Battery pack charging and replacing cooperative scheduling method and system of battery swap station

Abstract

The application discloses a battery pack charging and replacing cooperative scheduling method and system of a battery swap station. The method comprises the following steps: determining the total number of vehicles driving into the target battery swap station within the target time window; determining the arrival time sequence corresponding to each vehicle under the total number of vehicles; determining the available time sequence corresponding to each target battery pack in the target battery swap station within the target time window; matching the arrival time sequence with the available time sequence to determine the time sequence overlap degree; and performing charging and replacing scheduling on each target battery pack of the target battery swap station based on the time sequence overlap degree. The application solves the technical problem of high vehicle waiting time cost caused by unreasonable charging and replacing scheduling of batteries in the target battery swap station in the related art.

Description

Technical Field

[0001] This invention relates to the field of battery swapping stations, and more specifically, to a method and system for coordinated scheduling of battery pack charging and swapping at battery swapping stations. Background Technology

[0002] In related technologies, the demand for efficient electric vehicle charging is increasing. To ensure vehicles can quickly complete charging and improve the operational efficiency of charging stations, it is necessary to schedule the charging and swapping of battery packs in the battery swapping stations. However, in related technologies, there are technical problems in the scheduling of charging and swapping of battery packs in the battery swapping stations, such as unreasonable scheduling leading to high vehicle waiting time costs.

[0003] There is currently no effective solution to the above problems. Summary of the Invention

[0004] This invention provides a method and system for coordinated scheduling of battery pack charging and swapping at a battery swapping station, which at least solves the technical problem in related technologies where unreasonable charging and swapping scheduling leads to high vehicle waiting time costs when scheduling batteries in a target battery swapping station.

[0005] According to one aspect of the present invention, a method for coordinated charging and swapping of battery packs at a battery swapping station is provided, comprising: determining the total number of vehicles entering a target battery swapping station within a target time window; determining the arrival time sequence corresponding to each vehicle under the total number of vehicles, wherein the arrival time sequence includes the arrival times corresponding to each vehicle in chronological order within the target time window; determining the available time sequence corresponding to each target battery pack in the target battery swapping station within the target time window; matching the arrival time sequence with the available time sequence to determine the time overlap; and performing charging and swapping scheduling for each target battery pack in the target battery swapping station based on the time overlap.

[0006] Optionally, determining the available time sequence corresponding to each target battery pack in the target battery swapping station within the target time window includes: when each target battery pack includes each first battery pack and each second battery pack, obtaining the charging progress data corresponding to each first battery pack in the target battery swapping station, and the number of battery packs corresponding to each second battery pack, wherein each first battery pack is a battery pack that is being charged, and each second battery pack is a battery pack that is fully charged; and determining the available time sequence corresponding to each target battery pack in the target battery swapping station within the target time window based on the charging progress data corresponding to each first battery pack and the number of battery packs corresponding to each second battery pack.

[0007] Optionally, determining the available time sequence of each target battery pack in the target battery swapping station within the target time window based on the charging progress data corresponding to each of the first battery packs and the number of battery packs corresponding to each of the second battery packs includes: sorting the first battery packs according to the charging progress data corresponding to each of the first battery packs to obtain the charging priority of each of the first battery packs; determining the charging power corresponding to each of the first battery packs based on the charging priority of each of the first battery packs; charging the corresponding first battery packs according to the charging power corresponding to each of the first battery packs and determining the full charge time corresponding to each of the first battery packs; and determining the available time sequence of each target battery pack in the target battery swapping station within the target time window based on the full charge time corresponding to each of the first battery packs and the number of battery packs corresponding to each of the second battery packs.

[0008] Optionally, the step of scheduling charging and swapping for each target battery pack of the target battery swapping station based on the time overlap includes: determining the number of vehicles arriving at each time point in the arrival time sequence and the number of available batteries at each time point in the available time sequence; and scheduling charging and swapping for each target battery pack of the target battery swapping station based on the time overlap, the number of vehicles arriving at each time point, and the number of available batteries at each time point in the available time sequence.

[0009] Optionally, the step of scheduling charging and swapping for each target battery pack of the target battery swapping station based on the temporal overlap, the number of vehicles arriving at each time point, and the number of available batteries at each time point in the available time series includes: determining whether the temporal overlap is less than an overlap threshold to obtain an overlap determination result; determining whether the quantity deviation at each time point is greater than a deviation threshold to obtain a deviation determination result, wherein the quantity deviation is the deviation between the number of vehicles arriving at the corresponding time point and the number of available batteries; and scheduling charging and swapping for each target battery pack of the target battery swapping station based on the overlap determination result and the deviation determination result.

[0010] Optionally, the step of scheduling charging and swapping for each target battery pack of the target battery swapping station based on the overlap determination result and the deviation determination result includes: determining multiple time matching degrees corresponding to each target battery pack when the overlap determination result and the deviation determination result meet a first predetermined condition, wherein the multiple time matching degrees are the degree of closeness between the available time of the corresponding target battery pack and the arrival time corresponding to each vehicle; and scheduling charging and swapping for each target battery pack of the target battery swapping station according to the multiple time matching degrees corresponding to each target battery pack, wherein the first predetermined condition includes at least one of the following: the overlap determination result is that the temporal overlap degree is less than an overlap threshold, and the deviation determination result is that the quantity deviation corresponding to each time is greater than a deviation threshold.

[0011] Optionally, the step of scheduling charging and swapping for each target battery pack of the target battery swapping station based on the temporal overlap includes: determining the predicted waiting time corresponding to each vehicle based on the temporal overlap; identifying a target vehicle from among the vehicles, wherein the target vehicle is the vehicle among the vehicles whose predicted waiting time is greater than a predetermined waiting time; determining the station distance between the target battery swapping station and a neighboring battery swapping station, wherein the neighboring battery swapping station is another battery swapping station whose route distance from the target battery swapping station is less than a distance threshold; determining the entry time of the target vehicle to the neighboring battery swapping station and the waiting time for battery swapping at the neighboring battery swapping station at the entry time; and scheduling charging and swapping for each target battery pack of the target battery swapping station based on the entry time, the waiting time for battery swapping, and the predicted waiting time corresponding to each vehicle.

[0012] Optionally, determining the total number of vehicles entering the target battery swapping station within the target time window includes: acquiring historical entry data of the target battery swapping station and vehicle driving data along the target route, wherein the vehicle driving data includes vehicle location data and the target route is the traffic route corresponding to the target battery swapping station; and determining the total number of vehicles entering the target battery swapping station within the target time window based on the historical entry data and the vehicle driving data.

[0013] According to one aspect of the present invention, a battery pack charging and swapping coordinated scheduling device for a battery swapping station is provided, comprising: a first determining module, configured to determine the total number of vehicles entering a target battery swapping station within a target time window; a second determining module, configured to determine the arrival time sequence corresponding to each vehicle under the total number of vehicles, wherein the arrival time sequence includes the arrival times corresponding to each vehicle arranged in chronological order within the target time window; a third determining module, configured to determine the available time sequence corresponding to each target battery pack in the target battery swapping station within the target time window; a fourth determining module, configured to match the arrival time sequence with the available time sequence to determine the time sequence overlap; and a fifth determining module, configured to perform charging and swapping scheduling for each target battery pack in the target battery swapping station based on the time sequence overlap.

