A charging device scheduling method and a computing device

Abstract

The embodiment of the application provides a kind of charging equipment scheduling method and computing device, it is related to vehicle charging technical field, at least solve how to reasonably schedule the problem of charging equipment.Method includes: obtaining the charging efficiency of each available charging equipment in the multiple available charging equipment of charging station under different charging demand information, and the charging demand information of the vehicle to be charged;Charging demand information includes charging environment and charging power;Determine the current charging efficiency of each available charging equipment under the charging demand information of the vehicle to be charged, and generate the first scheduling sequence of each available charging equipment according to the current charging efficiency of each available charging equipment;According to the first scheduling sequence, available charging equipment is scheduled for the vehicle to be charged.

Description

Technical Field

[0001] This application relates to the field of vehicle charging technology, and in particular to a charging equipment scheduling method and computing device. Background Technology

[0002] With the increasing popularity of new energy vehicles, charging stations have become an increasingly important energy supply infrastructure. The charging equipment (also known as charging piles) deployed within these stations, as the core equipment, are receiving growing attention for their charging efficiency. Currently, users typically choose charging stations based on their needs, either those closest to the station's entrance / exit or those with ample parking space. This results in varying usage frequencies of the charging equipment within the station, thus affecting the overall charging efficiency of the charging station.

[0003] Therefore, how to rationally schedule multiple charging devices within a charging station is a technical problem that urgently needs to be solved. Summary of the Invention

[0004] This application provides a charging equipment scheduling method and computing device, which at least solves the problem of how to reasonably schedule charging equipment.

[0005] In a first aspect, embodiments of this application provide a charging equipment scheduling method, the method comprising: acquiring the charging efficiency of each available charging equipment in a charging station under different charging demand information, and the charging demand information of a vehicle to be charged; the charging demand information includes the charging environment and charging power; determining the current charging efficiency of each available charging equipment under the charging demand information of the vehicle to be charged, and generating a first scheduling sequence for each available charging equipment based on the current charging efficiency of each available charging equipment; and scheduling available charging equipment for the vehicle to be charged according to the first scheduling sequence.

[0006] In this scheme, by acquiring and comparing the charging efficiency of different available charging devices under specific charging demand information (i.e., the charging demand information of the vehicle to be charged), and generating a first scheduling sequence based on this, it helps to schedule available charging devices with better charging efficiency for the vehicle to be charged, thereby improving the overall energy efficiency of the charging station and realizing the reasonable scheduling of charging devices in the charging station.

[0007] Secondly, when determining the first scheduling sequence, the current charging efficiency of each available charging device can be determined based on the charging demand information, which includes key indicators such as specific charging power and charging environment. This makes the first scheduling sequence more in line with the charging power and charging environment requirements of the vehicles to be charged, avoiding the problem of unreasonable scheduling caused by environmental changes or power differences.

[0008] In some embodiments, a first scheduling sequence for each available charging device is generated based on the current charging efficiency of each available charging device, including: for the first available charging device among the charging devices, obtaining the cumulative thermal power consumption of the first available charging device; the cumulative thermal power consumption includes the thermal power consumption required to charge the vehicle to be charged and the historical thermal power consumption; and generating the first scheduling sequence in descending order of the current charging efficiency of each available charging device when the cumulative thermal power consumption of each available charging device meets the thermal power consumption balance condition.

[0009] In this embodiment, by introducing a forward-looking predictive index of cumulative thermal power consumption (including historical thermal power consumption and thermal power consumption required for this charging) for each available charging device, the loss of available charging devices can be predicted before the scheduling method is determined by combining the predicted thermal power consumption of this charging and historical thermal power consumption. This avoids the problem of uneven loss of available charging devices in the charging station caused by frequently scheduling the same one or more available charging devices.

[0010] Secondly, the first scheduling sequence, determined by charging efficiency, is generated only when the cumulative thermal power consumption of each available charging device meets the thermal power consumption balance condition. This helps to rationally schedule available charging devices based on charging efficiency on the basis of loss balance.

[0011] In some embodiments, the method further includes: when the cumulative thermal power consumption of each available charging device does not meet the thermal power consumption balance condition, generating a second scheduling sequence of each available charging device in ascending order of the cumulative thermal power consumption of each available charging device; and scheduling available charging devices for the vehicle to be charged according to the second scheduling sequence.

[0012] In this embodiment, when the cumulative thermal power consumption of each available charging device does not meet the thermal power consumption balance condition, a second scheduling sequence can be generated according to the cumulative thermal power consumption of each available charging device. This helps to reasonably schedule available charging devices based on the cumulative thermal power consumption on the basis of uneven loss, thereby making each available charging device tend to achieve loss balance.

[0013] In some embodiments, the thermal power equalization condition includes the cumulative thermal power difference of each available charging device being less than a thermal power threshold.

[0014] In this embodiment, the cumulative thermal power consumption range can directly quantify the aging dispersion of each available charging device. The cumulative thermal power consumption range can measure the dispersion (i.e., the range) of all charging devices in the charging station in terms of loss (also known as aging), thereby providing a basis for subsequently determining the scheduling sequence of available charging devices.

[0015] In some embodiments, the thermal power consumption threshold is determined based on the average thermal power consumption of each available charging device within a preset sub-cycle; the average thermal power consumption within the preset sub-cycle is obtained by dividing the total average thermal power consumption of each available charging device over its entire life cycle into equal parts according to the number of sub-cycles.

[0016] In this embodiment, the total thermal power consumption over the entire life cycle can be converted into a short-term scheduling constraint (i.e., the average thermal power consumption threshold of the sub-cycle), so that the embodiments of this application can continuously evaluate the loss balance of available charging devices in a preset sub-cycle.

