Method, device, equipment and storage medium for dispatching and processing of battery swapping stations

Abstract

The present application provides a method, apparatus, device, and storage medium for dispatching and processing in a battery swapping station. The method includes: using multiple sets of input data to perform battery swapping simulation on the battery swapping station through a simulation model of the battery swapping station, obtaining multiple first parameter values corresponding to the multiple sets of input data; each set of input data includes the number of heavy trucks, and the first parameter value is used to characterize the matching degree between the number of heavy trucks and the battery swapping capacity of the battery swapping station. Determine a target first parameter value from the multiple first parameter values. Dispatch the heavy trucks served by the battery swapping station according to the number of heavy trucks corresponding to the target first parameter value. The method of the present application solves the problem of how to more accurately dispatch the heavy trucks served by the battery swapping station.

Description

Technical Field

[0001] The present application relates to the technical field of power exchange station scheduling, and particularly to a method, device, equipment and storage medium for power exchange station scheduling and processing. Background Art

[0002] Currently, environmental problems are deteriorating day by day. Using heavy truck vehicles that can replace battery packs can effectively reduce the carbon emissions during the operation of heavy truck vehicles, and can quickly complete the energy replenishment of heavy truck vehicles by replacing battery packs, so that heavy truck vehicles can perform operation tasks efficiently and environmentally. However, the service capacity of the power exchange station required for heavy truck vehicle battery replacement affects the operation efficiency of heavy truck vehicles.

[0003] In the prior art, the judgment of the service capacity of a power exchange station depends on the vehicle's reserved battery replacement behavior, that is, the vehicle must perform a battery replacement behavior at the reserved time to determine the number of vehicles that the power exchange station needs to schedule. Therefore, if the vehicle cannot operate according to the reserved time, this method cannot accurately determine the service capacity of the power exchange station and the number of vehicles that need to be scheduled, resulting in poor real-time performance and low stability. Summary of the Invention

[0004] The present application provides a method, device, equipment and storage medium for power exchange station scheduling and processing, which is used to solve the problem of power exchange station scheduling and processing in the scenario where heavy truck vehicles do not have fixed routes, fixed driving times, and do not require battery replacement reservations.

[0005] In a first aspect, the present application provides a method for power exchange station scheduling and processing, including:

[0006] Using multiple sets of input data, performing a battery replacement simulation on the power exchange station through the simulation model of the power exchange station to obtain a plurality of first parameter values corresponding to the multiple sets of input data; each set of input data includes: the number of heavy truck vehicles, and the first parameter value is used to characterize the matching degree between the number of heavy truck vehicles and the battery replacement capacity of the power exchange station;

[0007] Determining a target first parameter value from the plurality of first parameter values;

[0008] Scheduling the heavy truck vehicles served by the power exchange station according to the number of heavy truck vehicles corresponding to the target first parameter value.

[0009] Optionally, the step of using multiple sets of input data to perform a battery replacement simulation on the power exchange station through the simulation model of the power exchange station to obtain a plurality of first parameter values corresponding to the multiple sets of input data includes:

[0010] Input each set of input data into the simulation model of the battery swapping station to perform battery swapping simulation on the battery swapping station through the simulation model of the battery swapping station, and obtain intermediate parameter values corresponding to each set of input data. The intermediate parameters include: the average discharge depth of the battery pack, the total time consumed for a single battery swap of a single heavy truck, the average number of loading and unloading trips completed by the heavy truck, and a second parameter of the battery swapping station, where the second parameter is used to characterize the average revenue data of the battery swapping station providing battery swapping services for heavy trucks;

[0011] Obtain the first parameter value corresponding to each set of input data according to the intermediate parameter value corresponding to each set of input data and the weight corresponding to each intermediate parameter value.

[0012] Optionally, the step of inputting each set of input data into the simulation model of the battery swapping station to perform battery swapping simulation on the battery swapping station through the simulation model of the battery swapping station and obtain intermediate parameter values corresponding to each set of input data includes:

[0013] Input each set of input data into the simulation model of the battery swapping station to enable the simulation model to perform battery swapping simulation within a target simulation duration to obtain initial parameter values corresponding to each set of input data. The initial parameter values include: the number of battery swaps of each heavy truck, the number of battery swaps of each battery pack, the total discharge depth of each battery pack, the total time consumed for a single battery swap of each heavy truck, and the initial power of the battery pack replaced each time by each heavy truck.

[0014] Obtain the intermediate parameter value corresponding to each set of input data according to the initial parameter value.

[0015] Optionally, the input data further includes at least one of the following: the initial power of the battery pack of each heavy truck, the identifier of each heavy truck, and the identifier of the battery pack of each heavy truck.

[0016] Optionally, before using multiple sets of input data to perform battery swapping simulation on the battery swapping station through the simulation model of the battery swapping station, the method further includes:

[0017] Receive configuration data of the simulation model, where the configuration data includes at least one of the following: the target simulation duration and the target number of battery packs of the battery swapping station.

[0018] Optionally, before using multiple sets of input data to perform battery swapping simulation on the battery swapping station through the simulation model of the battery swapping station and obtaining multiple first parameter values corresponding to the multiple sets of input data, it further includes:

[0019] Construct the simulation model according to simulation construction parameters. The construction parameters include: the simulation parameter value of the battery swapping station and the simulation parameter value of the working area of the heavy truck.

[0020] The simulation parameters of the battery swapping station include at least one of the following: the charging speed of the battery pack, the time taken for heavy truck battery swapping, the cost data required for charging the battery pack, and the construction cost data of the battery swapping station;

[0021] The simulation parameters of the working area of the heavy truck include at least one of the following: the threshold of the battery pack to be charged; the first remaining battery charge (SOC) consumption of the battery pack corresponding to the heavy truck traveling from the loading point to the unloading point, and the first time taken; the second SOC consumption of the battery pack corresponding to the heavy truck traveling from the unloading point to the loading point, and the second time taken; the third SOC consumption of the battery pack corresponding to the heavy truck traveling from the unloading point to the battery swapping station, and the third time taken.

[0022] Optionally, the method further includes:

[0023] Obtaining at least one of the simulation construction parameters according to the historical battery swapping data of the battery swapping station.

[0024] In a second aspect, the present application provides a battery swapping station scheduling processing device, including:

[0025] A simulation module, configured to use multiple sets of input data to perform battery swapping simulation on the battery swapping station through the simulation model of the battery swapping station, and obtain multiple first parameter values corresponding to the multiple sets of input data; each set of input data includes: the number of heavy trucks, and the first parameter value is used to characterize the matching degree between the number of heavy trucks and the battery swapping capacity of the battery swapping station;

[0026] A determination module, configured to determine a target first parameter value from the multiple first parameter values;

[0027] A scheduling module, configured to schedule the heavy trucks served by the battery swapping station according to the number of heavy trucks corresponding to the target first parameter value.

[0028] In a third aspect, the present application provides a battery swapping station scheduling processing device, including: a processor, a communication interface, and a memory; the processor is respectively communicatively connected to the communication interface and the memory;

[0029] The memory stores computer execution instructions;

[0030] The communication interface communicates with external devices;

[0031] The processor executes the computer execution instructions stored in the memory to implement the method according to any one of the first aspects.