[0014] According to one aspect of the present invention, an electronic device is provided, comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to execute the instructions to implement the battery pack charging and swapping coordinated scheduling method of any of the preceding claims.

[0015] In this embodiment of the invention, determining the total number of vehicles within the target time window and generating an arrival time sequence transforms the dispersed vehicle arrival times into ordered timeline data. Simultaneously generating the available time sequence for each battery pack maps the battery's fully charged or idle state onto the same timeline. Matching the two sequences and calculating the time overlap directly quantifies the degree of temporal agreement between vehicle arrival times and battery availability times. Since low time overlap directly indicates no battery available upon vehicle arrival or a long waiting time, charging and battery swapping scheduling based on this overlap can selectively adjust charging power or allocation order to match vehicle arrival patterns, thereby shortening the overall vehicle waiting time. This solves the technical problem in related technologies where unreasonable charging and battery swapping scheduling at the target battery swapping station leads to high vehicle waiting time costs. Attached Figure Description

[0016] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0017] Figure 1 This is a flowchart of a battery pack charging and swapping coordinated scheduling method for a battery swapping station according to an embodiment of the present invention;

[0018] Figure 2 This is a schematic diagram of the battery pack charging and swapping collaborative scheduling process framework of a battery swapping station in an optional embodiment of the present invention.

[0019] Figure 3 This is a schematic diagram of the scheduling framework module in an optional embodiment of the present invention;

[0020] Figure 4 This is a schematic diagram of the internal structural framework of the charging time sensing module in an optional embodiment of the present invention;

[0021] Figure 5 This is a schematic diagram illustrating the working principle of the collaborative control module in an optional embodiment of the present invention;

[0022] Figure 6 This is a structural block diagram of a battery pack charging and swapping coordinated scheduling device for a battery swapping station according to an embodiment of the present invention. Detailed Implementation

[0023] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0024] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0025] Example 1

[0026] According to an embodiment of the present invention, an embodiment of a battery pack charging and swapping coordinated scheduling method for a battery swapping station is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0027] Figure 1 This is a flowchart of a battery pack charging and swapping coordinated scheduling method for a battery swapping station according to an embodiment of the present invention, as shown below. Figure 1As shown, the method includes the following steps:

[0028] S102, Determine the total number of vehicles entering the target battery swapping station within the target time window;

[0029] This involves a target time window, which is a pre-determined time window for the coordinated scheduling of battery pack charging and swapping at the battery swapping station. For example, the target time window could be the next 15 minutes, the next 30 minutes, or the next hour, providing a time boundary for the coordinated scheduling of battery pack charging and swapping at the battery swapping station.

[0030] This includes target battery swapping stations, which are energy replenishment stations that provide power battery swapping services for electric vehicles. These stations are equipped with charging and battery swapping systems and can be used for vehicle battery swapping.

[0031] This involves the total number of vehicles, which is the total number of vehicles (vehicles waiting to be served) that are expected to enter the target battery swapping station within the target time window and have a need for recharging. This is used to quantify the total recharging demand within the target time window.

[0032] S104, determine the arrival time sequence of each vehicle under the total number of vehicles, wherein the arrival time sequence includes the arrival time of each vehicle arranged in chronological order within the target time window;

[0033] This involves arrival time series, which is a time series formed by arranging the arrival times (i.e., predicted arrival times) of each vehicle within the target time window in chronological order. For example, the arrival time series includes the arrival times corresponding to each vehicle.

[0034] This involves various vehicles, which are electric vehicles expected to enter the target battery swapping station within the target time window. For example, these vehicles may include vehicles that have been located and confirmed to be heading to the target battery swapping station via Global Positioning System (GPS), as well as potential vehicles that may enter based on historical data.

[0035] This includes arrival time, which is the estimated time for each vehicle to arrive at the target battery swapping station from the initial moment within the target time window. For example, if a vehicle is expected to arrive at the 5th minute within the target time window, then its arrival time is 5 minutes.

[0036] S106, Determine the available time series corresponding to each target battery pack in the target battery swapping station within the target time window;

[0037] This involves available time series, which is a time series formed by arranging the expected available times of each target battery pack in chronological order after the target time window is determined. For example, the available time series includes the expected available time of each target battery pack in chronological order within the target time window (such as the next 30 minutes) (such as the first battery pack reaching full charge and availability at the 5th minute, the second battery pack reaching full charge and availability at the 12th minute, the third battery pack reaching full charge and availability at the 18th minute, etc.).

[0038] In this system, each moment in the arrival time series and the available time series corresponds one-to-one, meaning that the moments in the arrival time series and the available time series are time-aligned.

[0039] This involves target battery packs, which are battery packs that are being charged or have been fully charged at the target battery swapping station and are available for subsequent battery swapping to provide power / electrical support for electric vehicles.

[0040] S108, the arriving time series is matched with available time series to determine the time series overlap;

[0041] This involves temporal overlap, which is determined by comparing the relative positions of the arrival times of vehicles at each moment in the arrival time series with the available times of the target battery pack at each moment in the available time series along the time dimension (time axis). This temporal overlap does not require complete overlap of time points; rather, it focuses on the proximity of the arrival time and the available time along the time axis.

[0042] S110, based on the time overlap, performs charging and swapping scheduling for each target battery pack at the target battery swapping station.

[0043] This involves charging and battery swapping scheduling, which involves charging and battery swapping operations for each vehicle based on the target battery pack within the target time window.

[0044] Through the aforementioned steps S102-S110, the total number of vehicles within the target time window is determined sequentially to quantify the total energy replenishment demand; arrival time series arranged chronologically are generated to characterize the temporal distribution of demand; and available time series for each battery pack are generated to characterize the resource release rhythm on the supply side. The two time series are then time-aligned and their time overlap is calculated. This quantifies the degree of matching between the release time of charging resources and the arrival time of user demand into a calculable indicator. Since this time overlap directly reflects the degree of mismatch between resource supply and demand in the time dimension, therefore... Based on this overlap, the system can perform differentiated charging and swapping scheduling for each battery pack, prioritizing the allocation of charging power to battery packs that are about to be completed to accelerate the release of fully charged resources. It also prioritizes recommending available battery packs with the closest arrival time for swapping, thereby solving the problem of resource waste and vehicle waiting caused by static reservations in the existing battery locking mode, which cannot cope with dynamic changes. This achieves the technical effect of actively aligning the charging release rhythm with the vehicle arrival rhythm, and further solves the technical problem in related technologies where unreasonable charging and swapping scheduling leads to high vehicle waiting time costs when scheduling batteries in the target swapping station.

[0045] As an optional embodiment, determining the available time sequence corresponding to each target battery pack in the target battery swapping station within the target time window includes: when each target battery pack includes each first battery pack and each second battery pack, obtaining the charging progress data corresponding to each first battery pack in the target battery swapping station, and the number of battery packs corresponding to each second battery pack, wherein each first battery pack is a battery pack that is being charged, and each second battery pack is a battery pack that is fully charged; and determining the available time sequence corresponding to each target battery pack in the target battery swapping station within the target time window based on the charging progress data corresponding to each first battery pack and the number of battery packs corresponding to each second battery pack.

[0046] This involves the first battery pack, which is a battery pack that is being charged at the target battery swapping station but has not yet reached full charge; that is, a battery pack that is being charged.