[0017] In some embodiments, the charging efficiency of each available charging device under different charging demand information includes the actual charging efficiency of each available charging device under different charging demand information in the current time period; obtaining the charging efficiency of each available charging device among multiple available charging devices in a charging station under different charging demand information includes: for each available charging device's second available charging device, obtaining the initial charging efficiency curve of the second available charging device and the actual charging efficiency of the second available charging device under charging demand information in a historical time period; the initial charging efficiency curve is used to represent the maximum charging efficiency supported by the second available charging device under different charging demand information; based on the actual charging efficiency of the second available charging device under charging demand information in a historical time period, correcting the initial charging efficiency curve of the second available charging device to obtain the actual charging efficiency of the second available charging device under different charging demand information in the current time period.

[0018] In this embodiment, since the actual charging efficiency under the charging demand information of historical time periods is usually discrete and sparse historical data, while the initial charging efficiency curve is usually static and fixed initial data, the correction of the initial charging efficiency curve by the actual charging efficiency under the charging demand information of historical time periods can effectively solve the problem that relying solely on discrete and sparse historical data cannot fully predict the charging efficiency, while relying solely on static and fixed initial data cannot adapt to the time-varying characteristics of the charging efficiency of available charging devices. This improves the flexibility and accuracy of determining the actual charging efficiency under different charging demand information in the current time period.

[0019] In some embodiments, the charging environment includes at least one of the following: ambient temperature, ambient humidity, altitude information, and dust concentration.

[0020] In this embodiment, since various charging environments have a certain impact on the charging efficiency of charging devices, obtaining comprehensive and diverse charging environments helps to ensure the accuracy of the predicted charging efficiency under different complex environments.

[0021] In some embodiments, obtaining charging demand information of a vehicle to be charged includes: receiving a charging reservation request; the charging reservation request includes a vehicle identifier and a charging reservation time period; determining the charging power of the vehicle to be charged based on the vehicle identifier; and determining the charging environment of the vehicle to be charged based on the charging reservation time period and the location of the charging station.

[0022] In this embodiment, the charging environment of the vehicle to be charged can be accurately determined by the charging reservation time period and the location of the charging station, and the charging power of the vehicle to be charged can also be accurately determined by the vehicle identification.

[0023] In some embodiments, when there are multiple vehicles waiting to be charged, and the charging reservation time periods for the multiple vehicles waiting to be charged are the same time period, scheduling available charging equipment for the vehicles waiting to be charged according to a first scheduling sequence includes: obtaining the arrival time of the multiple vehicles waiting to be charged at the charging station; and scheduling available charging equipment for the multiple vehicles waiting to be charged according to the order of their arrival time at the charging station and the first scheduling sequence.

[0024] In this embodiment, by following the basic principle of first-come, first-served charging, the resource competition problem when multiple vehicles waiting to be charged have conflicting pre-charging appointment time slots is effectively solved, thereby optimizing the overall operational efficiency of charging stations in high-concurrency scenarios.

[0025] Secondly, this application provides another method for scheduling charging equipment, which includes: obtaining the cumulative thermal power consumption of each available charging equipment among a plurality of available charging equipment in a charging station; when the cumulative thermal power consumption of each available charging equipment does not meet the thermal power consumption balance condition, generating a second scheduling sequence of each available charging equipment in ascending order of the cumulative thermal power consumption of each available charging equipment; and scheduling available charging equipment for a vehicle to be charged according to the second scheduling sequence.

[0026] In this scheme, if the cumulative thermal power consumption of each available charging device does not meet the thermal power consumption balance condition, a second scheduling sequence can be generated directly according to the ascending order of the cumulative thermal power consumption of each available charging device. This sequence is then used to schedule available charging devices for vehicles waiting to be charged. There is no need to calculate the current charging efficiency of each available charging device under the charging demand information of the vehicles waiting to be charged. This ensures the balanced lifespan of each available charging device while also improving the efficiency of charging device scheduling.

[0027] Thirdly, embodiments of this application provide a computing device including a processor and a memory; the processor is coupled to the memory; the memory is used to store computer instructions, which are loaded and executed by the processor to enable the computing device to implement the methods provided in the first or second aspect and their possible embodiments described above.

[0028] Fourthly, embodiments of this application provide a computer-readable storage medium comprising: computer software instructions; when the computer software instructions are executed in a computing device, they cause the computing device to implement the methods provided in the first or second aspect and their possible embodiments described above.

[0029] Fifthly, embodiments of this application provide a computer program product that, when run on a computing device, causes the computing device to execute the steps of the relevant methods described in the first aspect above, so as to implement the methods of the first or second aspect above.

[0030] The beneficial effects of the third to fifth aspects mentioned above can be referred to the corresponding descriptions in the first aspect, and will not be repeated here. Attached Figure Description

[0031] Figure 1 A schematic diagram of the system architecture of a charging equipment scheduling system provided in this application embodiment; Figure 2 A flowchart illustrating a charging device scheduling method provided in an embodiment of this application; Figure 3 A flowchart illustrating another charging device scheduling method provided in this application embodiment; Figure 4 A flowchart illustrating another charging device scheduling method provided in this application embodiment; Figure 5 A flowchart illustrating another charging device scheduling method provided in this application embodiment; Figure 6 This is a schematic diagram of the architecture of a computing device provided in an embodiment of this application. Detailed Implementation

[0032] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0033] In the description of this application, unless otherwise stated, " / " indicates that the objects before and after are in an "or" relationship. For example, A / B can mean A or B. "And / or" in this application is merely a description of the relationship between the related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. A and B can be singular or plural.

[0034] Furthermore, in the description of this application, unless otherwise stated, "multiple" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0035] Furthermore, to facilitate a clear description of the technical solutions in the embodiments of this application, the terms "first" and "second" are used in the embodiments of this application to distinguish identical or similar items with substantially the same function and effect. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and that "first" and "second" are not necessarily different. Meanwhile, in the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is being used as an example, illustration, or description. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of terms such as "exemplary" or "for example" is intended to present related concepts in a concrete manner for ease of understanding.

[0036] It should be noted that in the embodiments of this application, the words "exemplarily" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design scheme described as "exemplarily" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the words "exemplarily" or "for example" is intended to present the relevant concepts in a specific manner.

