Energy replenishment path planning method, storage medium, electronic device, and driving device

Abstract

An energy replenishment path planning method, a storage medium, an electronic device, and a driving device. The energy replenishment path planning method comprises: acquiring a resource attribute and distance-from-start-point mileage of each energy replenishment resource on paths between a start point and an end point, and a total mileage of the paths (S11); on the basis of dynamic planning, respectively acquiring recommended energy replenishment resources on each path (S12); acquiring a resource-dimension cost, a distance-from-start-point cost and a mileage-dimension cost of each path (S13); acquiring a comprehensive cost of the paths along which a driving device travels from the start point to the end point (S14); and on the basis of the comprehensive cost of the paths, performing energy replenishment path planning (S15).

Description

Energy replenishment path planning method, storage medium, electronic device and driving device

[0001] This application claims priority to Chinese patent application No. 202311790172.9 filed on December 22, 2023, with the invention name “Energy Recharging Path Planning Method, Storage Medium, Electronic Device and Driving Device”. The entire contents of the above Chinese patent application are incorporated into this application by reference. Technical Field

[0002] The present application relates to the field of energy replenishment for driving equipment, and specifically provides an energy replenishment path planning method, a storage medium, an electronic device, and a driving device. Background Art

[0003] Current solutions for planning recharging routes for electric vehicles have limited consideration of factors influencing resource selection and are unable to comprehensively consider multiple factors. Furthermore, resource weights are set fixedly, and recharging is dynamically weighted based on route conditions to provide the optimal recharging route planning, resulting in a poor user experience.

[0004] Accordingly, this field requires a new energy replenishment path planning solution to solve the above problems. Summary of the Invention

[0005] In order to overcome the above-mentioned defects, the present application is proposed to provide a method for energy replenishment path planning, a storage medium, an electronic device and a driving device to solve or at least partially solve the technical problem in the prior art that energy replenishment path planning is difficult to comprehensively consider and dynamically calculate.

[0006] In a first aspect, the present application provides a method for planning an energy replenishment path, which is applied to a driving device, comprising:

[0007] Obtain the resource attributes of each energy resource on each path between the starting point and the end point, as well as the mileage from the starting point and the total mileage of each path;

[0008] Perform dynamic planning based on the resource attributes of the energy replenishment resources and the mileage from the starting point to obtain recommended energy replenishment resources on each path;

[0009] The resource dimension cost of each path is obtained based on the resource attributes of the recommended energy replenishment resources on each path; the distance cost of each path from the starting point is obtained based on the mileage of the recommended energy replenishment resources closest to the starting point on each path; and the mileage dimension cost of each path is obtained based on the total mileage of each path.

[0010] Based on the resource dimension cost, the cost of being away from the starting point, and the mileage dimension cost, the comprehensive cost of each path of the driving device from the starting point to the end point is obtained;

[0011] The energy replenishment path planning is performed based on the comprehensive cost of each path.

[0012] In one technical solution of the above-mentioned energy replenishment path planning method, the resource attributes of each energy replenishment resource on each path between the starting point and the end point, the mileage from the starting point, and the total mileage of each path are obtained, wherein obtaining the resource attributes of each energy replenishment resource includes:

[0013] Obtaining a resource attribute influencing factor of each energy replenishment resource based on the priority of each resource attribute, wherein the resource attribute influencing factor includes an attribute factor and a location factor;

[0014] The attribute factors include at least a resource type factor, a resource rating factor, and a charging speed factor.

[0015] In one technical solution of the above energy replenishment path planning method, the step of obtaining the resource dimension cost of the path based on the resource attributes of the recommended energy replenishment resources on each path includes:

[0016] The hierarchical analysis method is used to obtain the weights corresponding to the influencing factors of each resource attribute;

[0017] Based on the resource attribute influencing factors of the recommended energy replenishment resources on each path and the weights corresponding to the resource attribute influencing factors, the resource dimension cost of the path is obtained.

[0018] In one technical solution of the above-mentioned energy replenishment path planning method, the use of the hierarchical analysis method to obtain the weights corresponding to the influencing factors of each resource attribute includes:

[0019] The resource attribute influencing factors are sorted, a positive and negative matrix is ​​constructed, the weights are solved, and the consistency is checked.

