Battery replacement scheduling simulation method and device, readable storage medium and server
By setting configuration data and optimizing algorithms in the map interactive interface, the problem of insufficient adaptability of existing battery swapping scheduling simulation methods is solved, enabling flexible simulation modeling and result display, and improving the adaptability and user experience of battery swapping scheduling simulation.
Patent Information
- Application Number
- CN202410650169.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-05-23
- Publication Date
- 2025-11-25
AI Technical Summary
Existing battery swapping scheduling simulation methods are difficult to apply to complex and ever-changing battery swapping scheduling simulation tasks with different needs and scenarios.
By flexibly setting configuration data in the map interactive interface, the server performs dynamic simulation modeling and optimization solutions, and displays the simulation results in the map interactive interface. The optimization solution is performed by decoupling the optimization algorithm and the algorithm server, and an animation of the vehicle driving trajectory is generated.
It improves the adaptability and flexibility of battery swapping scheduling simulation, allowing users to easily and intuitively configure and display results, and supports complex and ever-changing simulation tasks.
Smart Images
Figure CN121010109A_ABST
Abstract
Description
Technical Field
[0001] This application belongs to the field of battery swapping dispatching technology, and in particular relates to a battery swapping dispatching simulation method, device, computer-readable storage medium and server. Background Technology
[0002] The widespread adoption of electric vehicles (EVs) is a crucial way to address current environmental pollution and the fossil fuel crisis. With the continuous development of related technologies, EVs have gradually become the mainstream in the transportation sector. EVs can be categorized into charging and battery swapping types based on their charging methods. Compared to the former, battery swapping EVs offer advantages such as shorter charging times, convenient charging methods, and smaller space requirements. Therefore, the demand for battery swapping is increasing, leading to issues such as long swapping times and insufficient battery reserves due to concentrated battery swapping activity. To improve the service quality of battery swapping stations, reduce their operating costs, and promote the development of EV battery swapping models, accurate simulation of EV battery swapping scheduling has become an urgent problem to solve. However, existing battery swapping scheduling simulation methods are often only applicable to specific battery swapping tasks and are difficult to apply to complex and varied battery swapping scheduling simulation tasks with different needs and scenarios. Summary of the Invention
[0003] In view of this, embodiments of this application provide a battery swapping scheduling simulation method, apparatus, computer-readable storage medium, and server to solve the problem that existing battery swapping scheduling simulation methods are difficult to apply to complex and ever-changing battery swapping scheduling simulation tasks in different needs and scenarios.
[0004] A first aspect of this application provides a battery swapping scheduling simulation method, applied in a server, the battery swapping scheduling simulation method may include:
[0005] Call the map service to display the map interface on the front-end device;
[0006] Obtain the configuration data corresponding to the battery swapping scheduling simulation task input via the map interaction interface;
[0007] Based on the configuration data, establish a battery swapping scheduling simulation model corresponding to the battery swapping scheduling simulation task;
[0008] The battery swapping scheduling simulation model is optimized and solved using a preset optimization algorithm to obtain the battery swapping scheduling simulation results corresponding to the battery swapping scheduling simulation task.
[0009] The battery swapping scheduling simulation results corresponding to the battery swapping scheduling simulation task are displayed in the map interaction interface.
[0010] Using the above method, the corresponding configuration data can be flexibly set through the map interaction interface of the front-end device according to different needs and complex and ever-changing battery swapping scheduling simulation tasks in different scenarios. The server can perform dynamic simulation modeling and optimization based on the configuration data, and display the battery swapping scheduling simulation results in the map interaction interface, thereby effectively improving the adaptability of battery swapping scheduling simulation.
[0011] In one specific implementation of the first aspect, before optimizing the battery swapping scheduling simulation model using a preset optimization algorithm to obtain the battery swapping scheduling simulation result corresponding to the battery swapping scheduling simulation task, the method may further include:
[0012] Obtain the update algorithm parameters corresponding to the optimization algorithm;
[0013] The optimization algorithm is updated according to the updated algorithm parameters to obtain the optimized algorithm with updated parameters.
[0014] Accordingly, the step of using a preset optimization algorithm to optimize and solve the battery swapping scheduling simulation model to obtain the battery swapping scheduling simulation results corresponding to the battery swapping scheduling simulation task may include:
[0015] The battery swapping scheduling simulation model is optimized and solved using the updated optimization algorithm to obtain the battery swapping scheduling simulation results corresponding to the battery swapping scheduling simulation task.
[0016] Using the above method, the algorithm parameters can be flexibly updated according to different needs and scenarios of complex and ever-changing battery swapping scheduling simulation tasks. The battery swapping scheduling simulation model can be dynamically optimized and solved based on the optimized algorithm after parameter update, thereby further improving the adaptability of battery swapping scheduling simulation.
[0017] In one specific implementation of the first aspect, obtaining the configuration data corresponding to the battery swapping scheduling simulation task input via the map interaction interface may include:
[0018] Obtain the starting point and ending point of the route input via the map interaction interface;
[0019] The map service is invoked to draw the simulation task route from the starting point to the ending point of the route in the map interactive interface;
[0020] According to the simulation task route, candidate battery swapping station coordinates are selected from the preset set of battery swapping station coordinates and displayed in the map interaction interface.
