maximum power data in all the charging data as the types of historical charging vehicles corresponding to each maximum power data in multiple charging piles in the charging map.

[0168] The method for determining a charging map provided in an embodiment of the present application first determines the spatial similarity corresponding to each two target location data and the text similarity corresponding to each two target location data, and then determines a charging map suitable for vehicle charging based on the spatial similarity corresponding to each two target location data, the text similarity corresponding to each two target location data, and the charging data corresponding to multiple target location data. In this embodiment, by analyzing the spatial distribution of the target location data and determining the spatial similarity corresponding to each two target location data, target location data with similarity in spatial distribution can be effectively determined. By determining the text similarity corresponding to each two target location data, the text similarity corresponding to the address description information in the target location data can be effectively analyzed, thereby determining the similarity of the geographical location characteristics or geographical location attributes of each two target location data. By combining the spatial similarity corresponding to each two target location data and the text similarity corresponding to each two target location data, multiple target location data can be optimized, and two target location data with excessive spatial similarity and text similarity can be merged into one target location data, thereby avoiding the redundancy of target location data caused by differences in spatial distribution and differences in the expression of address description information, thereby determining a charging map suitable for vehicle charging. Moreover, by combining the charging data (such as charging power) corresponding to the multiple target location data, the charging data can be identified on the charging map, so that the vehicle can efficiently select a suitable charging pile in the charging map based on the identified charging data, thereby improving the charging efficiency of the vehicle and avoiding unstable charging or charging failure of the vehicle due to inappropriate charging data.

[0169] Based on the above embodiments, Figure 3 Schematic diagram of the process of determining the charging map provided in the embodiment of the present application Figure 3 .like Figure 3 As shown, a possible implementation of the above step S120 further includes the following steps:

[0170] S310 . For a plurality of charging status information, remove the charging status information whose time data is less than the charging duration to obtain a plurality of first charging status information.

[0171] In this step, for multiple charging status information, the time data in the multiple charging status information are compared with the charging duration, and the charging status information corresponding to the time data less than the charging duration is removed to obtain the first charging status information with multiple time data greater than or equal to the charging duration.

[0172] In one possible implementation, the charging status information of each historically charged vehicle includes multiple charging statuses corresponding to multiple time points within a preset time period. The time data of the historically charged vehicle in the charging status, that is, the time interval during which the historically charged vehicle was in the charging status, can be determined based on the multiple charging statuses corresponding to multiple time points within the preset time period.

[0173] According to the start time and end time of the time interval, the difference between the end time and the start time is calculated to determine the duration corresponding to the time interval. The duration is compared with the charging duration, and the charging status information whose duration corresponding to the time interval is less than the charging duration is removed.

[0174] S320 , for the plurality of first charging status information, remove the first charging status information whose position data is outside the charging position error to obtain a plurality of second charging status information.

[0175] In this step, for multiple first charging status information, the position data in the multiple first charging status information are compared with the charging position error, and the first charging status information whose position data is outside the charging position error is removed to obtain multiple second charging status information whose position data is within the charging position error.

[0176] In one possible implementation, the location data in the charging status information of each historical charging vehicle includes longitude data and latitude data corresponding to multiple time points within a preset time period. The standard deviation of the longitude data and the standard deviation of the latitude data can be calculated respectively based on the longitude data and latitude data corresponding to the multiple time points included in the location data in the first charging status information, and the standard deviation of the longitude data is compared with the longitude error of the charging position, and the standard deviation of the latitude data is compared with the latitude error of the charging position. The first charging status information corresponding to the location data whose standard deviation of the longitude data is greater than the longitude error of the charging position and whose standard deviation of the latitude data is greater than the latitude error of the charging position are removed, so as to avoid errors in the location data caused by the movement of historical charging vehicles or drift of positioning signals, and ensure the reliability of the data.

[0177] For example, the longitude data sequence corresponding to the multiple time points included in the location data in the first charging status information is {lng1, lng2, ..., lng n}, the latitude data sequence is {lat1,lat2,…,lat n}, n represents the number of time points included in the location data in the first charging status information, then the standard deviation of the longitude data and the standard deviation of the latitude data can be calculated as follows:

[0178]

[0179] Among them, σ lng is the standard deviation of the longitude data, μ lngis the mean value of the longitude data, σ lat is the standard deviation of the latitude data, μ lat is the average value of the latitude data.

[0180] S330: Determine the position data in the plurality of second charging status information as a plurality of target position data.

