Charging path planning method and device, equipment and medium

Abstract

The invention relates to a charging path planning method and device, equipment and a medium. The method comprises the following steps: determining an energy supplementing starting point of a vehicle; based on the energy complementing starting point, an energy complementing terminal point is determined according to driving information and battery information of the vehicle; under the condition that the energy complementing end point does not exceed the destination of the vehicle, based on a preset first position code of a charging station, screening a charging station group located on a segmented route between the energy complementing end point and the energy complementing starting point; taking the position of each candidate charging station in the charging station group as a new energy complementing starting point, and returning to the step of determining an energy complementing terminal point based on the energy complementing starting point according to the driving information and the battery information of the vehicle; if the complement end point exceeds the destination of the vehicle, a target complement path is generated based on a plurality of candidate charging stations in the group of charging stations. According to the invention, the planning efficiency and accuracy of the charging path can be improved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of new energy vehicles, and particularly to a charging path planning method, device, equipment and medium. Background Art

[0002] Intelligent charging path planning refers to using some information technologies and algorithms to plan the optimal charging route for devices such as electric vehicles that need to be regularly charged. Most traditional intelligent charging path planning methods calculate by traversing charging stations one by one. This method takes a long time and occupies a lot of computing resources, and cannot meet the requirement of quickly responding to users. At the same time, the distribution and service information of traditional charging stations is not transparent enough to provide data related to charging stations. In the case of lack of charging station data, the planned charging path is inaccurate and may not be the optimal choice for users, resulting in a poor charging experience for users. Summary of the Invention

[0003] To solve the above technical problems, the present disclosure provides a charging path planning method, device, equipment and medium.

[0004] According to one aspect of the present disclosure, there is provided a charging path planning method, including:

[0005] Determine the charging start point of the vehicle; wherein, the charging start point includes: the current position of the vehicle when a charging request is received;

[0006] Based on the charging start point, determine the charging end point according to the driving information and battery information of the vehicle; wherein, the charging end point is the position that the vehicle can reach when the remaining power is lower than a preset power threshold;

[0007] In the case that the charging end point does not exceed the destination of the vehicle, based on the first position code preset for the charging station, screen the charging station group located on the segmented route between the charging end point and the charging start point;

[0008] Take the position of each candidate charging station in the charging station group as a new charging start point respectively, and return to the step of determining the charging end point based on the charging start point according to the driving information and battery information of the vehicle;

[0009] In the case that the charging end point exceeds the destination of the vehicle, generate a target charging path based on the multiple candidate charging stations in the charging station group.

[0010] According to another aspect of the present disclosure, there is also provided a charging path planning device, including:

[0011] A charging start point determination module, configured to determine the charging start point of the vehicle; wherein, the charging start point includes: the current position of the vehicle when a charging request is received;

[0012] The charging end determination module is used to determine the charging end based on the charging start point according to the driving information and battery information of the vehicle, where the charging end is the position that the vehicle can reach when the remaining power is lower than a preset power threshold;

[0013] The charging station screening module is used to screen a group of charging stations located on the segmented route between the charging end and the charging start point based on the first position code preset for the charging station when the charging end does not exceed the destination of the vehicle;

[0014] The repeated execution module is used to take the position of each candidate charging station in the group of charging stations as a new charging start point respectively, and return to the steps executed by the charging end determination module;

[0015] The path generation module is used to generate a target charging path based on multiple candidate charging stations in the group of charging stations when the charging end exceeds the destination of the vehicle.

[0016] According to another aspect of the present disclosure, there is also provided an electronic device, which includes:

[0017] A processor;

[0018] A memory for storing executable instructions of the processor;

[0019] The processor is used to read the executable instructions from the memory and execute the instructions to implement the above method.

[0020] According to another aspect of the present disclosure, there is also provided a computer-readable storage medium, which stores a computer program for executing the above method.

[0021] The technical solution provided by the embodiments of the present disclosure has the following advantages compared with the prior art:

[0022] The technical solution provided by the embodiments of the present disclosure includes: First, determine the charging start point of the vehicle; Based on the charging start point, determine the charging end according to the driving information and battery information of the vehicle; When the charging end does not exceed the destination of the vehicle, screen a group of charging stations located on the segmented route between the charging end and the charging start point based on the first position code preset for the charging station; Then, take the position of each candidate charging station in the group of charging stations as a new charging start point respectively, and return to the step of determining the charging end based on the charging start point, according to the driving information and battery information of the vehicle; When the charging end exceeds the destination of the vehicle, generate a target charging path based on multiple candidate charging stations in the group of charging stations.