[0037] The following provides an exemplary description of the application scenarios of the embodiments of this application.

[0038] As described in the background section, charging stations equipped with multiple charging devices are becoming increasingly common. These charging stations are typically deployed in scenarios with high requirements for charging service capacity and reliability, such as highway service areas, urban public hubs, and large commercial centers.

[0039] In these scenarios, charging demand exhibits a degree of predictability; for example, users can reserve charging slots in advance through charging reservation applications. The charging equipment deployed within charging stations often varies in model, and even those of the same model can have individual performance differences due to variations in installation location, usage history, and maintenance conditions. Furthermore, the environment surrounding charging stations (such as temperature) undergoes periodic changes, all of which affect the actual charging efficiency of each charging device in real time.

[0040] Therefore, how to effectively manage a charging station consisting of dozens or even hundreds of charging devices is a pressing technical problem that needs to be solved.

[0041] To address the aforementioned issues, this application provides a charging equipment scheduling method. This method can obtain the charging efficiency of each available charging device at a charging station under different charging demand information, as well as the charging demand information of the vehicle to be charged. The charging demand information includes the charging environment and charging power. Next, the current charging efficiency of each available charging device under the charging demand information of the vehicle to be charged can be determined, and a first scheduling sequence for each available charging device can be generated based on its current charging efficiency. Subsequently, available charging devices can be scheduled for the vehicle to be charged according to the first scheduling sequence.

[0042] In this scheme, by acquiring and comparing the charging efficiency of different available charging devices under specific charging demand information (i.e., the charging demand information of the vehicle to be charged), and generating a first scheduling sequence based on this, it helps to schedule available charging devices with better charging efficiency for the vehicle to be charged, thereby improving the overall energy efficiency of the charging station and realizing the reasonable scheduling of charging devices in the charging station.

[0043] Secondly, when determining the first scheduling sequence, the current charging efficiency of each available charging device can be determined based on the charging demand information, which includes key indicators such as specific charging power and charging environment. This makes the first scheduling sequence more in line with the charging power and charging environment requirements of the vehicles to be charged, avoiding the problem of unreasonable scheduling caused by environmental changes or power differences.

[0044] The system architecture of the embodiments of this application will be described exemplarily below.

[0045] This application provides a system architecture for a charging equipment scheduling system, such as... Figure 1 As shown, the charging equipment scheduling system may include: a vehicle 101 to be charged, a computing device 102, and multiple charging devices 103 within the charging station (e.g., ...). Figure 1 (Charging devices 1-n in the middle).

[0046] The computing device 102 is communicatively connected to the vehicle 101 to be charged and multiple charging devices 103.

[0047] In one feasible approach, the vehicle 101 to be charged is equipped with an in-vehicle infotainment system. Users can reserve a charging slot at a suitable charging station by using a charging reservation application installed on the system. Users can also select a time slot when making a charging reservation.

[0048] In another possible approach, a charging reservation application can be installed on the user's terminal. The user can then reserve a charge for the vehicle 101 to be charged via their terminal.

[0049] The computing device 102 can receive charging reservation requests sent by a user's terminal or the vehicle system deployed on the vehicle 101 to be charged, and obtain equipment information of multiple charging devices 103 in the charging station (such as the charging efficiency of each available charging device under different charging demand information), thereby executing the charging device scheduling method provided in the embodiments of this application to schedule available charging devices for the vehicle to be charged.

[0050] Among them, the available charging equipment refers to the charging equipment in the charging station where the parking space is not occupied, no other vehicles are currently charging, and the equipment is in normal operating condition.

[0051] The aforementioned charging devices 103, also known as charging piles, primarily function to convert AC or DC power from the power grid into safe and controllable DC power that meets the technical requirements of vehicle battery packs, thereby charging the vehicle 101 to be charged. In this embodiment, the multiple charging devices 103 are dispatched objects, each possessing independent power supply capabilities and operating status. Each charging device 103 is connected to the computing device 102, accepting its unified scheduling management, and is able to execute charging tasks for the vehicle 101 to be charged according to scheduling instructions.

[0052] In one possible implementation, the computing device 102 can be deployed in a charging station or in the cloud, and this application embodiment does not limit this.

[0053] This application does not impose any restrictions on the specific form of the computing device 102. For example, the computing device 102 can be a server. The server can be a single server, or it can be a server cluster consisting of multiple servers. In some embodiments, the server cluster can also be a distributed cluster, and this application does not limit this. As another example, the computing device 102 can specifically be a terminal device. The terminal device can be referred to as: terminal, user equipment (UE), terminal device, etc.

[0054] It should be pointed out that, Figure 1 The system architecture shown does not constitute a limitation on the charging equipment scheduling system, except Figure 1 In addition to the devices shown, the charging equipment scheduling system may include more or fewer devices than illustrated, or combine certain devices, or have different device arrangements.

[0055] The charging equipment scheduling method provided in the embodiments of this application will be described in detail below.

[0056] like Figure 2 The diagram shown is a flowchart illustrating a charging device scheduling method provided in an embodiment of this application. Figure 2 The method shown can be applied to computing devices. For example, the method can be applied to... Figure 1 The computing device 102 shown. The charging device scheduling method includes: S201. Obtain the charging efficiency of each available charging device in the charging station under different charging demand information, as well as the charging demand information of the vehicle to be charged.

[0057] The charging demand information includes the charging environment and charging power. Multiple available charging devices can refer to all available charging devices in a charging station, or only a portion of them.

[0058] As described above, the computing device can receive a charging reservation request sent by the vehicle's infotainment system or a user's terminal. This charging reservation request can include desired parameters for the current charging session, such as the desired charging power and the desired charging time period (i.e., the charging reservation time period). The computing device can then query the environmental information corresponding to the charging reservation time period to determine the charging environment for that period.

[0059] In some embodiments, the charging environment includes at least one of the following: ambient temperature, ambient humidity, altitude information, and dust concentration.

