Cloud platform-based vehicle-to-vehicle charging method, device, and cloud platform server

Abstract

The present application relates to the field of vehicle charging technology, and in particular to a vehicle-to-vehicle charging method, device, and cloud platform server based on a cloud platform. The method comprises: obtaining charging demand information and serviceable vehicle information of any required vehicle; determining the best service vehicle among the serviceable vehicles that meets the charging needs of the required vehicle based on the charging demand information and serviceable vehicle information, planning the pairing position and common driving path of the required vehicle and the best service vehicle, and sending it to the required vehicle and the best service vehicle, so that the required vehicle and the best service vehicle are connected for charging at the pairing position, and while driving based on the common driving path, the best service vehicle is used to charge the required vehicle. This solves the problem of high charging delay in the related art, where a dedicated charging vehicle is usually used to charge electric vehicles.

Description

Technical Field

[0001] The present application relates to the field of vehicle charging technology, and in particular to a vehicle-to-vehicle charging method and device based on a cloud platform, and a cloud platform server. Background Art

[0002] Compared to traditional vehicles, electric vehicles produce lower greenhouse gas emissions throughout their lifecycle. Electrification is a key development direction for future transportation systems. However, electric vehicles have drawbacks such as limited driving range and long charging times. To address these shortcomings, the current main solution is to build a large-scale charging station infrastructure and establish a charging station network. However, the construction, maintenance, and management costs of charging stations are high, especially in urban areas with high travel demand and scarce land resources. Some automakers have also addressed range anxiety and limited charging station availability by equipping electric vehicles with large-capacity batteries. However, high-capacity batteries are expensive and heavy, further increasing energy consumption.

[0003] In related technologies, by receiving a charging request, the road conditions are analyzed based on the information carried by the charging vehicle and the charging request, and finally the meeting point between the car to be charged and the charging vehicle is determined based on the road conditions, so that the charging vehicle starts charging the car to be charged at the meeting point, thereby improving the agility of the car when charging while driving.

[0004] However, the related technology uses a dedicated charging vehicle to charge electric vehicles individually, and it is a physically connected wired charging mode, without considering the issues of network management and energy sharing. Summary of the Invention

[0005] The present application provides a vehicle-to-vehicle charging method, device, cloud platform server and storage medium based on a cloud platform to solve the problem that a dedicated charging vehicle is usually used to charge electric vehicles individually in the related art, resulting in high charging delays and other problems.

[0006] The first aspect of the present application provides a vehicle-to-vehicle charging method based on a cloud platform, comprising the following steps: obtaining charging demand information and serviceable vehicle information of any demand vehicle; determining the best service vehicle among the serviceable vehicles that meets the charging demand of the demand vehicle based on the charging demand information and serviceable vehicle information, and planning the pairing position and common driving path of the demand vehicle and the best service vehicle; sending the pairing position and the common driving path to the demand vehicle and the best service vehicle, so that after the demand vehicle and the best service vehicle are connected for charging at the pairing position and travel based on the common driving path, the demand vehicle is charged by the best service vehicle.

[0007] Optionally, in one embodiment of the present application, determining the best service vehicle among the serviceable vehicles that meets the charging needs of the demand vehicle based on the charging demand information and the serviceable vehicle information includes: collecting vehicle information of all serviceable vehicles to obtain an information set; calculating the initial distance, the maximum path overlap distance, and / or the actual power of the serviceable vehicle between each serviceable vehicle in the information set and the demand vehicle in turn; if any of the initial distance, the path overlap distance and the actual power does not meet the preset service conditions, determining that the serviceable vehicle and the demand vehicle are not matched; if the initial distance, the path overlap distance and the actual power all meet the preset service conditions, calculating the matching index between the serviceable vehicle and the demand vehicle based on the initial distance, the path overlap distance and the actual power; and determining the best service vehicle among the vehicles that meet the preset service conditions based on the matching index.

[0008] Optionally, in one embodiment of the present application, the maximum path overlap distance between the serviceable vehicle and the demand vehicle is calculated, including: using a preset K shortest path algorithm to calculate K travel paths for the serviceable vehicle and the demand vehicle respectively; determining the two paths with the longest path overlap distance between the serviceable vehicle and the demand vehicle from the K travel paths, and using the overlap distance of the two paths as the maximum path overlap distance between the serviceable vehicle and the demand vehicle.