[0021] Obtain the battery swapping station configuration data of the candidate battery swapping station coordinates input via the map interaction interface.
[0022] The above methods can be used to assist users in inputting configuration data through a map-based interactive interface, making the data configuration process more convenient and intuitive, and effectively improving configuration efficiency.
[0023] In one specific implementation of the first aspect, establishing a battery swapping scheduling simulation model corresponding to the battery swapping scheduling simulation task based on the configuration data may include:
[0024] Based on the vehicle configuration data and battery swapping station configuration data in the configuration data, node modeling is performed on the vehicles and battery swapping stations to obtain the nodes in the battery swapping scheduling simulation model.
[0025] Based on the road network configuration data in the configuration data, the road edges are modeled to obtain the edges in the battery swapping scheduling simulation model;
[0026] Based on the relationships between nodes and edges in the battery swapping scheduling simulation model, an adjacency matrix corresponding to the battery swapping scheduling simulation model is generated; wherein, the adjacency matrix is used to indicate whether there are edges connecting the nodes.
[0027] Using the above methods, the nodes, edges, and adjacency matrices of the battery swapping scheduling simulation model can be modeled based on vehicle configuration data, battery swapping station configuration data, and road network configuration data, respectively. This allows the battery swapping scheduling simulation model to be flexibly adapted to changes in tasks, enabling more adaptive battery swapping scheduling simulations.
[0028] In one specific implementation of the first aspect, the step of using a preset optimization algorithm to optimize and solve the battery swapping scheduling simulation model to obtain the battery swapping scheduling simulation result corresponding to the battery swapping scheduling simulation task may include:
[0029] The battery swapping scheduling simulation model is stored in a preset file system, and the corresponding storage address is obtained;
[0030] The storage address is sent to a preset algorithm server; wherein, the algorithm server is used to read the battery swapping scheduling simulation model from the file system according to the storage address, and use a preset optimization algorithm to optimize and solve the battery swapping scheduling simulation model to obtain the battery swapping scheduling simulation result corresponding to the battery swapping scheduling simulation task.
[0031] Obtain the battery swapping scheduling simulation results sent by the algorithm server corresponding to the battery swapping scheduling simulation task.
[0032] Using the above method, the specific optimization solution process can be handed over to the algorithm server. The server and the algorithm are decoupled, and only overall management and control are required, thereby further improving the adaptability of battery swapping scheduling simulation.
[0033] In one specific implementation of the first aspect, displaying the battery swapping scheduling simulation results corresponding to the battery swapping scheduling simulation task on the map interaction interface may include:
[0034] Based on the battery swapping scheduling simulation results corresponding to the battery swapping scheduling simulation task, generate an animation of the vehicle's driving trajectory.
[0035] The vehicle's driving trajectory animation is played in the map interaction interface.
[0036] Using the above method, the simulation results of battery swapping scheduling can be visualized through a map interactive interface, allowing users to obtain the simulation results more conveniently and intuitively.
[0037] In one specific implementation of the first aspect, the battery swapping scheduling simulation method may further include:
[0038] In response to the command to view historical simulation results, determine the task identifier of the historical simulation task corresponding to the command to view historical simulation results;
[0039] Based on the task identifier, query the battery swapping scheduling simulation results corresponding to the historical simulation task in the preset database;
[0040] The battery swapping scheduling simulation results corresponding to the historical simulation tasks are displayed in the map interaction interface.
[0041] Using the above method, the corresponding simulation results can be queried and displayed in the database based on the task identifier of historical simulation tasks, making it more convenient and intuitive for users to view, compare and analyze past simulation results.
[0042] A second aspect of this application provides a battery swapping scheduling simulation device, applied in a server, wherein the battery swapping scheduling simulation may include:
[0043] The map service invocation module is used to invoke map services to display the map interactive interface on the front-end device;
[0044] The configuration data acquisition module is used to acquire the configuration data corresponding to the battery swapping scheduling simulation task input via the map interaction interface;
[0045] The simulation model building module is used to build a battery swapping scheduling simulation model corresponding to the battery swapping scheduling simulation task based on the configuration data.
[0046] The optimization and solution module is used to optimize and solve the battery swapping scheduling simulation model using a preset optimization algorithm to obtain the battery swapping scheduling simulation results corresponding to the battery swapping scheduling simulation task.
[0047] The simulation results display module is used to display the battery swapping scheduling simulation results corresponding to the battery swapping scheduling simulation task in the map interaction interface.
[0048] With the above-mentioned device, the corresponding configuration data can be flexibly set through the map interaction interface of the front-end device according to different needs and complex and ever-changing battery swapping scheduling simulation tasks in different scenarios. The server can perform dynamic simulation modeling and optimization solutions based on the configuration data, and display the battery swapping scheduling simulation results in the map interaction interface, thereby effectively improving the adaptability of battery swapping scheduling simulation.
[0049] In one specific implementation of the second aspect, the battery swapping scheduling simulation device may further include:
[0050] An algorithm parameter acquisition module is used to acquire the updated algorithm parameters corresponding to the optimization algorithm;
[0051] The parameter update module is used to update the parameters of the optimization algorithm according to the update algorithm parameters, so as to obtain the optimized algorithm with updated parameters.
