Charging control method and device and computer equipment
By subdividing charging periods into equal and continuous time intervals and optimizing charging plans based on historical orders and the lowest charging cost, the problem of resource waste at battery swapping stations has been solved, and more efficient charging control and resource allocation have been achieved.
Patent Information
- Application Number
- CN202410741659.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-06-11
- Publication Date
- 2025-12-12
AI Technical Summary
The existing charging management model cannot efficiently support the large-scale operation of battery swapping stations, resulting in a waste of human and power resources and insufficient precision in charging control.
The charging period is divided into multiple equal and continuous time periods. The electricity price remains unchanged in each time period. The battery demand in each time period is determined based on historical battery swapping orders. The charging plan is optimized by minimizing the charging cost to ensure a balance of battery demand between adjacent time periods.
It improves the precision of charging control, reduces resource waste, lowers the amount of computation and computing power required, optimizes resource allocation, and reduces charging costs.
Smart Images
Figure CN121105883A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of battery swapping technology, specifically to a charging control method, device, and computer equipment. Background Technology
[0002] Currently, battery swapping services are gaining popularity among users as an important way to replenish energy for new energy vehicles due to their speed and convenience. However, with the continuous expansion of battery swapping station infrastructure, the existing charging management model lacks sufficient precision and cannot efficiently support large-scale operations, resulting in a waste of human and electrical resources.
[0003] Therefore, improving the precision of charging control is a pressing technical problem that needs to be solved. Summary of the Invention
[0004] In view of the above problems, this application provides a charging control method, apparatus and computer equipment to improve the precision of charging control.
[0005] Firstly, this application provides a charging control method, which includes: dividing a charging period into multiple equal and continuous time periods, wherein the electricity price remains constant within each time period, and each time period corresponds to multiple consecutive State of Charge (SOC) gradients; determining the battery demand quantity for each time period based on at least one historical battery swapping order, wherein each historical battery swapping order represents the correspondence between each time period and the battery demand quantity; determining the minimum charging cost corresponding to the charging period based on the electricity price corresponding to each time period, the SOC change corresponding to each SOC gradient, and the target battery quantity to be charged within each SOC gradient, wherein in two adjacent time periods, the target battery quantity at the maximum SOC gradient in the earlier time period is greater than or equal to the battery demand quantity in the later time period, and the sum of the target battery quantities in each time period is less than or equal to the number of charging bays; and charging the received batteries based on the correspondence between the time period corresponding to the minimum charging cost, the SOC gradient, and the target battery quantity.
[0006] Understandably, on the one hand, by subdividing charging periods and SOC gradients, and combining this with the number of target batteries that may be charged within each SOC gradient, the accuracy of calculating charging energy consumption can be improved, thereby enhancing charging control precision. On the other hand, by constraining the number of target batteries at the maximum SOC gradient in the earlier time period to be greater than or equal to the battery demand in the later time period, computational load can be reduced while accurately meeting user needs and improving resource allocation precision, thus lowering computing power requirements. Furthermore, by combining the electricity price within each time period, the potential charging cost can be quantified, and the received batteries can be charged based on the lowest charging cost, reducing costs while improving charging control precision and minimizing energy waste in energy allocation.
[0007] In one implementation, the minimum charging cost for a charging period is determined based on the electricity price for each time period, the SOC change for each SOC gradient, and the number of target batteries requiring charging within each SOC gradient, including:
[0008] The following formula is used to calculate the multiple charging costs corresponding to different charging periods:
[0009]
[0010] Where f is the charging cost corresponding to the charging period, R is the SOC-energy conversion factor, M is the number of time periods included in the charging period, and price i Let x be the electricity price corresponding to the i-th time period. i,j Let ΔSOC be the number of target batteries corresponding to the j-th SOC gradient in the i-th time period. j Let N be the SOC change during each battery charging process in the j-th SOC gradient, N be the number of SOC gradients corresponding to each time period, U be the number of charging bays, and x be the number of charging bays. i,N Let be the target number of batteries in the i-th time period that have the maximum SOC gradient, need i+1 This represents the battery demand in the (i+1)th time period.
[0011] Determine the lowest charging cost among multiple charging costs.
[0012] In one implementation, the difference between the target total number of batteries and the total number of batteries required is less than or equal to a preset threshold; the method further includes:
[0013] The total number of target batteries corresponding to the maximum SOC gradient is calculated based on the sum of the number of target batteries at the maximum SOC gradient in each time period.