[0009] Optionally, in one embodiment of the present application, after the demand vehicle is charged by the best service vehicle, it also includes: after detecting that charging is completed, generating a charging fee based on the charging power of the best service vehicle; sending the charging fee to the demand vehicle, and after the demand vehicle pays the charging fee, sending the charging fee to the preset account of the best service vehicle.

[0010] The second aspect of the present application provides a vehicle-to-vehicle charging device based on a cloud platform, including: an acquisition module for acquiring charging demand information and serviceable vehicle information of any demand vehicle; a planning module for determining the best service vehicle among the serviceable vehicles that meets the charging demand of the demand vehicle based on the charging demand information and serviceable vehicle information, and planning the pairing position and common driving path of the demand vehicle and the best service vehicle; a charging module for sending the pairing position and the common driving path to the demand vehicle and the best service vehicle, so that after the demand vehicle and the best service vehicle are connected for charging at the pairing position and travel based on the common driving path, the demand vehicle is charged by the best service vehicle.

[0011] Optionally, in one embodiment of the present application, the planning module includes: a collection unit for collecting vehicle information of all serviceable vehicles to obtain an information set; a calculation unit for sequentially calculating the initial distance, the maximum path overlap distance, and / or the actual power of the serviceable vehicle between each serviceable vehicle in the information set and the demand vehicle; a judgment unit for determining that there is no match between the serviceable vehicle and the demand vehicle when any of the initial distance, the path overlap distance and the actual power does not meet the preset service conditions; when the initial distance, the path overlap distance and the actual power all meet the preset service conditions, calculating the matching index between the serviceable vehicle and the demand vehicle based on the initial distance, the path overlap distance and the actual power; a determination unit for determining the best service vehicle among the vehicles that meet the preset service conditions based on the matching index.

[0012] Optionally, in one embodiment of the present application, the calculation unit is further used to calculate the K travel paths of the serviceable vehicle and the demand vehicle respectively using a preset K shortest path algorithm; determine the two paths with the longest path overlap distance between the serviceable vehicle and the demand vehicle from the K travel paths, and use the overlap distance of the two paths as the maximum path overlap distance between the serviceable vehicle and the demand vehicle.

[0013] Optionally, in one embodiment of the present application, it also includes: a sending module, which is used to generate a charging fee based on the charging power of the best service vehicle after the demand vehicle is charged by the best service vehicle and after detecting that the charging is completed; send the charging fee to the demand vehicle, and after the demand vehicle pays the charging fee, send the charging fee to the preset account of the best service vehicle.

[0014] The third embodiment of the present application provides a cloud platform server, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the vehicle-to-vehicle charging method of the cloud platform as described in the above embodiment.

[0015] The fourth aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, which is executed by a processor to implement the vehicle-to-vehicle charging method of the cloud platform as described in the above embodiment.

[0016] Therefore, this application has at least the following beneficial effects:

[0017] After obtaining the charging requirements and available vehicle information for any vehicle in need, the cloud platform determines the optimal vehicle among the available vehicles that meets the charging needs of the vehicle in need. A shared driving route is then planned, and power is transferred via physical or wireless connections during the shared driving process, reducing charging delays and the scale of charging station construction. This solves the problem of high charging delays that often occurs in related technologies, where dedicated charging vehicles are used to charge electric vehicles individually.

[0018] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0020] Figure 1 This is a flow chart of a vehicle-to-vehicle charging method based on a cloud platform provided according to an embodiment of the present application;

[0021] Figure 2 A flow chart of a vehicle pairing algorithm provided according to an embodiment of the present application;

[0022] Figure 3 A flowchart of the Dijkstra algorithm provided according to an embodiment of the present application;

[0023] Figure 4 A schematic diagram of a calculation example provided according to an embodiment of the present application;

[0024] Figure 5 Schematic diagram of a car-to-car charging device based on a cloud platform according to an embodiment of the present application;

[0025] Figure 6 This is a schematic diagram of the structure of a cloud platform server provided according to an embodiment of the present application.