[0181] In this step, the location data in the multiple second charging status information can accurately indicate the location where the historical charging vehicle is in the charging state. In order to accurately indicate the location where the vehicle can be charged, the location data in the multiple second charging status information is determined as multiple target location data.

[0182] In a possible implementation, the longitude data and latitude data corresponding to multiple time points included in the location data in the second charging status information may be deduplicated to obtain representative longitude data and representative latitude data of the location data in the second charging status information.

[0183] For example, the position data sequence in the second charging state information is {(λ j ,φ j )|j=1,…,m}, where m is the number of time points included in the position data, and the representative longitude data of the position data in the second charging state information can be obtained by using the deduplication operator Γ. and represents latitude data

[0184] In addition, a geocoding service may be used to perform position conversion on the representative longitude data and the representative latitude data of the location data in the second charging status information to obtain address description information corresponding to the location data in the second charging status information.

[0185] The method for determining a charging map provided in an embodiment of the present application first removes charging status information with time data less than the charging duration from multiple charging status information to obtain multiple first charging status information. Then, from the multiple first charging status information, removes first charging status information with location data outside the charging location error to obtain multiple second charging status information. Finally, the location data in the multiple second charging status information is determined as multiple target location data. In this embodiment, by removing charging status information with time data less than the preset charging duration, multiple first charging status information with longer charging durations are retained, thereby improving data accuracy, avoiding invalid or inaccurate charging status information due to insufficient charging duration, and improving the quality of the charging status information. By removing first charging status information with location data outside the charging location error, the accuracy of the location data is ensured, avoiding inaccurate location data due to excessively large charging location errors, and improving the quality of the charging status information. The time data and location data in the obtained multiple second charging status information are accurate and reliable. By determining the location data in the multiple second charging status information as multiple target location data, accurate target locations are provided, providing reliable data support for the subsequent determination of a charging map suitable for vehicle charging.

[0186] On the basis of the above embodiments, the following is a device for determining a charging map provided in an embodiment of the present application, which can execute the method provided in the above method embodiment.

[0187] Figure 4 This is a schematic diagram of the structure of the device for determining the charging map provided in the embodiment of the present application. Figure 4 As shown, the charging map determination device 400 includes:

[0188] An acquisition module 410 is configured to acquire charging status information corresponding to a plurality of historically charged vehicles, wherein the charging status information of each historically charged vehicle indicates time data, location data, and charging data during which the historically charged vehicle was in a charging state within a preset time period.

[0189] A filtering module 420 is configured to filter the plurality of charging status information according to a preset filtering condition to obtain a plurality of target location data, wherein the filtering condition is determined based on a preset charging duration and a preset charging location error;

[0190] The determination module 430 is configured to determine a charging map suitable for vehicle charging based on the plurality of target location data and the charging data corresponding to the plurality of target location data.

[0191] In one or more embodiments, the determination module 430 is specifically configured to:

[0192] Determine the spatial similarity corresponding to each two target position data and the text similarity corresponding to each two target position data;

[0193] A charging map suitable for vehicle charging is determined based on the spatial similarity corresponding to every two target location data, the text similarity corresponding to every two target location data, and the charging data corresponding to the plurality of target location data.

[0194] In one or more embodiments, a charging map suitable for vehicle charging is determined based on the spatial similarity corresponding to each two target location data, the textual similarity corresponding to each two target location data, and the charging data corresponding to the plurality of target location data. The determination module 430 is specifically configured to:

[0195] Determine the similarity and value of the spatial similarity and text similarity corresponding to each two target position data;

[0196] Determine two target position data whose similarity sum value is greater than a first similarity threshold as the same first target position data;

[0197] determining two target position data whose similarity sum value is less than or equal to a first similarity threshold as different second target position data;

[0198] A charging map suitable for vehicle charging is determined based on all first target location data, all second target location data, charging data corresponding to all first target location data, and charging data corresponding to all second target location data.

[0199] In one or more embodiments, the spatial similarity corresponding to each two target location data is determined by the determination module 430, specifically configured to:

[0200] Determine the linear distance and spherical distance corresponding to each two target position data based on the latitude and longitude information in each two target position data;

[0201] The spatial similarity corresponding to each two target location data is determined based on the straight-line distance and spherical distance corresponding to each two target location data, as well as the clustering radius, wherein the clustering radius is determined based on the physical area type where each two target location data are located and the longitude information in all target location data.