[0014] Based on the battery demand for each time period, calculate the total battery demand for each charging period.
[0015] In one implementation, in two adjacent time periods, the number of target batteries in the first SOC gradient in the earlier time period is less than or equal to the number of target batteries in the second SOC gradient in the later time period; wherein, the first SOC gradient is any one of a plurality of SOC gradients, and the maximum SOC of the first SOC gradient and the minimum SOC of the second SOC gradient are continuous.
[0016] In one implementation, the method further includes obtaining multiple consecutive SOC gradients based on the duration of each time period and the charging rate of each charging compartment.
[0017] In one implementation, the charging period is from 0:00 to 24:00 every day, and each time period lasts for 10 minutes.
[0018] Secondly, this application provides a charging control device, which includes:
[0019] The processing module is used to divide the charging period into multiple equal and continuous time periods, wherein the electricity price remains unchanged in each time period, and each time period corresponds to multiple continuous remaining power SOC gradients.
[0020] The first determining module is used to determine the battery demand quantity for each time period based on at least one historical battery swapping order, wherein each historical battery swapping order represents the correspondence between each time period and the battery demand quantity;
[0021] The second determining module is used to determine the minimum charging cost corresponding to the charging period based on the electricity price corresponding to each time period, the SOC change corresponding to each SOC gradient, and the number of target batteries that need to be charged within each SOC gradient. In this case, in two adjacent time periods, the number of target batteries at the maximum SOC gradient in the earlier time period is greater than or equal to the battery demand in the later time period, and the sum of the number of target batteries in each time period is less than or equal to the number of charging bays.
[0022] The charging control module is used to charge the received batteries based on the correspondence between the time period corresponding to the lowest charging cost, the SOC gradient, and the target number of batteries.
[0023] In one implementation, the second determining module is specifically used to: calculate multiple charging costs corresponding to the charging period using the following formula:
[0024]
[0025] Where f is the charging cost corresponding to the charging period, R is the SOC-energy conversion factor, M is the number of time periods included in the charging period, and price i Let x be the electricity price corresponding to the i-th time period. i,jLet ΔSOC be the number of target batteries corresponding to the j-th SOC gradient in the i-th time period. j Let N be the SOC change during each battery charging process in the j-th SOC gradient, N be the number of SOC gradients corresponding to each time period, U be the number of charging bays, and x be the number of charging bays. i,N Let be the target number of batteries in the i-th time period that have the maximum SOC gradient, need i+1 This represents the battery demand in the (i+1)th time period.
[0026] Determine the lowest charging cost among multiple charging costs.
[0027] In one embodiment, the difference between the total number of target batteries and the total number of batteries required is less than or equal to a preset threshold. The charging control device further includes: a first calculation module, used to calculate the total number of target batteries corresponding to the maximum SOC gradient based on the sum of the number of target batteries at the maximum SOC gradient in each time period; and a second calculation module, used to calculate the total number of batteries required for the charging period based on the battery demand corresponding to each time period.
[0028] In one implementation, in two adjacent time periods, the number of target batteries in the first SOC gradient in the earlier time period is less than or equal to the number of target batteries in the second SOC gradient in the later time period; wherein, the first SOC gradient is any one of a plurality of SOC gradients, and the maximum SOC of the first SOC gradient and the minimum SOC of the second SOC gradient are continuous.
[0029] In one embodiment, the device further includes a third calculation module for obtaining multiple consecutive SOC gradients based on the duration of each time period and the charging rate of each charging compartment.
[0030] In one implementation, the charging period is from 0:00 to 24:00 every day, and each time period lasts for 10 minutes.
[0031] Thirdly, this application provides a computer device, which includes: a processor and a memory storing computer program instructions;
[0032] When the processor executes computer program instructions, it implements a charging control method as described in any of the first aspects.
[0033] Fourthly, this application provides a readable storage medium storing computer program instructions, which, when executed by a processor, implement a charging control method as described in any of the first aspects.
[0034] Fifthly, this application provides a computer program product in which the instructions are executed by the processor of a computer device, causing the computer device to perform a charging control method as described in any of the first aspects.