[0026] Description of the reference numerals: acquisition module-100, planning module-200, charging module-300, memory-601, processor-602, communication interface-603. DETAILED DESCRIPTION

[0027] The following describes in detail embodiments of the present application, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0028] The following describes the car-to-car charging method, device, cloud platform server and storage medium based on the cloud platform of the embodiment of the present application with reference to the accompanying drawings. In response to the problems mentioned in the above background technology, the present application provides a car-to-car charging method based on the cloud platform. In this method, after obtaining the charging demand information and serviceable vehicle information of any demand vehicle, the cloud platform is used to determine the best service vehicle that meets the charging demand of the demand vehicle among the serviceable vehicles, and a common driving path is planned. The power transmission is completed during their common driving process through any physical or wireless connection, thereby reducing charging delays and the scale of charging pile construction. In this way, the problem of high charging delays and the like in the related art, which is usually solved by using a special charging vehicle to charge electric vehicles, is solved.

[0029] Specifically, Figure 1 A flow chart of a vehicle-to-vehicle charging method based on a cloud platform provided in an embodiment of the present application.

[0030] like Figure 1 As shown, the cloud platform-based vehicle-to-vehicle charging method includes the following steps:

[0031] In step S101 , the charging demand information and serviceable vehicle information of any demanding vehicle are obtained.

[0032] In a regional transportation network, electric vehicles with sufficient energy can upload their available energy information and travel information to the cloud platform. Vehicles with lower energy levels that need charging can also publish their demand information through the cloud platform. This embodiment of the application can obtain the charging demand information and serviceable vehicle information of any electric vehicle in a regional network, and through the energy cloud sharing service, enable vehicles that need charging to purchase energy from any nearby vehicles, thereby alleviating the range anxiety of pure electric vehicles and reducing the construction scale of the charging pile system to a certain extent.

[0033] In the embodiment of the present application, the vehicle with sufficient electric energy v j The information released through the cloud platform mainly includes the vehicle's real-time charge E j , its own real-time location information O j and your own travel destination D j ; Vehicles to be charged v r The demand information uploaded through the cloud platform mainly includes the real-time location information of the demand vehicle. r , power demand E r and your own travel destination D r ; During the actual implementation process, when the cloud platform receives vehicle charging demand information, the server can immediately collect information on vehicles with sufficient power within a certain range around the demand vehicle for calculation of the matching algorithm; when the cloud platform receives vehicle charging demand information, it can analyze the demand in real time and further match charging service vehicles through algorithms.

[0034] In step S102, the best service vehicle that meets the charging demand of the demand vehicle is determined among the serviceable vehicles according to the charging demand information and the serviceable vehicle information, and the pairing position and common driving path of the demand vehicle and the best service vehicle are planned.

[0035] It can be understood that the embodiments of the present application can analyze vehicle demand information and serviceable vehicle information, match the most suitable charging service vehicle for the demand vehicle through an algorithm, and plan the pairing position and common driving path of the paired vehicles through an algorithm based on the pairing information, so that the power transmission can be completed during the common driving process, thereby reducing charging delays.

[0036] In one embodiment of the present application, the best service vehicle among the serviceable vehicles that meets the charging demand of the demand vehicle is determined based on the charging demand information and the serviceable vehicle information, including: collecting the vehicle information of all serviceable vehicles to obtain an information set; sequentially calculating the initial distance, the maximum path overlap distance, and / or the actual power of the serviceable vehicle between each serviceable vehicle and the demand vehicle in the information set; if any of the initial distance, the path overlap distance and the actual power does not meet the preset service conditions, it is determined that the serviceable vehicle and the demand vehicle are not matched; if the initial distance, the path overlap distance and the actual power all meet the preset service conditions, the matching index between the serviceable vehicle and the demand vehicle is calculated based on the initial distance, the path overlap distance and the actual power; and the best service vehicle among the vehicles that meet the preset service conditions is determined based on the matching index.

[0037] The preset service conditions may include the following aspects:

[0038] 1) When demand occurs, service vehicle v j and demand charging vehicles v r The distance is within a certain range L0; when the distance between the two is too far, the vehicle in front may need to stop and wait, which will cause a large delay and may have a significant impact on road traffic.

[0039] 2) When demand occurs, service vehicle v j Instant power E j On the premise of meeting its own subsequent driving needs, it can provide the required power E of the service vehicle r .

[0040] 3) When the demand occurs, the service vehicle v j and demand charging vehicles v r The subsequent driving paths of the two coincide with each other, and the length of the coincident path is L[R(v r ),R(v j )] is enough to complete the charging process.

[0041] In the actual implementation process, when the demand occurs, the demand charging vehicle v r When there are multiple service vehicles that meet the above conditions within the L0 range of the present application, the embodiment of the application can rely on the matching index P(v r ,v j ) to select the most appropriate service vehicle.