[0023] This technical solution utilizes the first - position coding of charging stations to quickly obtain the charging stations along each segmented route, effectively improving the efficiency of searching for charging stations. Then, a large problem of searching for charging stations on a complete navigation route is decomposed into multiple small problems of searching for charging stations on segmented routes, reducing the complexity of searching for charging stations and path planning. Specifically, during the process of determining the charging start point, the charging end point, and the charging - station group on the segmented route between the two, a recursive strategy is used. Each recursive process can screen out the optimal candidate charging stations. When the charging end point exceeds the destination, multiple segmented charging routes are continuously expanded through the recursive process, and each segmented route corresponds to a charging - station group. Since the candidate charging stations in the charging - station group of each segmented route are the optimal charging stations determined through the recursive strategy, the target charging path generated based on these optimal candidate charging stations is the global optimal solution, with higher accuracy. Furthermore, based on the accurate candidate charging stations in the charging - station group, the optimal target charging path can be screened out, which helps to improve the user's charging experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The accompanying drawings herein are incorporated into and constitute a part of this specification, showing embodiments consistent with the present disclosure and, together with the specification, are used to explain the principles of the present disclosure.

[0025] To more clearly illustrate the technical solutions in the embodiments of the present disclosure or in the prior art, the following will briefly introduce the accompanying drawings required for use in the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0026] Figure 1 It is a flowchart of the charging - path planning method according to the embodiment of the present disclosure;

[0027] Figure 2 It is a schematic diagram of the navigation route according to the embodiment of the present disclosure;

[0028] Figure 3 It is a block diagram of the structure of the charging - path planning device according to the embodiment of the present disclosure;

[0029] Figure 4 It is a schematic diagram of the structure of the electronic device according to the embodiment of the present disclosure. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0030] In order to better understand the above - mentioned objects, features, and advantages of the present disclosure, the following will further describe the solutions of the present disclosure. It should be noted that, without conflict, the embodiments of the present disclosure and the features in the embodiments can be combined with each other.

[0031] In the following description, numerous specific details are set forth to provide a thorough understanding of the present disclosure, but the present disclosure may be practiced in other ways different from those described herein; obviously, the embodiments in the specification are only a part of the embodiments of the present disclosure, rather than all of the embodiments.

[0032] To efficiently and accurately plan a charging path for a user, an embodiment of the present disclosure provides a charging path planning method, apparatus, device, and medium. This solution uses the first position coding of charging stations to quickly obtain the charging stations along each segmented route, effectively improving the efficiency of searching for charging stations; during the process of determining the charging start point, the charging end point, and the charging station group on the segmented route between the two, a recursive strategy is used to screen out the optimal candidate charging stations on each segmented route, and then the optimal target charging path is screened from the accurate candidate charging stations in the charging station groups of multiple segmented routes. Therefore, the target charging path generated based on these optimal candidate charging stations will be more accurate.

[0033] Figure 1 As shown in the flowchart of a charging path planning method provided by an embodiment of the present disclosure, this method can be executed by a charging path planning device configured on the vehicle side, and this device can be implemented by software and / or hardware. As Figure 1 shown, the charging path planning method may include the following steps S102 to S110.

[0034] S102, determine the charging start point of the vehicle; wherein, the charging start point includes but is not limited to: the current position of the vehicle when a charging request is received.

[0035] In some embodiments, a charging request may be actively initiated by a user operation, or, a charging request may be automatically initiated when the remaining power of the vehicle's battery is lower than a specified power; the above-mentioned charging request is used to indicate the start of planning a charging path.

[0036] When a charging request is received, obtain the current position of the vehicle, use the current position as the charging start point for planning the charging path, and first execute the charging prediction algorithms described in subsequent steps S104 and S106 based on this charging start point.

[0037] The charging prediction algorithm described in subsequent steps S104 and S106 is used to predict candidate charging stations that the vehicle can reach before the remaining power of the vehicle battery is consumed to be lower than a preset power threshold. The charging prediction algorithm is executed recursively at least once; when the charging prediction algorithm is executed for the first time, the current position of the vehicle when the charging request is received is used as the charging starting point; when the charging prediction algorithm is not executed for the first time, the position of the candidate charging station determined by the previous execution of the charging prediction algorithm is used as the charging starting point for the current execution of the charging prediction algorithm, that is, the charging starting point can include: the current position of the vehicle when the charging request is received, or the position of the candidate charging station determined during the execution of the charging prediction algorithm. And so on, the charging prediction algorithm described in steps S104 and S106 is executed multiple times until the predicted charging end point reaches or exceeds the vehicle's destination and then stops.