[0020] In one technical solution of the above-mentioned energy replenishment path planning method, obtaining the resource dimension cost of the path based on the resource attribute influencing factors of the recommended energy replenishment resources on each path and the weights corresponding to the resource attribute influencing factors includes:

[0021] Obtaining a first resource cost for each resource attribute based on a resource attribute impact factor corresponding to each resource attribute, a weight corresponding to each resource attribute impact factor, and a preset first balance parameter;

[0022] The resource dimension cost of the path is obtained based on the sum of the first resource cost of each resource attribute of the recommended energy replenishment resource on each path.

[0023] In one technical solution of the above-mentioned energy replenishment path planning method, the cost of the path away from the starting point is obtained based on the distance from the starting point of the recommended energy replenishment resource closest to the starting point on each path, including:

[0024] The cost X of being away from the starting point is obtained based on the distance M from the starting point of the recommended energy replenishment resource closest to the starting point on the path, the remaining cruising range P of the driving device, the preset second balance parameter g and the preset distance sensitive parameter h.

[0025] Where a is a tuning parameter and 0<a<1.

[0026] In one technical solution of the above-mentioned energy replenishment path planning method, obtaining the mileage dimension cost of each path based on the total mileage of each path includes:

[0027] The mileage dimension cost of the path is obtained based on the total mileage of each path and a preset third balance parameter.

[0028] In a second aspect, the present application provides a computer-readable storage medium, which stores multiple program codes, and the program codes are suitable for being loaded and run by a processor to execute the energy replenishment path planning method described in any one of the technical solutions of the above-mentioned energy replenishment path planning method.

[0029] In a third aspect, the present application provides an electronic device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program, and when the computer program is executed by the at least one processor, it implements the energy replenishment path planning method described in any one of the technical solutions of the above-mentioned energy replenishment path planning method.

[0030] In a fourth aspect, the present application provides a driving device, including a driving device body and the above-mentioned electronic device.

[0031] The above one or more technical solutions of this application have at least one or more of the following beneficial effects:

[0032] In implementing the technical solution of this application, by converting the resource attributes of each energy replenishment resource on each path, the mileage from the starting point, and the total mileage of each path into a comprehensive cost, it becomes possible to comprehensively consider multiple factors and obtain accurate and efficient energy replenishment path planning.

[0033] The analytic hierarchy process (AHP) was used to assign weights to various resource attributes for energy replenishment, while the optimal resource was selected based on a comprehensive consideration of real-time route data and user preferences. The inverse proportional curve function was used to factor in distance from the starting point, achieving a decreasing effect of distance influence as distance from the starting point increases. This prevents excessive distance from contaminating other factors when the distance is too large.

[0034] The above-mentioned scheme, which comprehensively considers multiple factors and combines them with dynamic weight calculation of route information, uses statistical principles to scientifically allocate resource selection weights under multiple factors, thereby improving user satisfaction with the travel experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The disclosure of this application will be more easily understood with reference to the accompanying drawings. Those skilled in the art will readily appreciate that these drawings are for illustrative purposes only and are not intended to limit the scope of protection of this application. Furthermore, similar numbers in the figures represent similar components, where:

[0036] FIG1 is a schematic diagram of the main steps of a method for planning an energy replenishment path according to an embodiment of the present application;

[0037] FIG2 is a schematic diagram of the distribution of multiple energy replenishment resources according to an embodiment of the present application;

[0038] FIG3 is a schematic diagram of a comprehensive cost interface according to an embodiment of the present application;

[0039] FIG4 is a main structural block diagram of an energy replenishment path planning device according to an embodiment of the present application;

[0040] FIG5 is a main structural block diagram of an electronic device for executing the energy replenishment path planning method of the present application. DETAILED DESCRIPTION

[0041] Some embodiments of the present application are described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present application and are not intended to limit the scope of protection of the present application.