[0035] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description
[0036] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiments below. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:
[0037] Figure 1 This is a schematic flowchart of a charging control method according to some embodiments of this application;
[0038] Figure 2 This is a schematic flowchart of a charging control method according to other embodiments of this application;
[0039] Figure 3 This is a schematic diagram of the structure of a charging control device according to some embodiments of this application;
[0040] Figure 4 This is a schematic diagram of the structure of a computer device according to some embodiments of this application. Detailed Implementation
[0041] The embodiments of the technical solution of this application will now be described in detail with reference to the accompanying drawings. These embodiments are only used to more clearly illustrate the technical solution of this application and are therefore merely examples, and should not be used to limit the scope of protection of this application.
[0042] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.
[0043] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.
[0044] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.
[0045] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.
[0046] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two).
[0047] To facilitate understanding of the solutions in this application, the technical terms and background information used will be explained below:
[0048] I. Battery Swapping Stations:
[0049] A battery swapping station is a facility that provides a fast battery swapping service for electric vehicles. It allows electric vehicles to have their batteries replaced within minutes, thus avoiding long charging waits. The construction of battery swapping stations aims to improve the convenience of electric vehicle use, reduce user wait times through fast battery swapping services, and promote the widespread adoption of electric vehicles. With technological advancements and the maturation of the electric vehicle industry, battery swapping stations are becoming an important component of the electric vehicle energy replenishment network.
[0050] II. Peak-Side-Valley Electricity Pricing
[0051] Electricity pricing refers to a pricing strategy where power companies dynamically adjust prices based on electricity demand and generation costs throughout the day to regulate supply and demand and optimize resource allocation. This pricing system typically divides the day into four periods: peak, off-peak, and low-peak, each with a different price. Peak hours, usually during the daytime working hours, see the highest electricity demand and therefore higher prices. Off-peak hours have moderate demand and moderate prices. Low-peak hours, typically at night or during non-working hours, see lower demand and therefore lower prices.
[0052] III. SOC
[0053] State of Charge (SOC) refers to the percentage of usable charge remaining in a battery relative to its nominal capacity. It's a crucial monitoring metric for the battery management system (BMS), which uses the SOC value to control the battery's operating state. Essentially, the remaining charge reflects the battery's state of charge. For example, under ideal conditions, the SOC increases from 0% to 100% when the battery is fully discharged and fully charged.
[0054] Currently, battery swapping services, as an important way to replenish energy for new energy vehicles, are increasingly favored by users, especially those operating commercial vehicles, due to their speed and convenience. However, with the continuous expansion of battery swapping station infrastructure, existing charging management models are unable to efficiently support large-scale operations. For example, when receiving customer orders or approaching electricity price changes, decisions on how to manage charging are difficult, and precise 24 / 7 operation of the charging schedule for battery swapping stations is not feasible. This leads to situations where there are too many fully charged batteries at swapping stations, resulting in energy waste, or too few fully charged batteries, failing to meet users' battery swapping needs.
[0055] Therefore, improving the precision of charging control is a pressing technical problem that needs to be solved.
[0056] To address the aforementioned technical issues, this application provides a charging control method to improve the precision of charging control.
[0057] like Figure 1 As shown, the method includes:
[0058] Step 101: Divide the charging period into multiple equal and continuous time periods.
[0059] It should be noted that the charging period here can be from 12:00 to 24:00 in a 24-hour system, or from 0:00 to 24:00. In practical applications, it can be set according to the charging plan of the battery swapping station. This application does not limit it in this regard.
[0060] In addition, the electricity price remains unchanged within each time period. Understandably, the electricity pricing system usually divides a 24-hour day into four price periods: "peak-peak-flat-valley". If the time period in this application spans two or more electricity price periods, and the electricity pricing system may differ in different cities and regions, it will lead to an excessive amount of calculation when determining the charging cost in this application, thus making charging planning too difficult.
[0061] In one implementation, the charging period is from 0:00 to 24:00 every day, and each time period lasts for 10 minutes.
[0062] On the one hand, the electricity pricing system may differ in different regions. For most electricity pricing systems, this application divides the time into 10-minute intervals, which can ensure that each time period contains only one electricity price. For example, most charging management systems on the market divide charging time periods into 60-minute or 90-minute intervals, which may result in multiple electricity prices in one time period.
[0063] On the other hand, it can also avoid the problem of excessive calculation due to overly detailed settings, such as 5 minutes, which would make charging planning too difficult.