[0032] Fourthly, the present application provides a computer-readable storage medium storing computer-executable instructions, which are used to implement the swapping station scheduling processing method according to any one of the first aspect when executed by a processor.

[0033] Fifthly, the present application provides a program product, including: executable instructions stored in a readable storage medium. At least one processor of a computing device can read the executable instructions from the readable storage medium, and the at least one processor executing the executable instructions enables the computing device to implement the swapping station scheduling processing method according to any one of the first aspect above.

[0034] The swapping station scheduling processing method, device, equipment and storage medium provided by the present application respectively simulate the process of a swapping station providing swapping services for different numbers of heavy-duty truck vehicles through a simulation model of the swapping station, so as to obtain a first parameter capable of characterizing the matching degree between the number of heavy-duty truck vehicles and the swapping capacity of the swapping station, thereby the number of heavy-duty truck vehicles suitable for the swapping station can be obtained based on each first parameter, and then the heavy-duty truck vehicles served by the swapping station can be scheduled based on this number, improving the accuracy of scheduling the number of heavy-duty truck vehicles served by the swapping station. Description of the Drawings

[0035] The drawings here are incorporated into the description and form a part of this description, showing embodiments consistent with the present application, and are used to explain the principles of the present application together with the description.

[0036] Figure 1 It is a schematic diagram of the scenario of a swapping station scheduling processing method provided by an embodiment of the present application;

[0037] Figure 2 It is a schematic flowchart of a swapping station scheduling processing method provided by an embodiment of the present application;

[0038] Figure 3 It is a schematic flowchart of the simulation of a swapping station providing swapping services in a simulation model provided by an embodiment of the present application;

[0039] Figure 4 It is a schematic flowchart of another swapping station scheduling processing method provided by an embodiment of the present application;

[0040] Figure 5 It is a schematic structural diagram of a swapping station scheduling processing device provided by an embodiment of the present application;

[0041] Figure 6 It is a schematic structural diagram of a swapping station scheduling processing device provided by an embodiment of the present application.

[0042] Through the above-mentioned drawings, specific embodiments of the present application have been shown, and will be described in more detail hereinafter. These drawings and the written description are not intended to limit the scope of the concept of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by reference to specific embodiments. Detailed Description of the Embodiments

[0043] Exemplary embodiments will be described in detail herein, and examples thereof are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0044] For ease of understanding, first, the scenario of the power exchange station scheduling processing method provided by the present application will be introduced. Figure 1 It is a schematic diagram of the scenario of a power exchange station scheduling processing method provided by an embodiment of the present application. As Figure 1 shown, this scenario includes:

[0045] Power exchange station: used to replace the battery pack of a heavy truck vehicle and charge the replaced battery pack. Among them, N battery packs can be pre-existing in the power exchange station, and the model and / or capacity of the battery pack are the same as those of the battery pack installed and used in the heavy truck vehicle, where N is an integer greater than or equal to 1. In the following embodiments, it is assumed that each heavy truck vehicle can and can only install one battery pack for illustration.

[0046] Working area: This working area includes at least one loading area and at least one unloading area. The heavy truck vehicle performs loading and unloading operations between the loading area and the unloading area. When the heavy truck vehicle drives from the loading area to the unloading area, the heavy truck vehicle is in a fully loaded state; when the heavy truck vehicle drives from the unloading area to the loading area, the heavy truck vehicle is in an empty state. The consumption rate of the state of charge (SOC) of the heavy truck vehicle per minute is different in the fully loaded state and the empty state.

[0047] If there are multiple loading areas and multiple unloading areas, for each heavy truck vehicle, the loading area and the unloading area for each round trip can be the same group or different. For example, assume there are three loading areas, Loading Area 1, Loading Area 2, and Loading Area 3; and there are three unloading areas, Unloading Area 1, Unloading Area 2, and Unloading Area 3. For Heavy Truck Vehicle 1, it can be fixed to operate between Loading Area 1 and Unloading Area 1, or it can operate between Loading Area 1 and Unloading Area 1 for the first time and between Loading Area 1 and Unloading Area 2 for the second time. The present application does not limit this.

[0048] Among them, for each battery pack, there are a charging threshold and a to-be-charged threshold. The charging threshold means that after the battery pack is charged to a certain SOC in the battery swapping station, the battery pack is allowed to be replaced onto the heavy truck waiting for battery swapping; the to-be-charged threshold means that when the SOC of the battery pack on the heavy truck reaches this to-be-charged threshold, the heavy truck needs to go to the battery swapping station to replace the battery pack. The above charging threshold and to-be-charged threshold can be set according to user requirements, and this application does not limit this.

[0049] In the scenario of this application, the vehicles served by the battery swapping station are heavy trucks. The driving routes of such heavy trucks mainly depend on the content of the operation tasks. For example, the operation task instructs the heavy truck to first perform loading and unloading operations from loading point 1 to unloading point 2, and then perform loading and unloading operations from loading point 2 to unloading point 3, etc. Therefore, the driving routes, driving times, and the SOC consumed each time the operation task is executed of the heavy trucks are all different. Secondly, the battery swapping station only needs to swap the battery for the heavy trucks according to the actual arrival time sequence of the heavy trucks at the battery swapping station, and does not require the heavy trucks to make a battery swapping reservation in advance at the battery swapping station.

[0050] However, the existing battery swapping stations mainly provide battery swapping services for electric buses or electric vehicles that need to make a reservation for battery swapping. The scheduling and processing methods of such battery swapping stations mainly include the following two types:

[0051] Method 1: A battery swapping station scheduling and processing method based on fixed time and route.

[0052] This method is applied to the scenario where electric buses operate on a fixed route based on a departure schedule. This method simulates the operation process of electric buses according to the parameters characterizing the battery swapping capacity of the battery swapping station, such as the number of spare battery packs and the charging efficiency of the battery swapping station, and the parameters during the operation of electric buses, such as the number of electric buses, the power consumption speed of the battery packs, the driving routes, and the driving time statistical tables. Based on this operation process, corresponding evaluation indicators are extracted according to actual needs, so as to match the battery swapping requirements of electric buses and the battery charging requirements, ensure the balanced use of battery packs, and increase the service life of battery packs.

[0053] However, this method depends on the driving time and driving route of electric buses must conform to the specified time and route, and cannot solve the problem of battery swapping station scheduling and processing in the scenario of non-fixed routes and fixed driving times of the heavy trucks in this application.

[0054] Method 2: A battery swapping station scheduling and processing method based on reservation behavior.

[0055] This method is applicable to battery swapping vehicles that perform battery swapping for all real-time reservations. By obtaining the battery pack SOC data, the time required to fully charge the battery pack, and the number of battery swapping vehicles, the service capacity of the battery swapping station is evaluated, and scheduling processing is performed based on the service capacity of the battery swapping station.

[0056] However, this method relies on the real-time reservation behavior of battery swapping vehicles and cannot solve the problem of scheduling processing for battery swapping stations in the scenario where heavy truck vehicles do not make battery swapping reservations in this application.

[0057] In view of this, this application provides a method for scheduling processing of a battery swapping station. Through the simulation model of the battery swapping station, the processes of the battery swapping station providing battery swapping services for different numbers of heavy truck vehicles are respectively simulated to obtain a first parameter that can characterize the matching degree between the number of heavy truck vehicles and the battery swapping capacity of the battery swapping station. Thus, the number of heavy truck vehicles suitable for the battery swapping station can be obtained based on each first parameter, and based on this number, the heavy truck vehicles served by the battery swapping station are scheduled, improving the accuracy of scheduling the number of heavy truck vehicles served by the battery swapping station.