[0042] Specifically, the embodiment of the present application can determine the best service vehicle among the serviceable vehicles that meets the charging needs of the demand vehicle through the cloud platform matching algorithm, such as Figure 2 As shown, the following steps are included:

[0043] 1) When a charging request is generated, the cloud platform server will need to charge the vehicle v r The surrounding service vehicle information is aggregated into a set V (v1, v2, ..., v j ,…,v V ). Initialize j = 1;

[0044] 2) Calculate service vehicle v j and demand charging vehicles v r The initial distance d(v r ,v j );

[0045] 3) Determine d(v r ,v j )>d0?Yes:P(v r ,v j )=0 If true, go to 8); otherwise go to 4);

[0046] 4) Use K shortest path algorithm (K=3) to calculate v j With v r The three most likely travel paths are found, and the two paths with the longest overlapping distance R(v j ) and R(v r );

[0047] 5) According to the following formula (1), determine R(v j ) and R(v r ) of the overlap distance L[R(v j ),R(v r )]>L min (v j ,v r ), if true, go to 6); otherwise P(v r ,v j )=0 and go to 8);

[0048]

[0049] 6) Determine E according to the following formula (2) j >E u , if true, go to 7); otherwise P(v r ,v j )=0;

[0050]

[0051] 7) Calculate P(v) by the following formula (3) r ,v j );

[0052]

[0053] 8) j = j + 1;

[0054] 9) Determine v j ∈V, if it holds, go to 2); otherwise, end the loop and output the optimal solution according to the following formulas (4) and (5).

[0055]

[0056]

[0057] In the above formulas, L min (v r ,v j ) is the shortest distance threshold for the two vehicles to complete charging; u t is the upper speed limit of the road section; u d is the lower speed limit of the road section; is the average speed of the trip; p c is the charging power; E r The required charging amount; d(v r ,v j ) is v r With v j The initial distance; is the safety factor, L(R j ) is the vehicle v j The length of the path to the destination; e j For vehicle v j The average energy consumption per unit length on the path; η is the energy efficiency of charging, η<1; β is the safety factor, β>1; v op For the best service vehicle.

[0058] In step S103, the pairing position and the common driving route are sent to the demand vehicle and the best service vehicle, so that the demand vehicle and the best service vehicle are connected for charging at the pairing position, and the demand vehicle is charged by the best service vehicle while traveling based on the common driving route.

[0059] The embodiment of the present application can send subsequent driving path and pairing position information to the demand vehicle and the service vehicle respectively, and drive according to the received speed and path planning information until the two meet at the pairing position on the path to complete the pairing, and start driving together. Through any physical or wireless connection, electric energy is transmitted from the electric vehicle that can provide energy to the vehicle that needs to be charged, thereby alleviating the mileage anxiety problem of pure electric vehicles and reducing the construction scale of the charging pile system to a certain extent.

[0060] In one embodiment of the present application, after the demand vehicle is charged by the best service vehicle, it also includes: after detecting that charging is completed, generating a charging fee based on the charging power of the best service vehicle; sending the charging fee to the demand vehicle, and after the demand vehicle pays the charging fee, sending the charging fee to the preset account of the best service vehicle.

[0061] In one embodiment of the present application, the maximum path overlap distance between the serviceable vehicle and the demand vehicle is calculated, including: using a preset K shortest path algorithm to calculate K travel paths for the serviceable vehicle and the demand vehicle respectively; determining the two paths with the longest path overlap distance between the serviceable vehicle and the demand vehicle from the respective K travel paths, and using the overlap distance of the two paths as the maximum path overlap distance between the serviceable vehicle and the demand vehicle.

[0062] Specifically, the embodiment of the present application can use the K shortest path algorithm to calculate the most likely travel path between the serviceable vehicle and the demand vehicle, and find the two paths with the longest overlapping distance as the maximum path overlap distance between the serviceable vehicle and the demand vehicle, and then transmit power from the serviceable vehicle to the demand vehicle through any physical or wireless connection, so as to ensure that there is enough time to complete charging within the overlapping distance between the two. The embodiment of the present application can use the K shortest path algorithm (K=3) to calculate the three most likely travel paths for the vehicle to be charged and the service vehicle respectively. The steps of the K shortest path algorithm (K=3) are as follows:

