Battery swapping station determination method and vehicle

Abstract

This application discloses a method for determining a battery swapping station and a vehicle, belonging to the field of vehicle technology. The method for determining a battery swapping station includes: obtaining the demand category of a target vehicle, the actual state of charge of the target vehicle's battery, and the operating parameters of at least one battery swapping station; the demand category includes power pickup or power return; and based on the demand category, the actual state of charge of the battery, and the operating parameters of the at least one battery swapping station, determining a target battery swapping station from the at least one battery swapping station. The method for determining a battery swapping station in this application can effectively select the most suitable battery swapping station, has high reliability, low risk of selection results, low error cost, and can improve the user experience.

Description

Technical Field

[0001] This application belongs to the field of vehicles, and in particular relates to a method for determining a battery swapping station and a vehicle. Background Technology

[0002] Current battery swapping station operation models recommend locations for users to pick up and swap batteries. The relevant technologies primarily rely on the user's current location, sorting nearby swapping stations by distance from the user's location, allowing the user to choose a suitable station. However, during peak operating hours, swapping stations in popular areas are prone to overload, while in less populated areas, stations may remain vacant due to batteries being taken but not returned. Using the above method, users cannot select a suitable swapping station, resulting in high error costs and random selection, negatively impacting the user experience. Summary of the Invention

[0003] This application aims to address at least one of the technical problems existing in the related art. To this end, this application proposes a method and vehicle for determining a battery swapping station, which effectively selects the most suitable battery swapping station. The selection method has high reliability, low risk of selection results, low error cost, and can improve the user experience.

[0004] Firstly, this application provides a method for determining a battery swapping station, the method comprising:

[0005] The system obtains the demand category of the target vehicle, the actual battery state of charge of the target vehicle, and the operating parameters of at least one battery swapping station; the demand category includes either power pickup or power return.

[0006] Based on the demand category, the actual battery state of charge, and the operating parameters of the at least one battery swapping station, a target battery swapping station is determined from the at least one battery swapping station.

[0007] According to the method for determining the battery swapping station in this application, by comprehensively considering factors such as the area that the target vehicle can reach and the actual needs of the target vehicle, the battery swapping station can eliminate battery swapping stations that cannot meet the target vehicle's needs from multiple stations that the target vehicle can reach. Based on this, and combined with the operating parameters of each battery swapping station, the most suitable battery swapping station can be effectively selected. The selection method has high reliability, low risk of selection results, low error cost, and can improve the user experience.

[0008] According to the method for determining a battery swapping station in this application, determining a target battery swapping station from the at least one battery swapping station based on the demand category, the actual battery state of charge, and the operating parameters of the at least one battery swapping station includes:

[0009] Based on the actual battery state of charge, the driving range corresponding to the target vehicle is determined;

[0010] Based on the driving range, a battery swapping station located within the driving range is obtained from the at least one battery swapping station;

[0011] Based on the demand category, the first distance between each battery swapping station within the driving range and the target vehicle, and the operating parameters of the battery swapping stations within the driving range, the target battery swapping station is determined from the at least one battery swapping station.

[0012] According to the method for determining a battery swapping station in this application, determining the target battery swapping station from the at least one battery swapping station based on the demand category, the first distance between each battery swapping station within the driving range and the target vehicle, and the operating parameters of the battery swapping stations within the driving range includes:

[0013] Based on the demand category and the operating parameters of the battery swapping stations within the range, predict the usage trend of the battery swapping stations within the range.

[0014] The target battery swapping station is determined based on the usage trend, the demand category, and the first distance.

[0015] According to the method for determining a battery swapping station in this application, determining the target battery swapping station based on the usage trend, the demand category, and the first distance includes:

[0016] The usage trend, the demand category, and the first distance are weighted and calculated to obtain the recommendation score for each battery swapping station within the range.

[0017] The battery swapping station corresponding to the highest recommended score is determined as the target battery swapping station.