[0038] S104. Based on the charging starting point, determine the charging end point according to the driving information and battery information of the vehicle; wherein, the charging end point is the position that the vehicle can reach when the remaining power is lower than the preset power threshold.

[0039] In this embodiment, the driving information and battery information of the vehicle can be obtained first. Among them, the driving information can include, for example: the driving speed of the vehicle, the vehicle weight, the remaining navigation mileage, etc.; the battery information can include, for example: the battery capacity, the current remaining power of the battery, the temperature and humidity of the environment where the battery is currently located, etc.

[0040] For information such as the driving speed in the driving information, the remaining power in the battery information, and the temperature and humidity of the environment, they may change with the change of the charging starting point. Therefore, an example method for determining the above information is provided as follows.

[0041] When a charging request is initiated, that is, when the charging prediction algorithm is executed for the first time, the current driving information and battery information of the vehicle can be directly obtained through the in-vehicle system. When the charging prediction algorithm is not executed for the first time, the driving information of the vehicle can be estimated according to information such as the user's historical driving habits and the road congestion conditions of a section of the road before and after the charging starting point. Since the charging starting point is the position of the candidate charging station determined by the previous execution of the charging prediction algorithm, it can be considered that the battery is fully charged at the candidate charging station when the vehicle is at the charging starting point, so the current remaining power of the battery is determined to be 100%. And the temperature and humidity of the environment where the battery is located can be updated according to the weather forecast at the charging starting point.

[0042] After obtaining the driving information and battery information of the vehicle, through an energy consumption prediction algorithm based on machine learning, the charging end point that the vehicle can reach when the remaining power is lower than the preset power threshold can be determined according to the driving information and battery information of the vehicle. The above power threshold is, for example, 0, n% of the total battery capacity, etc.

[0043] The above charging end point is the position that the vehicle is predicted to reach before the battery runs out. The charging end point may not have reached the destination yet, so it is necessary to continue to execute the next round of charging prediction algorithm and determine the next new charging end point until the new charging end point reaches or exceeds the destination.

[0044] S106. When the charging end point does not exceed the destination of the vehicle, based on the first position code preset for the charging station, search for a group of charging stations on the segmented route between the charging end point and the charging start point.

[0045] The charging end point not exceeding the destination of the vehicle means that the battery energy of the vehicle is not sufficient to support the vehicle to drive to the destination and further charging is required. In this case, refer to this step S106 to search for a group of chargers that can charge on the segmented route between the charging end point and the charging start point.

[0046] By determining the charging start point and the charging end point of the vehicle, this embodiment can decompose a complete navigation route of the vehicle from the departure place to the destination into multiple segmented routes from the charging start point to the charging end point. Furthermore, a big problem of searching for charging stations on the complete navigation route is decomposed into multiple small problems of searching for charging stations on the segmented routes. And for each segmented route, the same method is used to search for charging stations. This method can reduce the route distance of searching for charging stations, effectively reduce the complexity of searching for charging stations, and improve the search efficiency.

[0047] In this embodiment, on the segmented route between the charging end point and the charging start point, based on the first position code preset for the charging station and the second position codes of multiple path points on the segmented route, starting from the charging end point, search for a group of charging stations along the way in the direction of the charging start point. Based on this, the implementation process of this step S106 can refer to the following steps (A1) and (A2).

[0048] (A1) Based on the first position code preset for the charging station, search for multiple initial charging stations on the segmented route between the charging end point and the charging start point.

[0049] In one embodiment, first, obtain the second position codes of multiple path points on the segmented route between the charging end point and the charging start point; secondly, perform a consistency comparison between the first position code preset for the charging station and the second position codes of the multiple path points; wherein, both the first position code and the second position code are based on a preset string of codes; then, determine the charging stations corresponding to the first position codes that are consistent with the second position codes as the initial charging stations on the segmented route between the charging end point and the charging start point.

[0050] The first location code of the charging station and the second location code of the waypoint can be strings based on a preset code such as GeoHash. Taking GeoHash as an example of the preset code, GeoHash is a method of geographical location coding. It can convert two-dimensional longitude and latitude coordinate points into a one-dimensional string, that is, the code. A certain string represents a certain rectangular area, which means that all longitude and latitude points in this rectangular area share a set of codes. The string based on GeoHash coding facilitates faster geographical spatial retrieval during retrieval to find locations that are close in distance.