[0202] In one or more embodiments, to determine the text similarity between each two target location data, the determination module 430 is specifically configured to:

[0203] Determine the address description information corresponding to each two target location data according to the latitude and longitude information in each two target location data;

[0204] Determine the edit distance between each two target location data according to the address description information corresponding to each two target location data;

[0205] The text similarity corresponding to each two target location data is determined according to the edit distance corresponding to each two target location data and the address description information corresponding to each two target location data.

[0206] In one or more embodiments, determining a charging map suitable for vehicle charging based on all first target location data, all second target location data, charging data corresponding to all first target location data, and charging data corresponding to all second target location data, the determining module 430 is specifically configured to:

[0207] Determining the locations of multiple charging piles in the charging map based on all the first target location data and all the second target location data;

[0208] According to the charging data corresponding to all the first target location data and the charging data corresponding to all the second target location data, the maximum power data of multiple charging piles in the charging map and the type of historical charging vehicles corresponding to each maximum power data are determined.

[0209] In one or more embodiments, the filtering module 420 is specifically configured to:

[0210] For the plurality of charging status information, removing the charging status information whose time data is less than the charging duration, to obtain a plurality of first charging status information;

[0211] For the plurality of first charging status information, removing the first charging status information whose position data is outside the charging position error, to obtain a plurality of second charging status information;

[0212] The position data in the plurality of second charging state information are determined as a plurality of target position data.

[0213] Based on the above embodiments, Figure 5 This is a schematic diagram of the structure of the electronic device provided in the embodiment of the present application. Figure 5 As shown, the electronic device 500 includes: a processor 510, a memory 520 and a bus 530;

[0214] The memory 520 is used to store computer-executable instructions of the processor 510;

[0215] The processor 510 is configured to execute the technical solution of any of the aforementioned method embodiments by executing computer execution instructions.

[0216] Optionally, the memory 520 may be independent or integrated with the processor 510 .

[0217] Optionally, the memory 520 may include a random access memory (RAM), and may also include a non-volatile memory (NVM), such as at least one disk memory.

[0218] Bus 530 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. Buses can be classified as address buses, data buses, control buses, etc. For ease of illustration, only one thick line is used in the drawings of this application, but this does not mean that there is only one bus or only one type of bus.

[0219] The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, and discrete hardware components.

[0220] The electronic device is used to execute the technical solution of any of the aforementioned method embodiments, and its implementation principle and technical effects are similar and will not be repeated here.

[0221] An embodiment of the present application also provides a computer-readable storage medium on which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the technical solution provided by any of the above method embodiments.

[0222] An embodiment of the present application also provides a computer program product, including a computer program, which includes computer instructions stored in a computer-readable storage medium. When the computer program is executed by a processor, it is used to implement the technical solution provided by any of the above method embodiments.

[0223] It should be noted that for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in this specification are all optional embodiments, and the actions and modules involved are not necessarily required by this application.

[0224] It should be further noted that, although the various steps in the flowchart are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps may be performed in other orders. Moreover, at least a portion of the steps in the flowchart may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily performed at the same time, but may be performed at different times. The execution order of these sub-steps or stages is not necessarily to be performed in sequence, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0225] It should be understood that the above-described device embodiments are merely illustrative, and the device of the present application may also be implemented in other ways. For example, the division of units / modules in the above-described embodiments is merely a logical functional division, and actual implementations may employ other division methods. For example, multiple units, modules, or components may be combined or integrated into another system, or some features may be omitted or not implemented.

[0226] In addition, unless otherwise specified, the functional units / modules in the various embodiments of the present application may be integrated into a single unit / module, each unit / module may exist physically separately, or two or more units / modules may be integrated together. The aforementioned integrated units / modules may be implemented in the form of hardware or software program modules.

[0227] If the integrated unit / module is implemented in hardware, the hardware may be digital circuits, analog circuits, etc. The physical implementation of the hardware structure includes, but is not limited to, transistors, memristors, etc. Unless otherwise specified, the processor may be any appropriate hardware processor, such as a CPU, GPU, FPGA, DSP, and ASIC. Unless otherwise specified, the storage unit may be any appropriate magnetic storage medium or magneto-optical storage medium, such as resistive random access memory (RRAM), dynamic random access memory (DRAM), static random access memory (SRAM), enhanced dynamic random access memory (EDRAM), high-bandwidth memory (HBM), hybrid memory cube (HMC), etc.