[0052] Accordingly, the optimization solution module can be specifically used to: optimize and solve the battery swapping scheduling simulation model using the optimized algorithm after parameter update, and obtain the battery swapping scheduling simulation result corresponding to the battery swapping scheduling simulation task.
[0053] The aforementioned device allows for flexible updates to algorithm parameters based on the complex and ever-changing battery swapping scheduling simulation tasks in different needs and scenarios. Furthermore, it enables dynamic optimization of the battery swapping scheduling simulation model based on the updated optimization algorithm, thereby further improving the adaptability of the battery swapping scheduling simulation.
[0054] In one specific implementation of the second aspect, the configuration data acquisition module may be specifically used to: acquire the starting point and ending point of the route input via the map interaction interface; call the map service to draw the simulation task route from the starting point to the ending point in the map interaction interface; select candidate battery swapping station coordinates from a preset set of battery swapping station coordinates based on the simulation task route, and display the candidate battery swapping station coordinates in the map interaction interface; and acquire the battery swapping station configuration data of the candidate battery swapping station coordinates input via the map interaction interface.
[0055] The aforementioned device allows users to input configuration data through a map-based interactive interface, making the data configuration process more convenient and intuitive, and effectively improving configuration efficiency.
[0056] In one specific implementation of the second aspect, the simulation model building module can be specifically used to: perform node modeling on vehicles and battery swapping stations based on vehicle configuration data and battery swapping station configuration data in the configuration data to obtain nodes in the battery swapping scheduling simulation model; perform edge modeling on roads based on road network configuration data in the configuration data to obtain edges in the battery swapping scheduling simulation model; and generate an adjacency matrix corresponding to the battery swapping scheduling simulation model based on the relationship between nodes and edges in the battery swapping scheduling simulation model; wherein, the adjacency matrix is used to indicate whether there is an edge connection between nodes.
[0057] Using the aforementioned device, the nodes, edges, and adjacency matrices of the battery swapping scheduling simulation model can be modeled based on vehicle configuration data, battery swapping station configuration data, and road network configuration data. This allows the battery swapping scheduling simulation model to flexibly adapt to changes in tasks and enables more adaptive battery swapping scheduling simulations.
[0058] In one specific implementation of the second aspect, the optimization solution module may be specifically used to: store the battery swapping scheduling simulation model in a preset file system and obtain the corresponding storage address; send the storage address to a preset algorithm server; wherein, the algorithm server is used to read the battery swapping scheduling simulation model from the file system according to the storage address, and use a preset optimization algorithm to optimize and solve the battery swapping scheduling simulation model to obtain the battery swapping scheduling simulation result corresponding to the battery swapping scheduling simulation task; and obtain the battery swapping scheduling simulation result corresponding to the battery swapping scheduling simulation task sent by the algorithm server.
[0059] The above-mentioned device allows the algorithm server to complete the specific optimization solution process. The server is decoupled from the algorithm and only needs to perform overall management and control, thereby further improving the adaptability of battery swapping scheduling simulation.
[0060] In one specific implementation of the second aspect, the simulation result display module can be specifically used to: generate a vehicle driving trajectory animation based on the battery swapping scheduling simulation result corresponding to the battery swapping scheduling simulation task; and play the vehicle driving trajectory animation in the map interaction interface.
[0061] The above-mentioned device allows for the visualization of battery swapping scheduling simulation results through a map-based interactive interface, enabling users to obtain these results more conveniently and intuitively.
[0062] In one specific implementation of the second aspect, the battery swapping scheduling simulation device may further include:
[0063] The historical simulation results viewing module is used to respond to the historical simulation results viewing command, determine the task identifier of the historical simulation task corresponding to the historical simulation results viewing command; query the battery swapping scheduling simulation results corresponding to the historical simulation task in a preset database according to the task identifier; and display the battery swapping scheduling simulation results corresponding to the historical simulation task in the map interaction interface.
[0064] The aforementioned device allows users to query and display the corresponding simulation results in the database based on the task identifiers of historical simulation tasks, enabling them to view, compare, and analyze past simulation results more conveniently and intuitively.
[0065] A third aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of any of the above-described battery swapping scheduling simulation methods.
[0066] A fourth aspect of this application provides a server including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of any of the above-described battery swapping scheduling simulation methods.
[0067] The fifth aspect of this application provides a computer program product that, when run on a server, causes the server to execute the steps of any of the above-described battery swapping scheduling simulation methods. Attached Figure Description
[0068] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0069] Figure 1 This is a schematic flowchart of a battery swapping scheduling simulation method in an embodiment of this application;
[0070] Figure 2 This is a schematic flowchart illustrating the process of establishing a battery swapping scheduling simulation model corresponding to the battery swapping scheduling simulation task based on the configuration data.
[0071] Figure 3 The diagram shown is a specific application scenario of an embodiment of this application;
[0072] Figure 4 This is a structural diagram of one embodiment of a battery swapping dispatch simulation device according to the present application.
[0073] Figure 5 This is a schematic block diagram of a server in an embodiment of this application. Detailed Implementation
[0074] To make the inventive objectives, features, and advantages of this application more apparent and understandable, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0075] It should be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.
[0076] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of the application. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.
[0077] It should also be further understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.