[0042] In the description of this application, "module" and "processor" may include hardware, software, or a combination of both. A module may include hardware circuitry, various suitable sensors, communication ports, and memory. It may also include software components, such as program code, or a combination of software and hardware. A processor may be a central processing unit, a microprocessor, an image processor, a digital signal processor, or any other suitable processor. A processor has data and / or signal processing capabilities. A processor may be implemented in software, hardware, or a combination of both. Non-transitory computer-readable storage media include any suitable medium capable of storing program code, such as magnetic disks, hard disks, optical disks, flash memory, read-only memory, random access memory, etc. The term "A and / or B" refers to all possible combinations of A and B, such as only A, only B, or both A and B. The terms "at least one of A or B" or "at least one of A and B" have similar meanings to "A and / or B" and may include only A, only B, or both A and B. The singular forms "a" and "the" may also include the plural forms.

[0043] The present application provides a method for planning an energy replenishment path, which is applied to driving equipment.

[0044] Referring to FIG1 , FIG1 is a schematic diagram of the main steps of a method for planning a charging path according to an embodiment of the present application. As shown in FIG1 , the method for planning a charging path in the embodiment of the present application mainly includes the following steps S11 to S15.

[0045] Step S11: Obtain the resource attributes of each energy replenishment resource on each path between the starting point and the end point, the mileage from the starting point, and the total mileage of each path.

[0046] In one embodiment of the present application, the resource attributes of each energy replenishment resource on each path between the starting point and the end point, the mileage from the starting point, and the total mileage of each path are obtained, wherein obtaining the resource attributes of each energy replenishment resource includes:

[0047] Obtaining a resource attribute influencing factor of each energy replenishment resource based on the priority of each resource attribute, wherein the resource attribute influencing factor includes an attribute factor and a location factor;

[0048] The attribute factors include at least a resource type factor, a resource rating factor, and a charging speed factor.

[0049] Specifically, in one embodiment, resource attributes include resource type, resource rating, charging speed, and relative position. For example, the resource types include, in order of priority, third-generation battery swap stations, second-generation battery swap stations, first-generation battery swap stations, DC charging piles, AC charging piles, and shared private piles, and their corresponding resource type factors increase in sequence. The resource ratings include high, medium, and low in order of priority, and their corresponding resource rating factors increase in sequence. The charging speeds include high, medium, and low in order of priority, and their corresponding charging speed factors increase in sequence. The relative positions include, in order of priority, service areas and the same side of the highway, and their corresponding location factors increase in sequence.

[0050] Exemplarily, the value range of each resource attribute influencing factor is 1-9.

[0051] Among them, the resource rating refers to the resource rating obtained based on user evaluation or evaluation by other institutions; the service area in the relative position means that the energy replenishment resource is within the service area, and the same side of the highway in the relative position means that the energy replenishment resource is on the same side of the highway on which the driving device is traveling or about to travel. When the user uses this energy replenishment resource, there is no need to take a long detour.

[0052] In one embodiment, for obtaining multiple energy replenishment resources, please refer to FIG2. FIG2 is a schematic diagram of the distribution of multiple energy replenishment resources in one embodiment of the present application.

[0053] Step S12: Dynamic planning is performed based on the resource attributes of the energy replenishment resources and the mileage from the starting point to obtain recommended energy replenishment resources on each path.

[0054] Among them, dynamic programming is a method for solving optimization problems. In dynamic programming, if a rechargeable energy resource is within the remaining range of the driving device, the resource attribute influencing factor of the rechargeable energy resource is used to determine whether to recommend the rechargeable energy resource. If a rechargeable energy resource is not within the remaining range of the driving device, a preset additional cost is assigned to the rechargeable energy resource. Based on the additional cost and the resource attribute influencing factor, it is determined whether to recommend the rechargeable energy resource. The mileage between two adjacent rechargeable energy resources can be obtained based on the mileage of each rechargeable energy resource from the starting point, and thus it can be determined whether the rechargeable energy resource is within the remaining range of the driving device. In the dynamic programming process, the recommended rechargeable energy resources before and after will affect each other during the acquisition process. Therefore, dynamic programming can be performed based on state transition equations, recursive calculations, backtracking and other steps to obtain recommended rechargeable energy resources on each path. In this step, the goal of dynamic programming is to obtain high-quality rechargeable energy resources as recommended rechargeable energy resources to reduce the number of times the vehicle recharges, thereby obtaining the minimum number of recharges.