[0064] On the other hand, if the smallest unit of time is 20 minutes or even longer, then after users learn that a fully charged battery will be available at the station, they may have to wait 20 minutes before they can swap batteries. This long waiting time will negatively impact the user experience.
[0065] Furthermore, each time period corresponds to multiple consecutive SOC gradients. These SOC gradients need to be continuous to ensure a continuous battery charging process, avoiding energy waste caused by intermittent start-stop of the charger due to discrete charging and excessively long waiting times for users.
[0066] In one implementation, multiple consecutive SOC gradients can be evenly distributed. Taking a user's incoming SOC of 30% underpowered and 90% fully charged as an example, multiple consecutive SOC gradients can be 30%–45%, 45%–60%, 60%–75%, and 75%–90%.
[0067] In one implementation, multiple consecutive SOC gradients can be obtained based on the duration of each time period and the charging rate of each charging bay. It is understood that when the battery is at a high SOC, such as 80%–90%, the change in SOC due to charging will decrease under the same charging duration and charging rate. Therefore, the SOC gradients can be set non-uniformly. For example, if a user enters the station with a 30% depleted SOC and a 98% fully charged SOC, multiple consecutive SOC gradients could be 30%–45%, 45%–60%, 60%–70%, 80%–88%, 88%–94%, and 94%–98%.
[0068] Step 102: Determine the battery demand quantity for each time period based on at least one historical battery swapping order.
[0069] It should be noted that each historical battery swap order represents the correspondence between the battery demand quantity and the time period. For multiple historical swap orders, the average number of battery charges corresponding to the same time period can be calculated to determine the battery demand quantity for each time period. Alternatively, a weighted average of the number of battery charges corresponding to the same time period can be calculated based on a preset weighting coefficient to determine the battery demand quantity for each time period.
[0070] In one embodiment, historical battery swapping orders are shown in Table 1:
[0071] date Time period Estimated order quantity Battery charge quantity 2024-3-1 12：50～13：00 4 50 2024-3-1 13：00～13：10 2 48 2024-3-1 13：10～13：20 1 46 2024-3-1 13：20～13：30 1 20 2024-3-1 13：30～13：40 1 10
[0072] Table 1
[0073] Step 103: Based on the electricity price corresponding to each time period, the SOC change corresponding to each SOC gradient, and the number of target batteries that need to be charged within each SOC gradient, determine the minimum charging cost corresponding to the charging period.
[0074] It should be noted that in two adjacent time periods, the number of target batteries at the maximum SOC gradient in the earlier time period must be greater than or equal to the battery demand in the later time period. For example, if the battery demand is 10 batteries from 13:30 to 13:40, then the number of target batteries charging at the maximum SOC gradient (94% to 98%) from 13:20 to 13:30 must be greater than 10 to meet the user's power demand.
[0075] It should also be noted that the total number of target batteries in each time period must be less than or equal to the number of charging bays. For example, if the number of charging bays in a battery swapping station is 50, then the total number of target batteries in each time period must be less than 50 to ensure the charging plan is feasible.
[0076] Step 104: Based on the correspondence between the time period corresponding to the lowest charging cost, the SOC gradient, and the target number of batteries, charge the received batteries.
[0077] For example, based on the correspondence between the time period corresponding to the lowest charging cost, the SOC gradient, and the target number of batteries, after outputting the intelligent charging plan, the intelligent charging plan can be dispatched through the cloud to control the chargers in the battery swapping station for charging management.
[0078] The following describes, in conjunction with embodiments, Figure 1 The charging control method shown is explained below:
[0079] In one implementation, for Figure 1 Step 102 shown: Based on the electricity price corresponding to each time period, the SOC change corresponding to each SOC gradient, and the number of target batteries that need to be charged within each SOC gradient, determine the minimum charging cost corresponding to the charging period, including:
[0080] The following formula is used to calculate the multiple charging costs corresponding to different charging periods:
[0081]
[0082] For the above formula: f is the charging cost corresponding to the charging period. For example, if the charging period is 24 hours a day, f is the charging cost for the whole day.
[0083] R is the SOC-energy conversion coefficient, which can be set according to the parameters of the battery pack produced by the manufacturer. This application does not limit this setting.
[0084] M represents the number of time periods included in the charging period. For example, if the charging period is 24 hours a day and the duration of each time period is 10 minutes, then M is 144.
