Charging path planning method and device, equipment and medium

Abstract

This disclosure relates to a charging route planning method, apparatus, device, and medium. The method includes: determining a charging start point for a vehicle; determining a charging destination based on the charging start point and the vehicle's driving and battery information; if the charging destination does not exceed the vehicle's destination, filtering a group of charging stations located on a segmented route between the charging destination and the charging start point based on a preset first location code of the charging stations; using the location of each candidate charging station in the charging station group as a new charging start point, and returning to the step of determining the charging destination based on the charging start point and the vehicle's driving and battery information; if the charging destination exceeds the vehicle's destination, generating a target charging route based on multiple candidate charging stations in the charging station group. This disclosure can improve the efficiency and accuracy of charging route planning.

Description

Technical Field

[0001] This disclosure relates to the field of new energy vehicle technology, and in particular to a charging path planning method, device, equipment and medium. Background Technology

[0002] Intelligent charging route planning refers to using information technology and algorithms to plan the optimal charging route for electric vehicles, which require regular refueling. Traditional intelligent charging route planning mostly involves traversing charging stations one by one for calculation. This method is time-consuming, computationally expensive, and cannot meet the demands of rapid user response. Furthermore, traditional charging station distribution and service information is not transparent enough, lacking relevant data. Without sufficient charging station data, the planned charging route may be inaccurate and not the optimal choice for the user, resulting in a poor charging experience. Summary of the Invention

[0003] To address the aforementioned technical problems, this disclosure provides a charging path planning method, apparatus, device, and medium.

[0004] According to one aspect of this disclosure, a charging path planning method is provided, comprising:

[0005] Determine the vehicle's refueling starting point; wherein, the refueling starting point includes: the vehicle's current location when the refueling request is received;

[0006] Based on the charging start point, the charging endpoint is determined according to the vehicle's driving information and battery information; wherein, the charging endpoint is the location that the vehicle can reach when the remaining power is lower than a preset power threshold.

[0007] If the charging destination does not exceed the vehicle's destination, a group of charging stations located on the segmented route between the charging destination and the charging start point is selected based on the first location code preset by the charging station.

[0008] The location of each candidate charging station in the charging station group is taken as a new charging starting point, and the process of determining the charging destination based on the charging starting point, the vehicle's driving information, and battery information is returned.

[0009] If the refueling destination exceeds the vehicle's destination, a target refueling path is generated based on multiple candidate charging stations in the charging station group.

[0010] According to another aspect of this disclosure, a charging path planning device is also provided, comprising:

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

[0012] The charging endpoint determination module is used to determine the charging endpoint based on the charging starting point, according to the vehicle's driving information and battery information, wherein the charging endpoint is the location that the vehicle can reach when the remaining power is lower than a preset power threshold.

[0013] The charging station filtering module is used to filter groups of charging stations located on the segmented route between the charging destination and the charging start point, based on a preset first location code of the charging station, when the charging destination does not exceed the vehicle's destination.

[0014] The repeat execution module is used to take the location of each candidate charging station in the charging station group as a new charging start point and return to the steps executed by the charging end point determination module.

[0015] The route generation module is used to generate a target charging route based on multiple candidate charging stations in the charging station group when the charging destination exceeds the vehicle's destination.

[0016] According to another aspect of this disclosure, an electronic device is also provided, the electronic device comprising:

[0017] processor;

[0018] Memory used to store the processor's executable instructions;

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

[0020] According to another aspect of this disclosure, a computer-readable storage medium is also provided, the storage medium storing a computer program for performing the above-described method.

[0021] The technical solution provided in this disclosure has the following advantages compared with the prior art:

[0022] The technical solution provided in this disclosure includes: first, determining the vehicle's charging start point; based on the charging start point, determining the charging destination according to the vehicle's driving information and battery information; if the charging destination does not exceed the vehicle's destination, filtering a group of charging stations located on the segmented route between the charging destination and the charging start point based on the charging station's preset first location code; then, taking the location of each candidate charging station in the charging station group as a new charging start point, and returning to the step of determining the charging destination based on the charging start point and the vehicle's driving information and battery information; if the charging destination exceeds the vehicle's destination, generating a target charging path based on multiple candidate charging stations in the charging station group.