[0047] This involves a second battery pack, which is a battery pack that has been fully charged and is ready for use in the target battery swapping station. For example, the second battery pack may be a spare battery pack that has been fully charged and stored in the battery compartment of the battery swapping station.

[0048] This includes charging progress data, which represents the current charging status and future charging trend of the first battery pack. For example, the charging progress data includes the current state of charge (SOC), charging current, battery temperature, and charging time.

[0049] This involves the number of battery packs, which is the total number of second battery packs (fully charged battery packs) in the target battery swapping station. For example, the number of battery packs can be 2, 3, or 5, etc., to quantify the total amount of fully charged resources that can be used for battery swapping immediately.

[0050] By sorting the charging progress data of each first battery pack, the system can identify battery packs that are about to be fully charged and assign them a higher charging priority. Based on this priority, the charging power is dynamically allocated, so that the power resources are concentrated on the battery packs that can release their full charge resources the fastest, thereby accelerating their full charge time. Since the full charge time of each first battery pack is accurately determined and together with the number of second battery packs available at the moment (the second battery packs are available from the beginning by default until they are used to directly respond to the vehicle's battery swapping needs without waiting), a usable time sequence is formed. Therefore, it can ensure that the resource release rhythm on the supply side is fully quantified, providing accurate timing input for solving the time mismatch problem between charging resource release and user demand arrival.

[0051] As an optional embodiment, based on the charging progress data corresponding to each first battery pack and the number of battery packs corresponding to each second battery pack, the available time sequence corresponding to each target battery pack in the target battery swapping station within the target time window is determined, including: sorting each first battery pack according to the charging progress data corresponding to each first battery pack to obtain the charging priority of each first battery pack; determining the charging power corresponding to each first battery pack based on the charging priority of each first battery pack; charging the corresponding first battery pack according to the charging power corresponding to each first battery pack and determining the full charge time corresponding to each first battery pack; and determining the available time sequence corresponding to each target battery pack in the target battery swapping station within the target time window based on the full charge time corresponding to each first battery pack and the number of battery packs corresponding to each second battery pack.

[0052] This involves charging priority, which is the order of charging services determined based on the charging progress data of the corresponding first battery pack. For example, the charging priority is sorted from shortest to longest remaining charging time, with the shorter the remaining time, the higher the priority.

[0053] This involves charging power, which is the power used to charge the corresponding first battery pack. For example, the charging power is dynamically adjusted according to the charging priority, and the battery pack with higher priority receives higher charging power to accelerate its full charge.

[0054] Since the remaining charging time of each first battery pack is different, the charging priority is determined by sorting them from shortest to longest remaining time, and higher power is allocated to the battery packs with higher priority. This can accelerate the release of batteries that are about to be fully charged, so as to ensure that the release rhythm of fully charged batteries matches the arrival time of the vehicles and shorten the waiting time of the vehicles.

[0055] As an optional embodiment, charging and swapping scheduling is performed on each target battery pack of the target battery swapping station based on the temporal overlap, including: determining the number of vehicles arriving at each time in the arrival time series and the number of available batteries at each time in the available time series; and performing charging and swapping scheduling on each target battery pack of the target battery swapping station based on the temporal overlap, the number of vehicles arriving at each time, and the number of available batteries at each time in the available time series.

[0056] This involves the number of vehicles arriving, which is the total number of vehicles expected to enter the target battery swapping station at the corresponding time in the arrival time series. For example, one vehicle arrives at the 5th minute, and two vehicles arrive simultaneously at the 10th minute, based on the instantaneous energy replenishment demand intensity at each time.

[0057] This involves the number of available batteries, which is the total number of target battery packs available for swapping at the target battery swapping station at the corresponding moment in the available time series. For example, if there are 2 fully charged batteries available at minute 0 (initial available number), and 1 first battery pack reaches full charge at minute 8, the number of available batteries increases to 3 (if 2 fully charged batteries were not used at minute 0). If a battery is used at minute 5, the number of available batteries at minute 8 needs to be reduced by the used part to quantify the instantaneous energy replenishment capacity at each moment.

[0058] Each moment in the arrival time series corresponds one-to-one with each moment in the available time series.

[0059] By determining the number of vehicles arriving at each moment in the arrival time series, the intensity of energy replenishment demand at each time point can be clearly identified. Simultaneously, by determining the number of available batteries at each moment in the availability time series, the energy replenishment supply capacity at each time point can be clearly identified. Based on this, and combined with the supply and demand levels reflected by the time series overlap, it is possible to identify which time points have supply gaps (the number of arriving vehicles exceeds the number of available batteries) and which time points have good supply-demand matching. Since the specific time and extent of the supply gap have been identified, targeted charging and swapping scheduling can be implemented for each target battery pack. Charging power can be prioritized for battery packs that can complete charging before the gap occurs, and available batteries can be prioritized for matching to vehicles with the closest arrival times. This avoids vehicles blindly waiting due to resource mismatch and achieves a dynamic balance between supply and demand over time.

[0060] As an optional embodiment, based on the temporal overlap, the number of vehicles arriving at each time point, and the number of available batteries at each time point in the available time series, charging and battery swapping scheduling is performed on each target battery pack of the target battery swapping station. This includes: determining whether the temporal overlap is less than an overlap threshold to obtain an overlap determination result; determining whether the quantity deviation at each time point is greater than a deviation threshold to obtain a deviation determination result, wherein the quantity deviation is the deviation between the number of vehicles arriving at the corresponding time point and the number of available batteries; and based on the overlap determination result and the deviation determination result, charging and battery swapping scheduling is performed on each target battery pack of the target battery swapping station.

[0061] This includes an overlap threshold, which is a pre-set critical value used to determine whether the timing match between the battery and the vehicle meets the scheduling requirements.

[0062] This involves the overlap determination result, which is a logical judgment result obtained by comparing the temporal overlap degree with the overlap threshold. For example, the overlap determination result can be "less than the overlap threshold" or "not less than the overlap threshold" (i.e., greater than or equal to the overlap threshold), to indicate whether the alignment degree between the vehicle arrival data and the data at the corresponding time is within an acceptable range.

[0063] This involves quantity deviation, which is the difference between the number of vehicles arriving and the number of available batteries at any given time. Specifically, it's the difference between the number of arriving vehicles and the number of available batteries. For example, if 3 vehicles arrive at a given time and 1 battery is available, the quantity deviation is 2. When the difference between the number of arriving vehicles and the number of available batteries is negative, it indicates that the battery pack has met the vehicle's recharging needs at that time, and the vehicle does not need to wait or be rescheduled.

[0064] This involves a deviation threshold, which is a preset critical value used to determine whether the quantity deviation exceeds the acceptable range. When the quantity deviation is greater than the deviation threshold, it means that the vehicle waiting time has exceeded the tolerance range.

[0065] This involves the deviation determination result, which is a logical judgment result obtained by comparing the quantity deviation with the deviation threshold. For example, the deviation determination result can be "greater than the deviation threshold" or "not greater than the deviation threshold" (i.e., less than or equal to the deviation threshold).