[0078] As used in this specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if [the described condition or event] is detected" may be interpreted, depending on the context, as "once determined," "in response to determination," "once [the described condition or event] is detected," or "in response to detection of [the described condition or event]."
[0079] Furthermore, in the description of this application, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.
[0080] The widespread adoption of electric vehicles (EVs) is a crucial way to address current environmental pollution and the fossil fuel crisis. With the continuous development of related technologies, EVs have gradually become the mainstream in the transportation sector. EVs can be categorized into charging and battery swapping types based on their charging methods. Compared to the former, battery swapping EVs offer advantages such as shorter charging times, convenient charging methods, and smaller space requirements. Therefore, the demand for battery swapping is increasing, leading to issues such as long swapping times and insufficient battery reserves due to concentrated battery swapping activity. To improve the service quality of battery swapping stations, reduce their operating costs, and promote the development of EV battery swapping models, accurate simulation of EV battery swapping scheduling has become an urgent problem to solve. However, existing battery swapping scheduling simulation methods are often only applicable to specific battery swapping tasks and are difficult to apply to complex and varied battery swapping scheduling simulation tasks with different needs and scenarios.
[0081] In view of this, embodiments of this application provide a battery swapping scheduling simulation method, apparatus, computer-readable storage medium, and server to solve the problem that existing battery swapping scheduling simulation methods are difficult to apply to complex and ever-changing battery swapping scheduling simulation tasks in different needs and scenarios.
[0082] In this embodiment, the corresponding configuration data can be flexibly set through the map interaction interface of the front-end device according to different needs and complex and ever-changing battery swapping scheduling simulation tasks in different scenarios. The server can perform dynamic simulation modeling and optimization solution based on the configuration data, and display the battery swapping scheduling simulation results in the map interaction interface, thereby effectively improving the adaptability of battery swapping scheduling simulation.
[0083] The method described in this application can be implemented by a server, which may include, but is not limited to, cloud servers and local servers. Please refer to [link / reference]. Figure 1 The battery swapping scheduling simulation method in this application embodiment may include:
[0084] Step S101: Call the map service to display the map interactive interface on the front-end device.
[0085] In this embodiment, any existing map service can be used as needed to display geographic information to the user in a visual form. The geographic information primarily originates from geographic information data sources, which may include, but are not limited to, Geographic Information Systems (GIS) and geographic databases. These data sources can provide geographic information data such as road topology, road length, and road travel time. Geographic information is typically represented in the form of geographic coordinates, which use longitude and latitude to determine location on Earth. Each vehicle and battery swapping station is assigned a geographic coordinate to represent its location in geographic space. The accuracy and precision of these geographic coordinates have a significant impact on the calculation and simulation results.
[0086] The map interface can assist users in inputting configuration data through map services and geographic information. Map services can provide accurate geographic location information and, by integrating map data and corresponding functions, offer users a visual representation and interactive functionality of geospatial information.
[0087] Step S102: Obtain the configuration data corresponding to the battery swapping scheduling simulation task input via the map interaction interface.
[0088] The configuration data may include, but is not limited to, vehicle configuration data, battery swapping station configuration data, and road network configuration data. Vehicle configuration data may include, but is not limited to, the number of vehicles, vehicle type, and initial vehicle location; battery swapping station configuration data may include, but is not limited to, the number of battery swapping stations, station location, and station capacity; road network configuration data may include, but is not limited to, road topology, road length, and road travel time.
[0089] In one specific implementation of this application, the user can pre-compile the configuration data corresponding to the battery swapping scheduling simulation task into a data file, i.e., a configuration data file, and then directly input the configuration data file through the data configuration interface. The server can obtain the configuration data file from the data configuration interface and parse it to obtain the configuration data corresponding to the battery swapping scheduling simulation task.
[0090] In another specific implementation of this application, after the server calls the map service to display the map interactive interface on the front-end device, the user can input configuration data corresponding to the battery swapping scheduling simulation task through the map interactive interface. The server can obtain the configuration data input through the map interactive interface from the data configuration interface.
[0091] As an example, users can first mark the starting and ending points of the route on the map interface, and also set the simulation period and other relevant information. The server can obtain the starting and ending points input through the map interface, call the map service to dynamically draw the simulation task route from the starting point to the ending point on the map interface, and select candidate battery swapping station coordinates from a preset set of battery swapping station coordinates based on the simulation task route, using regression tree algorithms or other algorithms, and display the candidate battery swapping station coordinates on the map interface. Users can place battery swapping stations at these candidate battery swapping station coordinates and configure related data. The server can obtain the battery swapping station configuration data from the candidate battery swapping station coordinates input through the map interface. Vehicle and road network related data configuration can also be completed by users through marking and configuring operations on the map interface.
[0092] The above methods can be used to assist users in inputting configuration data through a map-based interactive interface, making the data configuration process more convenient and intuitive, and effectively improving configuration efficiency.
[0093] Step S103: Based on the configuration data, establish a battery swapping scheduling simulation model corresponding to the battery swapping scheduling simulation task.