[0051] In this embodiment, the locations of all charging stations are saved as strings through preset coding, that is, the first location code. On the segmented route between the charging end point and the charging start point, multiple waypoints are set at preset intervals (such as 3 meters). The locations of all waypoints are also saved as strings through preset coding, that is, the second location code. In this embodiment, when the user initiates a navigation behavior, the waypoints on the navigation route can be encoded as the second location code online. This second location code can be used not only for navigation but also in the process of searching for charging stations and other planning of charging paths.

[0052] Since both the first location code of the charging station and the second location code of the waypoint are strings, in this embodiment, the first location code and the second location code are compared for consistency, which is essentially string matching. Obviously, the string matching efficiency is extremely high, and it can quickly determine the mutually matching strings, that is, determine the first location code and the second location code that are compared and consistent. The comparison being consistent indicates that the corresponding charging station and waypoint are located in the same geographical area. Furthermore, the charging station corresponding to the first location code that is compared and consistent with the second location code is determined as the initial charging station along the segmented route between the charging end point and the charging start point.

[0053] Compared with the existing method of traversing charging stations one by one, this method of string matching in this embodiment can quickly obtain the initial charging stations on the segmented route between the charging end point and the charging start point, effectively improving the efficiency of searching for charging stations.

[0054] (A2) Screen the initial charging stations according to the preset charging preference information, and form a charging station group with at least one candidate charging station selected; wherein, the above-mentioned charging preference information includes: distance, charging cost, and / or charging speed.

[0055] After this embodiment searches for multiple initial charging stations on the segmented route between the charging end point and the charging start point, it can obtain the user's charging preference information and the information of each initial charging station. The above-mentioned charging preference information is used to represent the information that the user pays more attention to during charging. For example, some users care about the distance of the charging station, and some users care about the charging speed and charging cost of the charging station.

[0056] In some examples, the charging preference information may include: distance. This distance can be understood as the distance between the charging station and the current position of the vehicle, or the distance between the charging station and the nearest intersection on the vehicle's navigation route where the vehicle can enter the charging station.

[0057] The charging preference information may include: charging cost. The charging cost is the cost per degree of electricity. The charging cost varies due to various factors, mainly including region, electricity quantity, charging equipment type, charging subsidy policy, etc.

[0058] The charging preference information may include: charging speed. Generally, the charging speed of a home charging pile is slow, and the corresponding charging cost will be low. The charging speed of a public fast charging pile is fast, and the corresponding charging cost will be high.

[0059] Obtain the information of each initial charging station, such as the location of the charging station, charging speed, charging pile type, charging cost, charging waiting time, weather conditions at the location of the charging station, etc.

[0060] According to the user's charging preference information and the information of each initial charging station, screen the initial charging stations to obtain the top N (e.g., N = 3) charging stations that best meet the user's preferences, and use these selected charging stations as candidate charging stations to form a charging station group.

[0061] In this embodiment, screening the initial charging stations according to the user's charging preference information can optimize the charging station group that meets the user's preferences and better meet the user's needs.

[0062] Through the above steps S104 and S106, a charging prediction algorithm is completed. By executing a charging prediction algorithm, a segmented route can be determined and an optimized charging station group that meets the user's preferences on this segmented route can be searched. Then, referring to the following step S108, the next charging prediction algorithm is continued to be executed.

[0063] S108, use the location of each candidate charging station in the charging station group as a new charging start point respectively, and return to the step of S104 above; which is equivalent to executing the charging prediction algorithm again based on the new charging start point.

[0064] Refer to Figure 2 As shown, take the example that the charging station group includes two candidate charging stations. Assume that the i-th execution of the charging prediction algorithm determines the charging end point i, and the charging station group on the segmented route between the charging end point i and the charging start point i includes candidate charging station a1 and candidate charging station b1. In this case, use candidate charging station a1 and candidate charging station b1 as new charging start points respectively, and return to step S104, that is, execute the charging prediction algorithm again.

[0065] S110. When the charging end point exceeds the destination of the vehicle, generate a target charging path based on multiple candidate charging stations in the charging station group.

[0066] Specifically, in this embodiment, the charging prediction algorithm is repeatedly executed until the charging end point exceeds the destination of the vehicle and then stops, and a target charging path is generated based on multiple candidate charging stations in the charging station group.