[0066] By comparing the temporal overlap with the overlap threshold to obtain the overlap determination result, the matching quality between the battery availability period and the vehicle arrival period can be accurately identified. Then, by comparing the quantity deviation at each time with the deviation threshold to obtain the deviation determination result, the degree of imbalance between energy supply and demand in the same period can be clearly determined. By combining the two determination results to carry out charging and swapping scheduling, the battery charging and swapping allocation strategy can be adjusted in a targeted manner according to the time matching situation and the supply and demand gap. This resolves the problem of mismatch between battery supply rhythm and vehicle demand rhythm, and the imbalance between supply and demand quantity, effectively shortens vehicle waiting time, and improves the utilization efficiency of charging and swapping resources in the station.

[0067] As an optional embodiment, based on the overlap determination result and the deviation determination result, charging and swapping scheduling is performed on each target battery pack of the target battery swapping station, including: when the overlap determination result and the deviation determination result meet a first predetermined condition, determining multiple time matching degrees corresponding to each target battery pack, wherein the multiple time matching degrees are the degree of closeness between the available time of the corresponding target battery pack and the arrival time corresponding to each vehicle; and according to the multiple time matching degrees corresponding to each target battery pack, charging and swapping scheduling is performed on each target battery pack of the target battery swapping station, wherein the first predetermined condition includes at least one of the following: the overlap determination result is that the temporal overlap degree is less than the overlap threshold, and the deviation determination result is that the quantity deviation corresponding to each time is greater than the deviation threshold.

[0068] This involves a first predetermined condition, which is a pre-set scheduling method trigger condition used to trigger fine-grained time-matching scheduling. The first predetermined condition includes at least one of the following: the overlap determination result is that the temporal overlap is less than the overlap threshold (indicating that there is a significant mismatch between the charging resource release rhythm and the vehicle arrival rhythm on the time axis), and the deviation determination result is that the quantity deviation corresponding to each time is greater than the deviation threshold (indicating that the energy supply gap between the number of vehicles arriving and the number of available batteries at the same time exceeds the tolerance range).

[0069] This involves time-matching degree, which is used to quantify the proximity between the available time of the corresponding target battery pack and the arrival time of the corresponding vehicle.

[0070] When the time sequence overlap is less than the overlap threshold or the quantity deviation is greater than the deviation threshold, it indicates a time mismatch between the battery's full-charge release time and the vehicle's arrival time. In this case, by calculating the time difference between the available time of each battery and the arrival time of each vehicle, the battery with the smallest time difference is allocated to the corresponding vehicle. This allows the battery release rhythm to proactively approximate the vehicle's arrival rhythm, thereby avoiding waiting caused by time mismatch and shortening the battery swapping time per vehicle.

[0071] As an optional embodiment, charging and swapping scheduling is performed on each target battery pack of the target battery swapping station based on temporal overlap, including: determining the predicted waiting time corresponding to each vehicle based on temporal overlap; identifying the target vehicle from among the vehicles, wherein the target vehicle is the vehicle among the vehicles whose predicted waiting time is greater than a predetermined waiting time; determining the station distance between the target battery swapping station and neighboring battery swapping stations, wherein neighboring battery swapping stations are other battery swapping stations whose route distance from the target battery swapping station is less than a distance threshold; determining the entry time of the target vehicle to the neighboring battery swapping station, and the waiting time for battery swapping at the neighboring battery swapping station at the entry time; and performing charging and swapping scheduling on each target battery pack of the target battery swapping station based on the entry time, the waiting time for battery swapping, and the predicted waiting time corresponding to each vehicle.

[0072] This includes predicting the waiting time, which is the estimated time that a vehicle will need to wait in line at the target battery swapping station, used to identify vehicles facing long waiting times.

[0073] This involves target vehicles, which are the vehicles whose predicted waiting time is longer than the predetermined waiting time.

[0074] This involves nearby battery swapping stations, which are other battery swapping stations whose route distance from the target battery swapping station is less than a distance threshold, and are used to provide alternative charging sites for the target vehicle.

[0075] This includes the entry time, which is the estimated arrival time of the target vehicle from its current location to the nearest battery swapping station, used to assess the battery swapping time of the target vehicle at the alternative stations.

[0076] This includes the waiting time for battery swapping, which is the estimated time that the target vehicle needs to queue at a nearby battery swapping station at the moment of entry, used to quantify the service efficiency of alternative stations.

[0077] By filtering out target vehicles with excessively long wait times based on predicted waiting times, and then comprehensively comparing the arrival times and waiting times of nearby battery swapping stations, vehicles with long wait times can be proactively diverted to alternative stations, thereby avoiding their aimless lingering and relieving the scheduling pressure on current stations, thus shortening the average battery swapping completion time for all vehicles.

[0078] As an optional embodiment, determining the total number of vehicles entering the target battery swapping station within the target time window includes: acquiring historical entry data of the target battery swapping station and vehicle driving data in the target route, wherein the vehicle driving data includes vehicle location data and the target route is the traffic route corresponding to the target battery swapping station; and determining the total number of vehicles entering the target battery swapping station within the target time window based on the historical entry data and the vehicle driving data.

[0079] This includes historical entry data, which is the number of vehicles entering the target battery swapping station over a period of time and the corresponding statistical information at the time points. For example, the historical entry data includes the distribution of the number of vehicles entering during different time periods (such as weekdays, weekends, and holidays), which is used to predict the arrival trend of vehicles in future time windows.

[0080] This involves vehicle driving data, which is real-time location dynamic information collected from vehicles in motion. For example, the vehicle driving data includes vehicle location data (such as vehicle GPS coordinates), traffic flow data, driving direction, vehicle speed, etc.

[0081] This involves a target route, which is a transportation route corresponding to the target battery swapping station. For example, the target route includes the road where the battery swapping station is located and the connecting road sections within a certain range upstream and downstream, used to screen out vehicles that may enter the target battery swapping station.

[0082] Historical arrival data reflects long-term arrival patterns, while real-time vehicle travel data reflects current travel trends. Combining the two can mutually calibrate and complement each other (e.g., using historical patterns to compensate for the sparsity of real-time data, and using real-time location to correct deviations in historical patterns), thereby more accurately determining the actual number of vehicles that will arrive within future time windows and providing a reliable vehicle demand base for subsequent scheduling.

[0083] Based on the above embodiments and optional embodiments, an optional implementation method is provided, which is described in detail below.

[0084] In related technologies, electric vehicle (new energy vehicle) refueling methods are mainly divided into charging mode and battery swapping mode. With the increasing demand for refueling efficiency, battery swapping mode has attracted attention due to its fast refueling speed (usually 1-5 minutes). In order to ensure that vehicles can quickly complete refueling and improve the operational efficiency of stations, it is necessary to schedule the charging and swapping of battery packs in the battery swapping station. However, in related technologies, there is a technical problem that unreasonable scheduling of charging and swapping of battery packs in the battery swapping station leads to high vehicle waiting time costs.

[0085] For example, in related technologies, users can reserve a battery swapping slot in advance and lock a fully charged battery through a corresponding application (APP) to ensure that a battery is available for swapping upon arrival. Although the battery reservation and locking mode solves the problem of "no battery upon arrival" to some extent, the following issues still exist:

[0086] 1) Static reservations cannot cope with dynamic changes: Battery reservation is essentially a "static operation." The user's actual arrival time, the charging progress of batteries in the station, and the queuing situation are all dynamically changing, but the reserved batteries do not adjust with these changes. If the user arrives early, the reserved batteries may not be fully charged; if the user arrives late, fully charged batteries are idle while other users wait in line, resulting in wasted resources.