[0055] Step S13: obtaining the resource dimension cost of the path based on the resource attributes of the recommended energy replenishment resources on each path; obtaining the cost of the path away from the starting point based on the mileage of the recommended energy replenishment resource closest to the starting point on each path; and obtaining the mileage dimension cost of the path based on the total mileage of each path.

[0056] In one embodiment of the present application, the acquiring of the resource dimension cost of each path based on the resource attributes of the recommended energy replenishment resource on each path includes:

[0057] The Analytic Hierarchy Process (AHP) is used to obtain the weights corresponding to the influencing factors of each resource attribute;

[0058] Based on the resource attribute influencing factors of the recommended energy replenishment resources on each path and the weights corresponding to the resource attribute influencing factors, the resource dimension cost of the path is obtained.

[0059] Furthermore, the method of using the hierarchical analysis method to obtain the weight corresponding to each resource attribute influencing factor includes:

[0060] The resource attribute influencing factors are sorted, a positive and negative matrix is ​​constructed, the weights are solved, and the consistency is checked.

[0061] Exemplarily, the resource attribute influencing factors are sorted in order of numerical values.

[0062] In AHP, a reciprocal matrix is ​​constructed to quantify the relative importance of factors. Resource attribute influencing factors are compared pairwise to determine the relative importance of one factor relative to another. The comparison scale typically ranges from 1 to 9, with 1 indicating equal importance and 9 indicating one factor is extremely important relative to another.

[0063] The comparison results are entered into an n×n matrix, where n is the number of factors. The diagonal elements represent the comparison of the factor relative to itself, which is 1. The off-diagonal elements are filled in with values ​​based on the comparison results. If factor i is more important than factor j, the value at position (i, j) in the matrix is ​​the comparison result; the value at position (j, i) is the inverse of 1 / (i, j).

[0064] In one embodiment, the positive reciprocal matrix may refer to the following Table 1. Table 1

[0065] The above-mentioned positive reciprocal matrix is ​​established by using resource attribute influencing factors, wherein the specific value of each resource attribute influencing factor can be set by those skilled in the art according to actual needs.

[0066] Using the data in the reciprocal matrix, the eigenvalue method is used to determine the weight of each factor relative to the other factors. The consistency index (CI) value is then calculated by calculating the maximum eigenvalue root for consistency verification. If the consistency verification passes, the priority ranking and weights of the resource attribute influencing factors are reliable. If the consistency verification fails, it indicates that there is a problem with the priority ranking of the resource attribute influencing factors in the current reciprocal matrix, which needs to be corrected.

[0067] Exemplarily, the weight solution and consistency check steps are as follows:

[0068] Determine the product of each row of the matrix:

[0069] Calculate the nth root of Mi: Where W i That is the solved weight.

[0070] Normalize a vector:

[0071] Calculate the characteristic roots of the judgment matrix:

[0072] Calculate the maximum eigenvalue of the judgment matrix:

[0073] Calculate the consistency index CI value: CI = (λ max-n) / (n-1)

[0074] The formula for the consistency ratio CR is: CR = CI / RI, where RI is the standard reference value, which can be obtained by referring to the following comparison table, as shown in Table 2. Table 2

[0075] When the consistency ratio CR value is less than a preset threshold, it is considered that the consistency verification has been passed. The preset threshold can be set by those skilled in the art according to actual needs.

[0076] Furthermore, the resource dimension cost of the path is obtained based on the resource attribute influencing factors of the recommended energy replenishment resources on each path and the weights corresponding to the resource attribute influencing factors, including:

[0077] Obtaining a first resource cost for each resource attribute based on a resource attribute impact factor corresponding to each resource attribute, a weight corresponding to each resource attribute impact factor, and a preset first balance parameter;

[0078] The resource dimension cost of the path is obtained based on the sum of the first resource cost of each resource attribute of the recommended energy replenishment resource on each path.

[0079] In one embodiment, the resource dimension cost R is obtained based on the following relationship:

[0080] Among them S i is the resource attribute influencing factor, W i is the weight corresponding to the resource attribute influencing factor, l is the preset first balance parameter, and n is the total number of resource attribute influencing factors corresponding to the recommended energy replenishment resources on the path.