[0067] Exemplarily, take candidate charging station a1 as the new charging start point, and execute the charging prediction algorithm again to determine the charging end point i + 1 corresponding to the charging start point a1. This charging end point i + 1 has exceeded the destination of the vehicle, so the execution of the charging prediction algorithm is stopped.

[0068] Take candidate charging station b1 as the new charging start point, and execute the charging prediction algorithm again to determine the charging end point i + 1 corresponding to the charging start point b1. This charging end point i + 1 has not reached the destination of the vehicle, so the charging prediction algorithm is executed again.

[0069] In a specific embodiment, considering that when the charging prediction algorithm is executed for the i-th time, among the multiple charging end points predicted by multiple different charging start points, some charging end points may reach the destination, while some other charging end points have not reached the destination. In this case, the charging prediction algorithm can be continued to be executed until there are no charging end points that have not reached the destination and then stop.

[0070] Regarding the above step S110, generating a target charging path based on candidate charging stations in multiple charging station groups may include: before the charging end point exceeds the destination of the vehicle, obtain multiple charging station groups; it can be understood that multiple charging station groups are obtained by executing the charging prediction algorithm multiple times. Perform path planning on the candidate charging stations in the multiple charging station groups to generate a target charging path.

[0071] In this embodiment, when the charging prediction algorithm is executed for the current i-th time, a corresponding charging station group i will be obtained. Each candidate charging station in this charging station group i will expand the charging station group i + 1 when the charging prediction algorithm is executed next time (the (i + 1)-th time). Exemplarily, candidate charging station b1 of the charging station group i obtained when the charging prediction algorithm is executed for the i-th time will obtain an expanded charging station group i + 1 when the charging prediction algorithm is executed next time (the (i + 1)-th time), and this charging station group i + 1 includes candidate charging station b1 - 1 and candidate charging station b1 - 2.

[0072] And so on, multiple charging station groups are obtained by executing the charging prediction algorithm multiple times. Then, referring to the following embodiments, perform path planning on the candidate charging stations in the multiple charging station groups to generate a target charging path.

[0073] This embodiment includes: (B1) Combining candidate charging stations in multiple different charging station groups to obtain multiple charging station combinations. Taking Figure 2 as an example, combining candidate charging station a1 and candidate charging station b1 in charging station group i with candidate charging station b1-1 and candidate charging station b1-2 in charging station group i+1 can obtain the following charging station combinations: {a1, b1-1}, {a1, b1-2}, {b1, b1-1}, and {b1, b1-2}.

[0074] In addition, since the charging end point corresponding to candidate charging station a1 has exceeded the destination, that is, after candidate charging station a1, there is a situation where there is no longer a charging station group. Based on this, candidate charging station a1 itself can be used as a charging station combination: {a1}. This situation is relatively common in short trips.

[0075] (B2) Adjusting the preset navigation path based on each charging station combination to obtain candidate charging paths corresponding to each charging station combination.

[0076] Among them, the preset navigation path is the initial path to the destination generated by the navigation when the user departs, such as Figure 2 shown by the black solid line in. Since the candidate charging stations are not necessarily located exactly on the preset navigation path but in the nearby area of the preset navigation path. Therefore, when it is necessary to recharge at a candidate charging station, it is necessary to drive from the preset navigation path to the candidate charging station, so the preset navigation path needs to be adjusted so that the adjusted path can pass through each candidate charging station in the charging station combination in sequence and finally reach the destination.

[0077] Taking the charging station combination {a1, b1-1} as an example, according to the positions of candidate charging station a1 and candidate charging station b1-1, it is determined to drive into candidate charging station a1 from intersection C of the preset navigation path, then drive from candidate charging station a1 and merge into intersection D of the preset navigation path, follow the preset navigation path, drive into candidate charging station b1-1 from intersection E of the preset navigation path, then drive from candidate charging station b1-1 and merge into intersection F of the preset navigation path, and drive from intersection F to the destination. Based on this example, the preset navigation path can be adjusted to a candidate charging path composed of the following nodes: intersection C, candidate charging station a1, intersection D, routing E, candidate charging station b1-1, intersection F, and destination Q according to the charging station combination {a1, b1-1}.

[0078] Similarly, taking the charging station combination {a1} as an example, the preset navigation path is adjusted based on this charging station combination {a1} to obtain a candidate charging path composed of the following nodes: intersection C, candidate charging station a1, intersection D, and destination Q.