[0087] 2) The charging process is a scheduling blind spot: The scheduling logic of existing battery swapping stations only focuses on the number of fully charged batteries and their state of health (SOH), lacking dynamic awareness and proactive intervention regarding when batteries in the charging process will become fully charged. Charging strategies (such as power allocation and charging priority) are fixed and do not adjust according to changes in user arrival time. This leads to a disconnect between the release rhythm of charging resources and the arrival rhythm of user demand.

[0088] 3) "Battery lock" rather than "time lock": The battery lock reservation solves the problem of whether there is a battery, but it fails to solve the problem of coordinating when a battery is available, when to charge it, and when to replace it. During peak hours, even if there is a fully charged battery, users may still have to wait for a long time due to queuing and unreasonable scheduling.

[0089] 4) Lack of two-way closed-loop scheduling: In related technologies, the charging system and the battery swapping system operate independently, and there is no dynamic closed loop between the user end and the station end based on the time matching degree. Therefore, it is impossible to actively adjust the charging power, recommend battery swapping, or push alternative solutions to users based on the matching degree between the charging progress and the user's arrival time.

[0090] There is currently no effective solution to the above problems.

[0091] In view of this, an optional embodiment of the present invention provides a method for coordinated scheduling of battery pack charging and swapping at a battery swapping station, which can effectively solve the above-mentioned technical problems.

[0092] Figure 2 This is a schematic diagram of the battery pack charging and swapping collaborative scheduling process framework of a battery swapping station in an optional embodiment of the present invention. Figure 3 This is a schematic diagram of the scheduling framework module in an optional embodiment of the present invention, such as... Figure 2 and Figure 3 As shown, the entire scheduling process framework mainly includes four modules:

[0093] Charging system module: includes at least one charging pile or charging stack for receiving and charging the battery pack from the battery swapping system module, and for receiving charging requests from the vehicle.

[0094] Battery swapping system module: includes a battery pack storage compartment, a battery swapping device, and at least one battery swapping station, used to store charged battery packs and perform battery swapping operations on the vehicle.

[0095] Charging time sensing module: Connects the charging system module and the battery swapping system module, obtains charging progress data in real time and predicts the remaining charging completion time of each battery pack (i.e., the first battery pack); at the same time, it obtains the state of charge data of each battery pack in the battery swapping system module and predicts the available battery swapping time of each fully charged battery pack.

[0096] Collaborative control module: It communicates with the above three modules, dynamically generates a joint scheduling strategy based on the predicted data output by the charging time sensing module, and sends it to the charging system and the battery swapping system for execution.

[0097] S1, determine the total number of vehicles entering the target battery swapping station within the target time window;

[0098] Specifically, determining the total number of vehicles entering the target battery swapping station within the target time window includes: obtaining historical entry data of the target battery swapping station and vehicle driving data along the target route, wherein the vehicle driving data includes vehicle location data and the target route is the traffic route corresponding to the target battery swapping station; based on the historical entry data and the vehicle driving data, determining the total number of vehicles entering the target battery swapping station within the target time window.

[0099] For example, Figure 4 This is a schematic diagram of the internal structural framework of the charging time sensing module in an optional embodiment of the present invention, as shown below. Figure 4 As shown. The charging time sensing module contains four units:

[0100] Charging progress tracking unit: Real-time monitoring of the current state of charge (SOC), charging current, battery temperature, and charging time of each charging battery pack.

[0101] Charging time prediction unit: Dynamically predicts the remaining charging time for each battery pack to reach a specified SOC threshold (e.g., 95%) based on monitoring data. For example, if a battery pack currently has an SOC of 35% (denoted as SOC35%), it is estimated that approximately 25 minutes will be needed based on the non-linear charging curve.

[0102] Battery swapping wait prediction unit: Based on the number of fully charged battery packs and the predicted remaining charging time mentioned above, calculate the expected availability time of the next available fully charged battery pack.

[0103] User arrival prediction unit: Based on historical battery swapping vehicle data and real-time vehicle location data (such as GPS), predict the number of vehicles entering the battery swapping station within a future time window (such as the next 30 minutes) and their expected energy replenishment needs.

[0104] The total number of vehicles entering the target battery swapping station within the target time window is determined by the user arrival prediction unit. Specifically, the user arrival prediction unit predicts the number of vehicles entering the battery swapping station within the target time window, i.e., the future time window (e.g., the next 30 minutes), and their respective expected energy replenishment needs, based on historical battery swapping vehicle data and real-time vehicle location data (such as GPS data).

[0105] S2, determine the arrival time sequence of each vehicle under the total number of vehicles, wherein the arrival time sequence includes the arrival time of each vehicle arranged in chronological order within the target time window;

[0106] For example, after obtaining the number of vehicles entering the battery swapping station and their expected energy replenishment needs based on the user arrival prediction unit, these expected arrival times are arranged in chronological order to obtain an arrival time series.

[0107] S3, determine the available time series corresponding to each target battery pack in the target battery swapping station within the target time window;

[0108] Specifically, determining the available time sequence corresponding to each target battery pack in the target battery swapping station within the target time window includes: when each target battery pack includes each first battery pack and each second battery pack, obtaining the charging progress data corresponding to each first battery pack in the target battery swapping station, and the number of battery packs corresponding to each second battery pack, wherein each first battery pack is a battery pack that is being charged, and each second battery pack is a battery pack that is fully charged; based on the charging progress data corresponding to each first battery pack and the number of battery packs corresponding to each second battery pack, determining the available time sequence corresponding to each target battery pack in the target battery swapping station within the target time window.

[0109] For example, the available time of each first battery pack is determined by a charging progress tracking unit and a charging time prediction unit, while the number of each second battery pack is counted by a battery swapping waiting prediction unit and its available time is determined. Specifically, the charging progress tracking unit monitors the current state of charge (SOC) of each charging battery pack in real time, and the charging time prediction unit dynamically predicts the remaining charging completion time of each charging battery pack when it reaches a specified SOC threshold based on the monitoring data, using these remaining charging completion times as the available time (i.e., the time when it can be used) of each first battery pack; the battery swapping waiting prediction unit counts the number of fully charged second battery packs and uses their current time as the available time of each second battery pack; the available time of each first battery pack and the available time of each second battery pack are combined and arranged in chronological order to obtain the available time sequence corresponding to each target battery pack within the target time window.

[0110] Specifically, based on the charging progress data corresponding to each first battery pack and the number of battery packs corresponding to each second battery pack, the available time sequence corresponding to each target battery pack in the target battery swapping station within the target time window is determined, including: sorting each first battery pack according to the charging progress data corresponding to each first battery pack to obtain the charging priority of each first battery pack; determining the charging power corresponding to each first battery pack based on the charging priority of each first battery pack; charging the corresponding first battery pack according to the charging power corresponding to each first battery pack and determining the full charge time corresponding to each first battery pack; and determining the available time sequence corresponding to each target battery pack in the target battery swapping station within the target time window based on the full charge time corresponding to each first battery pack and the number of battery packs corresponding to each second battery pack.