[0058] The execution subject of the embodiment of this application can be a computing device, or a computing cluster including multiple computing devices, or a cloud platform. The above-mentioned computing device can be, for example, a terminal device, a server, a virtual machine, etc. When the execution subject is a cloud platform, the method it executes can be provided to users in the form of cloud services. For example, users access the cloud platform through a client or a web page to use the cloud service to implement the method provided by the embodiment of this application.

[0059] Taking the execution subject as a computing device as an example below, the technical solutions of the embodiments of this application will be described in detail in combination with specific embodiments. These specific embodiments below can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments.

[0060] Figure 2 It is a schematic flowchart of a method for scheduling processing of a battery swapping station provided by an embodiment of this application. As Figure 2 shown, the method includes:

[0061] S201. Use multiple sets of input data to perform battery swapping simulation on the battery swapping station through the simulation model of the battery swapping station, and obtain multiple first parameter values corresponding to the multiple sets of input data.

[0062] Wherein, each set of input data includes: the number of heavy truck vehicles. This first parameter value is used to characterize the matching degree between the number of the heavy truck vehicles and the battery swapping capacity of the battery swapping station.

[0063] The number of the above heavy-duty trucks represents the number of heavy-duty trucks that the battery swapping station can serve in this simulation of the simulation model of the battery swapping station. According to this number of heavy-duty trucks, the purpose of scheduling the number of heavy-duty trucks served by the battery swapping station is achieved. This input parameter can be input by the user or randomly generated by the system under preset rules.

[0064] The simulation model of the battery swapping station can be built, for example, according to the parameters of the battery swapping station in reality, so as to simulate the process of the battery swapping station serving heavy-duty trucks. The simulation model of the battery swapping station can also be built, for example, according to the parameters of the battery swapping station input according to the actual needs of the user, in order to pre-simulate the ability of the battery swapping station to serve heavy-duty trucks under these parameters.

[0065] The above-mentioned ability of the battery swapping station to serve heavy-duty trucks includes the battery swapping ability. This battery swapping ability can include, for example: the time required for the battery swapping station to replace the battery pack of a heavy-duty truck, the charging speed of the battery swapping station to charge the battery pack, and how many heavy-duty trucks can have their battery packs replaced simultaneously, etc.

[0066] According to the above-mentioned battery swapping simulation, multiple sets of input parameters can be input for multiple battery swapping simulations to obtain corresponding multiple first parameter values. This first parameter value can be obtained, for example, by acquiring data such as the battery swapping behavior of heavy-duty trucks and the charging behavior of the battery swapping station during the battery swapping simulation. The matching degree between the number of the above-mentioned heavy-duty trucks and the battery swapping ability of the battery swapping station can be, for example, when serving a certain number of heavy-duty trucks by the battery swapping station, how to ensure as many loading and unloading trips of all heavy-duty trucks as possible, and the total time consumed by heavy-duty trucks for average battery swapping is shorter. In this example, when the first parameter value is larger, it means that under the condition of ensuring as many loading and unloading trips of all heavy-duty trucks as possible, the total time consumed by heavy-duty trucks for average battery swapping is shorter, and the above-mentioned matching degree is higher; when the first parameter value is larger, it means that under the condition of ensuring as many loading and unloading trips of all heavy-duty trucks as possible, the total time consumed by heavy-duty trucks for average battery swapping is longer, and the above-mentioned matching degree is lower.

[0067] S202. Determine the target first parameter value from the above multiple first parameter values.

[0068] According to actual needs, one of the above multiple first parameter values can be selected as the target first parameter value. For example, when a larger first parameter value represents a higher matching degree between the number of heavy-duty trucks and the battery swapping ability of the battery swapping station, the maximum value of the above multiple first parameter values is selected as the target first parameter value.

[0069] S203. Schedule the heavy-duty trucks served by the battery swapping station according to the number of heavy-duty trucks corresponding to the above target first parameter value.

[0070] After obtaining the target first parameter value, the input data input when the simulation model of the corresponding battery swap station obtains the target first parameter value is obtained, and the number of heavy trucks input is obtained from the above input data. At this time, the number of heavy trucks obtained is used as the basis for dispatching the number of heavy trucks served by the battery swap station. If the number of heavy trucks is too large, the excess heavy trucks will be dispatched to other battery swap stations; if the number of heavy trucks is too small, the excess heavy trucks in other battery swap stations will be dispatched to this battery swap station.

[0071] The battery swap station scheduling and processing method provided in the embodiment of the present application obtains multiple first parameter value results corresponding to each set of input data by inputting multiple groups of input data and performing multiple simulations using a simulation model of the battery swap station, and judges the matching degree between the number of heavy-duty trucks and the battery swapping capacity of the battery swap station. Thus, based on the determined target first parameter value, a better scheduling and processing strategy for the battery swap station can be obtained without requiring heavy-duty trucks to travel at the specified time and on the specified route, and without making battery swapping reservations, thereby scheduling the number of heavy-duty trucks served by the battery swap station.

[0072] Next, the simulation model of the battery swap station described above is used to simulate the process of the battery swap station serving a heavy truck. When there are multiple heavy trucks in the closed environment consisting of the battery swap station and the work area, the heavy truck identified as 1 is used as an example. The operation process of the heavy truck in the environment consisting of the battery swap station and the work area in the simulation is as shown in the following embodiment.

[0073] Figure 3 A simulation flow chart of a battery swap service provided by a battery swap station in a simulation model provided in an embodiment of the present application. Figure 3 As shown, the process includes:

[0074] S301, the heavy truck 1 travels back and forth between the loading point and the unloading point in the work area to perform operations until the battery pack 1 on the heavy truck 1 reaches a threshold value to be charged.

[0075] The initial position of the heavy truck 1 can be randomly generated by the simulation model in the work area; the initial SOC of the battery pack 1 of the heavy truck 1 can be input by the user as an input parameter, or can be randomly generated by the simulation model. The number of loading and unloading trips that the heavy truck 1 can complete with the initial SOC of the battery pack 1 is:

[0076] (Battery pack 1 initial SOC - battery replacement threshold) / (first remaining power SOC consumption + second remaining power SOC consumption)

[0077] S302: When the battery pack 1 on the heavy truck 1 reaches the charging threshold, the heavy truck 1 travels from the unloading point to the battery swap station.

[0078] Among them, the time required for the heavy truck vehicle 1 to travel from the unloading point to the battery swapping station is the third time consumed, and the power consumption is the third SOC consumption.

[0079] S303. The battery swapping station determines whether there is currently a battery pack that has reached the charging threshold. If there is, directly replace the battery pack that has reached the charging threshold onto the heavy truck vehicle 1; if not, the heavy truck vehicle 1 needs to wait for the battery swapping station to charge the battery pack until there is a battery pack that has reached the charging threshold.

[0080] Among them, if there are other heavy truck vehicles that arrived at the battery swapping station earlier than the heavy truck vehicle 1 waiting for battery swapping, or are in the process of battery swapping, the heavy truck vehicle 1 needs to queue up and wait for all the heavy truck vehicles before it to complete battery swapping before it can execute step S303.