[0063] 1) Input the adjacency matrix M of the road network. The embodiment of the present application can be based on the Dijkstra algorithm, such as Figure 3 As shown, calculate the shortest path length Dijkstra(i,j) between any two points ij in the road network;

[0064] 2) Input the starting point O, D and K value of the K-shortest path; O∈M, D∈M, num=1;

[0065] 3) For each node p x , define a four-dimensional array Among them, F(p x ) is from O through px The shortest path length to D; G(p x ) is the distance from O to p x The shortest path length; H(p x ) is from p x The length of the shortest path to D; For p x The parent node of p x The previous node number;

[0066] 4) Define two empty lists: open_list and close_list;

[0067] 5) Put the starting point O into open_list and calculate the corresponding four-dimensional number (Dijkstra(O,D),0,Dijkstra(O,D),O)

[0068] 6) Traverse all nodes in open_list and find F(p x ) value is the smallest node, and is selected as the current node p now , and move this node from open_list to close_list;

[0069] 7) Find the node with the current node p now All connected nodes p x , with p now As p x The parent node of , updates its corresponding array according to formulas (6) to (9);

[0070]

[0071] F(p x )=G(p x )+F(p x ) Formula (7)

[0072]

[0073] H(p x )=Dijkstra(p x ,D) Formula (9)

[0074] 8) The adjacent node p x Add to open_list, if p x Already exists in open_list, then use Distinguish, p x and They are the same node in the road network, but may have different parent nodes, F values, and G values.

[0075] 9) Determine the current node p now =D, if yes: go to 10); otherwise: go to 6);

[0076] 10) According to p now =D parent node information, search upward in sequence, and generate the path set from O to D now ;

[0077] 11) Determine the path set path now Does it contain duplicate nodes? If yes, go to step 6); otherwise, go to step 12.

[0078] 12) Output num short circuit: path now ;

[0079] 13) num = num + 1;

[0080] 14) Is num > K? If yes: end the process; otherwise: go to step 6).

[0081] in, For node p x and its parent node Length of the road section between

[0082] It is understandable that in the embodiment of the present application, after charging is completed, the cloud platform calculates the fee based on the charging power, the charging car pays the fee through the cloud platform, and the electric car that provides energy charges the corresponding fee through the cloud platform.

[0083] The following describes in detail the vehicle-to-vehicle charging method based on the cloud platform in the embodiment of the present application in conjunction with a specific embodiment. Figure 4 As shown in Table 1, under the current road network, a vehicle that needs charging sends a charging request to the cloud platform, which instantly obtains the information of the requesting vehicle and the information of all vehicles that can provide charging services within a radius of 1.5km. Table 1 is the vehicle information table.

[0084] Table 1

[0085]

[0086] The main calculation parameters involved in the example are shown in Table 2, where Table 2 is the parameter setting table.

[0087] Table 2

[0088]

[0089] The embodiment of the present application uses the K (K=3) shortest path algorithm to calculate the three possible travel paths for all vehicles within the area, and determines the maximum overlap distance between the travel paths of all available vehicles and the paths of the demanding vehicle. The results are shown in Table 3. Table 3 is a vehicle travel path information table.

[0090] Table 3

[0091]

[0092] Furthermore, based on the parameters set in Table 2 and the calculation results in Table 3, we calculated and determined whether the initial distance, path overlap length, and initial power of all available service vehicles met the requirements, and then calculated the matching degree between each service vehicle and the demand vehicle. The results are shown in Table 4. Table 4 is a matching degree calculation table.

[0093] Table 4

[0094]

[0095] According to the calculation results in Table 4, the analysis is as follows. First, in the initial vehicle distance judgment, vehicle v5 is closer to the required vehicle v r The straight-line distance between them is only 1.2km, but they are not on the same road. The path distance between them is far, and the time required for them to merge is too long, so they are not suitable for pairing. Based on the distance between the demand vehicle and different service vehicles, the overlapping paths and the required charging amount, it is calculated that the shortest path overlap distance required for 7 vehicles such as v1-v7 to complete the charging service is close, but the actual overlapping paths between v3, v4 and v6 and the demand vehicle are short. If they are selected as service vehicles, they need to change their original travel paths to a large extent, causing unnecessary delays, so they are not suitable for pairing with v r Based on the battery capacity, current SOC and vehicle energy consumption parameters of each vehicle, it is calculated that the current charge of v2 is relatively low. If the service is completed, there is a risk of not being able to complete its own trip, so it is not suitable to be selected as a service vehicle; finally, v1 and v7 are compared with vehicle v r The vehicle v1 with higher matching degree is selected as the service vehicle. Then the cloud platform sends r Send the subsequent driving route: 16-21-25-32-39, and prompt v r The vehicle speed is reduced and v1 increases until the two meet on the path and complete pairing, then start driving together and transmit electricity from the electric vehicle that can provide energy to the car that needs charging through any physical or wireless connection. When charging is completed, the cloud platform calculates the fee based on the charging power. The charging car pays the fee through the cloud platform, and the electric vehicle that provides energy collects the corresponding fee through the cloud platform.