[0111] Based on the above, the charging priority is obtained by sorting each first battery pack according to the charging progress data, which can identify which battery packs are closer to full charge. Differential charging power is allocated based on this priority, allowing battery packs that are close to full charge to receive higher power and further accelerate the charging speed, thus bringing their full charge time forward. Since the earlier full charge time directly determines the order in which each battery pack enters the available time sequence, combining the number of fully charged second battery packs to generate an available time sequence allows the battery's available time to be proactively adjusted to align with the vehicle's arrival time. Since the time difference between the battery's available time and the vehicle's arrival time directly determines the vehicle's waiting time at the station, compressing this time difference using the above method can avoid the vehicle arriving at the station without any batteries available or experiencing long waiting times, thereby reducing the vehicle's waiting time costs.

[0112] The available time series includes the time when each target battery pack reaches the available state, and the available state includes the fully charged state.

[0113] S4 will arrive at the time series and match it with the available time series to determine the time series overlap.

[0114] For example, each available time series corresponds one-to-one with a moment in the arrival time series; that is, they are two time-aligned sequences. The collaborative control module includes a time alignment unit, a scheduling decision unit, and an alternative scheme recommendation unit. Figure 5 This is a schematic diagram illustrating the working principle of the collaborative control module in an optional embodiment of the present invention, such as... Figure 5 As shown, the time alignment unit aligns the predicted remaining charging completion time of each charging battery pack output by the charging time sensing module with the expected arrival time of the vehicle output by the user arrival prediction unit to generate a charging and discharging time sequence diagram.

[0115] For example:

[0116] The expected completion time for each battery pack is marked on the charging completion timeline. ), thus obtaining usable time series;

[0117] The expected arrival time of future vehicles is marked on the battery swap arrival timeline. ), thus obtaining the arrival time series.

[0118] in, These are the expected completion times (i.e., available time) for the first target battery pack, the second target battery pack, and the third target battery pack, respectively. These are the expected arrival times of the first vehicle, the second vehicle, and the third vehicle, respectively.

[0119] The time alignment unit calculates the length of the overlap segment between the two time axes as the time matching degree. The longer the overlap segment, the better the release rhythm of charging resources matches the arrival rhythm of user demand; the shorter the overlap segment, the more serious the mismatch.

[0120] S5, based on the time overlap, performs charging and swapping scheduling for each target battery pack at the target battery swapping station.

[0121] Specifically, based on the temporal overlap, charging and swapping scheduling is performed separately for each target battery pack of the target battery swapping station, including: determining the number of vehicles arriving at each time in the arrival time series and the number of available batteries at each time in the available time series; and based on the temporal overlap, the number of vehicles arriving at each time and the number of available batteries at each time in the available time series, charging and swapping scheduling is performed separately for each target battery pack of the target battery swapping station.

[0122] Specifically, based on the temporal overlap, the number of vehicles arriving at each time point, and the number of available batteries at each time point in the available time series, charging and battery swapping scheduling is performed for each target battery pack at the target battery swapping station. This includes: determining whether the temporal overlap is less than an overlap threshold to obtain an overlap determination result; determining whether the quantity deviation at each time point is greater than a deviation threshold to obtain a deviation determination result, where the quantity deviation is the deviation between the number of vehicles arriving and the number of available batteries at the corresponding time point; and based on the overlap determination result and the deviation determination result, charging and battery swapping scheduling is performed for each target battery pack at the target battery swapping station.

[0123] Specifically, based on the overlap determination result and the deviation determination result, charging and swapping scheduling is performed on each target battery pack of the target battery swapping station, including: under the condition that the overlap determination result and the deviation determination result meet the first predetermined condition, determining multiple time matching degrees corresponding to each target battery pack, wherein the multiple time matching degrees are the closeness between the available time of the corresponding target battery pack and the arrival time corresponding to each vehicle; according to the multiple time matching degrees corresponding to each target battery pack, charging and swapping scheduling is performed on each target battery pack of the target battery swapping station, wherein the first predetermined condition includes at least one of the following: the overlap determination result is that the temporal overlap degree is less than the overlap threshold, and the deviation determination result is that the quantity deviation corresponding to each time is greater than the deviation threshold.

[0124] Specifically, based on temporal overlap, charging and swapping scheduling is performed separately for each target battery pack at the target battery swapping station, including: determining the predicted waiting time for each vehicle based on temporal overlap; identifying the target vehicle from among the vehicles, wherein the target vehicle is the vehicle whose predicted waiting time is longer than the predetermined waiting time; determining the distance between the target battery swapping station and neighboring battery swapping stations, wherein neighboring battery swapping stations are other battery swapping stations whose route distance from the target battery swapping station is less than a distance threshold; determining the entry time of the target vehicle to the neighboring battery swapping station and the waiting time for battery swapping at the neighboring battery swapping station at the entry time; and performing charging and swapping scheduling separately for each target battery pack at the target battery swapping station based on the entry time, the waiting time for battery swapping, and the predicted waiting time for each vehicle.

[0125] For example, the scheduling decision unit determines whether there is a shortage of energy replenishment resources based on the charge / discharge timing diagram and the matching degree (e.g., when the length of the overlapping section is less than a certain threshold, or when the number of future vehicles exceeds the number of available fully charged battery packs). Then, the following joint scheduling strategy is generated:

[0126] Charging priority sorting: Based on the predicted remaining charging completion time from shortest to longest, charging power is allocated to battery packs that are about to be completed in order to release fully charged battery packs to serve vehicles as soon as possible.

[0127] Battery swapping matching recommendation: When there are no fully charged batteries available at the station, based on the matching degree, it is recommended to use the battery pack that is about to be completed and is closest to the vehicle's arrival time for battery swapping to avoid vehicle waiting.

[0128] Dynamic charging power adjustment: When resources are scarce, the available charging power is concentrated on a few battery packs that are about to finish, thus shortening the overall waiting time.

[0129] When the matching degree is lower than a preset threshold (e.g., the overlap section length is less than 5 minutes, or the predicted waiting time is more than 10 minutes), the alternative solution recommendation unit recommends alternative solutions to the user, such as switching to a nearby battery swapping station, or temporarily charging to a level where the user can drive to a backup battery swapping station.

[0130] Furthermore, the time matching degree calculation can be replaced with fuzzy logic evaluation: instead of using time-series aligned length calculation, the "charging completion time" and "vehicle arrival time" are fuzzified into "very fast, moderate, slow" and "urgent, normal, not urgent," respectively, and a scheduling strategy is generated through a fuzzy rule base. User arrival prediction can be implemented based on the reservation system. Users need to reserve their battery swap time in advance on the corresponding reservation system, and then scheduling is carried out according to the reservation time, without the need for GPS prediction to assist input. Charging power adjustment can be replaced with charge-discharge energy storage coordination. Energy storage batteries are added to the battery swap station. When the charging power is insufficient, the energy storage batteries discharge to supplement the charging, thereby accelerating the charging process of specific battery boxes. And, alternative solution recommendation can be replaced with automatic order diversion: when the matching degree is lower than the threshold, the user's order is automatically assigned to a nearby battery swap station and a navigation route is pushed, without the need for the user to manually select.

[0131] The following description, based on the steps outlined above and with specific examples, provides further details.

[0132] St101: The charging time sensing module acquires the charging progress data of each battery pack in the charging system module and the state of charge data of each battery pack in the battery swapping system module, and predicts the remaining charging completion time of each battery pack; at the same time, it predicts the number of vehicles entering the battery swapping station in the future time window and their expected energy replenishment needs.