[0023] This technical solution utilizes the first location encoding of charging stations to quickly obtain charging stations along each segmented route, effectively improving the efficiency of charging station search. Furthermore, the large problem of searching for charging stations along a complete navigation route is decomposed into multiple smaller problems of searching for charging stations along segmented routes, reducing the complexity of charging station search and route planning. Specifically, in determining the charging start point, charging end point, and the charging station groups along the segmented routes between them, a recursive strategy is used. Each recursive process filters out the optimal candidate charging stations. When the charging end point exceeds the destination, the recursive process continuously expands to obtain multiple segmented charging routes, each corresponding to a charging station group. Since the candidate charging stations in each segmented route's charging station group are the optimal charging stations determined by the recursive strategy, the target charging path generated based on these optimal candidate charging stations is the globally optimal solution, with higher accuracy. Therefore, based on the accurate candidate charging stations in the charging station group, the optimal target charging path can be selected, contributing to an improved user charging experience. Attached Figure Description

[0024] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0025] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is a flowchart of the charging path planning method described in the embodiments of this disclosure;

[0027] Figure 2 This is a schematic diagram of the navigation route described in the embodiments of this disclosure;

[0028] Figure 3 This is a structural block diagram of the charging path planning device described in the embodiments of this disclosure;

[0029] Figure 4 This is a schematic diagram of the structure of the electronic device described in an embodiment of this disclosure. Detailed Implementation

[0030] To better understand the above-mentioned objectives, features, and advantages of this disclosure, the solutions disclosed herein will be further described below. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0031] Numerous specific details are set forth in the following description in order to provide a full understanding of this disclosure, but this disclosure may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only some, and not all, of the embodiments of this disclosure.

[0032] To efficiently and accurately plan charging routes for users, this disclosure provides a charging route planning method, apparatus, device, and medium. This solution utilizes the first location code of charging stations to quickly obtain charging stations along each segment of the route, effectively improving the efficiency of searching for charging stations. In determining the charging start point, charging end point, and the group of charging stations along the segmented routes between them, a recursive strategy is used to filter out the optimal candidate charging stations on each segmented route. Then, based on the accurate candidate charging stations in the group of charging stations across multiple segmented routes, the optimal target charging route is selected. Therefore, the target charging route generated based on these optimal candidate charging stations will be more accurate.

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

[0034] S102, determine the vehicle's refueling starting point; wherein, the refueling starting point includes, but is not limited to, the vehicle's current location when the refueling request is received.

[0035] In some embodiments, a charging request can be initiated actively by the user, or it can be initiated automatically when the remaining charge of the vehicle's battery is lower than a specified charge level; the charging request is used to indicate the start of charging path planning.

[0036] When a charging request is received, the current location of the vehicle is obtained, and the current location is used as the starting point for the planned charging route. Based on this starting point, the charging prediction algorithm described in subsequent steps S104 and S106 is executed for the first time.

[0037] The energy replenishment prediction algorithm described in subsequent steps S104 and S106 is used to predict the candidate charging stations that the vehicle can reach before its remaining battery power is depleted below a preset power threshold. The energy replenishment prediction algorithm is executed recursively at least once. During the first execution of the algorithm, the vehicle's current location when the energy replenishment request is received is used as the energy replenishment starting point. During subsequent executions, the location of the candidate charging station determined in the previous execution is used as the current energy replenishment starting point. That is, the energy replenishment starting point can include: the vehicle's current location when the energy replenishment request is received, or the location of the candidate charging station determined during the execution of the energy replenishment prediction algorithm. This process continues, with the energy replenishment prediction algorithm described in steps S104 and S106 being executed multiple times until the predicted energy replenishment endpoint reaches or exceeds the vehicle's destination.

[0038] S104, based on the charging start point, determine the charging endpoint according to the vehicle's driving information and battery information; wherein, the charging endpoint is the location that the vehicle can reach when the remaining power is lower than a preset power threshold.

[0039] In this embodiment, vehicle driving information and battery information can be obtained first. Driving information may include, for example, vehicle speed, vehicle weight, and remaining navigation range; battery information may include, for example, battery capacity, current remaining battery power, and the temperature and humidity of the battery's current environment.