[0096] According to the cloud-based vehicle-to-vehicle charging method proposed in the embodiments of this application, after obtaining the charging requirements and available vehicle information of any requesting vehicle, the cloud platform determines the best available vehicle that meets the charging needs of the requesting vehicle. A shared driving route is then planned, and power is transferred via any physical or wireless connection during the shared driving process, reducing charging delays and the scale of charging station construction. This solves the problem of high charging delays that is common in related technologies, where dedicated charging vehicles are often used to charge electric vehicles individually.

[0097] Next, a vehicle-to-vehicle charging device based on a cloud platform according to an embodiment of the present application will be described with reference to the accompanying drawings.

[0098] Figure 5 It is a block diagram of a cloud platform-based vehicle-to-vehicle charging device according to an embodiment of the present application.

[0099] like Figure 5 As shown, the cloud platform-based vehicle-to-vehicle charging device 10 includes: an acquisition module 100 , a planning module 200 and a charging module 300 .

[0100] Among them, the acquisition module 100 is used to obtain the charging demand information and serviceable vehicle information of any demand vehicle; the planning module 200 is used to determine the best service vehicle among the serviceable vehicles that meets the charging demand of the demand vehicle based on the charging demand information and serviceable vehicle information, and plan the pairing position and common driving path of the demand vehicle and the best service vehicle; the charging module 300 is used to send the pairing position and common driving path to the demand vehicle and the best service vehicle, so that after the demand vehicle and the best service vehicle are connected for charging at the pairing position, and while traveling based on the common driving path, the demand vehicle is charged by the best service vehicle.

[0101] In one embodiment of the present application, the planning module 200 includes: a collection unit, a judgment unit, and a determination unit.

[0102] Among them, the collection unit is used to collect vehicle information of all serviceable vehicles to obtain an information set; the calculation unit is used to calculate the initial distance, the maximum path overlap distance, and / or the actual power of the serviceable vehicle between each serviceable vehicle and the demand vehicle in the information set in turn; the judgment unit is used to determine that there is no match between the serviceable vehicle and the demand vehicle when any of the initial distance, path overlap distance and actual power does not meet the preset service conditions; when the initial distance, path overlap distance and actual power all meet the preset service conditions, the matching index between the serviceable vehicle and the demand vehicle is calculated based on the initial distance, path overlap distance and actual power; the determination unit is used to determine the best service vehicle among the vehicles that meet the preset service conditions based on the matching index.

[0103] In one embodiment of the present application, the calculation unit is further used to calculate K travel paths for the serviceable vehicle and the demand vehicle respectively using a preset K shortest path algorithm; determine the two paths with the longest path overlap distance between the serviceable vehicle and the demand vehicle from the K travel paths, and use the overlap distance of the two paths as the maximum path overlap distance between the serviceable vehicle and the demand vehicle.

[0104] Optionally, in one embodiment of the present application, the device 10 of the embodiment of the present application also includes: a sending module, which is used to generate a charging fee based on the charging power of the best service vehicle after the demand vehicle is charged by the best service vehicle and after detecting that the charging is completed; send the charging fee to the demand vehicle, and after the demand vehicle pays the charging fee, send the charging fee to the preset account of the best service vehicle.

[0105] It should be noted that the aforementioned explanation of the embodiment of the cloud platform-based vehicle-to-vehicle charging method is also applicable to the cloud platform-based vehicle-to-vehicle charging device of this embodiment, and will not be repeated here.

[0106] According to the cloud-based vehicle-to-vehicle charging device proposed in the embodiments of this application, after obtaining the charging requirements and available vehicle information of any requesting vehicle, the cloud platform determines the best available vehicle that meets the charging needs of the requesting vehicle, plans a common driving route, and completes power transmission during the shared driving process through any physical or wireless connection, thereby reducing charging delays and the scale of charging station construction. This solves the problem of high charging delays caused by the use of dedicated charging vehicles for single-vehicle charging in related technologies.