[0081] Based on the sum of the time consumed for the heavy truck vehicle 1 to reach the battery swapping station, the queuing time at the battery swapping station, the time for replacing the battery, and the time for returning to the work area after completing battery swapping, the total time consumed for a single battery swap of the heavy truck vehicle can be obtained as described above.

[0082] S304. When the heavy truck vehicle 1 completes battery swapping, the heavy truck vehicle returns from the battery swapping station to the work area and continues to operate.

[0083] Among them, after the heavy truck vehicle 1 completes battery swapping, the battery pack 1 is charged at the battery swapping station, and the remaining SOC of the newly replaced battery pack of the heavy truck vehicle 1 is at least greater than the aforementioned charging threshold.

[0084] S305. Loop through steps S301 - S304 until the target simulation duration is reached.

[0085] For other heavy truck vehicles in the simulation model, their operation processes are the same as that of the heavy truck vehicle 1, and the operation processes of multiple heavy truck vehicles are simultaneously simulated in the simulation model. The number of heavy truck vehicles is input by the aforementioned input data.

[0086] During the simulation process of the simulation model, the simulation model can record the battery pack data and heavy truck vehicle data generated during the simulation process for calculating the corresponding first parameter value, so as to schedule the heavy truck vehicles served by the battery swapping station.

[0087] Among them, the battery pack data generated during the simulation process may include, for example: the identification of the battery pack, the number of battery pack replacements, the SOC value of the battery pack, the status of the battery pack, etc. Different battery packs are distinguished according to the identification of the battery pack, so as to record the different states of each battery pack and the SOC values at different time points under different states. The status of the battery pack may include, for example: charging in the battery swapping station, performing operations on the heavy truck with the heavy truck, being disassembled from the heavy truck, and just being installed on the heavy truck, etc. Through the status of the battery pack, the SOC value of the battery pack at the beginning of each state is obtained, so that the number of battery pack replacements and the SOC values of multiple groups of battery packs can be obtained. The SOC value of each group of battery packs may be grouped, for example, based on two battery swapping behaviors of the battery pack.

[0088] Therefore, according to the battery pack data, the number of battery pack replacements for each battery pack, and the SOC value of each battery pack when it is just replaced on the heavy truck vehicle, the SOC value when starting to charge, the time required to charge the battery pack to the charging threshold, and other data can be obtained. Thus, data such as the average discharge depth of the battery pack and the average number of loading and unloading trips completed by the heavy truck vehicle can be conveniently calculated.

[0089] The heavy truck vehicle data generated during the simulation process may include, for example: the identification of the heavy truck vehicle, the time point when each heavy truck vehicle arrives at the battery swapping station, the battery swapping sequence of each heavy truck vehicle, etc. Different heavy truck vehicles are distinguished according to the identification of the heavy truck vehicle. The time point when each heavy truck vehicle arrives at the battery swapping station can be determined according to the judgment of the operating state of the heavy truck vehicle. The operating state may include, for example: in operation, driving to the battery swapping station, waiting for battery swapping in the battery swapping station, performing battery swapping, and returning to the work area, etc.

[0090] Through the heavy truck vehicle data generated during the above simulation process, when the battery swapping station provides battery swapping services, the number of battery swaps of the heavy truck vehicle, the exact time consumed by the heavy truck vehicle, etc. can be obtained, thereby providing a data basis for calculating the total duration consumed by a single heavy truck vehicle for a single battery swap.

[0091] The method provided in the embodiments of the present application simulates the operation process of a heavy truck vehicle in an environment composed of a battery swapping station and a work area, collects the battery pack data and heavy truck vehicle data generated during this operation process, to be used for calculating the corresponding first parameter value, thereby scheduling the heavy truck vehicles served by the battery swapping station to meet the number of heavy truck vehicles corresponding to the first parameter value.

[0092] Next, a method for constructing a simulation model of the above-mentioned battery swapping station will be introduced. Before using multiple groups of input data to perform battery swapping simulation on the battery swapping station through the simulation model of the battery swapping station to obtain multiple first parameter values corresponding to the multiple groups of input data, it also includes constructing the simulation model of the above-mentioned battery swapping station according to the simulation construction parameters. The construction process of this simulation model is specifically as follows:

[0093] The above-mentioned construction parameters include: simulation parameter values of the battery swap station and simulation parameter values of the working area of the heavy truck.

[0094] Among them, the simulation parameters of the battery swap station include at least one of the following: the charging speed of the battery pack, the time consumed for battery swapping of heavy trucks, the cost data required for charging the battery pack, and the construction cost data of the battery swap station.

[0095] The charging speed of the battery pack can be, for example, the speed at which the battery swap station can charge the battery pack per minute, which can be calculated by the charging rate of the battery swap station (charging current of the battery swap station / rated capacity of the battery pack). The charging speed of the battery pack can be used to calculate the charging status of the battery pack being charged in the battery swap station, and then determine whether there is a battery pack that has reached the charging threshold when the heavy truck is swapping batteries, thereby affecting the total time consumed for a single battery swap of a single heavy truck.

[0096] The time spent on battery replacement for a heavy truck refers to the time it takes for a battery replacement station to remove the battery pack of a heavy truck and replace it with a new one. The time spent on battery replacement for the heavy truck, the time spent waiting for battery replacement, the time spent driving from the unloading point to the battery replacement station, and the time spent driving from the battery replacement station to the loading point after the battery replacement are the total time spent on a single battery replacement for a single heavy truck.

[0097] The cost data required for charging the battery pack may be, for example, the charging cost data required when the battery swap station charges one battery pack per minute, for example, the electricity cost data.

[0098] The construction cost data of the battery swap station can be, for example, the construction cost data generated when the battery swap station was built historically, or the construction cost data expected to be generated when the battery swap station is built in the future, and the construction cost data allocated to the total time the battery swap station is expected to provide services. For example, the construction cost data generated when the battery swap station was built historically is 1 million yuan, and the battery swap station is expected to provide battery swap services for 10 years, then the annually allocated construction cost data is 100,000 yuan. This application can also further allocate the allocated construction cost data to each month, day, etc., which will not be repeated here.

[0099] Among them, the simulation parameters of the working area of the heavy-duty truck include at least one of the following: the charging threshold of the battery pack; the first remaining power SOC consumption of the battery pack corresponding to the heavy-duty truck traveling from the loading point to the unloading point, and the first time consumed; the second SOC consumption of the battery pack corresponding to the heavy-duty truck traveling from the unloading point to the loading point, and the second time consumed; the third SOC consumption of the battery pack corresponding to the heavy-duty truck traveling from the unloading point to the battery swap station, and the third time consumed.

[0100] The charging threshold of the battery pack means that when the State of Charge (SOC) of the battery pack on the heavy-duty truck reaches this charging threshold, the heavy-duty truck needs to go to the battery swapping station to replace the battery pack.

[0101] The first remaining SOC consumption of the battery pack corresponding to the heavy-duty truck traveling from the loading point to the unloading point is the SOC consumed by the heavy-duty truck traveling from the loading point to the unloading point. When there are actually multiple loading points and multiple unloading points, the consumed SOC can be, for example, the average value of the SOC consumed by all combinations of loading points and unloading points. The first duration consumed is the duration taken by the heavy-duty truck to travel from the loading point to the unloading point. When there are actually multiple loading points and multiple unloading points, the consumed duration can be the average duration.