[0081] Specifically, the first balancing parameter l is used to balance the influence of the resource dimension cost R in the comprehensive cost, and can be obtained by those skilled in the art based on historical data or simulation data. In this embodiment, the first balancing parameter l is between 10,000 and 500,000.

[0082] In one embodiment of the present application, the step of obtaining the distance cost of each path from the starting point based on the distance from the starting point of the recommended energy replenishment resource closest to the starting point on each path includes:

[0083] The cost X of being away from the starting point is obtained based on the distance M from the starting point of the recommended energy replenishment resource closest to the starting point on the path, the remaining cruising range P of the driving device, the preset second balance parameter g and the preset distance sensitive parameter h.

[0084] Where a is a tuning parameter and 0<a<1.

[0085] Specifically, the second balancing parameter g is used to balance the influence of the cost X of being away from the starting point in the comprehensive cost, and can be obtained by those skilled in the art based on historical data or simulation data; the distance sensitive parameter h is used to adjust the influence of energy replenishment resources at different distances on the cost X of being away from the starting point. If the energy replenishment resource is far from the starting point, the distance is insensitive; if the energy replenishment resource is close to the starting point, the distance is sensitive. In this embodiment, In other embodiments of the present application, the adjustment parameter a can be set by those skilled in the art as needed. In this embodiment, the second balance parameter g is between 5000-100000; the distance sensitive parameter h is between 40000-100000.

[0086] In one embodiment of the present application, obtaining the mileage dimension cost of each path based on the total mileage of each path includes:

[0087] The mileage dimension cost of the path is obtained based on the total mileage of each path and a preset third balance parameter.

[0088] In one embodiment, the mileage dimension cost D is obtained based on the following relationship: D=L×q, where q is a preset third balancing parameter, and L is the total mileage of each path.

[0089] The third balancing parameter q is used to balance the influence of the mileage dimension cost D in the comprehensive cost, and can be obtained by those skilled in the art based on historical data or simulation data.

[0090] In this embodiment, the third balancing parameter q=1.

[0091] Step S14: Based on the resource dimension cost, the cost of being away from the starting point, and the mileage dimension cost, a comprehensive cost of each path of the driving device from the starting point to the end point is obtained.

[0092] In one embodiment, the comprehensive cost T is obtained based on the following relationship:

[0093] T=D+R+X, where D is the mileage dimension cost, R is the resource dimension cost, and X is the cost of being away from the starting point.

[0094] The comprehensive cost T can also be called the total distance cost, which is the total distance converted after unifying all influencing factors of the energy replenishment resource in the mileage dimension, resource dimension, and distance from the starting point dimension, so as to intuitively indicate whether each energy replenishment resource is worth recommending.

[0095] For example, in one embodiment, the comprehensive cost (total distance cost) calculation interface is shown in Figure 3. Figure 3 is a schematic diagram of the comprehensive cost interface according to one embodiment of the present application.

[0096] From a user's perspective, in some cases, they are willing to travel further for a better charging experience. For example, Figure 3 shows the calculation of the comprehensive cost for each path, with resource attributes prioritized in descending order from G01 to G16. G01 represents the best resource, with a total distance cost (comprehensive cost) of 26,500 meters, while the worst resource has a total distance cost of 147,000 meters. This means that choosing the worst resource for charging requires an additional detour of 120,500 meters (147,000 - 26,500 meters) compared to the best resource. This indicates that good resources have lower detour costs, making them more likely to be selected.

[0097] Step S15: planning energy replenishment paths according to the comprehensive costs of the paths.

[0098] Specifically, among the paths from the user's starting point to the end point, the path with the lowest comprehensive cost is the optimal path, and this path is recommended to the user so that the user can recharge the driving device when passing by the recommended recharging resource.

[0099] Based on the above steps S11 to S15, by converting the resource attributes of each energy replenishment resource on each path between the starting point and the end point, the mileage from the starting point, and the total mileage of each path into a comprehensive cost, it is possible to comprehensively consider multiple factors and obtain accurate and efficient energy replenishment path planning.