[0018] According to the method for determining a battery swapping station in this application, determining a target battery swapping station from the at least one battery swapping station based on the demand category, the actual battery state of charge, and the operating parameters of the at least one battery swapping station includes:

[0019] The demand category, the actual battery state of charge, and the operating parameters of at least one battery swapping station are input into the target prediction model to obtain the target battery swapping station output by the target prediction model. The target prediction model is trained based on sample demand categories, sample actual battery state of charge, and sample operating parameters of multiple sample battery swapping stations.

[0020] According to the method for determining a battery swapping station in this application, the operating parameters include at least one of the following: battery swapping cabinet identifier, latitude and longitude coordinates corresponding to the battery swapping cabinet identifier, service type corresponding to the battery swapping cabinet in each time period, quantity corresponding to the service type, warehouse status type corresponding to the battery swapping cabinet in each time period, quantity corresponding to the warehouse status type, state of charge of batteries in the warehouse, charging efficiency characteristics, and user battery swapping station usage characteristics.

[0021] Secondly, this application provides a vehicle that determines a target battery swapping station based on the battery swapping station determination method described in the first aspect.

[0022] Thirdly, this application provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for determining a battery swapping station as described in the first aspect above.

[0023] Fourthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the method for determining a battery swapping station as described in the first aspect above.

[0024] The above-described one or more technical solutions in the embodiments of this application have at least one of the following technical effects:

[0025] By considering factors such as demand category, the actual battery state of charge of the target vehicle, and the operating parameters of the battery swapping station, the system can comprehensively assess the area that the target vehicle can reach and its actual needs. It can eliminate battery swapping stations that do not meet the target vehicle's demand category from among multiple stations that the target vehicle can reach. Based on this, and combined with the operating parameters of each battery swapping station, the system can effectively select the most suitable battery swapping station. The selection method is highly reliable, with low risk and low error cost, which can improve the user experience.

[0026] Furthermore, by obtaining the actual state of charge of the battery, the maximum distance that the target vehicle can travel is determined, effectively determining the number of selectable battery swapping stations. Based on the operating parameters and demand categories of each battery swapping station, the most suitable battery swapping station that can meet the needs of the target vehicle is determined from multiple battery swapping stations.

[0027] Furthermore, by acquiring the operating parameters of battery swapping stations within the driving range, the usage trend of each battery swapping station corresponding to the target vehicle's demand category can be predicted. By combining the usage trends of each battery swapping station, the first distance, and the demand category, the most suitable target vehicle can be selected, effectively avoiding the risks and losses caused by selecting an unsuitable battery swapping station and improving the user experience.

[0028] Furthermore, by weighting usage trends, demand categories, and first distance, and taking into account the importance of different factors, the accuracy of the recommendation process is effectively improved, making the recommendation results more consistent with the actual situation. It also allows for flexible adjustment of the importance of each factor, thereby accurately selecting the most suitable battery swapping station.

[0029] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0030] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which:

[0031] Figure 1 This is one of the flowcharts illustrating the method for determining a battery swapping station provided in the embodiments of this application;

[0032] Figure 2 This is a second flowchart illustrating the method for determining a battery swapping station provided in the embodiments of this application;

[0033] Figure 3 This is the third flowchart illustrating the method for determining a battery swapping station provided in the embodiments of this application;

[0034] Figure 4 This is a schematic diagram of the structure of the device for determining a battery swapping station provided in an embodiment of this application;

[0035] Figure 5 This is a schematic diagram of the vehicle structure provided in the embodiments of this application. Detailed Implementation

[0036] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0037] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0038] The following description, in conjunction with the accompanying drawings, details the method for determining a battery swapping station, the device for determining a battery swapping station, the vehicle, and the readable storage medium provided in this application, through specific embodiments and application scenarios.

[0039] The method for determining the battery swapping station can be applied to the terminal, and can be executed by the hardware or software in the terminal.