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

[0041] When a charging request is initiated, i.e., the first time the charging prediction algorithm is executed, the vehicle's current driving and battery information can be directly obtained through the vehicle's infotainment system. When the charging prediction algorithm is executed again, it can estimate the vehicle's driving information based on the user's historical driving habits and road congestion conditions along the route before and after the charging point. Since the charging point is the location of a candidate charging station determined by the previous charging prediction algorithm execution, it can be assumed that the vehicle has already fully charged the battery at the candidate charging station when it reaches the charging point, thus determining the battery's current remaining charge to be 100%. Furthermore, the temperature and humidity of the battery's environment can be updated based on the weather forecast at the charging point.

[0042] After obtaining the vehicle's driving and battery information, a machine learning-based energy consumption prediction algorithm can be used to determine the recharging endpoint the vehicle can reach when the remaining battery power is below a preset threshold. This threshold could be, for example, 0, or n% of the total battery capacity.

[0043] The aforementioned recharge endpoint is the predicted location that the vehicle can reach before the battery energy is depleted. The recharge endpoint may not have reached the destination yet, so it is necessary to continue to execute the next round of recharge prediction algorithm and determine the next new recharge endpoint until the new recharge endpoint reaches or exceeds the destination.

[0044] S106, if the charging destination does not exceed the vehicle's destination, search for a group of charging stations located on the segmented route between the charging destination and the charging start point based on the first location code preset by the charging station.

[0045] If the charging endpoint does not exceed the vehicle's destination, it means that the vehicle's battery energy is insufficient to support driving to the destination, and further charging is required. In this case, referring to step S106, a group of charging stations that can provide charging services is searched along the segmented route between the charging endpoint and the charging starting point.

[0046] By determining the vehicle's charging start and end points, this embodiment can decompose a complete navigation route from the origin to the destination into multiple segmented routes from the charging start to the charging end. Furthermore, it breaks down a large problem of searching for charging stations along the complete navigation route into multiple smaller problems of searching for charging stations along the segmented routes. For each segmented route, the same method is used to search for charging stations. This approach reduces the distance of the search route, effectively lowers the complexity of the search, and improves search efficiency.

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

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

[0049] In one embodiment, firstly, the second location codes of multiple path points on the segmented route between the charging endpoint and the charging start point are obtained; secondly, the first location code preset by the charging station is compared with the second location codes of the multiple path points for consistency; wherein, the first location code and the second location code are both strings based on preset codes; then, the charging station corresponding to the first location code that matches the second location code is determined as the initial charging station located on the segmented route between the charging endpoint and the charging start point.

[0050] The primary location code for charging stations and the secondary location code for waypoints can be strings based on preset codes such as GeoHash. Taking GeoHash as an example, GeoHash is a geolocation coding method that converts two-dimensional latitude and longitude coordinates into one-dimensional strings, i.e., codes. A single string represents a rectangular area, meaning all latitude and longitude points within that area share the same code. Strings encoded using GeoHash facilitate faster geospatial searches and finding nearby locations.

[0051] In this embodiment, the locations of all charging stations are saved as strings using a preset encoding, i.e., the first location code. Along the segmented route between the charging endpoint and the charging start point, multiple waypoints are set at preset intervals (e.g., 3 meters), and the locations of all waypoints are also saved as strings using a preset encoding, i.e., the second location code. This embodiment allows the waypoints on the navigation route to be encoded as the second location code online when the user initiates navigation. This second location code can be used for navigation as well as for planning charging routes, such as searching for charging stations.

[0052] Since both the first location code of the charging station and the second location code of the waypoint are strings, this embodiment performs a consistency comparison between the first and second location codes, which is essentially string matching. Clearly, string matching is highly efficient, quickly identifying matching strings, i.e., determining the first and second location codes that match. Matching indicates that the corresponding charging station and waypoint are located within the same geographical area. Therefore, the charging station corresponding to the first location code that matches the second location code is identified as the initial charging station along the segmented route between the charging endpoint and the charging start point.

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

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

[0055] In this embodiment, after searching for multiple initial charging stations along the segmented route between the charging endpoint and the charging start point, the user's charging preference information and information about each initial charging station can be obtained. The aforementioned charging preference information indicates the information the user is more concerned about when charging; for example, some users care about the distance to the charging station, while others care about the charging speed and cost.

[0056] In some examples, charging preference information may include distance. This distance can be understood as the distance between the charging station and the vehicle's current location, or the distance between the nearest intersection on the vehicle's navigation route that leads to the charging station and the charging station itself.

