Battery number configuration method and device, storage medium and battery replacement device

Abstract

The application discloses a battery quantity configuration method and device, a storage medium and a battery replacement equipment, wherein the battery quantity configuration method is applied to the battery replacement station, and the battery quantity configuration method comprises the following steps: obtaining historical operation data sets of the battery replacement station; dividing the historical operation data sets into historical operation data subsets corresponding to multiple time periods; determining an operation load rate maximum value of the battery replacement station in a current time period according to the historical operation data subset corresponding to the current time period; obtaining a battery position quantity and a current available battery quantity of the battery replacement station; and determining a battery configuration quantity in the current time period according to the operation load rate maximum value in the current time period, the battery position quantity and the current available battery quantity. Therefore, accurate prediction and automatic scheduling of battery management can be realized, the scientificity of battery configuration and operation efficiency are significantly improved, operation cost is significantly reduced, and smooth transition and efficient utilization of battery resources are ensured.

Description

Technical Field

[0001] This invention relates to the field of battery quantity configuration technology in battery swapping stations, and more particularly to a battery quantity configuration method, a computer-readable storage medium, a battery quantity configuration device, and a battery swapping equipment. Background Technology

[0002] In the operation of electric vehicle charging and battery swapping stations, battery management and scheduling constitute a core technical challenge. With the booming development of the electric vehicle market, the number of battery swapping stations continues to rise. How to scientifically and rationally allocate and schedule batteries within the stations to ensure a dynamic balance between battery swapping demand and battery supply has become a key factor affecting operational efficiency and user experience.

[0003] Most battery swapping stations rely heavily on manual experience for battery configuration and scheduling. Managers manually adjust the quantity and distribution of batteries based on their intuitive understanding of the business and long-term experience. While this traditional method can maintain basic operations in the short term, its significant drawback lies in the lack of systematic and intelligent data analysis support. Therefore, battery configuration often remains unstable, making it difficult to adjust flexibly according to real-time swapping demand and operational load. This not only leads to severe resource waste but also increases operational risks and uncertainties.

[0004] Among the related technologies, a dynamic scheduling system based on machine learning is used to achieve more accurate prediction and scheduling by collecting and analyzing a large amount of real-time data. However, the implementation of related solutions is often accompanied by high cost investment, including complex hardware support systems and high-precision data acquisition and analysis systems, which undoubtedly increases the operational burden of battery swapping stations. Summary of the Invention

[0005] This invention aims to at least partially solve one of the technical problems in related technologies. Therefore, the first objective of this invention is to propose a method for configuring the number of batteries, which enables accurate prediction and automated scheduling of battery management, significantly improves the scientific nature and operational efficiency of battery configuration, significantly reduces operating costs, and ensures a smooth transition and efficient utilization of battery resources.

[0006] A second objective of this invention is to provide a computer-readable storage medium.

[0007] A third objective of this invention is to provide a battery quantity configuration device.

[0008] The fourth objective of this invention is to provide a battery swapping device.

[0009] To achieve the above objectives, a first aspect of the present invention proposes a method for configuring the number of batteries, which is applied to a battery swapping station. The method includes: acquiring a historical operation dataset of the battery swapping station; dividing the historical operation dataset into multiple historical operation data subsets corresponding to different time periods; determining the maximum operating load rate of the battery swapping station in the current time period based on the historical operation data subset corresponding to the current time period; acquiring the number of battery bays and the number of batteries currently available for shipment from the battery swapping station; and determining the battery configuration quantity for the current time period based on the maximum operating load rate, the number of battery bays, and the number of batteries currently available for shipment.

[0010] According to the battery quantity configuration method of this invention, historical operation datasets of battery swapping stations are acquired and divided into subsets corresponding to multiple time periods. The maximum operating load rate of the battery swapping station in the current time period is determined based on the subset of historical operation data corresponding to the current time period. The number of battery bays and the number of batteries currently available for shipment at the battery swapping station are then obtained. Finally, the battery configuration quantity for the current time period is determined based on the maximum operating load rate, the number of battery bays, and the number of batteries currently available for shipment. This enables accurate prediction and automated scheduling of battery management, significantly improves the scientific nature and operational efficiency of battery configuration, significantly reduces operating costs, and ensures a smooth transition and efficient utilization of battery resources.