[0040] The terminal includes, but is not limited to, portable communication devices such as mobile phones or tablets. It should also be understood that, in some embodiments, the terminal may not be a portable communication device, but rather a desktop computer.

[0041] The following embodiments describe a terminal including a display and a touch-sensitive surface. However, it should be understood that the terminal may include one or more other physical user interface devices such as a physical keyboard, mouse, and joystick.

[0042] This application provides a method for determining a battery swapping station. The subject executing this method can be a vehicle, a device for determining a battery swapping station installed on a vehicle, a server electrically connected to the vehicle, or a user terminal communicatively connected to the vehicle, including but not limited to mobile terminals and non-mobile terminals.

[0043] like Figure 1 As shown, the method for determining the battery swapping station includes steps 110 and 120.

[0044] Step 110: Obtain the demand category of the target vehicle, the actual battery state of charge of the target vehicle, and the operating parameters of at least one battery swapping station;

[0045] In this step, the demand categories include drawing power or returning power.

[0046] In actual implementation, power supply includes at least one of power swapping and power supply.

[0047] The target vehicles are those that require power access or power return.

[0048] The actual battery state of charge is the state of charge of the target vehicle's battery at the current data collection moment.

[0049] In actual implementation, the category of demand can be determined by the actual demand sent by the target vehicle to the control unit, and the category of user demand can also be predicted by the actual condition of the target vehicle's battery.

[0050] The operating parameters are the parameters corresponding to the factors that need to be considered when selecting a battery swapping station.

[0051] In some embodiments, the operating parameters may include at least one of the following: battery swapping cabinet identifier, latitude and longitude coordinates corresponding to the battery swapping cabinet identifier, business type corresponding to the battery swapping cabinet in each time period, quantity corresponding to the business type, warehouse status type corresponding to the battery swapping cabinet in each time period, quantity corresponding to the warehouse status type, state of charge of batteries in the warehouse, charging efficiency characteristics, and user battery swapping station usage characteristics.

[0052] In this embodiment, the battery swapping cabinet is identified by a number that distinguishes each battery swapping cabinet.

[0053] The latitude and longitude coordinates corresponding to the battery swapping cabinet's identifier are used to determine the location of the battery swapping cabinet.

[0054] The service type corresponding to the battery swapping cabinet in each time period is the actual service situation of the battery swapping cabinet in each time period.

[0055] The service types include: the service types for electricity collection and the service types for electricity return.

[0056] The quantity corresponding to the business type is the number of battery swapping cabinets in the battery swapping station that perform the same business type.

[0057] The storage status type of the battery swapping cabinet in each time period corresponds to the storage status of the battery swapping cabinet in each time period.

[0058] The quantity corresponding to the warehouse status type is the quantity of the battery swapping cabinets with the same storage status.

[0059] The charging efficiency characteristic refers to the energy conversion efficiency of the battery in the battery swapping cabinet during the charging process.

[0060] User battery swapping stations use user characteristic data within the target range of the battery swapping station.

[0061] User battery swapping station usage characteristics include: user's habits of drawing or returning electricity, the actual charge status of the user's vehicle, and the distance between the user's vehicle and the battery swapping station.

[0062] Operating parameters can be determined based on the actual operating conditions of each battery swapping station.

[0063] Understandably, the operating parameters can be obtained from the historical log data of the battery swapping cabinets in each battery swapping station.

[0064] Of course, the operating parameters of each battery swapping cabinet can also be obtained through any other feasible means.

[0065] According to the method for determining a battery swapping station provided in the embodiments of this application, by acquiring multiple operating parameters of each battery swapping station, the actual operating status of each battery swapping station can be effectively determined based on multiple operating parameters, thereby providing data support for providing users with the optimal battery swapping station in the future.

[0066] Step 120: Based on the demand category, the actual battery state of charge, and the operating parameters of at least one battery swapping station, determine the target battery swapping station from at least one battery swapping station.