[0060] All of the above-mentioned charging environments have a certain impact on the charging efficiency of charging devices. For example, under otherwise unchanged conditions, in a scenario with a low ambient temperature (e.g., -10 degrees Celsius), the charging power of the charging device will be reduced by about 10% compared to a scenario with a normal ambient temperature (e.g., 18 degrees Celsius).

[0061] While ambient humidity has a relatively small impact on the charging efficiency of charging devices, it can still affect the charging efficiency to some extent (for example, under extreme humid and hot conditions, it may reduce the charging efficiency by 1%-3%).

[0062] Correspondingly, altitude and dust concentration also affect charging efficiency to some extent. For example, charging efficiency may decrease by 1%-5% in areas with an altitude of 2000-3000 meters. Prolonged exposure (e.g., for several months) in severely polluted areas with dust concentrations exceeding 300 mg / m³ can lead to a 2%-8% decrease in charging efficiency. Therefore, by obtaining the charging efficiency of charging equipment under different charging environments, computing devices can consider not only the basic performance of the charging equipment but also its actual performance in real, complex environments when scheduling charging equipment, greatly improving the robustness and flexibility of scheduling charging equipment.

[0063] In some embodiments, the charging power may be the maximum allowable receiving power of the vehicle battery to be charged, or it may be a power value manually set by the user. This application does not limit this.

[0064] When the charging power is the maximum allowable receiving power of the vehicle's battery, the computing device can also obtain the charging power from a network server storing vehicle information of the vehicle to be charged via the vehicle identifier. In this case, obtaining the charging demand information of the vehicle to be charged includes: It receives charging reservation requests that include vehicle identification and a charging reservation time period, and determines the charging power of the vehicle to be charged based on the vehicle identification, and determines the charging environment of the vehicle to be charged based on the charging reservation time period and the location of the charging station.

[0065] After receiving a charging reservation request, the computing device can parse the vehicle identifier carried in the request.

[0066] In one feasible approach, the vehicle identifier can be the vehicle identification number (VIN) of the vehicle to be charged, a unique charging account identifier, or a registered license plate number. The computing device uses this vehicle identifier as a query key to access the associated backend vehicle database or user profile. This backend vehicle database or user profile contains pre-stored or dynamically updated vehicle charging technical parameters corresponding to each vehicle identifier, including the maximum or recommended charging power that the vehicle's power battery can accept. The computing device retrieves the charging power associated with this vehicle identifier from the database and determines it as the charging power required for this charging operation.

[0067] Correspondingly, the computing device can extract the user-specified charging reservation time period from the charging reservation request. Simultaneously, the computing device can obtain the fixed location information of the charging station (such as latitude and longitude coordinates). The computing device can then call an external meteorological data service interface, using the charging station's location information and the charging reservation time period as request parameters, to obtain weather data for that geographical location within the corresponding charging reservation time period.

[0068] In one feasible approach, environmental monitoring sensors deployed locally at charging stations (such as temperature and humidity sensors installed on the roof or charging piles) can provide real-time environmental data as a supplement to or calibration of weather data. Computing equipment can then use the weather data, combined with real-time environmental data and predicted trends, to perform fusion calculations and obtain the charging environment for the current charge.

[0069] In practical applications, when the charging station is an indoor station or a station with local temperature control facilities, its charging environment can directly adopt a preset constant value or be provided by environmental monitoring sensors deployed inside the charging station.

[0070] The charging efficiency of the aforementioned available charging devices under different charging demand information can be represented by a three-dimensional efficiency curve (also known as an environment-load rate-efficiency three-dimensional data model, energy efficiency mapping relationship, etc.). This three-dimensional efficiency curve describes the dynamic change of charging efficiency with charging demand information.

[0071] In one feasible approach, the computing device can test the charging equipment under various different charging demand conditions when it leaves the factory or before it is put into operation, record the charging efficiency under different charging demand conditions, and thus obtain the three-dimensional efficiency curve.

[0072] In another possible approach, the computing device can also obtain the actual charging efficiency of the charging device under various charging demand information during historical usage phases, thereby obtaining the three-dimensional efficiency curve.

[0073] Of course, the computing device integrates the two methods of determining the three-dimensional efficiency curve to obtain a more accurate three-dimensional efficiency curve. The specific implementation process can be found in the description below, and will not be repeated here.

[0074] In practical applications, the aforementioned three-dimensional efficiency curves can be stored in a database connected to a computing device and can be queried and retrieved using the unique identifier of the charging device.

[0075] S202. Determine the current charging efficiency of each available charging device under the charging demand information of the vehicle to be charged, and generate the first scheduling sequence of each available charging device based on the current charging efficiency of each available charging device.

[0076] After acquiring the charging demand information of the vehicle to be charged and the three-dimensional efficiency curves of each available charging device, the computing device can substitute the charging demand information of the vehicle to be charged into the three-dimensional efficiency curves of each available charging device to obtain the current charging efficiency of each available charging device under the charging demand information of the vehicle to be charged. Then, the computing device can sort the available charging devices according to their current charging efficiency to obtain the first scheduling sequence of the available charging devices.

[0077] For example, suppose there are three available charging devices in a charging station that are currently idle, namely device D1, device D2, and device D3. The charging demand information of the vehicles to be charged obtained by the devices includes: charging power of 80kW, and the ambient temperature of the charging environment during the scheduled charging time period is 15 degrees Celsius (other charging environment parameters such as charging humidity are not considered for the time being).

[0078] First, the computing device can use the charging power of 80kW and the ambient temperature of 15℃ from the charging demand information as query keys to query the current charging efficiency of each available charging device from the three-dimensional efficiency curves corresponding to each available charging device.

[0079] The computer query showed that the charging efficiency of device D1 at 80kW and 15℃ was 92%, that of device D2 at 80kW and 15℃ was 93%, and that of device D3 at 80kW and 15℃ was 91%.