[0094] In this embodiment, the server can transform geographical information and configuration data into an operable model, namely a battery swapping scheduling simulation model, and store it in a preset database. The battery swapping scheduling simulation model can use techniques such as graph theory and network analysis to represent the relationships between vehicles, battery swapping stations, and the road network. Its specific construction process may include, for example... Figure 2 The steps shown are as follows:
[0095] Step S1031: Based on the vehicle configuration data and the battery swapping station configuration data, perform node modeling for the vehicle and the battery swapping station to obtain the nodes in the battery swapping scheduling simulation model.
[0096] In the battery swapping scheduling simulation model, each vehicle can be abstracted as a node in the model, and vehicle information such as vehicle type and initial location can be used as the attribute information of the corresponding node. Similarly, each battery swapping station can also be abstracted as a node in the model, and station information such as station location and capacity can be used as the attribute information of the corresponding node. Each node in the battery swapping scheduling simulation model can have a unique identifier and geographical location information.
[0097] Step S1032: Based on the road network configuration data, perform edge modeling on the roads to obtain the edges in the battery swapping scheduling simulation model.
[0098] In the battery swapping scheduling simulation model, roads in the road network can be abstracted as edges in the model. Each edge can connect two different nodes and can have attribute information such as road length and road travel time.
[0099] Step S1033: Generate an adjacency matrix corresponding to the battery swapping scheduling simulation model based on the relationships between nodes and edges in the battery swapping scheduling simulation model.
[0100] The adjacency matrix is used to represent whether there are edges connecting nodes. It's like a table where each row and column represents a node. If there's a direct connection between two nodes (i.e., an edge exists), the cell representing those two nodes will be marked with 1 or the edge weight; if there's no direct connection between two nodes, the cell will be marked with 0.
[0101] In the process of constructing the battery swapping scheduling simulation model, factors such as vehicles, battery swapping stations, and road networks were fully considered. Through data modeling, geographical information and configuration data can be transformed into graph theory models, which facilitates subsequent algorithm calculations and optimizations.
[0102] When a user adjusts the configuration parameters, the server can remodel based on the new configuration parameters, including but not limited to adding, deleting or modifying nodes and edges, as well as updating the related adjacency matrix, to obtain an updated battery swapping scheduling simulation model, which will then replace the battery swapping scheduling simulation model already stored in the database.
[0103] Using the above method, corresponding vehicle configuration data, battery swapping station configuration data, and road network configuration data can be flexibly set according to different needs and scenarios of complex and ever-changing battery swapping scheduling simulation tasks. Based on these configuration data, the nodes, edges, and adjacency matrices of the battery swapping scheduling simulation model can be modeled respectively, so that the battery swapping scheduling simulation model can be flexibly adapted to the changes in tasks and can perform more adaptive battery swapping scheduling simulations.
[0104] Step S104: Use a preset optimization algorithm to optimize and solve the battery swapping scheduling simulation model to obtain the battery swapping scheduling simulation results corresponding to the battery swapping scheduling simulation task.
[0105] An optimization algorithm is an algorithm used to find the optimal solution. It finds the value of minimizing or maximizing a certain objective function through iteration and search. In the embodiments of this application, any optimization algorithm in the prior art can be used according to the actual situation, including but not limited to steepest descent, Newton's method, conjugate gradient method, genetic algorithm, simulated annealing algorithm, tabu search algorithm, and particle swarm optimization algorithm. Each optimization algorithm has its corresponding algorithm parameters. Taking the genetic algorithm as an example, the algorithm parameters may include, but are not limited to, crossover rate and mutation rate.
[0106] The optimization algorithm can iteratively calculate and search based on the nodes, edges, and adjacency matrix in the battery swapping scheduling simulation model, aiming to maximize the number of transport vehicles per day. The algorithm then solves for the battery swapping scheduling simulation results corresponding to the task, which may include, but are limited to, the optimal battery swapping time and optimal battery swapping site for each vehicle. The specific optimization solution process can be completed by a server or by a pre-defined algorithm server.
[0107] As an example, the server can store the battery swapping scheduling simulation model and various data related to the optimization algorithm into a pre-defined file system, obtain the corresponding storage address, and then send the storage address to the algorithm server via network interface messages or other means. The algorithm server can read the battery swapping scheduling simulation model and various data related to the optimization algorithm from the file system according to the storage address, and use the pre-defined optimization algorithm to optimize and solve the battery swapping scheduling simulation model, obtaining the battery swapping scheduling simulation result corresponding to the battery swapping scheduling simulation task, and sending it to the server. The server can then obtain the battery swapping scheduling simulation result corresponding to the battery swapping scheduling simulation task sent by the algorithm server.
[0108] Using the above method, the specific optimization solution process can be handed over to the algorithm server. The server and the algorithm are decoupled, and only overall management and control are required, thereby further improving the adaptability of battery swapping scheduling simulation.
[0109] In one specific implementation of this application, an optimization algorithm can be directly used to optimize and solve the battery swapping scheduling simulation model to obtain the battery swapping scheduling simulation result corresponding to the battery swapping scheduling simulation task. The algorithm parameters used in the optimization algorithm can be pre-stored algorithm parameters.
[0110] In another specific implementation of this application, the algorithm parameters can be flexibly updated according to different needs and the complex and ever-changing battery swapping scheduling simulation tasks in different scenarios, and the battery swapping scheduling simulation model can be dynamically optimized and solved according to the optimized algorithm after parameter update, thereby further improving the adaptability of battery swapping scheduling simulation.