[0057] Charging preference information may include: charging cost. Charging cost is the price per kilowatt-hour (kWh). Charging cost varies depending on various factors, primarily including region, amount of electricity consumed, type of charging equipment, and charging subsidy policies.

[0058] Charging preference information can include charging speed. Generally, home charging stations offer slower charging speeds, resulting in lower charging costs. Public fast charging stations offer faster charging speeds, but at a higher cost.

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

[0060] Based on the user's charging preference information and the information of each initial charging station, the initial charging stations are screened to obtain the top N (e.g., N=3) charging stations that best match the user's preferences. These selected charging stations are then used as candidate charging stations to form a charging station group.

[0061] This embodiment filters initial charging stations based on user charging preference information, which can optimize the group of charging stations that meet user preferences and better meet user needs.

[0062] Through steps S104 and S106 above, one charging prediction algorithm is completed. By executing one charging prediction algorithm, a segmented route can be determined and a preferred group of charging stations that matches the user's preferences can be searched along that segmented route. Then, referring to step S108 below, the next charging prediction algorithm is executed.

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

[0064] Reference Figure 2 As shown, taking a charging station group containing two candidate charging stations as an example. Assume that the charging prediction algorithm determines the charging endpoint i in the i-th execution, and the charging station group located on the segmented route between the charging endpoint i and the charging starting point i includes candidate charging station a1 and candidate charging station b1. In this case, candidate charging station a1 and candidate charging station b1 are respectively taken as new charging starting points, and the process returns to step S104, that is, the charging prediction algorithm is executed again.

[0065] S110, if the recharging endpoint exceeds the vehicle's destination, a target recharging path is generated based on multiple candidate charging stations in the charging station group.

[0066] Specifically, in this embodiment, the energy replenishment prediction algorithm is repeatedly executed until the energy replenishment endpoint exceeds the vehicle's destination, and a target energy replenishment path is generated based on multiple candidate charging stations in the charging station group.

[0067] For example, candidate charging station a1 is used as the new charging starting point, and the charging prediction algorithm is executed again to determine the charging destination i+1 corresponding to the charging starting point a1. Since the charging destination i+1 has exceeded the vehicle's destination, the charging prediction algorithm is stopped.

[0068] The candidate charging station b1 is selected as the new charging starting point, and the charging prediction algorithm is executed again to determine the charging destination i+1 corresponding to the charging starting point b1. Since the charging destination i+1 has not yet reached the vehicle's destination, the charging prediction algorithm is executed again.

[0069] In a specific embodiment, considering that during the i-th execution of the energy replenishment prediction algorithm, among the multiple energy replenishment endpoints predicted by multiple different energy replenishment starting points, some energy replenishment endpoints may reach the destination, while others may not. In this case, the energy replenishment prediction algorithm can continue to be executed until there are no more energy replenishment endpoints that have not reached the destination.

[0070] Regarding step S110 above, generating a target charging route based on candidate charging stations in multiple charging station groups may include: acquiring multiple charging station groups before the charging destination exceeds the vehicle's destination; it can be understood that multiple charging station groups are obtained by executing the charging prediction algorithm multiple times. Path planning is then performed on the candidate charging stations in the multiple charging station groups to generate the target charging route.

[0071] In this embodiment, the current i-th execution of the energy replenishment prediction algorithm will result in a corresponding charging station group i. Each candidate charging station in this charging station group i will expand the charging station group i+1 for the next (i+1) execution of the energy replenishment prediction algorithm. For example, candidate charging station b1 in the charging station group i obtained in the i-th execution of the energy replenishment prediction algorithm will be expanded into the charging station group i+1 for the next (i+1) execution of the energy replenishment prediction algorithm. This charging station group i+1 includes candidate charging station b1-1 and candidate charging station b1-2.

[0072] Similarly, by executing the energy replenishment prediction algorithm multiple times, multiple charging station groups are obtained. Then, referring to the following embodiments, path planning is performed on candidate charging stations in the multiple charging station groups to generate target energy replenishment paths.

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

[0074] Furthermore, since the charging endpoint corresponding to candidate charging station a1 has already exceeded the destination, meaning there is no longer a group of charging stations after candidate charging station a1, candidate charging station a1 itself can be considered as a charging station group: {a1}. This situation is more common in short-distance travel.