[0080] In this case, the computing device can sort the charging efficiency of the three charging devices in order of magnitude to obtain the first scheduling sequence as: device D2, device D1 and device D3.

[0081] S203. In accordance with the first scheduling sequence, schedule available charging equipment for vehicles waiting to be charged.

[0082] In one feasible approach, when the number of vehicles to be charged is one, the computing device can select the first available charging device in the first scheduling sequence as the charging device for the vehicle to be charged.

[0083] In another possible implementation, when there are multiple vehicles waiting to be charged, the computing device can schedule available charging devices for the multiple vehicles waiting to be charged in the order of the available charging devices in the first scheduling sequence.

[0084] In some embodiments, when there are multiple vehicles waiting to be charged, and the charging reservation time periods for these vehicles are the same, the computing device can reasonably schedule available charging equipment based on the arrival times of the multiple vehicles at the charging station. Therefore, scheduling available charging equipment for the vehicles according to the first scheduling sequence includes: The system obtains the arrival times of multiple vehicles waiting to be charged at the charging station, and schedules available charging equipment for these vehicles according to their arrival times and the first scheduling sequence.

[0085] In other words, when the charging reservation time slots of multiple vehicles overlap, the computing device can obtain the arrival time of each vehicle at the charging station in real time through the vehicle positioning data or entry sensing devices of the multiple vehicles, and establish a charging queue according to the order at that moment. Subsequently, the computing device can schedule available charging equipment for each vehicle according to this queue order and the determined first scheduling sequence.

[0086] During the process of scheduling available charging equipment for vehicles to be charged according to the first scheduling sequence, the computing device can also monitor the operating status of the target charging equipment (i.e., the charging equipment that has been identified as the charging equipment for the vehicles to be charged) in real time. When the target charging equipment malfunctions or is unusable due to the parking space being occupied, the next available charging equipment in the first scheduling sequence can be automatically selected as the new target charging equipment.

[0087] In one feasible approach, after identifying the charging equipment for the vehicle to be charged, the computing device can generate scheduling confirmation information containing the location number of the target charging equipment (i.e., the charging equipment identified for the vehicle to be charged) and send it to the vehicle's infotainment system or the user's terminal via a communication interface to guide the user to the charging location of the target charging equipment. Simultaneously, the computing device can also send an authorization command to the target charging equipment, preparing it to receive charging connection requests from the vehicle to be charged.

[0088] In some embodiments, the charging efficiency of each available charging device under different charging demand information includes the actual charging efficiency of each available charging device under different charging demand information in the current time period. That is, the actual charging efficiency of each available charging device may decrease over time during use. Therefore, when obtaining the charging efficiency of each available charging device under different charging demand information in the current time period, the computing device can comprehensively determine it by combining historical data and factory data. In this case, such as... Figure 3 As shown, in S201 above, obtaining the charging efficiency of each available charging device among multiple available charging devices in the charging station under different charging demand information includes: S301. Obtain the initial charging efficiency curve of each available charging device and the actual charging efficiency under the charging demand information of historical time periods.

[0089] The computing device obtains the initial charging efficiency curve of each available charging device and the actual charging efficiency under the charging demand information of historical time periods in the same way. Therefore, this application embodiment takes the second available charging device among the available charging devices as an example to introduce the specific implementation method of obtaining the initial charging efficiency curve of each available charging device and the actual charging efficiency under the charging demand information of historical time periods.

[0090] The second available charging device can be any one of the available charging devices. For example, the second available charging device and the first available charging device mentioned above can be the same device or different devices; this embodiment does not limit this. For each available charging device, the initial charging efficiency curve of the second available charging device and the actual charging efficiency of the second available charging device under the charging demand information of the historical time period are obtained.

[0091] The initial charging efficiency curve represents the maximum charging efficiency supported by the second available charging device under different charging demand information.

[0092] The initial charging efficiency curve can be obtained by the manufacturer of the second available charging device through charging efficiency testing before shipment. In the charging efficiency test, the second charging device can be placed in a controlled environmental simulation chamber, and multiple discrete charging environment parameters (e.g., ambient temperature) are selected as charging environment test points. Then, at each charging environment test point, different discrete load rates are set as load rate test points to control the stable operation of the second charging device. At each charging environment test point and load rate test point, the input and output electrical energy of the second charging device are measured, and the charging efficiency under that charging demand information is calculated. Next, based on the rated power of the second charging device, the aforementioned load rate and charging power can be converted to obtain the charging efficiency of the second charging device under different charging environments and different charging powers. Finally, all these discrete data can be used to construct a continuous function curve or a data interpolation model through a preset curve fitting or three-dimensional interpolation algorithm. This function curve or data interpolation model is the aforementioned initial charging efficiency curve.

[0093] In one possible implementation, the aforementioned initial charging efficiency curve can be stored in a database connected to a computing device and can be queried and retrieved using the unique identifier of a second available charging device.

[0094] Correspondingly, the computing device can also obtain the actual charging efficiency of the second available charging device over a historical period. The computing device can continuously collect this actual charging efficiency during the daily operation of the second available charging device. Each time the second available charging device charges a vehicle, the computing device can record the charging demand information for that charging session and obtain the actual charging efficiency of the second charging device during the charging process or at the end of the task.

[0095] S302. Based on the actual charging efficiency of the second available charging device under the charging demand information of the historical time period, correct the initial charging efficiency curve of the second available charging device to obtain the actual charging efficiency of the second available charging device under different charging demand information in the current time period.

[0096] After obtaining the actual charging efficiency and initial charging efficiency curve of the second available charging device under the charging demand information of the historical time period, since the actual charging efficiency of the second available charging device under the charging demand information of the historical time period is usually discrete single-point data, the computing device can replace the maximum charging efficiency under the same charging demand information in the initial charging efficiency curve with the discrete single-point data, and update the charging efficiency under other unreplaced charging demand information through a preset curve fitting or three-dimensional interpolation algorithm, thereby obtaining the actual charging efficiency of the second available charging device under different charging demand information in the current time period.

