A method and system for planning the flow of replacement current based on vehicle interconnection

Abstract

The present invention provides a method and system for planning the flow of replacement current based on vehicle interconnection, which relates to the field of intelligent control technology. The method includes: collecting regional data of the target management and control area information to obtain battery operation and maintenance point distribution data, collecting the vehicle usage distribution positions in the target management and control area information to obtain vehicle usage distribution position data, screening the vehicles for power replenishment from the vehicle real-time data generated by real-time data interaction with the vehicles to obtain the first power level vehicle data, aggregating the vehicle usage distribution positions, generating an aggregated planning result, inputting the aggregated planning result and the battery operation and maintenance point distribution data into a path planning model for operation and maintenance path planning, generating a replacement power operation and maintenance path planning result, and then performing replacement power management on the vehicles, so as to solve the technical problem in the prior art that the distribution positions of low-power vehicles are uneven, resulting in low battery recovery efficiency of the final low-power vehicles, and realizing ensuring that the low-power vehicles are all concentrated in a certain centralized area and improving the battery recovery efficiency of the low-power vehicles.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent control, and particularly to a method and system for planning the flow of battery replacement based on vehicle interconnection. Background Art

[0002] With the development of social economy, especially the development of the sharing industry, under the promotion of the sharing economy, shared electric vehicles have become a popular product, solving the problem of difficult short- and medium-distance travel in cities, mainly within the range of 3 - 10 kilometers. Since they are electrically driven, although they are more time-saving and labor-saving compared to shared bicycles, users are required to use and return shared electric vehicles at fixed parking points, and the electric vehicles in the parking points cannot charge themselves. Therefore, operators must use manual operations to provide battery replacement services for low-battery electric vehicles. As time goes by, due to the mobility of electric vehicles within the area, the number of low-battery electric vehicles in the parking points will change, making the number of electric vehicles that need battery replacement uncertain.

[0003] In the prior art, the distribution positions of low-battery vehicles are uneven. Each operation and maintenance personnel responsible for a region replaces the batteries of low-battery vehicles with battery replacement requirements (such as the battery level being lower than the threshold) at each station in the region, resulting in low efficiency of battery replacement and recycling for low-battery vehicles. Summary of the Invention

[0004] The present application provides a method and system for planning the flow of battery replacement based on vehicle interconnection, aiming to solve the technical problem in the prior art that the distribution positions of low-battery vehicles are uneven, resulting in low efficiency of battery recycling for low-battery vehicles.

[0005] In view of the above problems, the present application provides a method and system for planning the flow of battery replacement based on vehicle interconnection.

[0006] In a first aspect, the present application provides a method for planning the flow of replacement current based on vehicle interconnection. The method includes: obtaining target control area information, collecting area data for the target control area information to obtain battery operation and maintenance point distribution data; collecting the vehicle usage distribution locations in the target control area information to obtain vehicle usage distribution location data, where the vehicle usage distribution location data includes vehicle concentrated usage distribution locations and vehicle non-concentrated usage distribution locations; performing real-time data interaction with the vehicles, and generating vehicle real-time data according to the data interaction results; screening vehicles for power replenishment according to the vehicle real-time data and the vehicle usage distribution location data, and obtaining first power level vehicle data according to the screening results; aggregating the vehicle usage distribution locations according to the first power level vehicle data to generate an aggregation planning result; inputting the aggregation planning result and the battery operation and maintenance point distribution data into a path planning model for operation and maintenance path planning to generate a replacement current operation and maintenance path planning result; and performing replacement current management on the vehicles according to the replacement current operation and maintenance path planning result.

[0007] In a second aspect, the present application provides a system for planning the flow of replacement current based on vehicle interconnection. The system includes: a battery operation and maintenance point distribution data obtaining module, which is used to obtain target control area information, collect area data for the target control area information, and obtain battery operation and maintenance point distribution data; a location data obtaining module, which is used to collect the vehicle usage distribution locations in the target control area information to obtain vehicle usage distribution location data, where the vehicle usage distribution location data includes vehicle concentrated usage distribution locations and vehicle non-concentrated usage distribution locations; a vehicle real-time data generating module, which is used to perform real-time data interaction with the vehicles and generate vehicle real-time data according to the data interaction results; a first power level vehicle data obtaining module, which is used to screen vehicles for power replenishment according to the vehicle real-time data and the vehicle usage distribution location data, and obtain first power level vehicle data according to the screening results; an aggregation planning result generating module, which is used to aggregate the vehicle usage distribution locations according to the first power level vehicle data to generate an aggregation planning result; a replacement current operation and maintenance path planning result generating module, which is used to input the aggregation planning result and the battery operation and maintenance point distribution data into a path planning model for operation and maintenance path planning to generate a replacement current operation and maintenance path planning result; and a replacement current management module, which is used to perform replacement current management on the vehicles according to the replacement current operation and maintenance path planning result.