[0011] In addition, the battery quantity configuration method according to the above embodiments of the present invention may further include the following additional technical features:

[0012] According to one embodiment of the present invention, the subset of historical operational data includes the number of historical battery swapping orders and the number of historically available batteries at the battery swapping station.

[0013] According to one embodiment of the present invention, determining the maximum operating load rate of the battery swapping station in the current time period based on a subset of historical operating data corresponding to the current time period includes: determining the set of operating load rates corresponding to the current time period based on the number of historical battery swapping orders and the number of historical batteries available for shipment; calculating the average value and standard deviation of the set of operating load rates; and determining the maximum operating load rate of the battery swapping station in the current time period based on the average value and the standard deviation.

[0014] According to one embodiment of the present invention, after obtaining the historical operation dataset of the battery swapping station, the method includes: cleaning the historical operation dataset to filter out invalid historical battery swapping orders and data corresponding to historical batteries that can be shipped out of the warehouse with a SOC less than a preset SOC threshold.

[0015] According to one embodiment of the present invention, determining the battery configuration quantity for the current period based on the maximum operating load rate of the current period, the number of battery storage spaces, and the number of batteries currently available for shipment includes: determining a suggested battery quantity for the current period based on the maximum operating load rate of the current period, the number of battery storage spaces, and the number of batteries currently available for shipment; calculating a first difference between the suggested battery quantity and the number of batteries currently available for shipment; and determining the battery configuration quantity for the current period based on the suggested battery quantity, the number of batteries currently available for shipment, and the first difference.

[0016] According to one embodiment of the present invention, determining the recommended battery quantity for the current period based on the maximum operating load rate of the current period, the number of battery storage units, and the number of batteries currently available for shipment includes: calculating the recommended battery quantity to be corrected for the current period based on the maximum operating load rate of the current period and the number of batteries currently available for shipment; and correcting the recommended battery quantity to be corrected based on the number of battery storage units to obtain the recommended battery quantity.

[0017] According to one embodiment of the present invention, correcting the suggested number of batteries to be corrected based on the number of battery compartments includes: if the suggested number of batteries to be corrected is greater than or equal to the number of battery compartments, then assigning a value to the suggested number of batteries based on the number of battery compartments; if the suggested number of batteries to be corrected is less than the number of battery compartments, then assigning a value to the suggested number of batteries based on the suggested number of batteries to be corrected.

[0018] According to one embodiment of the present invention, determining the battery configuration quantity for the current period based on the suggested battery quantity, the current available battery quantity, and the first difference includes: if the suggested battery quantity is greater than or equal to the current available battery quantity, then assigning a value to the battery configuration quantity for the current period based on the suggested battery quantity; if the suggested battery quantity is less than the current available battery quantity, then judging the current available battery quantity and the first difference; if the current available battery quantity of a preset multiple is greater than or equal to the first difference, then assigning a value to the battery configuration quantity for the current period based on the suggested battery quantity, wherein the preset multiple is a positive number less than one; if the current available battery quantity of the preset multiple is less than the first difference, then calculating the battery configuration quantity for the current period based on a preset model.

[0019] According to one embodiment of the present invention, the preset model is:

[0020] Y = ceil(a*s_n + b*now_b)

[0021] Where Y represents the number of batteries configured in the current time period, s_n represents the suggested number of batteries, now_b represents the number of batteries that can be shipped out at present, and a and b represent model parameters, the magnitude of which is related to the magnitude of the number of batteries that can be shipped out at present.

[0022] To achieve the above objectives, a second aspect of the present invention provides a computer-readable storage medium storing a battery quantity configuration program thereon, which, when executed by a processor, implements the battery quantity configuration method of the aforementioned embodiments of the present invention.