[0079] According to the above embodiments, multiple combinations of charging stations correspond to multiple candidate energy replenishment paths.

[0080] (B3) Screen the candidate energy replenishment paths according to the preset path selection information to determine the target energy replenishment path; wherein, the path selection information may include, but is not limited to, at least one of the number of charging times, cost, driving distance, detour distance, and driving duration.

[0081] The path selection information in this embodiment can be set by the user according to personal needs; or, it can also be automatically determined by the system according to the setting results of a large number of users; moreover, priorities can be set between different path selection information.

[0082] In the path selection information, the number of charging times is equal to the number of charging stations passed by the candidate energy replenishment path. The number of charging times of the candidate energy replenishment path corresponding to the charging station combination {a1} is 1 time of charging at charging station a1; the number of charging times of the candidate energy replenishment path corresponding to the charging station combination {a1, b1-1} is 2 times of charging at charging stations a1 and b1-1.

[0083] The cost may include all costs generated by charging. For highways, it may also include highway tolls. In short, the cost includes all costs caused by driving behavior and charging behavior.

[0084] The driving distance can be understood as the distance of the candidate energy replenishment path.

[0085] The detour distance can be understood as the total distance of the additional detour routes required to drive the vehicle to each candidate charging station relative to the preset navigation path.

[0086] The driving duration may include the charging duration of all charging stations and the driving duration on the candidate energy replenishment path.

[0087] This embodiment uses at least one of the above path selection information to screen the candidate energy replenishment paths and determine the top K (for example, K = 3) optimal target energy replenishment paths. When screening the candidate energy replenishment paths in this embodiment, not only the distance factor is considered, but also multiple factors such as the cost and time of the charging stations are comprehensively considered to ensure that the selected target energy replenishment path is not only short in distance, but also reduces the time cost and money cost, and can provide the target energy replenishment path that best meets the user's needs, meet the diverse energy replenishment needs of different users, and improve the user experience.

[0088] Based on the above embodiments, the charging path planning method provided in this embodiment may further include: presenting the navigation information of the target energy replenishment path and the charging station information of each charging station on the target energy replenishment path to the user; the above information can be presented to the user in the form of a charging layer, which is convenient for the user to view and select.

[0089] Specific example: after screening out K target charging paths for the user, the navigation information of the K target charging paths and the charging station information of each charging station on the target charging paths can be displayed on the user interface of the application or in-vehicle system. Good user experience design is also an important part of intelligent charging path planning. The user interface is intuitive and easy to use, and can clearly display information such as charging station information, estimated arrival time, and cost estimate, allowing the user to make decisions quickly.

[0090] According to the user's selection operation, determine the path finally used for navigation from the K target charging paths, and use the selected path to provide navigation services for the user.

[0091] In summary, for the charging path planning method provided by the embodiments of the present disclosure, first, determine the charging start point of the vehicle; based on the charging start point, determine the charging end point according to the driving information and battery information of the vehicle; when the charging end point does not exceed the destination of the vehicle, based on the first position coding preset for the charging station, screen out the charging station group located on the segmented route between the charging end point and the charging start point; then, use the position of each candidate charging station in the charging station group as a new charging start point respectively, and based on the charging start point, determine the charging end point according to the driving information and battery information of the vehicle; when the charging end point exceeds the destination of the vehicle, generate target charging paths based on multiple candidate charging stations in the charging station group.

[0092] This solution uses the first position coding of the charging station to quickly obtain the charging stations along each segmented route, effectively improving the efficiency of searching for charging stations. Then, it decomposes a large problem of searching for charging stations for a complete navigation route into multiple small problems of searching for charging stations for segmented routes, reducing the complexity of searching for charging stations and path planning. Specifically, in the process of determining the charging start point, the charging end point, and the charging station group on the segmented route between the two, a recursive strategy is used, and the optimal candidate charging stations can be screened out every time the charging prediction algorithm is executed; when the charging end point exceeds the destination, stop executing the charging prediction algorithm. At this time, multiple segmented charging routes are continuously expanded through the recursive process, and each segmented route corresponds to a charging station group; since the candidate charging stations in the charging station group of each segmented route are the optimal charging stations determined through the recursive strategy, the target charging paths generated based on these optimal candidate charging stations are the global optimal solutions, with higher accuracy. Furthermore, based on the accurate candidate charging stations in the charging station group, the optimal and most accurate target charging paths can be screened out. In summary, this solution can improve the planning efficiency and accuracy of the target charging paths, and help improve the user charging experience.