[0008] One or more technical solutions provided in the present application have at least the following technical effects or advantages:

[0009] A method for planning the flow of battery swapping based on vehicle interconnection provided by the present application relates to the field of intelligent control technology, solves the technical problem in the prior art that the distribution positions of low-battery vehicles are uneven, resulting in low efficiency of battery replacement and recycling for the final low-battery vehicles, and realizes ensuring that low-battery vehicles are gathered in a certain centralized area and improving the efficiency of battery replacement and recycling for low-battery vehicles. Description of the Drawings

[0010] Figure 1 FIG. is a schematic flow chart of a method for planning the flow of battery swapping based on vehicle interconnection provided by the present application;

[0011] Figure 2 FIG. is a schematic structural diagram of a system for planning the flow of battery swapping based on vehicle interconnection provided by the present application.

[0012] Description of the reference numerals: Module 1 for obtaining distribution data of battery operation and maintenance points, Module 2 for obtaining position data, Module 3 for generating real-time vehicle data, Module 4 for obtaining data of first-battery vehicles, Module 5 for generating aggregation planning results, Module 6 for generating planning results of battery swapping operation and maintenance paths, and Module 7 for battery swapping management. Detailed Embodiments

[0013] The present application provides a method for planning the flow of battery swapping based on vehicle interconnection to solve the technical problem in the prior art that the distribution positions of low-battery vehicles are uneven, resulting in low efficiency of battery recycling for the final low-battery vehicles.

[0014] Embodiment 1

[0015] As Figure 1 shown, the embodiment of the present application provides a method for planning the flow of battery swapping based on vehicle interconnection, and the method includes:

[0016] Step S100: Obtain target control area information, collect area data for the target control area information, and obtain distribution data of battery operation and maintenance points;

[0017] Specifically, the area information of the target vehicle to be controlled is collected. The target control area can be a specific area delimited by human, geographical factors, and buildings. Taking a first-tier city as an example, the control area can be different districts already divided within the city. Then, data collection is carried out in different sub-areas of the already divided different districts, that is, for the different districts already divided within the designated target control area, the positions of low-battery vehicles, the vehicle battery levels, and the position concentration of low-battery vehicles are collected. Further, the distribution data of battery maintenance points is obtained. A battery maintenance point refers to the replacement of the vehicle battery when the vehicle is in a low-battery state, that is, the maintenance personnel replace the battery of the low-battery vehicle, so as to ensure that low-battery vehicles gather in a certain concentrated area. At the same time, the positions of each battery maintenance point are integrated to generate the distribution data of the battery maintenance points, thus laying a solid foundation for improving the recycling efficiency of low-battery vehicle batteries through battery swapping management.

[0018] Step S200: Collect the vehicle usage distribution positions in the target control area information to obtain vehicle usage distribution position data, where the vehicle usage distribution position data includes vehicle concentrated usage distribution positions and vehicle non-concentrated usage distribution positions;

[0019] Specifically, based on the above-collected target control area information, the vehicle usage distribution positions in the target control area are collected. Exemplarily, the vehicle usage distribution positions need to be determined according to user needs, and the vehicle demand positions can be subway entrances, community entrances, school entrances, etc. Among them, the collected vehicle usage distribution position data includes vehicle concentrated usage distribution positions and vehicle non-concentrated usage distribution positions. The collected vehicle concentrated usage distribution positions and the collected vehicle non-concentrated usage distribution positions are integrated to obtain more detailed vehicle usage distribution positions. Further, obtaining the vehicle usage distribution position data is one of the important bases for improving the recycling efficiency of low-battery vehicle batteries through subsequent vehicle battery swapping management.

[0020] Step S300: Perform real-time data interaction on the vehicle, and generate vehicle real-time data according to the data interaction results;

[0021] Specifically, real-time data interaction is carried out on the target vehicle. The real-time data of the vehicle can be the real-time data of the vehicle when it is in operation, stationary, locked, charging, low power, etc. That is, the current state, location, and power of the vehicle will be interacted between the vehicle and the platform. After the connection is completed, the corresponding vehicle real-time data can be generated through the obtained vehicle real-time data interaction results. And the operation and maintenance personnel can understand the real-time location and power of the vehicle through the vehicle power and vehicle location in the obtained vehicle real-time data, providing an important reference for improving the replacement and recycling efficiency of the batteries of low-power vehicles in the subsequent battery replacement management of the vehicle.

[0022] Step S400: Screen the vehicles for power replenishment according to the vehicle real-time data and the vehicle usage distribution location data, and obtain the first power vehicle data according to the screening results;

[0023] Specifically, after obtaining the vehicle real-time location, state, power and other data in the above-obtained vehicle real-time data, the obtained vehicle real-time data is screened for power replenishment with the obtained vehicle usage distribution location data. For example, when the power is lower than 30%, it is defined that the vehicle battery needs to be recycled and a battery with a higher power needs to be replaced. When the data monitors that the power of the vehicle is lower than 30%, the vehicle with a power lower than 30% is screened out, and at the same time, it is determined that the vehicle needs to have its battery recycled and a battery with a higher power replaced. Then, the first power vehicle data is generated from the screening and determination results, providing a reference basis for improving the replacement and recycling efficiency of the batteries of low-power vehicles in the subsequent battery replacement management of the vehicle.