[0102] The second SOC consumption of the battery pack corresponding to the heavy-duty truck traveling from the unloading point to the loading point, and the second duration consumed; and the third SOC consumption of the battery pack corresponding to the heavy-duty truck traveling from the unloading point to the battery swapping station, and the third duration consumed are similar to the first remaining SOC consumption of the battery pack corresponding to the heavy-duty truck traveling from the loading point to the unloading point and the first duration consumed, except for the difference in the starting point and the arrival point. Details are not described here again.

[0103] In a possible implementation, at least one of the simulation construction parameters can be obtained based on the historical battery swapping data of the battery swapping station to schedule heavy-duty trucks at the battery swapping station.

[0104] In another possible implementation, the battery swapping data of the battery swapping station can be set according to actual needs, and at least one of the simulation construction parameters can be obtained to solve the scheduling processing problem of building a future battery swapping station that conforms to the battery swapping data.

[0105] Based on the above construction parameters, simulate the operation process of each heavy-duty truck in the environment composed of the battery swapping station and the working area, and build a simulation model of the battery swapping station.

[0106] The method provided by the embodiments of this application builds a simulation model of the corresponding battery swapping station in the case where the vehicle does not need to run according to a fixed time and a fixed route and does not need to make a battery swapping reservation by setting multiple construction parameters and simulating the operation process of the heavy-duty truck in the actual situation, thereby expanding the application scope of the simulation model and improving the accuracy of the scheduling process of the battery swapping station.

[0107] In the process of scheduling heavy truck vehicles served by the swap station using the above-mentioned simulation model of the swap station, there can be multiple implementation methods. For example, for the above-mentioned "using multiple sets of input data to perform a swapping simulation on the swap station through the simulation model of the swap station to obtain multiple first parameter values corresponding to the multiple sets of input data", the first parameter value can be directly output by the above-mentioned simulation model, or it can be that the simulation model calculates and outputs an intermediate parameter value, and the calculation device calculates and obtains the first parameter value based on this intermediate parameter value. Below, taking the simulation model calculating and outputting an intermediate parameter value, and the calculation device calculating and obtaining the first parameter value based on this intermediate parameter value as an example, a detailed description is given:

[0108] Figure 4 It is a schematic flowchart of another swap station scheduling processing method provided by an embodiment of the present application.

[0109] As Figure 4 shown, the above step S201 may include, for example:

[0110] S401. Input each set of input data into the simulation model of the swap station to perform a swapping simulation on the swap station through the simulation model of the swap station to obtain an intermediate parameter value corresponding to each set of input data.

[0111] The above intermediate parameters include: the average discharge depth of the battery pack, the total time consumed for a single swapping of a single heavy truck vehicle, the average number of loading and unloading trips completed by the heavy truck vehicle, and a second parameter of the swap station, where the second parameter is used to characterize the average revenue data of the swap station providing swapping services for heavy truck vehicles.

[0112] Among them, the average discharge depth of the battery pack is the average discharge depth of each battery pack under the current input data. The above battery packs include the battery packs on each heavy truck vehicle and the battery packs in the swap station. That is, the calculation method of the average discharge depth of the battery pack is specifically shown in formula (1):

[0113] P = M + N (1)

[0114] Among them, P is the total number of battery packs, M is the number of battery packs in the swap station, and N is the number of heavy truck vehicles. Since according to the foregoing assumption, there is only one battery pack on each heavy truck vehicle, the number of heavy truck vehicles here is the number of battery packs on all heavy truck vehicles.

[0115] At this time, the average discharge depth (Depth of discharge, DoD) of each battery pack can be obtained according to the total number of battery packs. The discharge depth mentioned here is the percentage of the discharge amount of the battery pack to the rated capacity of the battery pack. The calculation method of the average discharge depth of the battery pack is specifically shown in formula (2):

[0116]

[0117] Among them, avg_DOD is the average depth of discharge of the battery pack; DOD p is the total depth of discharge of battery pack p under multiple battery swapping conditions. For example, if battery pack 1 is swapped onto a heavy truck vehicle 3 times, the depth of discharge for the first time is 60%, the depth of discharge for the second time is 65%, and the depth of discharge for the third time is 70%, then DOD P is 195%; L P is the number of battery swaps of battery pack p.

[0118] The total time consumed for a single battery swap of a heavy truck vehicle is the average time consumed for a single battery swap by each heavy truck vehicle during the simulation process. The time consumed for a single battery swap mentioned here is the time period from when the heavy truck vehicle departs from the work area to when it returns to the work area after completing the battery swap, that is, specifically as shown in formula (3):

[0119]

[0120] Among them, avg_time is the total time consumed for a single battery swap of a heavy truck vehicle; is the time consumed for heavy truck vehicle n to drive from the unloading area to the battery swapping station; is the time consumed for heavy truck vehicle n to drive from the battery swapping station to the loading area; T change_n is the time consumed for heavy truck vehicle n to replace the battery pack in the battery swapping station; T line_n is the time consumed for heavy truck vehicle n to queue up for battery swapping in the battery swapping station.

[0121] The average number of loading and unloading trips completed by heavy truck vehicles refers to the sum of the loading and unloading trips of all heavy truck vehicles divided by the number of heavy truck vehicles. Among them, during this simulation process, each heavy truck vehicle takes the process from loading at the loading area to unloading at the unloading area as one complete loading and unloading trip. Its calculation method is specifically as shown in formula (4):

[0122]

[0123] The above avg_L is the average number of loading and unloading trips completed by heavy truck vehicles; L n is the total number of loading and unloading trips of heavy truck vehicle n during the simulation process. Among them, the computing device can directly obtain the number of loading and unloading trips of heavy truck vehicle n during the simulation process, or can calculate the average number of loading and unloading trips completed by heavy truck vehicles through the total depth of discharge of each battery pack corresponding to heavy truck vehicle n, as well as the depth of discharge of heavy truck vehicle once fully loaded from the loading area to the unloading area and the depth of discharge of heavy truck vehicle once empty from the unloading area to the loading area.

[0124] For the second parameter of the battery swapping station, the average revenue data for the battery swapping station to provide battery swapping services for heavy-duty trucks can be the battery swapping revenue data obtained when the battery swapping station provides battery swapping services for heavy-duty trucks; or it can be the combination of the cost data of the battery swapping station to provide battery swapping services and the revenue data obtained from the operations of heavy-duty trucks. Exemplarily, the combination of this revenue data can be, for example:

[0125] When the battery swapping station provides battery swapping services for heavy-duty trucks, there are cost data, such as the charging cost data of the battery pack, the allocation of the initial construction cost data of the battery swapping station, etc.; there is also revenue data brought about by the loading and unloading of heavy-duty trucks. The revenue data mentioned here for the battery swapping station to provide battery swapping services for heavy-duty trucks is the revenue data of the battery swapping station minus the cost data of the battery swapping station.