[0100] The analytic hierarchy process (AHP) was used to assign weights to various resource attributes for energy replenishment, while the optimal resource was selected based on a comprehensive consideration of real-time route data and user preferences. The inverse proportional curve function was used to factor in distance from the starting point, achieving a decreasing effect of distance influence as distance from the starting point increases. This prevents excessive distance from contaminating other factors when the distance is too large.

[0101] The above-mentioned scheme, which comprehensively considers multiple factors and combines them with dynamic weight calculation of route information, uses statistical principles to scientifically allocate resource selection weights under multiple factors, thereby improving user satisfaction with the travel experience.

[0102] It should be pointed out that although the various steps in the above embodiments are described in a specific order, those skilled in the art will understand that in order to achieve the effect of the present application, different steps do not have to be performed in such an order. They can be performed simultaneously (in parallel) or in other orders. These changes are within the scope of protection of the present application.

[0103] All of the above optional technical solutions can be combined in any way to form optional embodiments of the present application, and will not be described in detail here.

[0104] Furthermore, the present application also provides an energy replenishment path planning device.

[0105] Referring to Figure 4 , Figure 4 is a block diagram of the main structure of a power-replenishing path planning device according to one embodiment of the present application. As shown in Figure 4 , the power-replenishing path planning device in this embodiment of the present application primarily includes an acquisition module 41, a dynamic planning module 42, a cost conversion module 43, a comprehensive cost acquisition module 44, and a path planning module 45. In some embodiments, one or more of the acquisition module 41, dynamic planning module 42, cost conversion module 43, comprehensive cost acquisition module 44, and path planning module 45 may be combined into a single module.

[0106] In some embodiments, the acquisition module 41 can be configured to obtain the resource attributes of each energy replenishment resource on each path between the starting point and the end point, the mileage from the starting point, and the total mileage of each path. The dynamic planning module 42 can be configured to perform dynamic planning based on the resource attributes of the energy replenishment resources and the mileage from the starting point, and respectively obtain the recommended energy replenishment resources on each path. The cost conversion module 43 can be configured to obtain the resource dimension cost of the path based on the resource attributes of the recommended energy replenishment resources on each path; obtain the cost of the path away from the starting point based on the mileage from the starting point of the recommended energy replenishment resource closest to the starting point on each path; and obtain the mileage dimension cost of the path based on the total mileage of each path. The comprehensive cost acquisition module 44 can be configured to obtain the comprehensive cost of each path of the driving device from the starting point to the end point based on the resource dimension cost, the cost of being away from the starting point, and the mileage dimension cost. The path planning module 45 can be configured to plan the energy replenishment path according to the comprehensive cost of each path.

[0107] In one embodiment, the description of the specific implementation functions can be found in steps S11 to S15.

[0108] The above-mentioned energy replenishment path planning device is used to execute the embodiment of the energy replenishment path planning method shown in Figure 1. The technical principles, technical problems solved and technical effects produced by the two are similar. Technical personnel in this technical field can clearly understand that for the convenience and conciseness of description, the specific working process and related instructions of the energy replenishment path planning device can refer to the contents described in the embodiment of the energy replenishment path planning method, and will not be repeated here.

[0109] It should be understood that since the configuration of each module is merely for the purpose of illustrating the functional units of the apparatus of the present application, the physical devices corresponding to these modules may be the processor itself, or a portion of the software in the processor, a portion of the hardware, or a combination of software and hardware. Therefore, the number of modules in the figure is merely illustrative.

[0110] Those skilled in the art will appreciate that the various modules in the device can be adaptively split or merged. Such splitting or merging of specific modules will not cause the technical solution to deviate from the principles of this application. Therefore, the technical solutions after splitting or merging will fall within the scope of protection of this application.

[0111] Furthermore, the present application also provides a computer-readable storage medium. In one embodiment of the computer-readable storage medium according to the present application, the computer-readable storage medium can be configured to store a program for executing the energy replenishment path planning method of the above method embodiment, and the program can be loaded and executed by a processor to implement the above energy replenishment path planning method.

[0112] For ease of explanation, only the parts related to the embodiments of the present application are shown. For specific technical details not disclosed, please refer to the method section of the embodiments of the present application. The computer-readable storage medium can be a storage device formed by various electronic devices. Optionally, the computer-readable storage medium in the embodiments of the present application is a non-transitory computer-readable storage medium.