[0024] Step S500: Aggregate the vehicle usage distribution location data according to the first power vehicle data to generate an aggregated planning result;

[0025] Specifically, based on the above-obtained first electric vehicle data and the usage distribution locations of the obtained vehicles, the two are aggregated. That is, the vehicle usage distribution location data of low-power vehicles with a battery level lower than 30% is refined. Exemplarily, when there are multiple low-power vehicles with a battery level lower than 30% in different regions, the vehicle usage distribution location data of these low-power vehicles needs to be statistically analyzed and integrated. When the proportion of low-power vehicles in the same region reaches 40% of the total vehicles in the current region, it is considered that the current region belongs to the vehicle concentrated usage distribution location in the vehicle usage distribution location data. Exemplarily, when the proportion of low-power vehicles parked at the entrance of a community is higher than 40% of the total vehicles, it is necessary to record the location of the target region and the low-power vehicles to determine whether the region belongs to the vehicle concentrated usage distribution location or the vehicle non-concentrated usage distribution location in the vehicle usage distribution location data. Aggregate the obtained low-power vehicles with the region location data whose region attribute is determined to be the vehicle concentrated usage distribution location, and further generate an aggregated planning result, so as to make the battery replacement management of vehicles more accurate and reasonable in improving the replacement and recycling efficiency of low-power vehicle batteries.

[0026] Step S600: Perform an operation and maintenance path planning according to the aggregated planning result and the battery operation and maintenance point distribution data input into the path planning model to generate a battery replacement operation and maintenance path planning result;

[0027] Specifically, integrate the above-obtained aggregated planning results with the above-obtained vehicle battery operation and maintenance point distribution data, that is, conduct real-time data interaction according to the vehicle and the platform, and use the generated vehicle real-time data to screen each vehicle in the vehicle concentrated use distribution positions in the vehicle use distribution position data for low-power vehicles with a vehicle power lower than 30%, so as to obtain the position data of low-power vehicles. Then, aggregate the position data of the low-power vehicles with the vehicle concentrated use distribution positions in the vehicle use distribution position data collected based on the target control area information to obtain the vehicle concentrated use distribution position data of the low-power vehicles. Combine this data with the distribution data of the above battery operation and maintenance points, and then input it into the path planning model for operation and maintenance path planning. The path planning model refers to giving a reasonable objective function within the target control area and finding the optimal solution of the objective function within a certain range, so that the intelligent control system can recycle the vehicle battery of the low-power vehicle and replace it with a battery with a higher power, thereby finding the usage duration of the vehicle in the non-concentrated area and reducing the number of battery replacements by the operation and maintenance personnel in the non-concentrated area, that is, avoiding the operation and maintenance personnel from going to the non-concentrated use distribution positions of the vehicles in the vehicle use distribution position data, making this section of the path an inefficient path. Furthermore, the operation and maintenance personnel put the batteries with lower power into the vehicle concentrated use distribution positions in the vehicle use distribution position data and regard this section of the path as the optimal path, further generating the operation and maintenance path planning result for battery replacement, so as to ensure that all low-power vehicles are gathered in the vehicle concentrated use distribution positions in the vehicle use distribution position data, and finally improve the battery recycling efficiency of low-power vehicles in battery replacement management.

[0028] Step S700: Perform battery replacement management on the vehicle according to the operation and maintenance path planning result for battery replacement.

[0029] Specifically, based on the vehicle position, vehicle status, vehicle power, and real-time vehicle use distribution position data of the low-power vehicle, the intelligent control system matches with the operation and maintenance personnel for battery replacement and recycling of the vehicle to obtain the operation and maintenance path planning result for battery replacement. The operation and maintenance path planning result for battery replacement refers to that when the vehicle power is lower than 30%, it is determined as a low-power vehicle. At the same time, when the vehicle use distribution position data of the low-power vehicle is the vehicle concentrated use distribution position, the intelligent control system will remind the operation and maintenance personnel that they need to perform the operations of vehicle battery replacement and recycling. Further, interact with the real-time position of the low-power vehicle in the vehicle concentrated use distribution position according to the vehicle use distribution position data, and locate the low-power vehicle in the vehicle concentrated use distribution position, so as to find the optimal route for the operation and maintenance personnel to find the low-power vehicle in the vehicle concentrated use distribution position with the vehicle use distribution position data in the target control area, so that the operation and maintenance personnel can perform vehicle battery replacement management according to the generated operation and maintenance path planning result for battery replacement to improve the replacement and recycling efficiency of the low-power vehicle battery.

[0030] Furthermore, the present invention provides a method and system for planning the flow of battery swapping based on vehicle interconnection, which relates to the field of intelligent control technology. The method includes: collecting regional data of the target control area information to obtain the distribution data of battery operation and maintenance points, collecting the distribution positions of vehicle usage in the target control area information to obtain the distribution position data of vehicle usage, and then screening the vehicles for power replenishment based on the vehicle real-time data generated by real-time data interaction with the vehicles. After obtaining the first power vehicle data according to the screening results, aggregating the distribution positions of vehicle usage to generate an aggregated planning result, and inputting the aggregated planning result and the distribution data of battery operation and maintenance points into a path planning model for operation and maintenance path planning. After generating the battery swapping operation and maintenance path planning result, performing battery swapping management on the vehicles. The present invention solves the technical problem in the prior art that the distribution positions of low-power vehicles are uneven, resulting in low efficiency of battery replacement and recycling of low-power vehicles in the end, and realizes ensuring that low-power vehicles are gathered in a certain centralized area, improving the efficiency of battery replacement and recycling of low-power vehicles.