[0228] If the integrated unit / module is implemented in the form of a software program module and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes a number of instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes various media that can store program codes, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0229] In the above embodiments, the description of each embodiment has its own emphasis. For parts not described in detail in a particular embodiment, please refer to the relevant description of other embodiments. The technical features of the above embodiments can be combined in any way. To keep the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0230] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present invention that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, and the true scope and spirit of the present application are indicated by the following claims.

[0231] It should be understood that the present application is not limited to the exact structure described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for determining a charging map, characterized in that: include: Obtaining charging status information corresponding to a plurality of historically charged vehicles, wherein the charging status information of each historically charged vehicle indicates time data, location data, and charging data of the historically charged vehicle in the charging state within a preset time period; Filtering the plurality of charging status information according to a preset filtering condition to obtain a plurality of target position data, wherein the filtering condition is determined based on a preset charging duration and a preset charging position error; A charging map suitable for vehicle charging is determined based on the plurality of target location data and the charging data corresponding to the plurality of target location data.

2. The method according to claim 1, characterized in that The determining, based on the plurality of target location data and the charging data corresponding to the plurality of target location data, a charging map suitable for vehicle charging includes: Determine the spatial similarity corresponding to each two target position data and the text similarity corresponding to each two target position data; A charging map suitable for vehicle charging is determined according to the spatial similarity corresponding to every two target location data, the text similarity corresponding to every two target location data, and the charging data corresponding to the plurality of target location data.

3. The method according to claim 2, characterized in that The determining of a charging map suitable for vehicle charging based on the spatial similarity corresponding to each two target location data, the text similarity corresponding to each two target location data, and the charging data corresponding to the plurality of target location data includes: Determine the similarity and value of the spatial similarity and text similarity corresponding to each two target position data; Determine two target position data whose similarity sum value is greater than a first similarity threshold as the same first target position data; determining two target position data whose similarity sum value is less than or equal to the first similarity threshold as different second target position data; A charging map suitable for vehicle charging is determined based on all first target location data, all second target location data, charging data corresponding to all first target location data, and charging data corresponding to all second target location data.

4. The method according to claim 2, characterized in that Determining the spatial similarity corresponding to each two target position data includes: Determine the linear distance and spherical distance corresponding to each two target position data based on the latitude and longitude information in each two target position data; The spatial similarity corresponding to each two target location data is determined based on the straight-line distance and spherical distance corresponding to each two target location data, as well as the clustering radius, wherein the clustering radius is determined based on the physical area type in which each two target location data are located and the longitude information in all target location data.

5. The method according to claim 2, characterized in that Determining the text similarity corresponding to each two target position data includes: Determine the address description information corresponding to each two target location data according to the latitude and longitude information in each two target location data; Determine the edit distance between each two target location data according to the address description information corresponding to each two target location data; The text similarity corresponding to each two target location data is determined according to the edit distance corresponding to each two target location data and the address description information corresponding to each two target location data.

6. The method according to claim 3, characterized in that The determining of a charging map suitable for vehicle charging based on all first target location data, all second target location data, charging data corresponding to all first target location data, and charging data corresponding to all second target location data includes: Determining the locations of a plurality of charging piles in the charging map according to all the first target location data and all the second target location data; According to the charging data corresponding to all the first target location data and the charging data corresponding to all the second target location data, the maximum power data of the plurality of charging piles in the charging map and the type of historical charging vehicle corresponding to each maximum power data are determined.

7. The method according to any one of claims 1 to 6, characterized in that The filtering of the plurality of charging status information according to the preset filtering conditions to obtain a plurality of target location data includes: For the plurality of charging status information, removing the charging status information whose time data is less than the charging duration, to obtain a plurality of first charging status information; For the plurality of first charging status information, removing the first charging status information whose position data is outside the charging position error, to obtain a plurality of second charging status information; The position data in the plurality of second charging state information are determined as the plurality of target position data.

8. A device for determining a charging map, characterized in that: include: An acquisition module is configured to acquire charging status information corresponding to a plurality of historically charged vehicles, wherein the charging status information of each historically charged vehicle indicates time data, location data, and charging data of the historically charged vehicle during a preset time period when the vehicle was in a charging state; a filtering module, configured to filter the plurality of charging status information according to a preset filtering condition to obtain a plurality of target position data, wherein the filtering condition is determined based on a preset charging duration and a preset charging position error; The determining module is configured to determine a charging map suitable for vehicle charging based on the plurality of target location data and the charging data corresponding to the plurality of target location data.

9. An electronic device, characterized in that: include: Memory, processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor performs the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 7 when executed by a processor.

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