[0085] price i The electricity price is the price corresponding to the i-th time period. The electricity price can be set according to the electricity price system of the region where the charging control method of this application is implemented. This application does not limit this.
[0086] x i,j Let x be the number of target batteries corresponding to the j-th SOC gradient in the i-th time period. 1,1 This represents the number of target batteries corresponding to the first SOC gradient in the first time period.
[0087] ΔSOC j Let ΔSOC be the change in SOC for each battery during the charging process in the j-th SOC gradient. For example, ΔSOC1 is the change in SOC for each battery during the charging process in the 1-th SOC gradient.
[0088] N is the number of SOC gradients corresponding to each time period. For example, if multiple consecutive SOC gradients corresponding to each time period are 30%–45%, 45%–60%, 60%–70%, 80%–88%, 88%–94%, and 94%–98%, then N is 6.
[0089] U represents the number of charging bays. The number of charging bays can be set according to the number of charging bays and chargers in the battery swapping station or other energy storage facilities. This application does not limit this number.
[0090] x i,N Let x be the number of target batteries at the maximum SOC gradient in the i-th time period. For example, if each time period corresponds to multiple consecutive SOC gradients of 30%–45%, 45%–60%, 60%–70%, 80%–88%, 88%–94%, and 94%–98%, and N is 6, then x 1,6 The target number of batteries in the first time period is between 94% and 98%.
[0091] need i+1 Let be the battery demand for the (i+1)th time period. For example, need2 is the battery demand for the second time period.
[0092] Understandably, based on the formula in this implementation, there is only one independent variable, namely x. i,j And x i,j Constrained by the maximum and minimum values, therefore x i,j Substituting all possibilities into this formula yields a finite number of charging costs. Observing this formula, it can be seen that the charging cost obtained is a comprehensive result of considering electricity prices, energy consumption, charging speed, and user demand.
[0093] Furthermore, the lowest charging cost among multiple charging costs is determined. This lowest charging cost is a comprehensive result of considering electricity prices, energy consumption, charging speed, and user demand, aiming to meet user needs as much as possible, avoid wasting electricity resources, and reduce power supply costs.
[0094] In one implementation, the difference between the target total number of batteries and the total number of batteries required is less than or equal to a preset threshold; for example, the preset threshold can be 0. Figure 2 As shown, the method also includes:
[0095] Step 201: Calculate the total number of target batteries corresponding to the maximum SOC gradient based on the sum of the number of target batteries at the maximum SOC gradient in each time period.
[0096] Step 202: Calculate the total number of batteries required for each charging period based on the battery demand for each time period.
[0097] Understandably, keeping the difference between the target total number of batteries and the total number of batteries required less than or equal to a preset threshold can avoid energy waste caused by excessive backup power. For example, if the total number of batteries required is 500 and the target total number of batteries is 550, 50 batteries may be left idle, resulting in energy waste and increased costs.
[0098] In addition, adding a constraint on the total number of target batteries in this embodiment can further reduce the computational load of the charging cost calculation formula, that is, while meeting user needs and avoiding energy waste, it can accelerate the charging planning speed.
[0099] In one implementation, in two adjacent time periods, the number of target batteries in the first SOC gradient in the earlier time period is less than or equal to the number of target batteries in the second SOC gradient in the later time period; wherein, the first SOC gradient is any one of a plurality of SOC gradients, and the maximum SOC of the first SOC gradient and the minimum SOC of the second SOC gradient are continuous.
[0100] Understandably, in practical applications, once a battery in the first SOC gradient of the preceding time period finishes charging, it becomes a battery in the second SOC gradient of the following time period, continuing to charge until it is fully charged. To avoid violating this rule, it is necessary to plan that the number of target batteries in the first SOC gradient of the preceding time period is less than or equal to the number of target batteries in the second SOC gradient of the following time period.
[0101] In addition, adding a constraint on the total number of target batteries in this embodiment can further reduce the computational load of the charging cost calculation formula, that is, while meeting user needs and avoiding energy waste, it can accelerate the charging planning speed.
[0102] Based on the same technical concept, this application also provides a charging control device. The implementation of the device can refer to the implementation of the above-described charging control method, and the repeated parts will not be described again.
[0103] like Figure 3 As shown, the charging control device 30 includes a processing module 301, a first determining module 302, a second determining module 303, and a charging control module 304.