[0067] In this step, the target battery swapping station is the optimal battery swapping station that the target vehicle can select from among multiple battery swapping stations.

[0068] In actual implementation, after determining the demand category of the target vehicle, the actual operating conditions of multiple battery swapping stations are considered within the actual battery charge state that the target vehicle can use, and the most suitable battery swapping station is selected from multiple battery swapping stations.

[0069] For example, during peak operating hours of a battery swapping station, if a target vehicle needs to obtain power, a battery swapping station that is relatively far away but can meet the target vehicle's power needs can be selected from among the multiple battery swapping stations that the target vehicle can reach.

[0070] During the research and development process, the inventors discovered that in related technologies, the nearest battery swapping stations are sorted by distance from the vehicle's current location, and then the user selects a suitable swapping station. However, the selected swapping station may be overloaded in popular areas during peak hours, resulting in frequent battery swapping and leaving no battery with the required state of charge. In addition, in areas with low traffic, the station may be vacant due to the removal of batteries and the return of few batteries.

[0071] This application determines the actual needs of the target vehicle by obtaining the demand category, determines the area that the target vehicle can reach by the actual battery charge state of the target vehicle, and determines the actual operation of each battery swapping station based on the operating parameters of the battery swapping stations in the area that the target vehicle can reach. It selects a suitable battery swapping station from multiple stations, and further considers the actual operation of each station in addition to the distance between the target vehicle and the battery swapping station, effectively selecting a suitable battery swapping station, effectively reducing the risk of randomly selecting a less suitable battery swapping station, and improving the user experience.

[0072] According to the method for determining a battery swapping station provided in this application, by considering the demand category, the actual battery charge state of the target vehicle, and the operating parameters of the battery swapping station, the method can comprehensively consider the area that the target vehicle can reach and the actual needs of the target vehicle. It can exclude battery swapping stations that cannot meet the demand category of the target vehicle from multiple battery swapping stations that the target vehicle can reach. On this basis, combined with the operating parameters of each battery swapping station, the most suitable battery swapping station can be effectively selected. The selection method has high reliability, low risk of selection results, low error cost, and can improve the user experience.

[0073] In some embodiments, step 120 may further include:

[0074] Determine the driving range of the target vehicle based on the actual battery state of charge.

[0075] Based on the driving range, select a battery swapping station located within the driving range from at least one battery swapping station;

[0076] Based on the demand category, the first distance between each battery swapping station and the target vehicle within the driving range, and the operating parameters of the battery swapping stations within the driving range, the target battery swapping station is determined from at least one battery swapping station.

[0077] In this embodiment, the driving range is the farthest distance that the target vehicle can travel in its actual battery charge state at the current data collection time.

[0078] The battery swapping stations within the driving range are one or more battery swapping stations within the target area determined based on the location of the target vehicle and the driving range.

[0079] The target area can be a region determined based on the location and range of the target vehicle.

[0080] In some embodiments, the target area may be a circular area defined by the target vehicle as the center and the driving range as the radius.

[0081] The target area can also be determined based on any other feasible method, and this application does not limit the specific method of determining the target area.

[0082] The first distance is the distance between the target vehicle's current location at the time of data collection and any battery swapping station within its range.

[0083] Understandably, the value corresponding to the first distance will vary depending on the battery swapping station.

[0084] In actual execution, after obtaining the demand category of the target vehicle, the maximum distance that the target vehicle can continue to travel is determined by the actual battery charge state of the target vehicle. The optimal battery swapping station is selected from multiple battery swapping stations between the current location of the target vehicle and the maximum distance that the target vehicle can continue to travel.

[0085] When selecting the optimal battery swapping station, the actual operating conditions of each station can be taken into account.

[0086] For example, if it is determined that there are 5 battery swapping stations within the target vehicle's driving range, and the user's demand type is power access, analyze the suitability of the 5 battery swapping stations within the target vehicle's driving range.