[0023] According to embodiments of the present invention, a computer-readable storage medium, by executing a battery quantity configuration program through a processor, can achieve accurate prediction and automated scheduling of battery management, significantly improve the scientific nature and operational efficiency of battery configuration, significantly reduce operating costs, and ensure a smooth transition and efficient utilization of battery resources.

[0024] To achieve the above objectives, a third aspect of the present invention provides a battery quantity configuration device, which is applied to a battery swapping station. The device includes: a first acquisition module for acquiring historical operation datasets of the battery swapping station; a processing module for dividing the historical operation datasets into multiple historical operation data subsets corresponding to different time periods; a first determination module for determining the maximum operating load rate of the battery swapping station in the current time period based on the historical operation data subsets corresponding to the current time period; a second acquisition module for acquiring the number of battery bays and the number of batteries currently available for shipment at the battery swapping station; and a second determination module for determining the battery configuration quantity for the current time period based on the maximum operating load rate, the number of battery bays, and the number of batteries currently available for shipment.

[0025] According to an embodiment of the present invention, a battery quantity configuration device acquires historical operation datasets of a battery swapping station through a first acquisition module, divides the historical operation datasets into multiple historical operation data subsets corresponding to different time periods through a processing module, and then determines the maximum operating load rate of the battery swapping station in the current time period through a first determination module based on the historical operation data subset corresponding to the current time period. A second acquisition module acquires the number of battery bays and the number of batteries currently available for shipment from the battery swapping station, and then the second determination module determines the battery configuration quantity for the current time period based on the maximum operating load rate, the number of battery bays, and the number of batteries currently available for shipment. This enables accurate prediction and automated scheduling of battery management, significantly improves the scientific nature and operational efficiency of battery configuration, significantly reduces operating costs, and ensures a smooth transition and efficient utilization of battery resources.

[0026] To achieve the above objectives, a fourth aspect of the present invention provides a battery swapping device, including a battery quantity configuration device as described in the foregoing embodiments of the present invention.

[0027] According to the vehicle of the present invention, by adopting the battery quantity configuration device of the above embodiments of the present invention, accurate prediction and automated scheduling of battery management can be achieved, significantly improving the scientific nature and operational efficiency of battery configuration, significantly reducing operating costs, and ensuring a smooth transition and efficient utilization of battery resources.

[0028] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0029] Figure 1 This is a flowchart illustrating a method for configuring the number of batteries according to an embodiment of the present invention;

[0030] Figure 2 This is a flowchart illustrating a method for configuring the number of batteries according to another embodiment of the present invention;

[0031] Figure 3 This is a flowchart illustrating a method for configuring the number of batteries according to yet another embodiment of the present invention;

[0032] Figure 4 This is a flowchart illustrating a method for configuring the number of batteries according to another embodiment of the present invention;

[0033] Figure 5 This is a flowchart illustrating a method for configuring the number of batteries according to a specific embodiment of the present invention;

[0034] Figure 6 This is a block diagram of a battery quantity configuration device according to an embodiment of the present invention;

[0035] Figure 7 This is a block diagram of a power swapping device according to an embodiment of the present invention. Detailed Implementation

[0036] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0037] The following description, with reference to the accompanying drawings, outlines an embodiment of the present invention, including a method for configuring the number of batteries, a computer-readable storage medium, a device for configuring the number of batteries, and a battery swapping device.

[0038] Figure 1 This is a flowchart illustrating a method for configuring the number of batteries according to an embodiment of the present invention.

[0039] Specifically, in some embodiments of the present invention, the battery quantity configuration method is applied to battery swapping stations, such as... Figure 1 As shown, the configuration method for the number of batteries includes:

[0040] S101, Obtain the historical operation dataset of the battery swapping station.

[0041] Specifically, in this embodiment, the historical operation dataset of the battery swapping station can be obtained from the station's storage system. For example, historical operation data within three months can be obtained. Furthermore, the present invention does not specifically limit the method of obtaining historical operation data.

[0042] S102 divides the historical operation dataset into subsets of historical operation data corresponding to multiple time periods.