[0111] Specifically, the update algorithm parameters corresponding to the optimization algorithm can be obtained first. Similar to configuration data, users can input the update algorithm parameters corresponding to the optimization algorithm through the data configuration interface, and the server can obtain the update algorithm parameters from the data configuration interface. After obtaining the update algorithm parameters, the optimization algorithm can be updated according to the update algorithm parameters to obtain the optimized algorithm with updated parameters. Then, the optimized algorithm with updated parameters can be used to optimize and solve the battery swapping scheduling simulation model to obtain the battery swapping scheduling simulation results corresponding to the battery swapping scheduling simulation task.
[0112] Step S105: Display the battery swapping scheduling simulation results corresponding to the battery swapping scheduling simulation task on the map interactive interface.
[0113] After obtaining the battery swapping scheduling simulation results, they can be displayed on a preset map interactive interface. This means that the map interactive interface can be used to visualize the distribution of the battery swapping scheduling simulation results in geographic space, so that users can obtain the battery swapping scheduling simulation results more conveniently and intuitively, and understand the vehicle movement path, the distribution of battery swapping stations, and the scheduling effect.
[0114] As an example, the server can generate vehicle trajectory animations based on the battery swapping scheduling simulation results corresponding to the battery swapping scheduling simulation task, and then play these animations on the map interactive interface. Users can view the vehicle's trajectory and understand the vehicle's route and battery swapping operation process.
[0115] After obtaining the battery swapping scheduling simulation results, they can be stored in a database for later viewing.
[0116] When a user needs to view historical simulation results, they can send a historical simulation result viewing command to the server through a preset command interface. The historical simulation result viewing command can carry the task identifier of the historical simulation task. The task identifier is used to identify different battery swapping scheduling simulation tasks, that is, different battery swapping scheduling simulation tasks have different task identifiers.
[0117] When the server responds to the command to view historical simulation results, it can first determine the task identifier of the historical simulation task corresponding to the command. Then, based on the task identifier, it can query the battery swapping scheduling simulation results corresponding to the historical simulation task in the database. The server can also display the battery swapping scheduling simulation results corresponding to the historical simulation task on the map interactive interface. It can also display the configuration data, algorithm parameters and other relevant data corresponding to the historical simulation task.
[0118] Using the above method, the corresponding simulation results can be queried and displayed in the database based on the task identifier of historical simulation tasks, making it more convenient and intuitive for users to view, compare and analyze past simulation results.
[0119] Figure 3 The diagram illustrates a specific application scenario of this application. As shown, the user can interact with the device through a map interface on the front-end device, while the cloud server executes the control process for battery swapping scheduling simulation. The cloud server can quickly expand or shrink its resources to adapt to the constantly changing needs of the battery swapping scheduling simulation. During the simulation, the cloud server can call map services to display a map interface on the front-end device. The user can input configuration data and algorithm parameters through the map interface and other interfaces. After obtaining the configuration data and algorithm parameters, the cloud server can build a battery swapping scheduling simulation model based on the configuration data and store various data related to the optimization algorithm, such as algorithm parameters, into a file system. The storage address of this data in the file system is then passed to the algorithm server. The algorithm server can read relevant data from the file system based on the storage address, perform specific optimization and solution processes, and send the obtained battery swapping scheduling simulation results back to the cloud server. During the battery swapping scheduling simulation, the user can flexibly update the configuration parameters and algorithm parameters dynamically according to different needs and the complex and ever-changing battery swapping scheduling simulation tasks in different scenarios. Correspondingly, the battery swapping scheduling simulation model and optimization algorithm can also be dynamically updated in real time. The cloud server can store the battery swapping scheduling simulation results in a database. When users need to view historical simulation results, the cloud server can perform corresponding queries in the database.
[0120] In summary, the embodiments of this application can flexibly set corresponding configuration data through the map interaction interface of the front-end device according to different needs and complex and ever-changing battery swapping scheduling simulation tasks in different scenarios. The server can perform dynamic simulation modeling and optimization solutions based on the configuration data, and display the battery swapping scheduling simulation results in the map interaction interface, thereby effectively improving the adaptability of battery swapping scheduling simulation.
[0121] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.
[0122] Corresponding to the battery swapping scheduling simulation method described in the above embodiments, Figure 4 This illustration shows a structural diagram of an embodiment of a battery swapping scheduling simulation device applied to a server, as provided in this application.
[0123] In this embodiment, a battery swapping scheduling simulation device may include:
[0124] The map service invocation module 401 is used to invoke map services to display the map interactive interface on the front-end device.
[0125] The configuration data acquisition module 402 is used to acquire the configuration data corresponding to the battery swapping scheduling simulation task input via the map interaction interface;
[0126] The simulation model building module 403 is used to build a battery swapping scheduling simulation model corresponding to the battery swapping scheduling simulation task based on the configuration data.
[0127] The optimization and solution module 404 is used to optimize and solve the battery swapping scheduling simulation model using a preset optimization algorithm to obtain the battery swapping scheduling simulation results corresponding to the battery swapping scheduling simulation task.
[0128] The simulation result display module 405 is used to display the battery swapping scheduling simulation results corresponding to the battery swapping scheduling simulation task in the map interaction interface.