[0087] Taking five battery swapping stations—the first, second, third, fourth, and fifth—as an example, the distance between the five stations increases from closest to furthest. The number of battery swapping cabinets at each station, determined by their identification, is 10, 15, 5, 10, and 20 respectively. In the past week, the average number of power withdrawals at the first station between 8:00 AM and 10:00 AM was 10, at the second station it was 5, at the third station it was 4, at the fourth station it was 8, and at the fifth station it was 12.

[0088] Given that the target vehicle's actual battery charge status is based on data collected at 8:15 AM, the distance to each battery swapping station and the number of transactions at different times can be considered to recommend that the target vehicle drive to the second battery swapping station for power.

[0089] Of course, in actual implementation, the target battery swapping station can also be determined by comprehensively considering other operating parameters of each battery swapping station.

[0090] According to the method for determining a battery swapping station provided in the embodiments of this application, the maximum distance that the target vehicle can travel is determined by acquiring the actual state of battery charge, effectively determining the number of selectable battery swapping stations, and determining the most suitable battery swapping station from multiple battery swapping stations that can meet the needs of the target vehicle based on the operating parameters and demand categories of each battery swapping station.

[0091] In some embodiments, determining a target battery swapping station from at least one battery swapping station based on demand category, a first distance between each battery swapping station and the target vehicle within the driving range, and operating parameters of the battery swapping stations within the driving range may further include:

[0092] Based on demand categories and the operating parameters of battery swapping stations within the driving range, the usage trend of battery swapping stations within the driving range is predicted.

[0093] Target battery swapping stations are determined based on usage trends, demand categories, and initial distance.

[0094] In this embodiment, the usage trend represents the potential usage of the battery swapping station in various future time periods.

[0095] Usage trends are curves that gradually change along a future timeline.

[0096] It is understandable that the usage trends of different battery swapping stations may be the same or different.

[0097] Usage trends include: electricity consumption trends or electricity return trends.

[0098] The power consumption trend represents the potential power consumption of the battery swapping station in different time periods in the future.

[0099] The electricity usage trend represents the potential electricity usage of the battery swapping station in different time periods.

[0100] The specific category of usage trends can be determined based on the demand category of the target vehicle.

[0101] Usage trend can be the number of battery swapping cabinets in the station that may have already been powered, or the number of battery swapping cabinets that may remain available for power generation.

[0102] like Figure 2 As shown, in actual implementation, after determining the demand category of the target vehicle, we can obtain the characteristic data of users around the battery swapping station and other operating parameters of the battery swapping station. Based on the characteristic data of users around the battery swapping station and the operating parameters of the battery swapping station, we can predict the usage trend of each battery swapping station.

[0103] For example, continuing with the example of five battery swapping stations within the driving range, and the user's need for power replenishment, these are the first, second, third, fourth, and fifth battery swapping stations. The distance between each battery swapping station increases from near to far. Users near the first battery swapping station have a higher demand for power replenishment between 5 pm and 6 pm, users near the second battery swapping station have a higher demand for power replenishment between 10 am and 12 pm, users near the third battery swapping station have a higher demand for power replenishment between 8 am and 10 am, users near the fourth battery swapping station have a higher demand for power replenishment between 12 pm and 1 pm, and users near the fifth battery swapping station have a higher demand for power replenishment between 2 pm and 4 pm.

[0104] Based on the above information, after obtaining the power demand of the target vehicle, the usage trend of each battery swapping station in subsequent time periods can be predicted based on the collection time corresponding to the current power demand. Then, based on the predicted usage trend and further considering the distance between each battery swapping station and the target vehicle, the most suitable battery swapping station can be selected from multiple battery swapping stations.

[0105] According to the method for determining a battery swapping station provided in the embodiments of this application, by obtaining the operating parameters of the battery swapping stations within the driving range, the usage trend of each battery swapping station corresponding to the demand category of the target vehicle is predicted. Then, by combining the usage trends of each battery swapping station, the first distance, and the demand category, the most suitable target vehicle is selected, effectively avoiding the risks and losses caused by selecting an unsuitable battery swapping station and improving the user experience.