[0126] In this case, its calculation method is specifically shown in formula (5):

[0127]

[0128] Wherein, is the average revenue data for the battery swapping station to provide battery swapping services for heavy-duty trucks; G_l is the revenue data of all heavy-duty trucks for loading and unloading, and the revenue data of all heavy-duty trucks for loading and unloading can be obtained according to the number of loading and unloading trips of heavy-duty trucks and the revenue data for each loading and unloading; C_DOD is the total charging cost data, and the total charging cost data can be obtained according to the product of the sum of the discharge depths of all battery packs and the charging cost data for each 1% of the battery pack SOC; C_all is the initial construction cost data of the battery swapping station, and Y is the total time for which the battery swapping station expects to provide services, thereby allocating the initial construction cost data of the battery swapping station to the unit time of the battery swapping station to provide services.

[0129] Regarding how to perform battery swapping simulation on the battery swapping station through the simulation model of the battery swapping station to obtain the intermediate parameter values corresponding to each set of input data, for example, there can be the following implementation methods:

[0130] Implementation method A: The simulation model outputs the initial parameter values, and the intermediate parameter values are calculated through these initial parameter values.

[0131] Input each set of input data into the simulation model of the battery swapping station, so that the simulation model performs battery swapping simulation within the target simulation duration to obtain the initial parameter values corresponding to each set of input data, and according to these initial parameter values, obtain the intermediate parameter values corresponding to each set of input data.

[0132] Wherein, the above initial parameter values include: the number of battery swapping times for each heavy-duty truck, the number of battery swapping times for each battery pack, the total discharge depth of each battery pack, the total duration consumed for each battery swapping of each heavy-duty truck, and the initial power of each battery pack replaced by each heavy-duty truck each time.

[0133] During the replacement power simulation process, the initial parameter values can be obtained through the simulation model of the replacement power station. For example, according to the recorded replacement power behavior of each heavy truck vehicle, the number of replacement power times of each heavy truck vehicle is obtained. According to the recorded replacement power behavior of each battery pack, the number of replacement power times of each battery pack is obtained. According to the recorded SOC when each battery pack is just replaced onto the heavy truck vehicle and the SOC when it is just replaced off the heavy truck vehicle, the SOC consumed by each battery pack each time on the heavy truck vehicle is obtained, so as to obtain the sum of the SOC consumed each time after being replaced onto the heavy truck vehicle. Taking the sum of the SOC consumed each time after being replaced onto the heavy truck vehicle as the total discharge depth of the battery pack. Among them, the SOC consumed each time after being replaced onto the heavy truck vehicle can also be obtained by subtracting the charging threshold from the initial power of the battery pack replaced by each heavy truck vehicle each time. According to the monitored time points when each heavy truck vehicle reaches the power replacement threshold and the time points when each heavy truck vehicle returns to the working area after completing the power replacement, the total duration of a single power replacement of each heavy truck vehicle is obtained.

[0134] After obtaining the initial parameter values, according to the calculation method of each intermediate parameter value in step S401, the calculation device calculates the intermediate parameter values based on the initial parameter values.

[0135] A possible implementation manner is that the above input data further includes at least one of the following: the initial power of the battery pack of each heavy truck vehicle, the identifier of each heavy truck vehicle, and the identifier of the battery pack of each heavy truck vehicle.

[0136] Among them, the initial power of the battery pack of each heavy truck vehicle is used to determine the SOC consumed by the battery pack during the first power replacement; the identifier of each heavy truck vehicle is used to distinguish the power replacement behavior of different heavy truck vehicles, as well as the loading and unloading behavior, etc.; the identifier of the battery pack of each heavy truck vehicle is used to distinguish the battery packs replaced by different heavy truck vehicles each time.

[0137] By inputting the initial power of the battery pack of each heavy truck vehicle, the process of the replacement power station serving heavy truck vehicles under different conditions can be simulated more accurately, thereby expanding the applicable range of the simulation model.

[0138] In addition, before performing the power replacement simulation on the replacement power station through the simulation model of the replacement power station using multiple sets of input data, the calculation device can also receive the configuration data of the simulation model to configure the model.

[0139] The above configuration data includes at least one of the following: the target simulation duration and the target number of battery packs of the replacement power station.

[0140] The above target simulation duration can be set according to the actual needs of the user and pre-configured in the simulation model. The above target simulation duration can be set to, for example, 6 hours, one day, etc. Correspondingly, the simulation model simulates the battery swapping behavior within 6 hours, or one day. When the simulation behavior of the simulation model reaches the target simulation duration, the simulation stops, and this simulation ends. It is necessary to input the next set of input data to start the next simulation. Thus, according to the results of multiple simulation simulations corresponding to multiple sets of data, the heavy truck vehicles served by the battery swapping station are scheduled. 。

[0141] The target number of battery packs of the above battery swapping station refers to the number of battery packs included in the battery swapping station. This number can be determined according to the actual number of battery packs of the existing battery swapping station, or can be determined according to the expected number of battery packs of the battery swapping station to be built in the future. When the number of battery packs of the battery swapping station changes, the battery swapping capacity of the battery swapping station will also change accordingly. Therefore, by configuring the target number of battery packs of the battery swapping station, the model can be applied to more battery swapping station scenarios.

[0142] Embodiment B: The simulation model directly outputs intermediate parameter values.

[0143] During the simulation process, the simulation model of the battery swapping station can directly record intermediate parameter values such as the average discharge depth of the battery pack, the total duration consumed by a single heavy truck for a single battery swap, the average number of loading and unloading trips completed by the heavy truck, and the second parameter of the battery swapping station. The second parameter is used to characterize the average revenue data of the battery swapping station providing battery swapping services for heavy trucks. After the simulation ends, the simulation model outputs the intermediate parameter values it records.

[0144] S402. Obtain the first parameter value corresponding to each group of input data according to the intermediate parameter value corresponding to each group of input data and the weight corresponding to each intermediate parameter value.

[0145] Among them, the weight corresponding to each intermediate parameter value can be set according to actual needs, and this application does not limit this. In this step, by performing weighted summation of each intermediate parameter value and its corresponding weight, the value obtained by weighted summing each intermediate parameter value and its corresponding weight is used as the first parameter value corresponding to each group of input data.

[0146] Exemplarily, the calculation method of the first parameter value is specifically shown in formula (6):

[0147]

[0148] Among them, E N is the first parameter value corresponding when the number of heavy trucks in the input data is N; α 1,N is the weight value corresponding to the average discharge depth of the battery pack; avg_DODN When the number of heavy - duty trucks in the input data is N, the average discharge depth of the battery pack; α 2,N The weight value corresponding to the total time consumed for a single battery swap of a single heavy - duty truck; avg_time N When the number of heavy - duty trucks in the input data is N, the total time consumed for a single battery swap of a single heavy - duty truck; α 3,N The weight value corresponding to the average number of loading and unloading trips completed by heavy - duty trucks; avg_L N When the number of heavy - duty trucks in the input data is N, the average number of loading and unloading trips completed by heavy - duty trucks; α 4,N The weight value corresponding to the second parameter of the battery - swapping station; When the number of heavy - duty trucks in the input data is N, the second parameter of the battery - swapping station.

[0149] After obtaining multiple first - parameter values corresponding to multiple groups of input data, the target first - parameter value can be determined according to the method in the foregoing step S202. Based on this target first - parameter value, the battery - swapping station is scheduled according to the method in the foregoing step S203.

[0150] Exemplarily, if the number of heavy - duty trucks in each group of input data of the present application is different, then according to the number of heavy - duty trucks in the input data corresponding to the target first - parameter value, the scheduling strategy of the battery - swapping station is determined, that is, the number of heavy - duty trucks served by the battery - swapping station is scheduled to the number of heavy - duty trucks in the input data corresponding to the above - mentioned target first - parameter value.