[0104] The processing module 301 is used to divide the charging period into multiple equal and continuous time periods, wherein the electricity price remains unchanged in each time period and each time period corresponds to multiple continuous state of charge (SOC) gradients.
[0105] The first determining module 302 is used to determine the battery demand quantity for each time period based on at least one historical battery swapping order, wherein each historical battery swapping order represents the correspondence between each time period and the battery demand quantity.
[0106] The second determining module 303 is used to determine the minimum charging cost corresponding to the charging period based on the electricity price corresponding to each time period, the SOC change corresponding to each SOC gradient, and the number of target batteries that need to be charged within each SOC gradient. In the case of two adjacent time periods, the number of target batteries at the maximum SOC gradient in the earlier time period is greater than or equal to the battery demand in the later time period, and the sum of the number of target batteries in each time period is less than or equal to the number of charging bays.
[0107] The charging control module 304 is used to charge the received battery based on the correspondence between the time period corresponding to the lowest charging cost, the SOC gradient, and the target number of batteries.
[0108] In one implementation, such as Figure 3 As shown, the second determining module 303 is specifically used to: calculate multiple charging costs corresponding to the charging period using the following formula:
[0109]
[0110] Where f is the charging cost corresponding to the charging period, R is the SOC-energy conversion factor, M is the number of time periods included in the charging period, and price i Let x be the electricity price corresponding to the i-th time period. i,j Let ΔSOC be the number of target batteries corresponding to the j-th SOC gradient in the i-th time period. j Let N be the SOC change during each battery charging process in the j-th SOC gradient, N be the number of SOC gradients corresponding to each time period, U be the number of charging bays, and x be the number of charging bays. i,N Let be the target number of batteries in the i-th time period that have the maximum SOC gradient, need i+1 This represents the battery demand in the (i+1)th time period.
[0111] Determine the lowest charging cost among multiple charging costs.
[0112] In one implementation, the difference between the target total number of batteries and the total number of batteries required is less than or equal to a first threshold, such as... Figure 3 As shown, the charging control device 30 further includes: a first calculation module 305, used to calculate the total number of target batteries corresponding to the maximum SOC gradient based on the sum of the number of target batteries at the maximum SOC gradient in each time period;
[0113] The second calculation module 306 is used to calculate the total number of batteries required for each charging period based on the battery demand for each time period.
[0114] In one implementation, in two adjacent time periods, the number of target batteries in the first SOC gradient in the earlier time period is less than or equal to the number of target batteries in the second SOC gradient in the later time period; wherein, the first SOC gradient is any one of a plurality of SOC gradients, and the maximum SOC of the first SOC gradient and the minimum SOC of the second SOC gradient are continuous.
[0115] In one implementation, such as Figure 3 As shown, the device 30 also includes a third calculation module 307, which is used to obtain multiple consecutive SOC gradients based on the duration of each time period and the charging rate of each charging compartment.
[0116] In one implementation, the charging period is from 0:00 to 24:00 every day, and each time period lasts for 10 minutes.
[0117] Based on the same technical concept, this application provides a computer device, such as... Figure 4 As shown, the computer device 40 includes: a processor 401 and a memory 402 storing computer program instructions;
[0118] When the processor 401 executes computer program instructions, it implements some or all of the charging control methods in this application.
[0119] This application provides a readable storage medium storing computer program instructions, which, when executed by a processor, implement a charging control method as described in any of the first aspects.
[0120] This application also provides a computer-readable storage medium storing computer program instructions; when executed by a processor, the computer program instructions implement the charging control method provided in this application.
[0121] Furthermore, in conjunction with the charging control method, apparatus, and readable storage medium described in the above embodiments, this application can provide a computer program product for implementation. When the instructions in the computer program product are executed by the processor of a computer device, the computer device performs any of the charging control methods described in the above embodiments.
[0122] The foregoing flowcharts and / or block diagrams of charging control methods, charging control devices, computer equipment, storage media, and computer program products according to embodiments of the present disclosure have described various aspects of the present disclosure. It should be understood that each block in the flowcharts and / or block diagrams, and combinations of blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to create a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowcharts and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by dedicated hardware performing the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.
[0123] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.