[0133] St102: The collaborative control module generates a charging and discharging timing diagram based on the predicted data, aligns the predicted remaining charging completion time with the vehicle's expected arrival time, and calculates the time matching degree.

[0134] St103: The collaborative control module generates a joint scheduling strategy (charging priority ranking and battery swapping matching recommendation) based on the charging and discharging timing diagram and matching degree.

[0135] St104: The collaborative control module will distribute the joint scheduling strategy to the charging system module and the battery swapping system module for execution.

[0136] St105 (optional): When the matching degree is lower than the preset threshold, the alternative solution recommendation unit generates alternative energy replenishment solutions and reminds the user.

[0137] For example, the battery swapping station has five battery packs, three of which are currently charging (SOC: 35%, 60%, and 82% respectively), and two are fully charged and ready for use. The total charging power of the charging system module is 120kW. The charging time sensing module predicts that the battery pack with an SOC of 82% will need 8 minutes to reach 95%, the one with an SOC of 60% will need 18 minutes, and the one with an SOC of 35% will need 25 minutes. Simultaneously, the user arrival prediction unit predicts that two electric vehicles will enter the battery swapping station within the next 15 minutes, with one of them arriving within 5 minutes.

[0138] In response, the collaborative control module generated a charging and discharging timing diagram. After calculating the matching degree, it found that vehicles arriving within 5 minutes could not be matched with any battery packs (the earliest completion time was 8 minutes), indicating resource scarcity. The scheduling decision unit immediately adjusted the charging priority: increasing the charging power of battery packs with 82% SOC from 40kW to 60kW, enabling them to complete charging within 7 minutes. Simultaneously, it recommended alternative options to users arriving within 5 minutes: wait 2 minutes for battery swapping, or temporarily charge for 5 minutes and then proceed to a backup station, achieving dynamic matching and proactive intervention.

[0139] Based on the above steps, users do not need to make an appointment in advance. Through real-time sensing and scheduling, the battery's full charge release rhythm actively approaches the user's arrival rhythm. Compared with related technologies, the user's waiting time is reduced from 8 minutes to 2 minutes, and alternative solutions are provided to avoid blind waiting.

[0140] Furthermore, if the battery reservation locking mode in the relevant technology is adopted: User A reserves a fully charged battery in advance, but User A actually arrives 5 minutes earlier than the reserved time. At this time, the locked fully charged battery may still be charging, causing User A to wait. In other words, it is impossible to actively adjust the charging strategy to adapt to User A's early arrival.

[0141] This solution eliminates the need for users to pre-book and lock in a specific battery. When it detects that user A will arrive in 5 minutes, and the earliest available battery at the station (which originally required 8 minutes to fully charge) cannot be directly matched, the scheduling decision unit proactively intervenes, increasing the charging power of the 82% SOC battery from 40kW to 60kW, reducing its full charge time to 7 minutes. After arriving in 5 minutes, user A only needs to wait 2 minutes to swap batteries.

[0142] The above optional implementation methods can achieve at least the following beneficial effects:

[0143] (1) Compared with related technologies, the present invention quantifies the total number of vehicles in the target time window to quantify the total energy replenishment demand, generates an arrival time sequence arranged in time order to characterize the time distribution of the demand side, generates an available time sequence of each battery pack to characterize the resource release rhythm of the supply side, and then aligns the two time sequences and calculates the time overlap, so that the matching degree between the release time of charging resources and the arrival time of user demand is quantified into a calculable index. Since the time overlap directly reflects the degree of mismatch between resource supply and demand in the time dimension, it is possible to carry out differentiated charging and swapping scheduling for each battery pack based on the overlap, realize the priority allocation of charging power to the battery pack that is about to be completed to accelerate the release of fully charged resources, and prioritize recommend the available battery pack with the closest arrival time for swapping matching, thereby solving the problem of resource waste and vehicle waiting caused by static reservation in the existing battery lock mode that cannot cope with dynamic changes, and achieving the technical effect of actively approaching the vehicle arrival rhythm with the charging release rhythm. In this way, it solves the technical problem in related technologies that when the battery is charged and swapped in the target swapping station, the charging and swapping scheduling is unreasonable, resulting in high vehicle waiting time costs.

[0144] (2) Compared with related technologies, this invention obtains charging priority by sorting each first battery pack according to charging progress data, which can identify which battery packs are closer to full charge. Based on this priority, differentiated charging power is allocated, so that the battery packs that are almost fully charged receive higher power and the charging speed is further accelerated, thereby bringing forward the time when these battery packs are fully charged. Since the advance of the time when the battery is fully charged directly determines the order in which each battery pack enters the available time sequence, the available time sequence is generated together with the number of fully charged second battery packs, which can make the battery available time actively adjusted to the vehicle arrival time. Since the time difference between the battery available time and the vehicle arrival time directly determines the vehicle's waiting time at the station, compressing this time difference in the above way can avoid the vehicle arriving at the station without any batteries available or waiting for a long time, thereby reducing the vehicle's waiting time cost.

[0145] (3) Compared with related technologies, this invention uses a charging time sensing module to dynamically predict the charging completion time as the main decision variable for joint scheduling, aligning it with the user's arrival time. This is the core difference from the static "reservation-based battery locking" mode in related technologies. Furthermore, by using a charging and discharging time sequence diagram and calculating the time matching degree, the predicted charging completion time and the vehicle's expected arrival time are plotted on two time axes respectively, and the length of the overlapping segment is calculated as the matching degree, providing an intuitive quantitative evaluation method that does not require complex formulas. In addition, the joint scheduling strategy based on the time matching degree includes charging priority sorted by the predicted remaining charging completion time, battery swapping matching recommendation based on the matching degree, and dynamic adjustment of charging power, so that the battery's full-charge release rhythm actively approaches the user's arrival rhythm, shortening the average waiting time of the vehicle and improving the utilization rate of charging resources. Moreover, by setting up an alternative solution recommendation mechanism, when the matching degree is lower than the threshold, alternative energy replenishment solutions (switching to a battery swapping station or temporary charging) are actively pushed to the user, forming a closed loop of "prediction → scheduling → user intervention".

[0146] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, because according to the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0147] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to 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 the present invention, or the part that contributes to the prior art, can be embodied in the form of a 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 device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0148] Example 2

[0149] According to embodiments of the present invention, an apparatus for implementing the above-described battery pack charging and swapping coordinated scheduling method for battery swapping stations is also provided. Figure 6 This is a structural block diagram of a battery pack charging and swapping coordinated scheduling device for a battery swapping station according to an embodiment of the present invention, as shown below. Figure 6As shown, the device includes: a first determining module 602, a second determining module 604, a third determining module 606, a fourth determining module 608, and a fifth determining module 610. The device will be described in detail below.

[0150] The first determining module 602 is used to determine the total number of vehicles entering the target battery swapping station within the target time window.

[0151] The second determining module 604 is connected to the first determining module 602 and is used to determine the arrival time sequence of each vehicle under the total number of vehicles. The arrival time sequence includes the arrival times of each vehicle arranged in chronological order within the target time window.

[0152] The third determining module 606 is connected to the second determining module 604 and is used to determine the available time sequence corresponding to each target battery pack in the target battery swapping station within the target time window.