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

[0076] The preset navigation path is the initial path to the destination generated by navigation when the user departs, for example... Figure 2 As shown by the solid black line, candidate charging stations are not necessarily located directly on the preset navigation route, but rather in the vicinity of it. Therefore, when you need to recharge at a candidate charging station, you need to drive from the preset navigation route to the candidate charging station. This requires adjusting the preset navigation route so that the adjusted route passes through each candidate charging station in the charging station group in sequence and finally reaches the destination.

[0077] Taking the charging station combination {a1, b1-1} as an example, based on the locations of candidate charging stations a1 and b1-1, the route is determined as follows: drive from intersection C on the preset navigation path to candidate charging station a1, then from candidate charging station a1 to intersection D on the preset navigation path, continue along the preset navigation path, drive from intersection E on the preset navigation path to candidate charging station b1-1, then from candidate charging station b1-1 to intersection F on the preset navigation path, and continue driving 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 nodes: intersection C, candidate charging station a1, intersection D, route 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 the charging station combination {a1} to obtain a candidate charging path consisting of the nodes of intersection C, candidate charging station a1, intersection D and destination Q.

[0079] According to the above embodiments, there are multiple candidate charging paths corresponding to various charging station combinations.

[0080] (B3) Filter candidate charging routes based on preset route selection information to determine the target charging route; wherein, route selection information may include, but is not limited to, at least one of the following: number of charging times, cost, driving distance, detour distance and driving time.

[0081] In this embodiment, the path selection information can be set by the user according to their personal needs; or it can be automatically determined by the system based on the settings of a large number of users; moreover, different path selection information can be assigned priorities.

[0082] In the route selection information, the number of charging times is equal to the number of charging stations the candidate charging route passes through. The number of charging times for the candidate charging route corresponding to charging station combination {a1} is 1 charging through charging station a1; the number of charging times for the candidate charging route corresponding to charging station combination {a1, b1-1} is 2 charging through charging stations a1 and b1-1.

[0083] The fee can include all costs incurred during charging, and for highways, it may also include highway tolls. In short, the fee includes all costs arising from driving and charging activities.

[0084] Driving distance can be understood as the distance of the candidate refueling path.

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

[0086] Driving time can include charging time at all charging stations, as well as driving time on candidate charging routes.

[0087] This embodiment utilizes at least one of the aforementioned path selection information to filter candidate charging routes and determine the optimal top K (e.g., K=3) target charging routes. When filtering candidate charging routes, this embodiment considers not only distance but also the cost and time of charging stations, ensuring that the selected target charging routes are not only close in distance but also reduce time and financial costs. This provides users with the most suitable charging routes, meeting the diverse charging needs of different users and improving the user experience.

[0088] Based on the above embodiments, the charging route planning method provided in this embodiment may further include: displaying navigation information of the target charging route and charging station information of each charging station on the target charging route to the user; the above information can be presented to the user in the form of a charging layer for easy viewing and selection by the user.

[0089] For example, after selecting K target charging routes for the user, navigation information for these routes and charging station information for each route can be displayed on the user interface of the application or in-vehicle system. A good user experience design is also a crucial component of intelligent charging route planning. An intuitive and easy-to-use user interface clearly displays charging station information, estimated arrival time, cost estimates, and other relevant information, enabling users to make quick decisions.

[0090] Based on the user's selected actions, the final navigation path is determined from K target energy replenishment paths, and the selected path is used to provide navigation services to the user.

[0091] In summary, the charging route planning method provided in this disclosure firstly determines the vehicle's charging starting point; based on the charging starting point, and according to the vehicle's driving information and battery information, determines the charging destination; if the charging destination does not exceed the vehicle's destination, based on the charging station's preset first location code, a group of charging stations located on the segmented route between the charging destination and the charging starting point is selected; then, the location of each candidate charging station in the charging station group is taken as a new charging starting point, and the charging destination is determined based on the charging starting point and the vehicle's driving information and battery information; if the charging destination exceeds the vehicle's destination, a target charging route is generated based on multiple candidate charging stations in the charging station group.