[0043] Specifically, in this embodiment, the historical operation dataset can be divided into multiple historical operation data subsets corresponding to different time periods. For example, the historical operation dataset can be divided into 48 historical operation data subsets corresponding to different time periods each day, at a frequency of 30 minutes per day. Here, the present invention does not specifically limit the specific method of division. The historical operation data subsets include the number of historical battery swapping orders and the number of historically available batteries at the battery swapping station.

[0044] S103, determine the maximum operating load rate of the battery swapping station in the current period based on the subset of historical operating data corresponding to the current period.

[0045] Specifically, in this embodiment, the historical operation data subset includes the historical number of battery swapping orders and the historical number of batteries available for shipment at the battery swapping station. The set of operating load rates corresponding to the current time period is determined based on the historical number of battery swapping orders and the historical number of batteries available for shipment. The average value and standard deviation of the set of operating load rates are calculated. The maximum operating load rate of the battery swapping station in the current time period is determined based on the average value and standard deviation.

[0046] S104: Obtain the number of battery compartments and the number of batteries that can be dispensed from the battery swapping station.

[0047] Specifically, in this embodiment, the number of battery compartments and the number of batteries currently available for shipment at a battery swapping station can be obtained by querying the system database. Furthermore, the present invention does not impose specific limitations on the method of obtaining the number of battery compartments and the number of batteries currently available for shipment at a battery swapping station.

[0048] S105, determine the battery configuration quantity for the current period based on the maximum operating load rate, the number of battery storage spaces, and the number of batteries currently available for shipment.

[0049] Specifically, in this embodiment, the recommended number of batteries to be corrected for the current period is calculated based on the maximum operating load rate and the current number of batteries available for delivery. The recommended number of batteries to be corrected is then adjusted according to the number of battery storage spaces to obtain the recommended number of batteries. A first difference between the recommended number of batteries and the current number of batteries available for delivery is calculated. If the recommended number of batteries is greater than or equal to the current number of batteries available for delivery, the battery configuration quantity for the current period is assigned a value based on the recommended number of batteries. If the recommended number of batteries is less than the current number of batteries available for delivery, the current number of batteries available for delivery and the first difference are compared. If the current number of batteries available for delivery is greater than or equal to the first difference by a preset multiple, the battery configuration quantity for the current period is assigned a value based on the recommended number of batteries. Here, the preset multiple is a positive number less than one. If the current number of batteries available for delivery by the preset multiple is less than the first difference, the battery configuration quantity for the current period is calculated according to a preset model.

[0050] Furthermore, in some embodiments of the present invention, such as Figure 2 As shown, the maximum operating load rate of the battery swapping station in the current time period is determined based on a subset of historical operating data corresponding to the current time period, including:

[0051] S201, determine the set of operating load rates corresponding to the current period based on the number of historical battery swapping orders and the number of historically available batteries.

[0052] Specifically, in this embodiment, the historical operation dataset can be divided into multiple historical operation data subsets corresponding to different time periods. These subsets include the historical number of battery swapping orders and the historical number of batteries available for shipment at the battery swapping station. For example, the historical operation dataset can be divided according to a time dimension, such as a frequency of 30 minutes per day, resulting in 48 time periods per day. For each time period, a corresponding historical operation data subset is constructed, containing the historical number of battery swapping orders and the historical number of batteries available for shipment within that time period. If the current time period is the first time period of the day, the set of operational load rates corresponding to the current time period can be determined based on the historical number of battery swapping orders and the historical number of batteries available for shipment within the first time period of the day. It should be noted that the operational load rate corresponding to the current time period = (historical number of battery swapping orders in the current time period / historical number of batteries available for shipment in the current time period) × 100%. If 100 days of data are obtained, 100 operational load rates can be calculated, and these operational load rates constitute the set of operational load rates corresponding to the current time period.

[0053] S202 calculates the mean and standard deviation of the set of operating load rates.

[0054] Specifically, in this embodiment, after determining the set of operating load rates corresponding to the current time period based on the number of historical battery swapping orders and the number of historically available batteries, the average value and standard deviation of the set of operating load rates can be calculated using the following formula.