[0113] Another aspect of the present application further provides an electronic device. Please refer to Figure 5, which is a main structural block diagram of the electronic device used to execute the energy replenishment path planning method of the present application.

[0114] As shown in Figure 5, the electronic device 500 may include at least one processor 501; and a memory 502 communicatively connected to the at least one processor 501; wherein the memory 502 stores a computer program 503, and when the computer program 503 is executed by the at least one processor 501, it implements the method described in any of the above embodiments. The electronic device described in this application can be a terminal device such as a smartphone, wearable device, tablet computer, desktop computer, laptop computer, PDA, or a cloud server. Exemplarily, the memory 502 and processor 501 are communicatively connected via a bus.

[0115] Exemplarily, the processor 501 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0116] Memory 502 can be an internal storage unit of electronic device 500, such as a hard disk or memory of electronic device 500. Memory 502 can also be an external storage device of electronic device 500, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, etc. equipped on electronic device 500. Furthermore, memory 502 can include both an internal storage unit of electronic device 500 and an external storage device. Memory 502 is used to store computer programs and other programs and data required by electronic device 500. Memory 502 can also be used to temporarily store data that has been output or is about to be output.

[0117] In some possible implementations, the electronic device 500 may include multiple processors 501 and memories 502. The program code 503 for executing the energy replenishment path planning method of the above-mentioned method embodiment may be divided into multiple subroutines, and each subroutine may be loaded and run by the processor 501 to execute different steps of the energy replenishment path planning method of the above-mentioned method embodiment. Specifically, each subroutine may be stored in different memories 502, and each processor 501 may be configured to execute programs in one or more memories 502 to jointly implement the energy replenishment path planning method of the above-mentioned method embodiment, that is, each processor 501 executes different steps of the energy replenishment path planning method of the above-mentioned method embodiment to jointly implement the energy replenishment path planning method of the above-mentioned method embodiment.

[0118] The multiple processors 501 may be processors deployed on the same device. For example, the electronic device may be a high-performance device composed of multiple processors, and the multiple processors 501 may be processors configured on the high-performance device. Furthermore, the multiple processors 501 may be processors deployed on different devices. For example, the electronic device may be a server cluster, and the multiple processors 501 may be processors on different servers in the server cluster.

[0119] The electronic device 500 may include, but is not limited to, a processor 501 and a memory 502. Those skilled in the art will appreciate that FIG5 is merely an example of the electronic device 500 and does not limit the electronic device 500. The electronic device 500 may include more or fewer components than shown, or may combine certain components or different components. For example, the electronic device may further include input and output devices, network access devices, buses, and the like.

[0120] Furthermore, the present application also provides a driving device, including a driving device body and the above-mentioned electronic device.

[0121] In some embodiments of the present application, the driving device further includes at least one sensor configured to sense information. The sensor is communicatively coupled to any of the processors described herein. Optionally, the driving device further includes an autonomous driving system configured to guide the driving device to autonomous driving or provide assisted driving. The processor communicates with the sensor and / or autonomous driving system to perform the method described in any of the above embodiments.

[0122] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0123] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments of this application can be implemented with electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0124] In the embodiments provided in this application, it should be understood that the disclosed electronic devices and methods can be implemented in other ways. For example, the electronic device embodiments described above are merely schematic. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods. Multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, devices or units, which may be electrical, mechanical or other forms.

[0125] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0126] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0127] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by the processor, it can implement the steps of the above-mentioned various method embodiments. The computer program may include computer program code, which may be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0128] The relevant user personal information that may be involved in the various embodiments of this application is strictly in accordance with the requirements of laws and regulations, following the principles of legality, legitimacy and necessity, and based on the reasonable purposes of business scenarios, to process the personal information that users actively provide during the use of products / services or generated due to the use of products / services, as well as the personal information obtained with the user's authorization.

[0129] The user personal information processed by this application will vary depending on the specific product / service scenario and must be based on the specific scenario in which the user uses the product / service. This may involve the user's account information, device information, driving information, vehicle information, or other related information. This application will treat the user's personal information and its processing with a high degree of diligence.