[0107] Figure 6 This is a schematic diagram of the structure of the cloud platform server provided in an embodiment of the present application. The cloud platform server may include:

[0108] A memory 601 , a processor 602 , and a computer program stored in the memory 601 and executable on the processor 602 .

[0109] When the processor 602 executes the program, the cloud platform-based vehicle-to-vehicle charging method provided in the above embodiment is implemented.

[0110] Furthermore, the cloud platform server also includes:

[0111] The communication interface 603 is used for communication between the memory 601 and the processor 602 .

[0112] The memory 601 is used to store computer programs that can be run on the processor 602 .

[0113] The memory 601 may include a high-speed RAM (Random Access Memory) memory, and may also include a non-volatile memory, such as at least one disk memory.

[0114] If the memory 601, the processor 602, and the communication interface 603 are implemented independently, the communication interface 603, the memory 601, and the processor 602 can be connected to each other via a bus and communicate with each other. The bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 6 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0115] Optionally, in a specific implementation, if the memory 601, the processor 602 and the communication interface 603 are integrated on a chip, the memory 601, the processor 602 and the communication interface 603 can communicate with each other through an internal interface.

[0116] The processor 602 may be a CPU (Central Processing Unit), or an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present application.

[0117] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned cloud platform-based vehicle-to-vehicle charging method.

[0118] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0119] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of technical features indicated. Thus, a feature specified as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of this application, "N" means at least two, for example, two, three, etc., unless otherwise specifically defined.

[0120] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application belong.

[0121] It should be understood that various parts of the present application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiment, the N steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array, a field programmable gate array, etc.

[0122] Those skilled in the art will understand that all or part of the steps in the method of the above embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0123] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A vehicle-to-vehicle charging method based on a cloud platform, characterized in that: The following steps are involved: Obtain charging demand information and serviceable vehicle information of any required vehicle; Determine the best service vehicle among the serviceable vehicles that meets the charging demand of the demand vehicle based on the charging demand information and the serviceable vehicle information, and plan a pairing position and a common driving path between the demand vehicle and the best service vehicle; Sending the pairing location and the common driving route to the demand vehicle and the best serving vehicle, so that after the demand vehicle and the best serving vehicle are connected for charging at the pairing location and travel along the common driving route, the demand vehicle is charged by the best serving vehicle; The method of determining the best service vehicle among the serviceable vehicles that meets the charging demand of the demand vehicle based on the charging demand information and the serviceable vehicle information includes: collecting vehicle information of all serviceable vehicles to obtain an information set; sequentially calculating the initial distance, the maximum path overlap distance, and / or the actual power of the serviceable vehicle between each serviceable vehicle in the information set and the demand vehicle; if any of the initial distance, the path overlap distance, and the actual power does not meet a preset service condition, determining that the serviceable vehicle and the demand vehicle are not matched; if the initial distance, the path overlap distance, and the actual power all meet the preset service condition, calculating a matching index between the serviceable vehicle and the demand vehicle based on the initial distance, the path overlap distance, and the actual power; and determining the best service vehicle among the vehicles that meet the preset service condition based on the matching index; The preset service conditions may include the following aspects: The distance between the serviceable vehicle and the vehicle requiring charging is within the preset distance; The instantaneous power of the service vehicle can provide the required power of the serviced vehicle while meeting its own subsequent driving needs; The subsequent driving paths of the serviceable vehicle and the vehicle requiring charging overlap, and the length of the overlapping paths is sufficient to complete the charging process; When there are multiple serviceable vehicles that meet the preset service conditions within the preset distance range of the vehicle requiring charging, the best service vehicle among the vehicles that meet the preset service conditions is determined based on the matching index, wherein the matching index is calculated as follows: Among them, P(v r ,v j ) matching index, v j is the serviceable vehicle, v r Charging vehicles for demand, L min (v r ,v j ) is the shortest distance threshold between the serviceable vehicle and the demand vehicle for charging to be completed, d0 is the preset distance between the serviceable vehicle and the demand vehicle, L(v r , v j ) is the initial distance between the serviceable vehicle and the demand vehicle, R(v j ) is the first path with the longest overlap distance, R(v r ) is the second path with the longest overlap distance, E j The instantaneous amount of power available for service, E r The amount of electricity required to charge the vehicle; Calculating the maximum path overlap distance between the serviceable vehicle and the demand vehicle, including: using a preset K shortest path algorithm to calculate K travel paths for the serviceable vehicle and the demand vehicle respectively; determining two paths with the longest path overlap distance between the serviceable vehicle and the demand vehicle from the respective K travel paths, and using the overlap distance of the two paths as the maximum path overlap distance between the serviceable vehicle and the demand vehicle.