[0031] Furthermore, step S400 of the present application further includes:

[0032] Step S410: Obtain the power data and position distribution of parked vehicles according to the vehicle real-time data, and screen to obtain the regional vehicle power data according to the power data of parked vehicles and the distribution position data of vehicle usage;

[0033] Step S420: Obtain the centralized data of the distribution positions of vehicle usage according to the distribution position data of vehicle usage;

[0034] Step S430: Obtain the non-centralized data of the distribution positions of vehicle usage according to the distribution position data of vehicle usage;

[0035] Step S440: Estimate the power consumption of vehicles according to the centralized data and non-centralized data of the distribution positions of vehicle usage, and screen to obtain the estimated vehicle power consumption data based on the power consumption estimation result and the regional vehicle concentration;

[0036] Step S450: Obtain the first power vehicle data according to the vehicle power data and the estimated vehicle power consumption data.

[0037] Specifically, based on the above-obtained real-time vehicle data, the vehicle power data and location distribution data of the vehicles in the parking state in the real-time vehicle data are extracted. Further, the parked power data extracted from the real-time vehicle data is integrated and screened with the above-obtained vehicle usage distribution location data to further obtain regional vehicle power data, where the regional vehicle power data includes the vehicle power data and the vehicle location distribution data associated with the vehicle power data. At the same time, the concentrated data of the vehicle usage distribution location and the non-concentrated data of the vehicle usage distribution location are respectively obtained according to the above-obtained vehicle usage distribution location data, so as to estimate the power consumption of the vehicle based on the concentrated data and the non-concentrated data of the obtained vehicle usage distribution location, that is, estimate the vehicle power decline speed in units of time, and screen the obtained power consumption estimation result with the regional concentration degree of the vehicle. Further, the estimated vehicle power consumption data is obtained. The concentrated data of the vehicle usage distribution location refers to that when the proportion of low-power vehicles in the same area reaches 40% of the total vehicles in the current area, it is regarded that the current area belongs to the concentrated usage distribution location of the vehicles in the vehicle usage distribution location data, and the non-concentrated data of the vehicle usage distribution location refers to that when the proportion of low-power vehicles in the same area is lower than 40% of the total vehicles in the current area, it is regarded that the current area belongs to the non-concentrated usage distribution location of the vehicles in the vehicle usage distribution location data. Finally, the first power vehicle data is obtained from the obtained vehicle power data and the obtained estimated vehicle power consumption data, achieving the technical effect of providing an important basis for realizing battery swapping management in the later stage.

[0038] Furthermore, step S600 of this application further includes:

[0039] Step S610: Obtain the real-time vehicle location data within the target control area;

[0040] Step S620: Set a calibrated power threshold, screen the real-time vehicle location data through the calibrated power threshold, and obtain the location distribution data of the calibrated vehicles according to the screening results;

[0041] Step S630: Perform location optimization aggregation on the calibrated vehicles according to the location distribution data and the vehicle usage distribution location data to obtain a location optimization aggregation result;

[0042] Step S640: Optimize the path of the battery swapping operation and maintenance path planning result according to the location optimization aggregation result.

[0043] Specifically, the driving data of the vehicles within the target control area can be obtained from the real-time position data of the vehicles, and then a calibrated power threshold can be set. The calibrated power threshold can be set to 40% - 50%. When the power of a vehicle is within the calibrated power threshold, the real-time position of the vehicle is screened. That is, if the real-time position of the vehicle is dynamic at this time, the position data of the final parking area of the vehicle within the calibrated power threshold is collected. If the real-time position of the vehicle is static at this time, the battery loss reduction rate of the vehicle within the calibrated power threshold is collected. If the reduction rate is fast, the position data of the parking area of the vehicle is further collected, and then the position distribution data of the calibrated vehicles is generated. Further, based on the obtained position distribution data of the calibrated vehicles and the obtained vehicle usage distribution position data, the position optimization aggregation of the calibrated vehicles is performed. The position optimization aggregation of the calibrated vehicles refers to judging the position data of the final parking area of the vehicle within the calibrated power threshold collected according to the real-time position of the vehicle, and judging whether the obtained position data belongs to the vehicle concentrated usage distribution position in the vehicle usage distribution position data. If the position optimization aggregation of the calibrated vehicles refers to the position of the final parking area of the vehicle within the calibrated power threshold collected according to the real-time position of the vehicle belonging to the vehicle concentrated usage distribution position in the vehicle usage distribution position data, a position optimization aggregation result is generated, and thus the path of the battery swapping operation and maintenance path planning result is optimized according to the obtained position optimization aggregation result to ensure the efficiency during battery swapping management.