[0097] In one feasible approach, if there is a sufficient amount of data on the actual charging efficiency of the second available charging device under the charging demand information of a historical time period, the computing device can directly perform curve fitting or three-dimensional interpolation on the actual charging efficiency of the second available charging device under the charging demand information of a historical time period to construct a continuous function curve or a data interpolation model as the actual charging efficiency of the second available charging device under different charging demand information in the current time period.

[0098] In some embodiments, the charging equipment in a charging station has a limited lifespan. This lifespan is closely related to its thermal power consumption. Therefore, based on scheduling charging equipment for vehicles waiting to be charged according to charging efficiency, to avoid excessive use of high-efficiency charging equipment and thus reducing its lifespan, the computing device can further optimize the method of scheduling charging equipment for vehicles waiting to be charged based on the thermal power consumption of available charging equipment as a constraint. In this case, such as... Figure 4 As shown, another charging device scheduling method provided in this application includes: S401. Obtain the initial charging efficiency curve of each available charging device and the actual charging efficiency under the charging demand information of historical time periods.

[0099] S402. Based on the actual charging efficiency of the second available charging device under the charging demand information of the historical time period, correct the initial charging efficiency curve of the second available charging device to obtain the actual charging efficiency of the second available charging device under different charging demand information in the current time period.

[0100] For descriptions and specific implementation methods of S401-S402, please refer to the above explanations of S301-S302.

[0101] S403. Obtain charging demand information for vehicles to be charged.

[0102] For a description of S403 and its specific implementation, please refer to the above explanation of S201.

[0103] S404. Obtain the cumulative thermal power consumption of each available charging device.

[0104] The cumulative thermal power consumption includes the thermal power consumption required to charge the vehicle to be charged and the historical thermal power consumption.

[0105] Since the computing devices obtain the cumulative thermal power consumption of each available charging device in the same way, this application embodiment takes the first available charging device among the various charging devices as an example to introduce the specific implementation method of obtaining the cumulative thermal power consumption of each available charging device.

[0106] For the first available charging device among all charging devices, based on the charging demand information of the vehicle to be charged and the current charging efficiency of the first available charging device, the heat power consumption required by the first available charging device to charge the vehicle to be charged is predicted, and based on the heat power consumption required by the first available charging device to charge the vehicle to be charged and the historical heat power consumption of the first available charging device, the cumulative heat power consumption of the first available charging device is determined.

[0107] The first available charging device is any one of the available charging devices.

[0108] After acquiring the charging demand information of the vehicle to be charged and the current charging efficiency of an available charging device, the computing device can predict the heat dissipation required by the first available charging device to charge the vehicle to be charged, based on the principle of energy conservation.

[0109] In one feasible approach, the computing device can multiply the charging power by the estimated charging duration of the vehicle to be charged to obtain the total electrical energy that the first charging device needs to transfer for this charging of the vehicle. Then, based on the current charging efficiency of the first charging device, the computing device can determine the portion of electrical energy that will be lost as heat during the energy conversion process. This portion is the heat dissipation required for charging the vehicle, also known as the additional heat dissipation. This additional heat dissipation satisfies the following formula: New thermal power consumption = charging power * estimated charging duration * (1 / current charging efficiency - 1).

[0110] The estimated charging duration for the vehicle to be charged can be calculated using the charging efficiency and the remaining battery power of the vehicle. Alternatively, the duration of the charging reservation period carried in the charging reservation request sent by the vehicle to be charged can be used as the estimated charging duration. This application embodiment does not limit this.

[0111] Next, the computing device can access a database storing the cumulative thermal power consumption of charging equipment in the charging station to query the historical thermal power consumption of the first available charging equipment. This historical thermal power consumption can be the cumulative value recorded since the first available equipment was put into operation, continuously adding the thermal power consumption generated by its previous charging tasks.

[0112] The computing device sums the calculated new thermal power consumption with the historical thermal power consumption retrieved from the thermal power consumption accumulation database. The result is the new cumulative thermal power consumption that the first available charging device will reach if it undertakes the charging task.

[0113] Correspondingly, the computing device can use the same method to calculate the cumulative thermal power consumption of each available charging device, thereby obtaining the cumulative thermal power consumption of each available charging device.

[0114] S405. When the cumulative thermal power consumption of each available charging device meets the thermal power consumption balance condition, generate the first scheduling sequence according to the current charging efficiency of each available charging device in descending order.

[0115] In some embodiments, the above-mentioned thermal power equalization condition includes the cumulative thermal power difference of each available charging device being less than a thermal power threshold.

[0116] The range of cumulative thermal power consumption for each available charging device is the difference between the maximum and minimum values ​​of the cumulative thermal power consumption for each available charging device.

[0117] The cumulative thermal power consumption range can directly quantify the aging dispersion of multiple available charging devices in a charging station, transforming a complex multi-objective optimization problem into a simple, real-time calculable quantitative value. The cumulative thermal power consumption range can measure the dispersion (i.e., the range) of the service life loss (also known as the degree of aging) of all charging devices in a charging station, thereby providing a basis for subsequently determining the scheduling sequence of available charging devices.

[0118] In some embodiments, the aforementioned thermal power consumption threshold is determined based on the average thermal power consumption of each available charging device within a preset sub-cycle. The average thermal power consumption within the preset sub-cycle is obtained by dividing the total average thermal power consumption of each available charging device over its entire lifecycle by the number of sub-cycles.

[0119] In other words, the computing device can average the total thermal power consumption of the available charging device over its entire lifespan into multiple consecutive, equally long, preset sub-cycles. Each preset sub-cycle is assigned an equal amount of thermal power consumption, which is the thermal power consumption threshold for judgment.

[0120] It should be noted that the models of available charging equipment in a charging station may differ, and therefore their total thermal power consumption may also differ. In this case, the computing device can obtain the total thermal power consumption of each available charging device and take the average of the total thermal power consumption of these available charging devices as the total average thermal power consumption of each available charging device over its entire life cycle.