[0130] This application attaches great importance to the security of user personal information and has taken reasonable and feasible security protection measures that comply with industry standards to protect user information and prevent personal information from being accessed, disclosed, used, modified, damaged or lost without authorization.

[0131] Thus far, the technical solutions of the present application have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is readily understood by those skilled in the art that the scope of protection of the present application is obviously not limited to these specific embodiments. Without departing from the principles of the present application, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present application.

Claims

1. A method for planning a charging path, applied to a driving device, characterized in that: include: Obtain the resource attributes of each energy replenishment resource on each path between the starting point and the end point, as well as the mileage from the starting point and the total mileage of each path; Based on the resource attributes of the energy replenishment resources and the mileage from the starting point, dynamic planning is performed to obtain recommended energy replenishment resources on each path; The resource dimension cost of each path is obtained based on the resource attributes of the recommended energy replenishment resources on each path; the cost of the path away from the starting point is obtained based on the mileage of the recommended energy replenishment resources closest to the starting point on each path; the mileage dimension cost of each path is obtained based on the total mileage of each path; Based on the resource dimension cost, the cost of being away from the starting point, and the mileage dimension cost, the comprehensive cost of each path of the driving device from the starting point to the end point is obtained; The energy replenishment path planning is performed according to the comprehensive cost of each path.

2. The method according to claim 1, characterized in that The step of obtaining the resource attributes of each energy replenishment resource on each path between the starting point and the end point, the mileage from the starting point, and the total mileage of each path, wherein obtaining the resource attributes of each energy replenishment resource includes: Obtaining a resource attribute influencing factor of each energy replenishment resource based on the priority of each resource attribute, wherein the resource attribute influencing factor includes an attribute factor and a location factor; The attribute factors include at least a resource type factor, a resource rating factor and a charging speed factor.

3. The method according to claim 2, characterized in that The obtaining the resource dimension cost of the path based on the resource attribute of the recommended energy replenishment resource on each path includes: The analytic hierarchy process is used to obtain the weights corresponding to the influencing factors of each resource attribute; Based on the resource attribute influencing factors of the recommended energy replenishment resources on each path and the weights corresponding to the resource attribute influencing factors, the resource dimension cost of the path is obtained.

4. The method according to claim 3, characterized in that The method of using the hierarchical analysis method to obtain the weights corresponding to the influencing factors of each resource attribute includes: The resource attribute influencing factors are sorted, a positive reciprocal matrix is ​​constructed, weights are solved, and consistency is checked.

5. The method according to any one of claims 3 to 4, characterized in that: The obtaining of the resource dimension cost of the path based on the resource attribute influencing factors of the recommended energy replenishment resources on each path and the weights corresponding to the resource attribute influencing factors includes: Based on the resource attribute influencing factor corresponding to each resource attribute, the weight corresponding to each resource attribute influencing factor, and a preset first balancing parameter, obtaining a first resource cost for each resource attribute; The resource dimension cost of the path is obtained based on the sum of the first resource cost of each resource attribute of the recommended energy replenishment resource on each path.

6. The method according to claim 1, characterized in that The step of obtaining the distance-from-starting-point cost of each path based on the mileage from the starting point to the recommended energy replenishment resource closest to the starting point on each path includes: The cost X of being away from the starting point is obtained based on the distance M from the starting point of the recommended energy replenishment resource closest to the starting point on the path, the remaining cruising range P of the driving device, the preset second balance parameter g and the preset distance sensitive parameter h, Where a is the adjustment parameter and 0<a<1.

7. The method according to claim 1, characterized in that The obtaining the mileage dimension cost of each path based on the total mileage of each path includes: The mileage dimension cost of the path is obtained based on the total mileage of each path and a preset third balance parameter.

8. A computer-readable storage medium storing a plurality of program codes, characterized in that: The program code is suitable for being loaded and run by a processor to execute the energy replenishment path planning method according to any one of claims 1 to 7.

9. An electronic device, characterized in that: include: at least one processor; and, a memory communicatively coupled to the at least one processor; Wherein, a computer program is stored in the memory, and when the computer program is executed by the at least one processor, the energy replenishment path planning method described in any one of claims 1 to 7 is implemented.

10. A driving device, characterized in that: It comprises a driving device body and the electronic device described in claim 9.

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