[0093] Furthermore, the development of intelligent energy replenishment path planning technology not only enhances the energy replenishment experience of users but also makes important contributions to promoting the development of the new energy vehicle industry. With the progress of technology, intelligent energy replenishment path planning in the future will be more intelligent and personalized, better serving the majority of users.

[0094] Referring to Figure 3 , corresponding to the charging path planning method provided in the foregoing embodiment, this embodiment provides a charging path planning device, which may include the following modules:

[0095] An energy replenishment starting point determination module 310, configured to determine the energy replenishment starting point of the vehicle; wherein, the energy replenishment starting point includes: the current position of the vehicle when receiving an energy replenishment request;

[0096] An energy replenishment ending point determination module 320, configured to determine an energy replenishment ending point based on the energy replenishment starting point according to the driving information and battery information of the vehicle, where the energy replenishment ending point is the position that the vehicle can reach when the remaining power is lower than a preset power threshold;

[0097] A charging station screening module 330, configured to, when the energy replenishment ending point does not exceed the destination of the vehicle, screen a charging station group located on the segmented route between the energy replenishment ending point and the energy replenishment starting point based on the first position code preset for the charging station;

[0098] A repeated execution module 340, configured to use the position of each candidate charging station in the charging station group as a new energy replenishment starting point respectively, and return to the steps executed by the energy replenishment ending point determination module 320;

[0099] A path generation module 350, configured to, when the energy replenishment ending point exceeds the destination of the vehicle, generate a target energy replenishment path based on multiple candidate charging stations in the charging station group.

[0100] In one embodiment, the charging station screening module 330 is further configured to:

[0101] Search for multiple initial charging stations located on the segmented route between the energy replenishment ending point and the energy replenishment starting point based on the first position code preset for the charging station;

[0102] Screen the initial charging stations according to preset charging preference information, and form a charging station group with at least one candidate charging station selected; wherein, the charging preference information includes: distance, charging cost, and / or charging speed.

[0103] For the device provided in this embodiment, its implementation principle and the technical effects generated are the same as those of the foregoing method embodiment. For the sake of brief description, for the parts not mentioned in the device embodiment, reference may be made to the corresponding content in the foregoing method embodiment.

[0104] Figure 4 The structural schematic diagram of an electronic device provided by an embodiment of the present disclosure. As Figure 4 shown, the electronic device 400 includes one or more processors 401 and a memory 402.

[0105] The processor 401 may be a central processing unit (CPU) or other forms of processing units with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 400 to perform desired functions.

[0106] The memory 402 may include one or more computer program products, and the computer program products may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory, etc. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 401 may run the program instructions to implement the charging path planning method of the embodiment of the present disclosure described above and / or other desired functions. Various contents such as input signals, signal components, noise components, etc. may also be stored in the computer-readable storage medium.

[0107] In one example, the electronic device 400 may further include: an input device 403 and an output device 404, and these components are interconnected through a bus system and / or other forms of connection mechanisms (not shown).

[0108] In addition, the input device 403 may further include, for example, a keyboard, a mouse, etc.

[0109] The output device 404 may output various information to the outside, including determined distance information, direction information, etc. The output device 404 may include, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, etc.

[0110] Of course, for simplicity, Figure 4 only some of the components related to the present disclosure in the electronic device 400 are shown, and components such as buses, input / output interfaces, etc. are omitted. In addition, according to specific application scenarios, the electronic device 400 may further include any other appropriate components.

[0111] Furthermore, this embodiment also provides a computer-readable storage medium, and the storage medium stores a computer program, and the computer program is used to execute the above-mentioned charging path planning method.

[0112] A computer program product of a charging path planning method, device, electronic device and medium provided by an embodiment of the present disclosure includes a computer-readable storage medium storing program code, and the instructions included in the program code can be used to execute the method described in the foregoing method embodiment. For specific implementation, reference can be made to the method embodiment, which will not be elaborated herein.

[0113] It should be noted that in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variation thereof is intended to cover a non-exclusive inclusion, such that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the phrase "comprising a..." does not exclude the presence of additional identical elements in the process, method, article or device comprising the element.