[0121] When the available charging devices in a charging station are of the same model and have the same total thermal power consumption, the computing device can directly divide the total thermal power consumption of an available charging device over its entire life cycle into equal parts based on the number of sub-cycles, thereby obtaining the thermal power consumption threshold.

[0122] For example, for a usable charging device with a total lifespan of 5 years (60 months), the preset total thermal power consumption over the entire lifespan is 84,000 kWh. The computing device can distribute this total thermal power consumption evenly across each monthly sub-cycle, so the thermal power consumption threshold for each month is 84,000 kWh divided by 60 months, resulting in 1,400 kWh.

[0123] When determining the scheduling method of available charging devices, the computing device can calculate the cumulative thermal power consumption range of each available charging device and compare this cumulative thermal power consumption range with the aforementioned thermal power consumption threshold (1400 kWh) to determine whether the cumulative thermal power consumption of each available charging device meets the thermal power consumption balance condition.

[0124] In one possible implementation, the above-mentioned sub-cycle can be a month or a week, and the embodiments of this application do not limit this.

[0125] In one possible implementation, the above-mentioned thermal power consumption equalization conditions may also include conditions such as the cumulative thermal power consumption variance of each available charging device being less than a preset variance and the cumulative thermal power consumption average being less than a preset average, which are used to characterize thermal power consumption equalization. The embodiments of this application do not limit this.

[0126] If the cumulative thermal power consumption of all available charging devices meets the thermal power consumption balance condition, it indicates that the lifespan degradation of each available charging device is similar. In this case, the computing device can prioritize charging efficiency to maximize the charging efficiency provided to the vehicles waiting to be charged. Therefore, the computing device can generate a first scheduling sequence according to the current charging efficiency of each available charging device in descending order.

[0127] S406. In accordance with the first scheduling sequence, schedule available charging equipment for vehicles waiting to be charged.

[0128] In some embodiments, the method provided in this application further includes: S407. If the cumulative thermal power consumption of each available charging device does not meet the thermal power consumption balance condition, generate a second scheduling sequence for each available charging device in ascending order of cumulative thermal power consumption.

[0129] If the cumulative thermal power consumption of all available charging devices does not meet the thermal power consumption balance condition, it indicates that the lifespan degradation of the available charging devices has become significantly uneven, with some devices being overused while others are underutilized. Therefore, the computing device can switch from a scheduling method prioritizing charging efficiency to prioritizing the goal of balancing the lifespan degradation of available charging devices, in order to delay the overall aging of available charging devices and prevent individual devices from prematurely failing.

[0130] In this scenario, the computing device can generate a second scheduling sequence based on the ascending order of the cumulative thermal power consumption of each available charging device calculated in step S301. In this second scheduling sequence, the first available charging device has the lowest cumulative thermal power consumption; that is, from the perspective of total lifecycle loss, this is the available charging device with the least consumption. Therefore, the computing device can prioritize allocating the first available charging device to charge the vehicle according to the second scheduling sequence, thereby reducing the loss gap between available charging devices and enabling each available charging device to return to a state of thermal power consumption equilibrium.

[0131] S408. In accordance with the second scheduling sequence, schedule available charging equipment for vehicles waiting to be charged.

[0132] The specific implementation of the computing device scheduling available charging equipment for the vehicle to be charged according to the second scheduling sequence can be referred to in S203 above, which describes the specific implementation of scheduling available charging equipment for the vehicle to be charged according to the first scheduling sequence. It will not be repeated here.

[0133] In some embodiments, the computing device can also directly schedule available charging devices based on the cumulative thermal power consumption of each available charging device. In this case, embodiments of this application also provide another charging device scheduling method. Figure 5 As shown, this method can be applied to the aforementioned computing device, including: S501. Obtain the cumulative thermal power consumption of each available charging device among multiple available charging devices in the charging station.

[0134] S502. If the cumulative thermal power consumption of each available charging device does not meet the thermal power consumption balance condition, generate a second scheduling sequence for each available charging device in ascending order of cumulative thermal power consumption.

[0135] S503. In accordance with the second scheduling sequence, schedule available charging equipment for vehicles waiting to be charged.

[0136] In other words, when the computing device determines that the cumulative thermal power consumption of each available charging device does not meet the thermal power consumption balance condition, it can directly generate a second scheduling sequence according to the ascending order of the cumulative thermal power consumption of each available charging device, and use this sequence to schedule available charging devices for the vehicle to be charged. There is no need to calculate the current charging efficiency of each available charging device under the charging demand information of the vehicle to be charged. This ensures the balanced lifespan of each available charging device and also improves the efficiency of charging device scheduling.

[0137] In an exemplary embodiment, this application also provides a charging device scheduling apparatus. This charging device scheduling apparatus may be a computing device that performs the aforementioned charging device scheduling method, or it may be a processor within the computing device. The charging device scheduling apparatus may include one or more functional modules for implementing the charging device scheduling method of the above method embodiments.

[0138] This application also provides a computing device. Figure 6 This is a schematic diagram of the architecture of a computing device provided in an embodiment of this application. Figure 6 As shown, the computing device 100 includes: one or more memories 120, one or more processors 110, a communication bus 140, and a communication interface 130. The processors 110 and memories 120 are connected via the communication bus 140; the one or more memories 120 are used to store computer program code, which includes computer instructions; when the one or more processors 110 execute the computer instructions, the computing device 100 performs the charging device scheduling method provided in this embodiment.

[0139] Optionally, the memory 120 may be a non-transitory computer-readable storage medium, such as a read-only memory (ROM), random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc. The embodiments of this application do not impose any limitations on this.

[0140] The processor 110 may be a central processing unit (CPU), a network processor (NP), a digital signal processor (DSP), a microprocessor, a microcontroller, a programmable logic device (PLD), or any combination thereof, and the embodiments of this application do not impose any limitations on this.