[0044] Furthermore, step S620 of the present application includes:

[0045] Step S621: Obtain the position data set of the calibrated vehicles according to the vehicle usage distribution position data;

[0046] Step S622: Evaluate the regional concentration of the vehicles according to the vehicle position data set, and generate a regional concentration evaluation result;

[0047] Step S623: Generate a battery placement feedback parameter according to the regional concentration evaluation result, and identify the vehicle real-time position data through the battery placement feedback parameter.

[0048] Specifically, based on the obtained vehicle usage distribution location data, all the calibrated vehicle location data therein are integrated to further obtain a location dataset of the calibrated vehicles, so as to evaluate the regional concentration of the vehicles according to the obtained vehicle location dataset. Wherein, when the proportion of vehicles in the same region is greater than or equal to 5% of the total regional vehicles, the current region is regarded as a vehicle concentration area; when the proportion of vehicles in the same region is less than 5% of the total regional vehicles, the current region is regarded as a non-vehicle concentration area. Furthermore, a regional concentration evaluation result is generated, and a battery placement feedback parameter is generated based on the obtained regional concentration evaluation result. The battery placement feedback parameter is used to determine whether the battery of the vehicle needs to be recycled and replaced according to the concentration of the region where the vehicle is located and the power data of the vehicle, so as to identify the real-time location data of the vehicle based on the generated battery placement feedback parameter, and finally achieve the technical effect of providing a reference for the battery swapping management.

[0049] Furthermore, step S700 of the present application further includes:

[0050] Step S710: Collect historical vehicle usage data of the vehicle usage distribution location;

[0051] Step S720: Parse the historical vehicle usage data, and generate vehicle usage distribution location identification data according to the data parsing result;

[0052] Step S730: Obtain the time window throughput data of the vehicle usage location according to the vehicle usage distribution location identification data;

[0053] Step S740: Perform a matching evaluation on the vehicle usage distribution location identification data and the time window throughput data through the vehicle real-time data, and generate a matching evaluation result;

[0054] Step S750: Generate a regional vehicle concentration influence parameter of the vehicle usage distribution location according to the matching evaluation result;

[0055] Step S760: Adjust the operation and maintenance path planning through the regional vehicle concentration influence parameter to obtain an adjusted battery swapping operation and maintenance path planning result, and perform battery swapping management on the vehicle through the adjusted battery swapping operation and maintenance path planning result.

[0056] Specifically, collect and count the historical vehicle usage data in the usage distribution locations of vehicles within the target control area. Based on this historical vehicle usage data, perform data parsing on the historical vehicle usage data within the target control area. Exemplarily, the demand for vehicles varies in different regions. In the historical vehicle usage data, mainly screen out two types of regions: regions with high demand for vehicles but insufficient supply of battery recycling and replacement for low-battery vehicles, and regions with low demand for vehicles but excessive supply of battery recycling and replacement for low-battery vehicles. Obtain the identification data of the number of battery recycling and replacement times of the vehicles from the data parsing results. Further, allocate the number of battery recycling and replacement times of the vehicles in the regions with excessive supply of battery recycling and replacement for low-battery vehicles with low demand for vehicles to the regions with insufficient supply of battery recycling and replacement for low-battery vehicles with high demand for vehicles, in order to meet the supply and demand problems of battery recycling and replacement for low-battery vehicles in each region. Then, obtain the time-window throughput data of the vehicle usage locations from the obtained vehicle usage distribution location identification data. The time-window throughput data of the vehicle usage locations refers to the number of battery recycling and replacement times of each low-battery vehicle within the target control area. The time axis is divided into independent small blocks at certain intervals, and then the throughput of the number of battery recycling and replacement times of each low-battery vehicle within the target control area is statistically obtained based on these small blocks, which is the time-window throughput data of the vehicle usage locations. Furthermore, match the time-window throughput data of the vehicle usage locations with the vehicle usage distribution location identification data, and further generate the time-window throughput data result based on the real-time vehicle data. Then, based on this matching evaluation result, generate the regional vehicle concentration influence parameter, which means that when low-battery vehicles are recycled and replaced in different regions, due to the continuous change of the vehicle location, the concentrated area of the vehicles also changes accordingly, resulting in a new concentrated area. And during the process of battery recycling and replacement of low-battery vehicles, there are route problems for the maintenance personnel when going to the concentrated area. Therefore, according to the different concentrations in different regions and the different routes between different regions, when the maintenance personnel go to the concentrated area to recycle and replace the batteries of low-battery vehicles within the target control area, adjust and plan the route in a timely manner as the concentrated area changes, adjust the regional vehicle concentration influence parameter, so as to obtain the corresponding adjusted battery replacement operation and maintenance path planning result, and perform battery replacement management on the vehicles according to the obtained adjusted battery replacement operation and maintenance path planning result, finally achieving the technical effect of timely adjustment of battery replacement management.

[0057] Furthermore, step S760 of the present application further includes:

[0058] Step S761: Construct a training data set for the regional vehicle concentration influence parameter through the matching evaluation result;

[0059] Step S762: Perform incremental learning of the path planning model through the training data set of the regional vehicle concentration influence parameters to obtain an incremental learning path planning model;

[0060] Step S763: Input the aggregated planning result, the battery operation and maintenance point distribution data, and the path influence parameters into the incremental learning path planning model to obtain the adjusted battery swapping operation and maintenance path planning result.