[0092] This scheme utilizes the first location encoding of charging stations to quickly obtain charging stations along each segmented route, effectively improving the efficiency of charging station search. Then, the large problem of searching for charging stations along a complete navigation route is decomposed into multiple smaller problems of searching for charging stations along segmented routes, reducing the complexity of charging station search and route planning. Specifically, in determining the charging start point, charging end point, and the charging station groups along the segmented routes between them, a recursive strategy is used. Each execution of the charging prediction algorithm selects the optimal candidate charging station. When the charging end point exceeds the destination, the charging prediction algorithm stops executing. At this point, 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 groups of each segmented route are the optimal charging stations determined by the recursive strategy, the target charging path generated based on these optimal candidate charging stations is the globally optimal solution, with higher accuracy. Furthermore, based on the accurate candidate charging stations in the charging station groups, the optimal and most accurate target charging path can be selected. In summary, this solution can improve the planning efficiency and accuracy of target charging routes, which helps to improve the user charging experience.

[0093] Furthermore, the development of intelligent charging route planning technology has not only improved the user's charging experience but also made significant contributions to the development of the new energy vehicle industry. With technological advancements, intelligent charging route planning will become more intelligent and personalized in the future, better serving a wider range of users.

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

[0095] The refueling starting point determination module 310 is used to determine the refueling starting point of the vehicle; wherein, the refueling starting point includes: the current position of the vehicle when the refueling request is received;

[0096] The charging endpoint determination module 320 is used to determine the charging endpoint based on the charging starting point and according to the vehicle's driving information and battery information, wherein the charging endpoint is the location that the vehicle can reach when the remaining power is lower than a preset power threshold.

[0097] The charging station filtering module 330 is used to filter a group of charging stations located on the segmented route between the charging destination and the charging start point, based on a first location code preset by the charging station, when the charging destination does not exceed the destination of the vehicle.

[0098] The repeat execution module 340 is used to take the location of each candidate charging station in the charging station group as a new charging start point and return to the steps executed by the charging end point determination module 320.

[0099] The route generation module 350 is used to generate a target charging route based on multiple candidate charging stations in the charging station group when the charging destination exceeds the vehicle's destination.

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

[0101] Based on the first location code preset by the charging station, search for multiple initial charging stations located on the segmented route between the charging endpoint and the charging start point;

[0102] The initial charging stations are screened based on preset charging preference information, and at least one candidate charging station is selected to form a charging station group; wherein, the charging preference information includes: distance, charging cost and / or charging speed.

[0103] The device provided in this embodiment has the same implementation principle and technical effect as the aforementioned method embodiment. For the sake of brevity, any parts not mentioned in the device embodiment can be referred to the corresponding content in the aforementioned method embodiment.

[0104] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Figure 4 As shown, the electronic device 400 includes one or more processors 401 and memory 402.

[0105] The processor 401 may be a central processing unit (CPU) or other form of processing unit with data processing 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, which 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. 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 execute the program instructions to implement the charging path planning method of the embodiments of this disclosure described above and / or other desired functions. Various contents such as input signals, signal components, and noise components may also be stored in the computer-readable storage medium.

[0107] In one example, the electronic device 400 may also include an input device 403 and an output device 404, which are interconnected via a bus system and / or other forms of connection mechanism (not shown).

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

[0109] The output device 404 can 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 the sake of simplicity, Figure 4 Only some of the components of the electronic device 400 relevant to this disclosure are shown, omitting components such as buses, input / output interfaces, etc. In addition, the electronic device 400 may include any other suitable components depending on the specific application.

[0111] Furthermore, this embodiment also provides a computer-readable storage medium storing a computer program for executing the above-described charging path planning method.

[0112] The present disclosure provides a computer program product for a charging path planning method, apparatus, electronic device, and medium, including a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods described in the preceding method embodiments. For specific implementation details, please refer to the method embodiments, which will not be repeated here.