[0151] The method provided by the embodiments of the present application obtains the intermediate parameter values included in the battery - swapping simulation process of the simulation model of the battery - swapping station, performs weighted summation on these intermediate parameter values, thereby obtaining the first - parameter value of the battery - swapping station to reflect the battery - swapping ability of the battery - swapping station. Based on multiple groups of the first - parameter values of the battery - swapping station obtained from multiple groups of input data, the input data group suitable for the actual requirements is selected, thereby determining the scheduling target strategy of the battery - swapping station, and scheduling the heavy - duty trucks served by the battery - swapping station according to this scheduling target strategy.

[0152] Figure 5 It is a schematic structural diagram of a battery - swapping station scheduling device provided by an embodiment of the present application. This battery - swapping station scheduling device can be, for example, the aforementioned computing device. As Figure 5 shown, this battery - swapping station scheduling device includes: a simulation module 11, a determination module 12, and a scheduling module 13. In a possible implementation manner, it further includes: a receiving module 14 and a construction module 15.

[0153] The simulation module 11 is used to perform battery swapping simulation on the battery swapping station by means of the simulation model of the battery swapping station using multiple groups of input data, and obtain multiple first parameter values corresponding to the multiple groups of input data. Each group of input data includes: the number of heavy-duty trucks, and the first parameter value is used to characterize the matching degree between the number of heavy-duty trucks and the battery swapping capacity of the battery swapping station.

[0154] The determination module 12 is used to determine the target first parameter value from the multiple first parameter values.

[0155] The scheduling module 13 is used to schedule the heavy-duty trucks served by the battery swapping station according to the number of heavy-duty trucks corresponding to the target first parameter value.

[0156] A possible implementation manner, the simulation module 11 is specifically used to input each group of input data into the simulation model of the battery swapping station, so as to perform battery swapping simulation on the battery swapping station through the simulation model of the battery swapping station, and obtain intermediate parameter values corresponding to each group of input data. According to the intermediate parameter values corresponding to each group of input data and the weight corresponding to each intermediate parameter value, obtain the first parameter value corresponding to each group of input data. The above intermediate parameters include: the average discharge depth of the battery pack, the total duration consumed by a single heavy-duty truck for a single battery swap, the average number of loading and unloading trips completed by the heavy-duty truck, the second parameter of the battery swapping station, and the second parameter is used to characterize the average revenue data of the battery swapping station for providing battery swapping services to heavy-duty trucks.

[0157] A possible implementation manner, the simulation module 11 is specifically used to input each group of input data into the simulation model of the battery swapping station, so that the simulation model performs battery swapping simulation within the target simulation duration to obtain the initial parameter values corresponding to each group of input data. According to the initial parameter values, obtain the intermediate parameter values corresponding to each group of input data. The above initial parameter values include: the number of battery swaps of each heavy-duty truck, the number of battery swaps of each battery pack, the total discharge depth of each battery pack, the total duration consumed by each heavy-duty truck for a single battery swap, and the initial battery power of each battery pack replaced by each heavy-duty truck each time.

[0158] In this implementation manner, optionally, the above input data further includes at least one of the following: the initial battery power of the battery pack of each heavy-duty truck, the identifier of each heavy-duty truck, and the identifier of the battery pack of each heavy-duty truck.

[0159] A possible implementation manner, the receiving module 14 is used to receive the configuration data of the simulation model before the simulation module 11 performs battery swapping simulation on the battery swapping station by means of the simulation model of the battery swapping station using multiple groups of input data. The above configuration data includes at least one of the following: the target simulation duration, and the target number of battery packs of the battery swapping station.

[0160] A possible implementation, a construction module 15, is used to construct the simulation model according to the simulation construction parameters before the simulation module 11 uses multiple sets of input data to perform a battery swapping simulation on the battery swapping station through the simulation model of the battery swapping station to obtain multiple first parameter values corresponding to the multiple sets of input data. Among them, the construction parameters include: the simulation parameter values of the battery swapping station, and the simulation parameter values of the working area of the heavy truck. The simulation parameters of the battery swapping station include at least one of the following: the charging speed of the battery pack, the time consumed for the heavy truck to swap the battery, the cost data required for the battery pack to be charged, and the construction cost data of the battery swapping station. The simulation parameters of the working area of the heavy truck include at least one of the following: the threshold value of the battery pack to be charged; the first remaining state of charge (SOC) consumption of the battery pack corresponding to the heavy truck driving from the loading point to the unloading point, and the first time consumed; the second SOC consumption of the battery pack corresponding to the heavy truck driving from the unloading point to the loading point, and the second time consumed; the third SOC consumption of the battery pack corresponding to the heavy truck driving from the unloading point to the battery swapping station, and the third time consumed.

[0161] A possible implementation, the construction module 15, is further used to obtain at least one of the simulation construction parameters according to the historical battery swapping data of the battery swapping station.

[0162] The battery swapping station scheduling processing device provided in the embodiments of the present application can execute the battery swapping station scheduling processing method in the above method embodiments, and its implementation principle and technical effects are similar, which will not be elaborated here.

[0163] Figure 6 It is a schematic structural diagram of a battery swapping station scheduling processing device provided in the embodiments of the present application. Among them, the battery swapping station scheduling processing device is used to execute the aforementioned battery swapping station scheduling processing method, and for example, it can be the aforementioned computing device. As Figure 6 shown, the battery swapping station scheduling processing device 600 may include: at least one processor 601, a memory 602, and a communication interface 603.

[0164] The memory 602 is used to store programs. Specifically, the program may include program code, and the program code includes computer operation instructions.

[0165] The memory 602 may include a high-speed RAM memory, and may also include a non-volatile memory, such as at least one disk memory.

[0166] The processor 601 is configured to execute computer-executable instructions stored in the memory 602 to implement the methods described in the foregoing method embodiments. Among them, the processor 601 may be a CPU, or a specific integrated circuit (Application Specific Integrated Circuit, abbreviated as ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0167] The processor 601 can communicate with external devices through the communication interface 603. The external devices can be, for example, the user's terminal devices. In a specific implementation, if the communication interface 603, the memory 602, and the processor 601 are implemented independently, the communication interface 603, the memory 602, and the processor 601 can be interconnected through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc., but it does not mean that there is only one bus or one type of bus.

[0168] Optionally, in a specific implementation, if the communication interface 603, the memory 602, and the processor 601 are implemented integrated on a chip, the communication interface 603, the memory 602, and the processor 601 can communicate through an internal interface.

[0169] The present application also provides a computer-readable storage medium, which may include: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk, or an optical disc, etc. Specifically, the computer-readable storage medium stores program instructions, and the program instructions are used for the methods in the foregoing embodiments.

[0170] The present application also provides a program product, which includes executable instructions stored in a readable storage medium. At least one processor of the computing device can read the executable instructions from the readable storage medium, and the at least one processor executes the executable instructions to enable the computing device to implement the above-mentioned swapping station scheduling processing method.