[0129] In one specific implementation of this application embodiment, the battery swapping scheduling simulation device may further include:
[0130] An algorithm parameter acquisition module is used to acquire the updated algorithm parameters corresponding to the optimization algorithm;
[0131] The parameter update module is used to update the parameters of the optimization algorithm according to the update algorithm parameters, so as to obtain the optimized algorithm with updated parameters.
[0132] Accordingly, the optimization solution module can be specifically used to: optimize and solve the battery swapping scheduling simulation model using the optimized algorithm after parameter update, and obtain the battery swapping scheduling simulation result corresponding to the battery swapping scheduling simulation task.
[0133] In one specific implementation of this application embodiment, the configuration data acquisition module may be specifically used for: acquiring the route start point and route end point input via the map interaction interface; calling a map service to draw a simulation task route from the route start point to the route end point in the map interaction interface; selecting candidate battery swapping station coordinate points from a preset set of battery swapping station coordinate points according to the simulation task route, and displaying the candidate battery swapping station coordinate points in the map interaction interface; and acquiring battery swapping station configuration data of the candidate battery swapping station coordinate points input via the map interaction interface.
[0134] In one specific implementation of this application embodiment, the simulation model building module can be specifically used to: perform node modeling on vehicles and battery swapping stations based on vehicle configuration data and battery swapping station configuration data in the configuration data to obtain nodes in the battery swapping scheduling simulation model; perform edge modeling on roads based on road network configuration data in the configuration data to obtain edges in the battery swapping scheduling simulation model; and generate an adjacency matrix corresponding to the battery swapping scheduling simulation model based on the relationship between nodes and edges in the battery swapping scheduling simulation model; wherein, the adjacency matrix is used to indicate whether there is an edge connection between nodes.
[0135] In one specific implementation of this application embodiment, the optimization solution module may be specifically used to: store the battery swapping scheduling simulation model in a preset file system and obtain the corresponding storage address; send the storage address to a preset algorithm server; wherein, the algorithm server is used to read the battery swapping scheduling simulation model from the file system according to the storage address, and use a preset optimization algorithm to optimize and solve the battery swapping scheduling simulation model to obtain the battery swapping scheduling simulation result corresponding to the battery swapping scheduling simulation task; and obtain the battery swapping scheduling simulation result corresponding to the battery swapping scheduling simulation task sent by the algorithm server.
[0136] In one specific implementation of this application, the simulation result display module can be specifically used to: generate a vehicle driving trajectory animation based on the battery swapping scheduling simulation result corresponding to the battery swapping scheduling simulation task; and play the vehicle driving trajectory animation in the map interaction interface.
[0137] In one specific implementation of this application embodiment, the battery swapping scheduling simulation device may further include:
[0138] The historical simulation results viewing module is used to respond to the historical simulation results viewing command, determine the task identifier of the historical simulation task corresponding to the historical simulation results viewing command; query the battery swapping scheduling simulation results corresponding to the historical simulation task in a preset database according to the task identifier; and display the battery swapping scheduling simulation results corresponding to the historical simulation task in the map interaction interface.
[0139] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.
[0140] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.
[0141] Figure 5 A schematic block diagram of a server provided in an embodiment of this application is shown. For ease of explanation, only the parts related to the embodiment of this application are shown.
[0142] like Figure 5 As shown, the server 5 in this embodiment includes a processor 50, a memory 51, and a computer program 52 stored in the memory 51 and executable on the processor 50. When the processor 50 executes the computer program 52, it implements the steps in the various battery swapping scheduling simulation method embodiments described above, for example... Figure 1 Steps S101 to S105 are shown. Alternatively, when the processor 50 executes the computer program 52, it implements the functions of each module / unit in the above-described device embodiments, for example... Figure 4 The functions of modules 401 to 405 are shown.
[0143] For example, the computer program 52 may be divided into one or more modules / units, which are stored in the memory 51 and executed by the processor 50 to complete this application. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program 52 in the server 5.
[0144] Those skilled in the art will understand that Figure 5 This is merely an example of server 5 and does not constitute a limitation on server 5. It may include more or fewer components than shown, or combine certain components, or different components. For example, server 5 may also include input / output devices, network access devices, buses, etc.
[0145] The processor 50 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.
[0146] The memory 51 can be an internal storage unit of the server 5, such as a hard drive or memory. The memory 51 can also be an external storage device of the server 5, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the memory 51 can include both internal and external storage units of the server 5. The memory 51 is used to store the computer program and other programs and data required by the server 5. The memory 51 can also be used to temporarily store data that has been output or will be output.
[0147] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.
[0148] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.
[0149] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.
[0150] In the embodiments provided in this application, it should be understood that the disclosed apparatus / server and method can be implemented in other ways. For example, the apparatus / server embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.
[0151] The units described as separate components may or may not be physically separate. The 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 the units can be selected to achieve the purpose of this embodiment according to actual needs.
[0152] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.
[0153] If the integrated module / unit is implemented as 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, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable storage medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc. It should be noted that the content included in the computer-readable storage medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable storage medium does not include electrical carrier signals and telecommunication signals.
[0154] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.