[0114] The above are only specific embodiments of the present disclosure, enabling those skilled in the art to understand or implement the present disclosure. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure will not be limited to the embodiments described herein, but will be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A charging path planning method, characterized in that: include: Determine the energy replenishment starting point of the vehicle; wherein the energy replenishment starting point includes: the current position of the vehicle when the energy replenishment request is received; Based on the energy replenishment starting point, according to the driving information and battery information of the vehicle, determining the energy replenishment end point; wherein the energy replenishment end point is a position that the vehicle can reach when the remaining power is lower than a preset power threshold; In a case where the charging end point does not exceed the destination of the vehicle, based on a first position code preset at the charging station, a group of charging stations located on a segmented route between the charging end point and the charging start point are selected; Taking the position of each candidate charging station in the charging station group as a new charging starting point, and returning to the step of determining the charging end point based on the charging starting point and according to the driving information and battery information of the vehicle; In a case where the charging end point exceeds the destination of the vehicle, a target charging path is generated based on a plurality of candidate charging stations in the charging station group.

2. The method according to claim 1, characterized in that The step of selecting a charging station group located on a segmented route between the energy replenishment end point and the energy replenishment start point based on a preset first position code of the charging station includes: Based on a preset first position code of the charging station, searching for a plurality of initial charging stations located on a segmented route between the charging end point and the charging start point; The initial charging stations are screened according to preset charging preference information, and at least one screened candidate charging station is formed into a charging station group; wherein the charging preference information includes: distance, charging cost and / or charging speed.

3. The method according to claim 2, characterized in that The step of searching for a plurality of initial charging stations located on a segmented route between the energy replenishment end point and the energy replenishment start point based on a preset first position code of the charging station includes: Acquire second position codes of a plurality of path points on the segmented route between the energy replenishment end point and the energy replenishment start point; Compare the first position code preset for the charging station with the second position codes of the plurality of path points for consistency; wherein the first position code and the second position code shown are both character strings based on the preset code; The charging station corresponding to the first position code that is consistent with the second position code is determined as the initial charging station on the segmented route between the charging end point and the charging start point.

4. The method according to claim 1, characterized in that: The generating a target energy replenishment path based on a plurality of candidate charging stations in the charging station group includes: Before the energy replenishment endpoint exceeds the destination of the vehicle, obtaining a plurality of charging station groups; Path planning is performed on the candidate charging stations in the plurality of charging station groups to generate a target charging path.

5. The method according to claim 4, characterized in that The performing path planning for the candidate charging stations in the plurality of charging station groups to generate a target energy replenishment path includes: Combining the candidate charging stations in a plurality of different charging station groups to obtain a plurality of charging station combinations; Adjusting the preset navigation path based on each of the charging station combinations to obtain candidate energy replenishment paths corresponding to each of the charging station combinations; The candidate energy replenishment paths are screened according to preset path selection information to determine a target energy replenishment path; wherein the path selection information includes: at least one of the number of charging times, cost, driving distance, detour distance, and driving time.

6. The method according to claim 1, characterized in that The method further comprises: The navigation information of the target energy replenishment path and the charging station information of each charging station on the target energy replenishment path are displayed to the user.

7. A charging path planning device, characterized in that: include: The energy replenishment starting point determination module is used to determine the energy replenishment starting point of the vehicle; wherein the energy replenishment starting point includes: the current position of the vehicle when the energy replenishment request is received; A charging end point determination module, configured to determine a charging end point based on the charging starting point and according to the driving information and battery information of the vehicle, wherein the charging end point is a position that the vehicle can reach when the remaining power is lower than a preset power threshold; A charging station screening module, configured to screen a group of charging stations located on a segmented route between the charging end point and the charging starting point based on a preset first position code of the charging station when the charging end point does not exceed the destination of the vehicle; A repeated execution module is used to use the position of each candidate charging station in the charging station group as a new energy replenishment starting point, and return to the steps executed by the energy replenishment end point determination module; The path generation module is used to generate a target energy replenishment path based on a plurality of candidate charging stations in the charging station group when the energy replenishment end point exceeds the destination of the vehicle.

8. The device according to claim 7, characterized in that The charging station screening module is also used for: Based on a preset first position code of the charging station, searching for a plurality of initial charging stations located on a segmented route between the charging end point and the charging start point; The initial charging stations are screened according to preset charging preference information, and at least one screened candidate charging station is formed into a charging station group; wherein the charging preference information includes: distance, charging cost and / or charging speed.

9. An electronic device, characterized in that: The electronic device comprises: processor; a memory for storing instructions executable by the processor; The processor is used to read the executable instructions from the memory and execute the instructions to implement the method described in any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed on a terminal device, the terminal device implements the method according to any one of claims 1 to 6.

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