[0061] Specifically, based on the matching evaluation result obtained by matching and evaluating the vehicle usage distribution location data and the time window throughput data through real-time vehicle data, a training data set of regional vehicle concentration influence parameters is constructed. That is, when the operation and maintenance personnel recycle and replace the batteries of low-power vehicles, during their operation and maintenance process, some path influences that may occur on this section of the road, such as temporary road construction, cancellation or addition of concentrated areas, etc., are integrated and combined with the matching evaluation result to generate a training data set of regional vehicle concentration influence parameters. However, the newly added road conditions after generating the set are not included in the existing training data set of regional vehicle concentration influence parameters. Therefore, the path planning model needs to continuously perform incremental learning, such as temporary road closures, changes in concentrated areas, etc., and then initially generate an incremental learning path planning model. Further, the obtained aggregated planning result, the battery operation and maintenance point distribution data, and the above path influence parameters are integrated and input into the initially generated incremental learning path planning model to expand the path planning model. That is, for the location data of low-power vehicles that need battery recycling and replacement, the location data of the operation and maintenance personnel, and the road conditions during the operation and maintenance between these two places, including normal road conditions and newly added road conditions, on this basis, the battery swapping operation and maintenance path planning result is adjusted in real time to generate an adjusted battery swapping operation and maintenance path planning result to assist in battery swapping management.

[0062] Furthermore, step S760 of the present application further includes:

[0063] Step S810: Obtain real-time traffic data;

[0064] Step S820: Perform real-time execution path adjustment of the battery swapping operation and maintenance path planning result according to the real-time traffic data to obtain a real-time adjustment result;

[0065] Step S830: Manage the battery swapping of vehicles through the real-time adjustment result.

[0066] Specifically, on the basis of planning the operation and maintenance path for the battery recycling and replacement of low-battery vehicles in the incremental learning path planning model, traffic data in the generated route is collected at the same time. The obtained real-time traffic data is integrated with the result of the battery swapping operation and maintenance path planning, and the operation and maintenance path is further adjusted in real time according to the real-time traffic data. The adjusted operation and maintenance path for the battery recycling and replacement of low-battery vehicles is the real-time adjustment result. Then, the battery swapping management of the vehicle is appropriately adjusted according to the real-time adjustment result. Preferably, if the real-time traffic data in the operation and maintenance path planning for the battery recycling and replacement of low-battery vehicles shows severe congestion, then the time consumed by the severely congested section in the first generated operation and maintenance path can be compared with the detour time in the second generated operation and maintenance path. After comparing the two, an operation and maintenance path with the least time consumption is obtained, and the second generated operation and maintenance path is selected for real-time adjustment according to the traffic conditions, so as to achieve the technical effect of saving the time cost of vehicle battery swapping when performing vehicle battery swapping management.

[0067] Embodiment 2

[0068] Based on the same inventive concept as a battery swapping flow planning method based on vehicle interconnection in the foregoing embodiment, as Figure 2 shown, the present application provides a battery swapping flow planning system based on vehicle interconnection. The system includes:

[0069] A battery operation and maintenance point distribution data acquisition module 1, configured to acquire target control area information, perform area data acquisition on the target control area information, and acquire battery operation and maintenance point distribution data;

[0070] A position data acquisition module 2, configured to acquire vehicle usage distribution position data by collecting vehicle usage distribution positions in the target control area information, where the vehicle usage distribution position data includes vehicle concentrated usage distribution positions and vehicle non-concentrated usage distribution positions;

[0071] A vehicle real-time data generation module 3, configured to perform real-time data interaction on the vehicle and generate vehicle real-time data according to the data interaction result;

[0072] A first power vehicle data acquisition module 4, configured to screen power-supplemented vehicles according to the vehicle real-time data and vehicle usage distribution position data, and acquire first power vehicle data according to the screening result;

[0073] An aggregation planning result generation module 5, configured to aggregate the vehicle usage distribution position data according to the first power vehicle data to generate an aggregation planning result;

[0074] The battery replacement operation and maintenance path planning result generation module 6 is configured to perform operation and maintenance path planning by inputting the aggregated planning result and the battery operation and maintenance point distribution data into a path planning model, and generate a battery replacement operation and maintenance path planning result;

[0075] The battery replacement management module 7 is configured to perform battery replacement management on the vehicle according to the battery replacement operation and maintenance path planning result.

[0076] Furthermore, the system further includes:

[0077] The regional vehicle power data module is configured to obtain the parked vehicle power data and location distribution according to the vehicle real-time data, and filter and obtain the regional vehicle power data according to the parked vehicle power data and the vehicle usage distribution location data;

[0078] The vehicle centralized data module is configured to obtain the centralized data of the vehicle usage distribution location according to the vehicle usage distribution location data;

[0079] The vehicle non-centralized data module is configured to obtain the non-centralized data of the vehicle usage distribution location according to the vehicle usage distribution location data;

[0080] The estimated vehicle power consumption data module is configured to estimate the vehicle power consumption according to the centralized data of the vehicle usage distribution location and the non-centralized data of the vehicle usage distribution location, and filter and obtain the estimated vehicle power consumption data based on the power consumption estimation result and the regional vehicle concentration;

[0081] The first power vehicle data module is configured to obtain the first power vehicle data according to the vehicle power data and the estimated vehicle power consumption data.