Claims
1. A battery swapping dispatch simulation method, characterized in that, When applied to a server, the method includes: Call the map service to display the map interface on the front-end device; Obtain the configuration data corresponding to the battery swapping scheduling simulation task input via the map interaction interface; Based on the configuration data, establish a battery swapping scheduling simulation model corresponding to the battery swapping scheduling simulation task; The battery swapping scheduling simulation model is optimized and solved using a preset optimization algorithm to obtain the battery swapping scheduling simulation results corresponding to the battery swapping scheduling simulation task. The battery swapping scheduling simulation results corresponding to the battery swapping scheduling simulation task are displayed in the map interaction interface.
2. The battery swapping scheduling simulation method according to claim 1, characterized in that, Before optimizing the battery swapping scheduling simulation model using a preset optimization algorithm to obtain the battery swapping scheduling simulation result corresponding to the battery swapping scheduling simulation task, the process further includes: Obtain the update algorithm parameters corresponding to the optimization algorithm; The optimization algorithm is updated according to the updated algorithm parameters to obtain the optimized algorithm with updated parameters. Accordingly, the step of using a preset optimization algorithm to optimize and solve the battery swapping scheduling simulation model to obtain the battery swapping scheduling simulation results corresponding to the battery swapping scheduling simulation task includes: The battery swapping scheduling simulation model is optimized and solved using the updated optimization algorithm to obtain the battery swapping scheduling simulation results corresponding to the battery swapping scheduling simulation task.
3. The battery swapping dispatch simulation method according to any one of claims 1 to 2, characterized in that, The step of obtaining the configuration data corresponding to the battery swapping scheduling simulation task input via the map interaction interface includes: Obtain the starting point and ending point of the route input via the map interaction interface; The map service is invoked to draw the simulation task route from the starting point to the ending point of the route in the map interactive interface; According to the simulation task route, candidate battery swapping station coordinates are selected from the preset set of battery swapping station coordinates and displayed in the map interaction interface. Obtain the battery swapping station configuration data of the candidate battery swapping station coordinates input via the map interaction interface.
4. The battery swapping dispatch simulation method according to any one of claims 1 to 3, characterized in that, The step of establishing a battery swapping scheduling simulation model corresponding to the battery swapping scheduling simulation task based on the configuration data includes: Based on the vehicle configuration data and battery swapping station configuration data in the configuration data, node modeling is performed on the vehicles and battery swapping stations to obtain the nodes in the battery swapping scheduling simulation model. Based on the road network configuration data in the configuration data, the road edges are modeled to obtain the edges in the battery swapping scheduling simulation model; Based on the relationships between nodes and edges in the battery swapping scheduling simulation model, an adjacency matrix corresponding to the battery swapping scheduling simulation model is generated; wherein, the adjacency matrix is used to indicate whether there are edges connecting the nodes.
5. The battery swapping dispatch simulation method according to any one of claims 1 to 4, characterized in that, The step of optimizing and solving the battery swapping scheduling simulation model using a preset optimization algorithm to obtain the battery swapping scheduling simulation results corresponding to the battery swapping scheduling simulation task includes: The battery swapping scheduling simulation model is stored in a preset file system, and the corresponding storage address is obtained; The storage address is sent to a preset algorithm server; wherein, the algorithm server is used to read the battery swapping scheduling simulation model from the file system according to the storage address, and use a preset optimization algorithm to optimize and solve the battery swapping scheduling simulation model to obtain the battery swapping scheduling simulation result corresponding to the battery swapping scheduling simulation task. Obtain the battery swapping scheduling simulation results sent by the algorithm server corresponding to the battery swapping scheduling simulation task.
6. The battery swapping dispatch simulation method according to any one of claims 1 to 5, characterized in that, The step of displaying the battery swapping scheduling simulation results corresponding to the battery swapping scheduling simulation task in the map interaction interface includes: Based on the battery swapping scheduling simulation results corresponding to the battery swapping scheduling simulation task, generate an animation of the vehicle's driving trajectory. The vehicle's driving trajectory animation is played in the map interaction interface.
7. The battery swapping dispatch simulation method according to any one of claims 1 to 6, characterized in that, Also includes: In response to the command to view historical simulation results, determine the task identifier of the historical simulation task corresponding to the command to view historical simulation results; Based on the task identifier, query the battery swapping scheduling simulation results corresponding to the historical simulation task in the preset database; The battery swapping scheduling simulation results corresponding to the historical simulation tasks are displayed in the map interaction interface.
8. A battery swapping dispatch simulation device, characterized in that, The device, used in a server, includes: The map service invocation module is used to invoke map services to display the map interactive interface on the front-end device; The configuration data acquisition module is used to acquire the configuration data corresponding to the battery swapping scheduling simulation task input via the map interaction interface; The simulation model building module is used to build a battery swapping scheduling simulation model corresponding to the battery swapping scheduling simulation task based on the configuration data. The optimization and solution module is used to optimize and solve the battery swapping scheduling simulation model using a preset optimization algorithm to obtain the battery swapping scheduling simulation results corresponding to the battery swapping scheduling simulation task. The simulation results display module is used to display the battery swapping scheduling simulation results corresponding to the battery swapping scheduling simulation task in the map interaction interface.
9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the battery swapping scheduling simulation method as described in any one of claims 1 to 7.
10. A server comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the battery swapping scheduling simulation method as described in any one of claims 1 to 7.