2. The method according to claim 1, characterized in that After charging the demand vehicle by using the best service vehicle, the method further includes: After detecting that charging is completed, generating a charging fee according to the charging power of the best service vehicle; The charging fee is sent to the requesting vehicle, and after the requesting vehicle pays the charging fee, the charging fee is sent to a preset account of the best service vehicle.

3. A vehicle-to-vehicle charging device based on a cloud platform, characterized in that: include: The acquisition module is used to obtain the charging demand information and serviceable vehicle information of any required vehicle; a planning module, configured to determine the best service vehicle among the serviceable vehicles that meets the charging requirements of the requesting vehicle based on the charging requirement information and the serviceable vehicle information, and plan a pairing position and a common driving path between the requesting vehicle and the best service vehicle; a charging module, configured to transmit the pairing location and the common driving route to the demand vehicle and the best serving vehicle, so that after the demand vehicle and the best serving vehicle are connected for charging at the pairing location and travel along the common driving route, the demand vehicle is charged by the best serving vehicle; The planning module includes: A collection unit, used to collect vehicle information of all serviceable vehicles to obtain an information set; a calculation unit, configured to sequentially calculate an initial distance between each serviceable vehicle in the information set and the demand vehicle, a maximum path overlap distance, and / or an actual power level of the serviceable vehicle; a judgment unit, configured to determine that the serviceable vehicle and the demand vehicle are not matched when any of the initial distance, the path overlap distance, and the actual power level do not satisfy a preset service condition; and to calculate a matching index between the serviceable vehicle and the demand vehicle based on the initial distance, the path overlap distance, and the actual power level when all of the initial distance, the path overlap distance, and the actual power level satisfy the preset service condition; A determination unit, configured to determine the best service vehicle among the vehicles meeting the preset service conditions according to the matching index; The preset service conditions may include the following aspects: The distance between the serviceable vehicle and the vehicle requiring charging is within the preset distance; The instantaneous power of the service vehicle can provide the required power of the serviced vehicle while meeting its own subsequent driving needs; The subsequent driving paths of the serviceable vehicle and the vehicle requiring charging overlap, and the length of the overlapping paths is sufficient to complete the charging process; When there are multiple serviceable vehicles that meet the preset service conditions within the preset distance range of the vehicle requiring charging, the best service vehicle among the vehicles that meet the preset service conditions is determined based on the matching index, wherein the matching index is calculated as follows: Among them, P(v r ,v j ) matching index, v j are the serviceable vehicles j, v r Charging vehicle r, L for demand min (v r ,v j ) is the shortest distance threshold between the serviceable vehicle and the demand vehicle for charging to be completed, d0 is the preset distance between the serviceable vehicle and the demand vehicle, L(v r ,v j ) is the initial distance between the serviceable vehicle and the demand vehicle, R(v j ) is the first path with the longest overlap distance, R(v r ) is the second path with the longest overlap distance, E j The instantaneous amount of power available for service, E r The amount of electricity required to charge the vehicle; The computing unit is further configured to: A preset K shortest path algorithm is used to calculate K travel paths for each of the serviceable vehicle and the demand vehicle; the two paths with the longest path overlap distance between the serviceable vehicle and the demand vehicle are determined from the respective K travel paths, and the overlap distance of the two paths is used as the maximum path overlap distance between the serviceable vehicle and the demand vehicle.

4. The device according to claim 3, characterized in that Also includes: a sending module, configured to generate a charging fee according to the charging power of the best service vehicle after detecting completion of charging after the best service vehicle is used to charge the demand vehicle; The charging fee is sent to the requesting vehicle, and after the requesting vehicle pays the charging fee, the charging fee is sent to a preset account of the best service vehicle.

5. A cloud platform server, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the vehicle-to-vehicle charging method of the cloud platform as claimed in claim 1 or 2.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the vehicle-to-vehicle charging method of the cloud platform as claimed in claim 1 or 2.

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