[0141] The communication bus 140 can be an industry standard architecture (ISA) bus, a peripheral component interconnect (PCI) bus, or an extended industry standard architecture (EISA) bus, etc. This communication bus 140 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 6 It is represented by a single thick line, but this does not mean that there is only one bus or one type of communication bus.

[0142] Communication interface 130 uses any transceiver-like device for communicating with other devices or communication networks, such as control systems, radio access networks (RAN), wireless local area networks (WLAN), etc.

[0143] It should be noted that the system architecture and application scenarios described in the embodiments of this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided in the embodiments of this application. As those skilled in the art will know, with the evolution of system architecture and the emergence of new business scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0144] This application also provides a computer-readable storage medium. All or part of the processes in the above method embodiments can be executed by computer instructions instructing related hardware; for example, the related hardware can be a processor of a computing device. The program instructions can be stored in the above-mentioned computer-readable storage medium, and when executed, the processes of the above method embodiments can be implemented. The computer-readable storage medium can be memory. The above-mentioned computer-readable storage medium can also be an external storage device, such as a hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc. Further, the above-mentioned computer-readable storage medium can include both memory and external storage devices. The above-mentioned computer-readable storage medium is used to store the above-mentioned computer program instructions and other programs and data required by the above-mentioned charging device scheduling method.

[0145] This application also provides a computer program product, which includes a computer program that, when run on a computing device, causes the computing device to execute any of the charging device scheduling methods provided in the above embodiments.

[0146] Although this application has been described herein in conjunction with various embodiments, those skilled in the art, by reviewing the accompanying drawings, disclosure, and appended claims, will understand and implement other variations of the disclosed embodiments in carrying out the claimed application. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude multiple instances. A single processor or other unit can implement several functions listed in the claims. While different dependent claims may recite certain measures, this does not mean that these measures cannot be combined to produce good results.

[0147] Although this application has been described in conjunction with specific features and embodiments, it is obvious that various modifications and combinations can be made thereto without departing from the spirit and scope of this application. Accordingly, this specification and drawings are merely exemplary illustrations of this application as defined by the appended claims, and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from the spirit and scope of this application. Thus, if such modifications and modifications of this application fall within the scope of the claims of this application and their equivalents, this application is also intended to include such modifications and modifications.

[0148] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for scheduling charging equipment, characterized in that, include: The charging efficiency of each available charging device in a charging station under different charging demand information is obtained, as well as the charging demand information of the vehicle to be charged. The charging demand information includes the charging environment and charging power; Determine the current charging efficiency of each available charging device under the charging demand information of the vehicle to be charged, and generate a first scheduling sequence of each available charging device based on the current charging efficiency of each available charging device. According to the first scheduling sequence, available charging equipment is scheduled for the vehicle to be charged.

2. The method according to claim 1, characterized in that, The step of generating a first scheduling sequence for each available charging device based on its current charging efficiency includes: For the first available charging device among the various charging devices, the cumulative thermal power consumption of the first available charging device is obtained; the cumulative thermal power consumption includes the thermal power consumption required to charge the vehicle to be charged and the historical thermal power consumption. If the cumulative thermal power consumption of each available charging device meets the thermal power consumption balance condition, the first scheduling sequence is generated in descending order of the current charging efficiency of each available charging device.

3. The method according to claim 2, characterized in that, The method further includes: If the cumulative thermal power consumption of each available charging device does not meet the thermal power consumption equalization condition, a second scheduling sequence of each available charging device is generated in ascending order of cumulative thermal power consumption. According to the second scheduling sequence, available charging equipment is scheduled for the vehicle to be charged.

4. The method according to claim 2 or 3, characterized in that, The thermal power consumption equalization condition includes the cumulative thermal power consumption range of each available charging device being less than the thermal power consumption threshold.

5. The method according to claim 4, characterized in that, The thermal power consumption threshold is determined based on the average thermal power consumption of each available charging device within a preset sub-cycle; the average thermal power consumption within the preset sub-cycle is obtained by dividing the total average thermal power consumption of each available charging device over its entire life cycle into equal sub-cycles.

6. The method according to any one of claims 1-5, characterized in that, The charging efficiency of each available charging device under different charging demand information includes the actual charging efficiency of each available charging device under different charging demand information in the current time period. The process of obtaining the charging efficiency of each available charging device in a charging station under different charging demand information includes: For the second available charging device among the various available charging devices, obtain the initial charging efficiency curve of the second available charging device and the actual charging efficiency of the second available charging device under the charging demand information of the historical time period; the initial charging efficiency curve is used to represent the maximum charging efficiency supported by the second available charging device under different charging demand information. Based on the actual charging efficiency of the second available charging device under the charging demand information of the historical time period, the initial charging efficiency curve of the second available charging device is corrected to obtain the actual charging efficiency of the second available charging device under different charging demand information in the current time period.

7. The method according to any one of claims 1-6, characterized in that, The charging environment includes at least one of the following: ambient temperature, ambient humidity, altitude information, and dust concentration.

8. The method according to any one of claims 1-7, characterized in that, Obtaining the charging demand information of the vehicle to be charged includes: Receive a charging reservation request; the charging reservation request includes the vehicle identifier and the charging reservation time period; Based on the vehicle identification, the charging power of the vehicle to be charged is determined, and based on the charging reservation time period and the location of the charging station, the charging environment of the vehicle to be charged is determined.

9. The method according to claim 8, characterized in that, When there are multiple vehicles waiting to be charged, and the charging reservation time periods for these vehicles are the same, scheduling available charging equipment for the vehicles according to the first scheduling sequence includes: Obtain the arrival time of the multiple vehicles waiting to be charged at the charging station; According to the order in which the multiple vehicles waiting to be charged arrive at the charging station and the first scheduling sequence, available charging equipment is scheduled for the multiple vehicles waiting to be charged.

10. A computing device, characterized in that, The computing device includes a processor and a memory; the processor is coupled to the memory. The memory is used to store computer instructions; The computer instructions are loaded and executed by the processor to enable the computing device to perform the method as described in any one of claims 1-9.

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