Claims
1. A charging control method, characterized in that, The method includes: The charging period is divided into multiple equal and continuous time periods, wherein the electricity price remains unchanged in each time period, and each time period corresponds to multiple consecutive remaining power SOC gradients. Based on at least one historical battery swapping order, the battery demand quantity for each time period is determined, wherein each historical battery swapping order represents the correspondence between each time period and the battery demand quantity; Based on the electricity price corresponding to each time period, the SOC change corresponding to each SOC gradient, and the number of target batteries that need to be charged within each SOC gradient, the minimum charging cost corresponding to the charging period is determined. In two adjacent time periods, the number of target batteries at the maximum SOC gradient in the earlier time period is greater than or equal to the battery demand in the later time period, and the sum of the number of target batteries in each time period is less than or equal to the number of charging bays. Based on the correspondence between the time period corresponding to the lowest charging cost, the SOC gradient, and the target number of batteries, the received batteries are charged.
2. The charging control method according to claim 1, characterized in that, The process of determining the minimum charging cost corresponding to each charging period based on the electricity price for each time period, the SOC change for each SOC gradient, and the number of target batteries requiring charging within each SOC gradient includes: The multiple charging costs corresponding to the charging period are calculated using the following formula: Where f is the charging cost corresponding to the charging period, R is the SOC-energy conversion factor, M is the number of time periods included in the charging period, and price i Let x be the electricity price corresponding to the i-th time period. i,j The target battery number corresponding to the SOC gradient in the i-th time period and the j-th time interval, ΔSOC j Let N be the SOC change during each battery charging process in the j-th SOC gradient, N be the number of SOC gradients corresponding to each time period, U be the number of charging bays, and x be the number of charging bays. i,N The number of target batteries in the i-th time period that are at the maximum SOC gradient, need i+1 The battery demand during the (i+1)th time period; Determine the lowest charging cost among the plurality of charging costs.
3. The charging control method according to claim 1, characterized in that, The method further includes: where the difference between the target total number of batteries and the total number of batteries required is less than or equal to a preset threshold. Based on the sum of the number of target batteries at the maximum SOC gradient in each time period, calculate the total number of target batteries corresponding to the maximum SOC gradient; Based on the battery demand corresponding to each time period, calculate the total battery demand corresponding to the charging period.
4. The charging control method according to any one of claims 1-3, characterized in that, In two adjacent time periods, the number of target batteries in the first SOC gradient in the earlier time period is less than or equal to the number of target batteries in the second SOC gradient in the later time period; wherein, the first SOC gradient is any one of the plurality of SOC gradients, and the maximum SOC of the first SOC gradient and the minimum SOC of the second SOC gradient are continuous.
5. The charging control method according to claim 1, characterized in that, The method further includes: Based on the duration of each time period and the charging rate of each charging compartment, multiple consecutive SOC gradients are obtained.
6. The charging control method according to claim 1, characterized in that, The charging period is from 0:00 to 24:00 every day, and each time period lasts for 10 minutes.
7. A charging control device, characterized in that, The device includes: The processing module is used to divide the charging period into multiple equal and continuous time periods, wherein the electricity price remains unchanged in each time period, and each time period corresponds to multiple continuous remaining power SOC gradients. The first determining module is used to determine the battery demand quantity for each time period based on at least one historical battery swapping order, wherein each historical battery swapping order represents the correspondence between each time period and the battery demand quantity; The second determining module is used to determine the minimum charging cost corresponding to the charging period based on the electricity price corresponding to each time period, the SOC change corresponding to each SOC gradient, and the number of target batteries that need to be charged within each SOC gradient. In two adjacent time periods, the number of target batteries at the maximum SOC gradient in the earlier time period is greater than or equal to the battery demand in the later time period, and the sum of the number of target batteries in each time period is less than or equal to the number of charging bays. The charging control module is used to charge the received battery based on the correspondence between the time period corresponding to the lowest charging cost, the SOC gradient, and the target number of batteries.
8. A computer device, characterized in that, Computer equipment includes: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, it implements the charging control measurement method as described in any one of claims 1 to 6.
9. A readable storage medium, characterized in that, The readable storage medium stores computer program instructions that, when executed by a processor, implement the charging control method as described in any one of claims 1 to 6.
10. A computer program product, characterized in that, When the instructions in the computer program product are executed by the processor of the computer device, the computer device performs the charging control method as described in any one of claims 1 to 6.