[0106] In some embodiments, determining the target battery swapping station based on usage trends, demand categories, and a first distance may further include:

[0107] We calculate a weighted average of usage trends, demand categories, and first distance to obtain a recommended score for each battery swapping station within the driving range.

[0108] The battery swapping station with the highest recommended score is designated as the target battery swapping station.

[0109] In this embodiment, the recommendation score represents the degree to which each battery swapping station is recommended.

[0110] In actual implementation, the usage trend and first distance of each battery swapping station corresponding to the demand category can be weighted and calculated to obtain the recommendation score of each battery swapping station, and the station with the highest evaluation score can be recommended to the target vehicle.

[0111] In practice, different weights can be assigned to usage trend and first distance to calculate the recommendation score.

[0112] Understandably, distance can be given relatively high weight. While focusing on distance as a key factor, other factors should be considered further, and battery swapping stations should be recommended.

[0113] According to the method for determining a battery swapping station provided in the embodiments of this application, by weighting the usage trend, demand category, and first distance, and considering the different degrees of influence of different factors on the selection of battery swapping stations, the accuracy of the recommendation process is effectively improved, making the recommendation results more in line with the actual situation, and the importance of each factor can be flexibly adjusted, thereby accurately selecting the most suitable battery swapping station.

[0114] In some embodiments, step 120 may further include:

[0115] Input the demand category, actual battery state of charge, and operating parameters of at least one battery swapping station into the target prediction model to obtain the target battery swapping station output by the target prediction model;

[0116] The target prediction model was trained based on the sample demand category, the actual state of charge of the sample batteries, and the sample operation parameters of multiple sample battery swapping stations.

[0117] In some embodiments, the target prediction model is a model that predicts the usage trend of each battery swapping station.

[0118] The target prediction model can be a prediction model such as a deep learning model or a machine learning model.

[0119] The target battery swapping station output by the target prediction model can be information that identifies the target battery swapping station, such as its location and name.

[0120] In actual execution, after obtaining the demand category of the target vehicle, the target prediction model can obtain the operating data of each battery swapping station within the target vehicle's range. Based on the obtained operating data, it predicts the usage trend of each battery swapping station corresponding to the demand category. Based on the predicted usage trend and the distance between each battery swapping station and the target vehicle, it performs a weighted calculation and outputs the most suitable target battery swapping station.

[0121] The sample demand category is the demand category of the sample vehicles.

[0122] The actual state of charge of the sample battery is the actual state of charge of the sample vehicle battery.

[0123] The sample battery swapping stations consist of a predetermined number of battery swapping stations.

[0124] The sample operating parameters are feature data related to the usage of the battery swapping cabinets from the historical operating data of the sample battery swapping stations.

[0125] like Figure 3 As shown, sample operating parameters of each sample battery swapping station can be collected and preprocessed, such as performing correlation analysis, relationship graph establishment, data classification, and data labeling. Then, based on the preprocessed sample operating parameters, the target prediction model is trained to obtain the target prediction model.

[0126] According to the method for determining battery swapping stations provided in the embodiments of this application, by inputting the demand category into the target prediction model, the target battery swapping station output by the target prediction model can be obtained, thus efficiently recommending battery swapping stations and improving user experience. In addition, by training the target prediction model with the obtained sample demand category, sample actual battery state of charge, and sample operating parameters of multiple sample battery swapping stations, it only needs to be trained once and can be used multiple times in the future, thereby improving recommendation efficiency and effectively reducing recommendation costs.

[0127] The method for determining a battery swapping station provided in this application can be executed by a device for determining a battery swapping station. This application uses an example of a device for determining a battery swapping station executing the method to illustrate the device for determining a battery swapping station provided in this application.

[0128] This application also provides a device for determining a battery swapping station.