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

[0114] The above description is merely a specific embodiment of this disclosure, enabling those skilled in the art to understand or implement it. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not to be limited to the embodiments described herein, but is to 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 vehicle's charging starting point; wherein the charging starting point includes: the vehicle's current location when a charging request is received; and automatically initiate a charging request when the vehicle's battery charge is lower than a specified charge level. Based on the charging start point, the charging endpoint is determined according to the vehicle's driving information and battery information; wherein, the charging endpoint is the location that the vehicle can reach when the remaining battery power is lower than a preset battery power threshold; the driving information includes: the vehicle's driving speed, vehicle weight, and remaining navigation range; If the charging destination does not exceed the vehicle's destination, a group of charging stations located on the segmented route between the charging destination and the charging start point is filtered based on the first location code preset by the charging station; wherein, a consistency comparison is performed based on the first location code preset by the charging station and the second location codes of multiple path points on the segmented route, and a group of charging stations along the route is searched from the charging destination toward the charging start point. The location of each candidate charging station in the charging station group is taken as a new charging starting point, and the process of determining the charging destination based on the charging starting point, the vehicle's driving information, and battery information is returned. If the refueling destination exceeds the vehicle's destination, a target refueling path is generated based on multiple candidate charging stations in the charging station group.

2. The method according to claim 1, characterized in that, The step of filtering charging station groups located on segmented routes between the charging destination and the charging start point based on a preset first location code of the charging station includes: Based on the first location code preset by the charging station, search for multiple initial charging stations located on the segmented route between the charging endpoint and the charging start point; The initial charging stations are screened based on preset charging preference information, and at least one candidate charging station is selected to form 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 process of searching for multiple initial charging stations located on the segmented route between the charging destination and the charging start point, based on a preset first location code of the charging station, includes: Obtain the second location codes of multiple path points on the segmented route between the energy replenishment endpoint and the energy replenishment starting point; The first location code preset for the charging station is compared with the second location codes of the plurality of path points for consistency; wherein, the first location code and the second location code are both strings based on the preset code; The charging station corresponding to the first location code that matches the second location code is determined as the initial charging station located on the segmented route between the charging endpoint and the charging start point.

4. The method according to claim 1, characterized in that, The generation of a target charging path based on candidate charging stations in multiple charging station groups includes: Before the charging endpoint exceeds the vehicle's destination, acquire multiple groups of charging stations; Path planning is performed on the candidate charging stations in the multiple charging station groups to generate target charging routes.

5. The method according to claim 4, characterized in that, The step of performing path planning on the candidate charging stations in the multiple charging station groups to generate a target charging route includes: By combining the candidate charging stations from multiple different charging station groups, a variety of charging station combinations can be obtained; The preset navigation path is adjusted based on each of the charging station combinations to obtain candidate charging paths corresponding to each of the charging station combinations. The candidate charging routes are filtered according to preset route selection information to determine the target charging route; wherein, the route selection information includes at least one of the following: 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 includes: The system displays navigation information for the target charging route and charging station information for each charging station along the target charging route to the user.

7. A charging path planning device, characterized in that, include: A recharge starting point determination module is used to determine the recharge starting point of the vehicle; wherein, the recharge starting point includes: the current position of the vehicle when a recharge request is received; and automatically initiating a recharge request when the remaining battery power of the vehicle is lower than a specified power level. The charging endpoint determination module is used to determine the charging endpoint based on the charging starting point, according to the vehicle's driving information and battery information, wherein the charging endpoint is the location that the vehicle can reach when the remaining power is lower than a preset power threshold; the driving information includes: the vehicle's driving speed, vehicle weight, and remaining navigation range; The charging station filtering module is used to filter charging station groups located on the segmented route between the charging station endpoint and the charging station starting point, based on a preset first location code of the charging station, when the charging station endpoint does not exceed the vehicle's destination; wherein, a consistency comparison is performed based on the preset first location code of the charging station and the second location codes of multiple path points on the segmented route, and the charging station groups along the route are searched from the charging station endpoint toward the charging station starting point. The repeat execution module is used to take the location of each candidate charging station in the charging station group as a new charging start point and return to the steps executed by the charging end point determination module. The route generation module is used to generate a target charging route based on multiple candidate charging stations in the charging station group when the charging destination exceeds the vehicle's destination.

8. The apparatus according to claim 7, characterized in that, The charging station screening module is also used for: Based on the first location code preset by the charging station, search for multiple initial charging stations located on the segmented route between the charging endpoint and the charging start point; The initial charging stations are screened based on preset charging preference information, and at least one candidate charging station is selected to form 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 includes: processor; Memory used to store the processor's executable instructions; The processor is configured to read the executable instructions from the memory and execute the instructions to implement the method described in any one of claims 1-6.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed on a terminal device, cause the terminal device to perform the method as described in any one of claims 1-6.

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