[0082] Furthermore, the system further includes:

[0083] The real-time position data module is configured to obtain the vehicle real-time position data within the target control area;

[0084] The calibrated vehicle position distribution data module is configured to set a calibrated power threshold, filter the vehicle real-time position data through the calibrated power threshold, and obtain the calibrated vehicle position distribution data according to the filtering result;

[0085] The position optimization aggregation result module is configured to perform position optimization aggregation on the calibrated vehicle according to the position distribution data and the vehicle usage distribution location data, and obtain a position optimization aggregation result;

[0086] A path optimization module, which is used to optimize the path of the battery swapping operation and maintenance path planning result according to the position optimization aggregation result.

[0087] Furthermore, the system further includes:

[0088] A calibrated vehicle position dataset module, which is used to obtain the calibrated vehicle position dataset according to the vehicle usage distribution position data;

[0089] A regional concentration evaluation result module, which is used to evaluate the regional concentration of vehicles according to the vehicle position dataset and generate a regional concentration evaluation result;

[0090] An identification module, which is used to generate a battery placement feedback parameter according to the regional concentration evaluation result and identify the vehicle real-time position data through the battery placement feedback parameter.

[0091] Furthermore, the system further includes:

[0092] A historical vehicle usage data module, which is used to collect the historical vehicle usage data of the vehicle usage distribution position;

[0093] A vehicle usage distribution position identification data module, which is used to parse the historical vehicle usage data and generate vehicle usage distribution position identification data according to the data parsing result;

[0094] A time window module, which is used to obtain the time window throughput data of the vehicle usage position according to the vehicle usage distribution position identification data;

[0095] A matching evaluation result module, which is used to perform a matching evaluation of the vehicle usage distribution position identification data and the time window throughput data through the vehicle real-time data and generate a matching evaluation result;

[0096] A regional vehicle concentration influence parameter module, which is used to generate the regional vehicle concentration influence parameter of the vehicle usage distribution position according to the matching evaluation result;

[0097] An adjustment module, which is used to adjust the operation and maintenance path planning through the regional vehicle concentration influence parameter to obtain an adjusted battery swapping operation and maintenance path planning result, and perform battery swapping management on the vehicle through the adjusted battery swapping operation and maintenance path planning result.

[0098] Furthermore, the system further includes:

[0099] A construction module for constructing a training data set of regional vehicle concentration influence parameters by matching evaluation results;

[0100] An incremental learning module for performing incremental learning of the path planning model through the training data set of regional vehicle concentration influence parameters to obtain an incrementally learned path planning model;

[0101] An input module for inputting the aggregated planning result, the battery operation and maintenance point distribution data, and the path influence parameters into the incrementally learned path planning model to obtain the adjusted battery swapping operation and maintenance path planning result.

[0102] Furthermore, the system further includes:

[0103] A real-time traffic data module for obtaining real-time traffic data;

[0104] A real-time adjustment result module for performing real-time execution path adjustment of the battery swapping operation and maintenance path planning result according to the real-time traffic data to obtain a real-time adjustment result;

[0105] A battery swapping module for performing battery swapping management of vehicles through the real-time adjustment result.

[0106] Through the foregoing detailed description of a battery swapping flow planning method based on vehicle interconnection in this specification, those skilled in the art can clearly know a battery swapping flow planning method and system in this embodiment. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the description in the method part.

[0107] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to these embodiments shown herein, but will be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for planning the flow of replacement current based on vehicle interconnection, characterized in that, The method is applied to an intelligent control system, which is communicatively connected to a vehicle. The method includes: Obtaining target control area information, collecting area data of the target control area information to obtain battery operation and maintenance point distribution data; Collecting the vehicle usage distribution positions in the target control area information to obtain vehicle usage distribution position data, where the vehicle usage distribution position data includes vehicle concentrated usage distribution positions and vehicle non-concentrated usage distribution positions; Performing real-time data interaction with the vehicle, and generating vehicle real-time data according to the data interaction result; Screening vehicles for power replenishment according to the vehicle real-time data and the vehicle usage distribution position data, and obtaining first power level vehicle data according to the screening result; Aggregating the vehicle usage distribution position data according to the first power level vehicle data to generate an aggregation planning result; Inputting the aggregation planning result and the battery operation and maintenance point distribution data into a path planning model for operation and maintenance path planning to generate a battery replacement operation and maintenance path planning result; Performing battery replacement management on the vehicle according to the battery replacement operation and maintenance path planning result; Wherein, the method further includes: Obtaining parking vehicle power data and position distribution according to the vehicle real-time data, and screening to obtain regional vehicle power data according to the parking vehicle power data and the vehicle usage distribution position data; Obtaining the concentrated data of the vehicle usage distribution positions according to the vehicle usage distribution position data; Obtaining the non-concentrated data of the vehicle usage distribution positions according to the vehicle usage distribution position data; Performing vehicle power consumption estimation according to the concentrated data and the non-concentrated data of the vehicle usage distribution positions, and screening to obtain estimated vehicle power consumption data based on the power consumption estimation result and the regional vehicle concentration; Obtaining the first power level vehicle data according to the vehicle power data and the estimated vehicle power consumption data.