[0129] like Figure 4 As shown, the device for determining the battery swapping station includes: a first processing module 410 and a second processing module 420.

[0130] The first processing module 410 is used to obtain the demand category of the target vehicle, the actual battery state of charge of the target vehicle, and the operating parameters of at least one battery swapping station; the demand category includes power pickup or power return.

[0131] The second processing module 420 is used to determine the target battery swapping station from at least one battery swapping station based on the demand category, the actual battery state of charge, and the operating parameters of at least one battery swapping station.

[0132] According to the battery swapping station determination device provided in the embodiments of this application, by comprehensively considering factors such as the area that the target vehicle can reach and the actual needs of the target vehicle, the device can eliminate battery swapping stations that cannot meet the target vehicle's needs from multiple battery swapping stations that the target vehicle can reach. Based on this, and combined with the operating parameters of each battery swapping station, the device can effectively select the most suitable battery swapping station. The selection method has high reliability, low risk of selection results, and low error cost, which can improve the user experience.

[0133] In some embodiments, the second processing module 420 may also be used for:

[0134] Determine the driving range of the target vehicle based on the actual battery state of charge.

[0135] Based on the driving range, select a battery swapping station located within the driving range from at least one battery swapping station;

[0136] Based on the demand category, the first distance between each battery swapping station and the target vehicle within the driving range, and the operating parameters of the battery swapping stations within the driving range, the target battery swapping station is determined from at least one battery swapping station.

[0137] In some embodiments, the second processing module 420 may also be used for:

[0138] Based on demand categories and the operating parameters of battery swapping stations within the driving range, the usage trend of battery swapping stations within the driving range is predicted.

[0139] Target battery swapping stations are determined based on usage trends, demand categories, and initial distance.

[0140] In some embodiments, the second processing module 420 may also be used for:

[0141] We calculate a weighted average of usage trends, demand categories, and first distance to obtain a recommended score for each battery swapping station within the driving range.

[0142] The battery swapping station with the highest recommended score is designated as the target battery swapping station.

[0143] In some embodiments, the second processing module 420 may also be used for:

[0144] Input the demand category, actual battery state of charge, and operating parameters of at least one battery swapping station into the target prediction model to obtain the target battery swapping station output by the target prediction model;

[0145] The target prediction model was trained based on the sample demand category, the actual state of charge of the sample batteries, and the sample operation parameters of multiple sample battery swapping stations.

[0146] The device for determining the battery swapping station in this embodiment can be a vehicle or a component within the vehicle, such as an integrated circuit or a chip. The vehicle can be a terminal or other equipment besides a terminal.

[0147] The device for determining the battery swapping station in this embodiment can be a device with an operating system. This operating system can be Android, iOS, or other possible operating systems; this embodiment does not impose specific limitations on it.

[0148] The device for determining a battery swapping station provided in this application embodiment can achieve... Figures 1 to 3 The various processes implemented in the method implementation examples will not be described again here to avoid repetition.

[0149] In some embodiments, such as Figure 5 As shown, this application embodiment also provides a vehicle 500, including a processor 501, a memory 502, and a computer program stored in the memory 502 and executable on the processor 501. When the program is executed by the processor 501, it implements the various processes of the above-described method embodiment for determining a battery swapping station and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0150] It should be noted that the electronic devices in the embodiments of this application include the mobile electronic devices and non-mobile electronic devices described above.

[0151] This application also provides a vehicle.

[0152] The vehicle determines the target battery swapping station based on the battery swapping station determination method described in any of the above embodiments.

[0153] According to the vehicle provided in the embodiments of this application, by considering the demand category, the actual battery state of charge of the target vehicle, and the operating parameters of the battery swapping station, the vehicle can comprehensively consider the area that the target vehicle can reach and the actual needs of the target vehicle. From the multiple battery swapping stations that the target vehicle can reach, battery swapping stations that cannot meet the demand category of the target vehicle are excluded. On this basis, combined with the operating parameters of each battery swapping station, the most suitable battery swapping station is effectively selected. The selection method has high reliability, low risk of selection result, low error cost, and can improve the user experience.