[0171] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A dispatching processing method for a battery swapping station, characterized in that, The method comprises: Using multiple sets of input data, the battery swapping station is simulated through the simulation model of the battery swapping station to obtain multiple first parameter values corresponding to the multiple sets of input data; each set of input data includes: the number of heavy trucks, and the first parameter value is used to characterize the matching degree between the number of heavy trucks and the battery swapping capacity of the battery swapping station; determining a target first parameter value from the plurality of first parameter values; Dispatching the heavy trucks served by the battery swap station according to the number of heavy trucks corresponding to the target first parameter value; The process of simulating the battery swapping of the battery swapping station includes: The heavy truck moves back and forth between the loading point and the unloading point in the work area to perform operations until the battery pack on the heavy truck reaches a threshold value to be charged; When the battery pack on the heavy truck reaches a threshold to be charged, the heavy truck drives from the unloading point to the battery swap station; The battery swap station determines whether there is a battery pack that has reached the charging threshold. If so, the battery pack that has reached the charging threshold is replaced on the heavy truck. If not, the heavy truck waits for the battery swap station to charge the battery pack until there is a battery pack that has reached the charging threshold. After the heavy truck completes the battery replacement, it returns to the work area from the battery replacement station to continue the operation; The above process is repeated until the target simulation time is reached; The using of multiple sets of input data to simulate the battery swapping of the battery swapping station through the simulation model of the battery swapping station to obtain multiple first parameter values corresponding to the multiple sets of input data includes: Input each set of input data into the simulation model of the battery swap station, so as to simulate the battery swapping of the battery swap station through the simulation model of the battery swap station, and obtain the intermediate parameter value corresponding to each set of input data, wherein the intermediate parameters include: the average discharge depth of the battery pack, the total time consumed for a single battery swapping of a single heavy truck, the average number of loading and unloading trips completed by a heavy truck, and the second parameter of the battery swap station, which is used to characterize the average income data of the battery swapping service provided by the battery swap station for heavy trucks; According to the intermediate parameter value corresponding to each group of input data and the weight corresponding to each intermediate parameter value, the first parameter value corresponding to each group of input data is obtained.

2. The method according to claim 1, wherein The step of inputting each set of input data into the simulation model of the battery swap station to simulate the battery swapping of the battery swap station through the simulation model of the battery swap station to obtain an intermediate parameter value corresponding to each set of input data includes: Input each set of input data into the simulation model of the battery swap station, so that the simulation model performs battery swap simulation within the target simulation time, so as to obtain the initial parameter values corresponding to each set of input data; the initial parameter values include: the number of battery swaps for each heavy truck, the number of battery swaps for each battery pack, the total depth of discharge of each battery pack, the total time consumed for a single battery swap for each heavy truck, and the initial power of each battery pack replaced for each heavy truck; According to the initial parameter value, an intermediate parameter value corresponding to each set of input data is obtained.

3. The method according to claim 2, wherein The input data also includes at least one of the following: the initial power of the battery pack of each heavy truck, the identification of each heavy truck, and the identification of the battery pack of each heavy truck.

4. The method according to any one of claims 1-3, characterized in that, Before simulating the battery swapping of the battery swapping station by using a plurality of groups of input data through the simulation model of the battery swapping station, the method further includes: Receiving configuration data of the simulation model, where the configuration data includes at least one of the following: the target simulation duration, and the target number of battery packs of the battery swapping station.

5. The method according to any one of claims 1-3, characterized in that, Before simulating the battery swapping of the battery swapping station by using a plurality of groups of input data through the simulation model of the battery swapping station to obtain a plurality of first parameter values corresponding to the plurality of groups of input data, it further includes: Constructing the simulation model according to simulation construction parameters; where the construction parameters include: the simulation parameter values of the battery swapping station, and the simulation parameter values of the working area of the heavy truck vehicle. The simulation parameters of the battery swapping station include at least one of the following: the charging speed of the battery pack, the duration required for the heavy truck vehicle to swap the battery, the cost data required for charging the battery pack, and the construction cost data of the battery swapping station. The simulation parameters of the working area of the heavy truck vehicle include at least one of the following: the threshold of the battery pack to be charged; the first remaining battery charge (SOC) consumption of the battery pack corresponding to the heavy truck vehicle traveling from the loading point to the unloading point, and the first duration consumed; the second SOC consumption of the battery pack corresponding to the heavy truck vehicle traveling from the unloading point to the loading point, and the second duration consumed; the third SOC consumption of the battery pack corresponding to the heavy truck vehicle traveling from the unloading point to the battery swapping station, and the third duration consumed.

6. The method according to claim 5, wherein The method further includes: Obtaining at least one of the simulation construction parameters according to the historical battery swapping data of the battery swapping station.

7. A dispatching processing device for a battery swapping station, characterized in that, It includes: A simulation module, configured to simulate the battery swapping of the battery swapping station by using a plurality of groups of input data through the simulation model of the battery swapping station to obtain a plurality of first parameter values corresponding to the plurality of groups of input data; Each group of input data includes: the number of heavy truck vehicles, and the first parameter value is used to characterize the matching degree between the number of heavy truck vehicles and the battery swapping capacity of the battery swapping station; A determination module, configured to determine a target first parameter value from the plurality of first parameter values; A scheduling module, configured to schedule the heavy truck vehicles served by the battery swapping station according to the number of heavy truck vehicles corresponding to the target first parameter value; The simulation module is specifically configured to simulate the heavy truck vehicle performing operations between the loading point and the unloading point in the working area until the battery pack on the heavy truck vehicle reaches the threshold of the battery pack to be charged; when the battery pack on the heavy truck vehicle reaches the threshold of the battery pack to be charged, the heavy truck vehicle travels from the unloading point to the battery swapping station; the battery swapping station determines whether there is currently a battery pack reaching the charging threshold, if so, replaces the battery pack reaching the charging threshold with the battery pack on the heavy truck vehicle, if not, the heavy truck vehicle waits for the battery swapping station to charge the battery pack until there is a battery pack reaching the charging threshold; after the heavy truck vehicle completes the battery swapping, it returns from the battery swapping station to the working area and continues to perform operations; repeating the above process until the target simulation duration is reached; The simulation module is specifically further configured to input each set of input data into the simulation model of the battery swapping station, so as to perform battery swapping simulation on the battery swapping station through the simulation model of the battery swapping station, and obtain intermediate parameter values corresponding to each set of input data. The intermediate parameters include: the average discharge depth of the battery pack, the total duration consumed by a single heavy truck for a single battery swap, the average number of loading and unloading trips completed by the heavy truck, and a second parameter of the battery swapping station, where the second parameter is used to characterize the average revenue data provided by the battery swapping station for the heavy truck for battery swapping services; according to the intermediate parameter values corresponding to each set of input data, and the weight corresponding to each intermediate parameter value, obtain the first parameter value corresponding to each set of input data.

8. A dispatching and processing device for a battery swapping station, characterized in that Comprising: a processor, a communication interface, and a memory; The processor is communicatively connected to the communication interface and the memory respectively; The memory stores computer-executable instructions; The communication interface communicates with external devices; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that Computer-executable instructions are stored in the computer-readable storage medium, and when the computer-executable instructions are executed by the processor, they are used to implement the battery swapping station scheduling processing method according to any one of claims 1 to 6.

10. A computer program product, characterized in that, Comprising computer-executable instructions, and when the computer-executable instructions are executed by the processor, they are used to implement the battery swapping station scheduling processing method according to any one of claims 1 to 6.

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