2. The method according to claim 1, characterized in that, The method further includes: Obtaining vehicle real-time position data within the target control area; Setting a calibrated power threshold, screening the vehicle real-time position data through the calibrated power threshold, and obtaining the position distribution data of the calibrated vehicles according to the screening result; Performing position optimization aggregation of the calibrated vehicles according to the position distribution data and the vehicle usage distribution position data to obtain a position optimization aggregation result; Performing path optimization on the battery replacement operation and maintenance path planning result according to the position optimization aggregation result.

3. The method according to claim 2, wherein The method further includes: Obtaining the position data set of the calibrated vehicles according to the vehicle usage distribution position data; Evaluating the regional concentration of the vehicles according to the vehicle position data set to generate a regional concentration evaluation result; Generating battery placement feedback parameters according to the regional concentration evaluation result, and identifying the vehicle real-time position data through the battery placement feedback parameters.

4. The method according to claim 1, characterized in that, The method further includes: Collecting historical vehicle usage data of the vehicle usage distribution positions; Performing data parsing on the historical vehicle usage data, and generating vehicle usage distribution position identification data according to the data parsing result; Obtaining the time window throughput data of the vehicle usage positions according to the vehicle usage distribution position identification data; Perform matching evaluation on the vehicle usage distribution location identification data and the time window throughput data through the vehicle real-time data to generate a matching evaluation result; Generate the regional vehicle concentration influence parameter of the vehicle usage distribution location according to the matching evaluation result; Perform operation and maintenance path planning adjustment through the regional vehicle concentration influence parameter to obtain an adjusted battery replacement operation and maintenance path planning result, and perform battery replacement management on the vehicle through the adjusted battery replacement operation and maintenance path planning result.

5. The method according to claim 4, wherein The method further includes: Construct a training data set of regional vehicle concentration influence parameters through the matching evaluation result; Perform incremental learning of the path planning model through the training data set of the regional vehicle concentration influence parameters to obtain an incrementally learned path planning model; Input the aggregated planning result, the battery operation and maintenance point distribution data, and the path influence parameter into the incrementally learned path planning model to obtain the adjusted battery replacement operation and maintenance path planning result.

6. The method according to claim 1, characterized in that The method further includes: Obtain real-time traffic data; Perform real-time execution path adjustment on the battery replacement operation and maintenance path planning result according to the real-time traffic data to obtain a real-time adjustment result; Perform battery replacement management on the vehicle through the real-time adjustment result.

7. A current exchange flow planning system based on vehicle interconnection, characterized in that, The battery replacement flow planning system is communicatively connected to the vehicle, and the system includes: A battery operation and maintenance point distribution data acquisition module, which is used to obtain target control area information, perform regional data acquisition on the target control area information, and obtain battery operation and maintenance point distribution data; A location data acquisition module, which is used to collect the vehicle usage distribution location in the target control area information to obtain vehicle usage distribution location data, wherein the vehicle usage distribution location data includes the vehicle concentrated usage distribution location and the vehicle non-concentrated usage distribution location; A vehicle real-time data generation module, which is used to perform real-time data interaction on the vehicle and generate vehicle real-time data according to the data interaction result; A first power vehicle data acquisition module, which is used to screen power replenishment vehicles according to the vehicle real-time data and the vehicle usage distribution location data, and obtain first power vehicle data according to the screening result; An aggregated planning result generation module, which is used to aggregate the vehicle usage distribution location according to the first power vehicle data to generate an aggregated planning result; A battery replacement operation and maintenance path planning result generation module, which is used to input the aggregated planning result and the battery operation and maintenance point distribution data into a path planning model to perform operation and maintenance path planning, and generate a battery replacement operation and maintenance path planning result; A battery replacement management module, which is used to perform battery replacement management on the vehicle according to the battery replacement operation and maintenance path planning result; Wherein, the system further includes: Regional vehicle power data module, which is used to obtain parking vehicle power data and location distribution according to the vehicle real-time data, and screen and obtain regional vehicle power data according to the parking vehicle power data and vehicle usage distribution location data; Vehicle centralized data module, which is used to obtain the centralized data of the vehicle usage distribution location according to the vehicle usage distribution location data; Vehicle non-centralized data module, which is used to obtain the non-centralized data of the vehicle usage distribution location according to the vehicle usage distribution location data; Estimated vehicle power consumption data module, which is used to estimate vehicle power consumption according to the centralized data of the vehicle usage distribution location and the non-centralized data of the vehicle usage distribution location, and screen and obtain the estimated vehicle power consumption data based on the power consumption estimation result and the regional vehicle concentration; First power vehicle data module, which is used to obtain the first power vehicle data according to the vehicle power data and the estimated vehicle power consumption data.

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