[0153] The fourth determining module 608, connected to the third determining module 606, is used to match the arriving time series with the available time series to determine the time series overlap.

[0154] The fifth determining module 610, connected to the fourth determining module 608, is used to perform charging and swapping scheduling for each target battery pack of the target battery swapping station based on the time overlap.

[0155] It should be noted that the first determining module 602, the second determining module 604, the third determining module 606, the fourth determining module 608, and the fifth determining module 610 mentioned above correspond to steps S102 to S110 in the battery pack charging and swapping coordinated scheduling method for implementing a battery swapping station. The instances and application scenarios implemented by multiple modules and their corresponding steps are the same, but are not limited to the content disclosed in the above embodiment 1.

[0156] Example 3

[0157] According to another aspect of the present invention, an electronic device is also provided, comprising: a processor; and a memory for storing processor-executable instructions, wherein the processor is configured to execute instructions to implement the battery pack charging and swapping coordinated scheduling method of any of the above-described battery swapping stations.

[0158] Example 4

[0159] According to another aspect of the present invention, a computer-readable storage medium is also provided, which, when the instructions in the computer-readable storage medium are executed by the processor of an electronic device, enables the electronic device to perform the battery pack charging and swapping coordinated scheduling method of any of the above-described battery swapping stations.

[0160] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0161] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0162] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0163] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0164] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0165] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0166] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for coordinated scheduling of battery pack charging and swapping at a battery swapping station, characterized in that, include: Determine the total number of vehicles entering the target battery swapping station within the target time window; Determine the arrival time sequence for each vehicle under the total number of vehicles, wherein the arrival time sequence includes the arrival times of each vehicle arranged in chronological order within the target time window; Determine the available time sequence corresponding to each target battery pack in the target battery swapping station within the target time window; The arrival time series is matched with the available time series to determine the time series overlap. Based on the time overlap, charging and swapping scheduling is performed on each target battery pack of the target battery swapping station.

2. The method according to claim 1, characterized in that, The determination of the available time sequence corresponding to each target battery pack in the target battery swapping station within the target time window includes: When each target battery pack includes each first battery pack and each second battery pack, the charging progress data corresponding to each first battery pack in the target battery swapping station and the number of battery packs corresponding to each second battery pack are obtained, wherein each first battery pack is a battery pack that is being charged and each second battery pack is a battery pack that is fully charged. Based on the charging progress data corresponding to each of the first battery packs and the number of battery packs corresponding to each of the second battery packs, the available time sequence corresponding to each target battery pack in the target battery swapping station within the target time window is determined.

3. The method according to claim 2, characterized in that, The step of determining the available time sequence of each target battery pack in the target battery swapping station within the target time window, based on the charging progress data corresponding to each of the first battery packs and the number of battery packs corresponding to each of the second battery packs, includes: According to the charging progress data corresponding to each first battery pack, the first battery packs are sorted to obtain the charging priority of each first battery pack; Based on the charging priority of each first battery pack, the charging power corresponding to each first battery pack is determined. According to the charging power corresponding to each first battery pack, the corresponding first battery pack is charged, and the full charge time corresponding to each first battery pack is determined. Based on the full charge time corresponding to each of the first battery packs and the number of battery packs corresponding to each of the second battery packs, the available time sequence corresponding to each target battery pack in the target battery swapping station within the target time window is determined.

4. The method according to claim 1, characterized in that, The step of scheduling charging and swapping for each target battery pack at the target battery swapping station based on the time overlap includes: Determine the number of vehicles arriving at each time point in the arrival time series, and the number of available batteries at each time point in the available time series; Based on the time overlap, the number of vehicles arriving at each time point, and the number of available batteries at each time point in the available time series, charging and battery swapping scheduling is performed for each target battery pack at the target battery swapping station.

5. The method according to claim 4, characterized in that, Based on the time overlap, the number of vehicles arriving at each time point, and the number of available batteries at each time point in the available time series, the charging and swapping scheduling for each target battery pack at the target battery swapping station is performed, including: Determine whether the temporal overlap is less than the overlap threshold to obtain the overlap determination result; Determine whether the quantity deviation at each time point is greater than the deviation threshold to obtain the deviation determination result, wherein the quantity deviation is the deviation between the number of vehicles arriving and the number of available batteries at the corresponding time point; Based on the overlap determination result and the deviation determination result, charging and swapping scheduling is performed for each target battery pack of the target battery swapping station.

6. The method according to claim 5, characterized in that, The step of scheduling charging and swapping for each target battery pack at the target battery swapping station based on the overlap determination result and the deviation determination result includes: If the overlap determination result and the deviation determination result are within the first predetermined condition, a plurality of time matching degrees corresponding to each of the target battery packs are determined, wherein the plurality of time matching degrees are the degree of closeness between the available time of the corresponding target battery pack and the arrival time corresponding to each of the vehicles. According to the matching degree of each target battery pack at multiple time points, the charging and swapping scheduling of each target battery pack at the target battery swapping station is carried out respectively. The first predetermined condition includes at least one of the following: the overlap determination result is that the temporal overlap degree is less than the overlap threshold, and the deviation determination result is that the quantity deviation corresponding to each time point is greater than the deviation threshold.

7. The method according to claim 1, characterized in that, The step of scheduling charging and swapping for each target battery pack at the target battery swapping station based on the time overlap includes: Based on the temporal overlap, the predicted waiting time corresponding to each vehicle is determined; The target vehicle is determined from the vehicles, wherein the target vehicle is the vehicle whose predicted waiting time is longer than the predetermined waiting time. Determine the distance between the target battery swapping station and neighboring battery swapping stations, wherein the neighboring battery swapping stations are other battery swapping stations whose route distance from the target battery swapping station is less than a distance threshold; Determine the entry time of the target vehicle when it arrives at the nearest battery swapping station, and the waiting time for battery swapping at the nearest battery swapping station at the entry time; Based on the arrival time, the waiting time for battery swapping, and the predicted waiting time for each vehicle, charging and swapping scheduling is performed for each target battery pack at the target battery swapping station.

8. The method according to any one of claims 1 to 7, characterized in that, The total number of vehicles entering the target battery swapping station within the defined target time window includes: The historical entry data of the target battery swapping station and the vehicle driving data in the target route are obtained, wherein the vehicle driving data includes vehicle location data and the target route is the traffic route corresponding to the target battery swapping station. Based on the historical entry data and the vehicle driving data, the total number of vehicles entering the target battery swapping station within the target time window is determined.

9. A battery pack charging and swapping coordinated scheduling device for a battery swapping station, characterized in that, include: The first determining module is used to determine the total number of vehicles entering the target battery swapping station within the target time window; The second determining module is used to determine the arrival time sequence of each vehicle under the total number of vehicles, wherein the arrival time sequence includes the arrival times of each vehicle arranged in chronological order within the target time window; The third determining module is used to determine the available time sequence corresponding to each target battery pack in the target battery swapping station within the target time window; The fourth determining module is used to match the arrival time series with the available time series to determine the time series overlap. The fifth determining module is used to perform charging and swapping scheduling for each target battery pack of the target battery swapping station based on the time overlap.

10. An electronic device, characterized in that, include: processor; Memory used to store the processor's executable instructions; The processor is configured to execute the instructions to implement the battery pack charging and swapping coordinated scheduling method for a battery swapping station as described in any one of claims 1 to 8.

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