[0154] This application also provides a non-transitory computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the various processes of the above-described method for determining a battery swapping station and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0155] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0156] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method for determining a battery swapping station.

[0157] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0158] This application embodiment also provides a chip, which includes a processor and a communication interface. The communication interface and the processor are coupled. The processor is used to run programs or instructions to implement the various processes of the above-described method embodiment for determining a battery swapping station, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0159] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0160] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0161] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the related technology, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0162] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

[0163] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0164] Although embodiments of this application have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of this application, the scope of which is defined by the claims and their equivalents.

Claims

1. A method for determining a battery swapping station, characterized in that, include: Obtain the demand category of the target vehicle, the actual battery state of charge of the target vehicle, and the operating parameters of at least one battery swapping station; The operating parameters include at least one of the following: battery swapping cabinet identifier, latitude and longitude coordinates corresponding to the battery swapping cabinet identifier, service type of the battery swapping cabinet in each time period, quantity of the service type, warehouse status type of the battery swapping cabinet in each time period, quantity of the warehouse status type, state of charge of the batteries in the warehouse, and charging efficiency characteristics; the operating parameters also include user battery swapping station usage characteristics. Based on the demand category, the actual battery state of charge, and the operating parameters of the at least one battery swapping station, a target battery swapping station is determined from the at least one battery swapping station; The demand categories include power extraction, power swapping, or power return; The user battery swapping station usage characteristics are the characteristic data of users within the target range of the battery swapping station; the user battery swapping station usage characteristics include: the user's habit of drawing or returning electricity, the actual charge status of the user's vehicle, and the distance between the user's vehicle and the battery swapping station. The step of determining a target battery swapping station from the at least one battery swapping station based on the demand category, the actual battery state of charge, and the operating parameters of the at least one battery swapping station includes: Based on the actual battery state of charge, the driving range corresponding to the target vehicle is determined; Based on the driving range, a battery swapping station located within the driving range is obtained from the at least one battery swapping station; Based on the demand category, the first distance between each battery swapping station within the driving range and the target vehicle, and the operating parameters of the battery swapping stations within the driving range, the target battery swapping station is determined from the at least one battery swapping station; The process of determining the target battery swapping station from the at least one battery swapping station based on the demand category, the first distance between each battery swapping station within the driving range and the target vehicle, and the operating parameters of the battery swapping stations within the driving range includes: Based on the demand category and the operating parameters of the battery swapping stations within the range, predict the usage trend of the battery swapping stations within the range. The target battery swapping station is determined based on the usage trend, the demand category, and the first distance.

2. The method for determining a battery swapping station according to claim 1, characterized in that, The step of determining the target battery swapping station based on the usage trend, the demand category, and the first distance includes: The usage trend, the demand category, and the first distance are weighted and calculated to obtain the recommendation score for each battery swapping station within the range. The battery swapping station corresponding to the highest recommended score is determined as the target battery swapping station.

3. The method for determining a battery swapping station according to claim 1, characterized in that, The step of determining a target battery swapping station from the at least one battery swapping station based on the demand category, the actual battery state of charge, and the operating parameters of the at least one battery swapping station includes: The demand category, the actual battery state of charge, and the operating parameters of the at least one battery swapping station are input into the target prediction model to obtain the target battery swapping station output by the target prediction model. The target prediction model is trained based on the sample demand category, the actual state of charge of the sample batteries, and the sample operation parameters of multiple sample battery swapping stations.

4. A vehicle, characterized in that, The target battery swapping station is determined based on the method for determining battery swapping stations as described in any one of claims 1-3.

5. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the method for determining a battery swapping station as described in any one of claims 1-3.

6. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the method for determining a battery swapping station as described in any one of claims 1-3.

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