[0055]

[0056] Where μ represents the average of all operating load rates in the set of operating load rates, n represents the number of operating load rates in the set of operating load rates, and x i This represents each operating load rate in the set of operating load rates.

[0057]

[0058] Where σ represents the standard deviation, n represents the number of operating load rates in the set of operating load rates, and x i Let μ represent each operating load rate in the set of operating load rates, and let μ represent the average value of all operating load rates in the set of operating load rates.

[0059] S203, determine the maximum operating load rate of the battery swapping station for the current period based on the average value and standard deviation.

[0060] Specifically, in this embodiment, after calculating the average and standard deviation of the set of operating load rates, the maximum operating load rate of the battery swapping station in the current time period can be determined by the following formula:

[0061] η max =μ+3*σ;

[0062] Where, η max σ represents the maximum operating load rate, μ represents the average of all operating load rates in the set of operating load rates, and σ represents the standard deviation.

[0063] Furthermore, in some embodiments of the present invention, after obtaining the historical operation dataset of the battery swapping station, the process includes: cleaning the historical operation dataset to filter out invalid historical battery swapping orders and data corresponding to historical batteries that can be shipped out of the warehouse with a SOC less than a preset SOC threshold.

[0064] Specifically, in this embodiment, invalid orders include duplicate orders, cancelled orders, and abnormal orders caused by system failures or other reasons. Through algorithmic and rule-based matching, these invalid orders are identified and removed, ensuring that the dataset contains only genuine and valid battery swapping orders. The preset SOC threshold can preferably be set to 90%. All historical battery data with an SOC below 90% is identified as unqualified and removed, ensuring that the dataset contains only battery data with sufficient charge to meet battery swapping needs. Furthermore, this invention does not specifically limit the method for filtering invalid historical battery swapping orders and the data corresponding to historical batteries with an SOC below the preset SOC threshold, nor does it limit the value of the SOC threshold.

[0065] Furthermore, in some embodiments of the present invention, such as Figure 3 As shown, the battery configuration quantity for the current period is determined based on the maximum operating load rate, the number of battery storage spaces, and the current number of batteries available for shipment. This includes:

[0066] S301 determines the recommended number of batteries for the current period based on the maximum operating load rate, the number of battery storage spaces, and the number of batteries currently available for shipment.

[0067] Specifically, in this embodiment, the product of the maximum operating load rate for the current period and the current number of batteries available for delivery is calculated. If the product is less than the number of battery storage spaces, the recommended number of batteries is assigned based on the product. If the product is greater than or equal to the number of battery storage spaces, the recommended number of batteries is assigned based on the number of battery storage spaces.

[0068] S302, calculate the first difference between the recommended number of batteries and the current number of batteries available for shipment.

[0069] Specifically, in this embodiment, the first difference can be obtained by subtracting the current number of batteries that can be shipped from the recommended number of batteries.

[0070] S303 determines the battery configuration quantity for the current period based on the recommended battery quantity, the current number of batteries available for shipment, and the first difference.

[0071] Specifically, in this embodiment, if the suggested battery quantity is greater than or equal to the current available battery quantity, the battery configuration quantity for the current period is assigned a value based on the suggested battery quantity. If the suggested battery quantity is less than the current available battery quantity, a judgment is made between the current available battery quantity and a first difference. If the current available battery quantity with a preset multiple is greater than or equal to the first difference, the battery configuration quantity for the current period is assigned a value based on the suggested battery quantity. The preset multiple is a positive number less than one, and is preferably 0.2 times. If the current available battery quantity with the preset multiple is less than the first difference, the battery configuration quantity for the current period is calculated according to a preset model.

[0072] Furthermore, in some embodiments of the present invention, such as Figure 4 As shown, the recommended number of batteries for the current period is determined based on the maximum operating load rate, the number of battery storage spaces, and the current number of batteries available for shipment. This includes:

[0073] S401, calculate the recommended number of batteries to be corrected for the current period based on the maximum operating load rate for the current period and the current number of batteries available for shipment.

[0074] Specifically, in this embodiment, the number of batteries to be corrected is equal to the product of the maximum operating load rate for the current period and the current number of batteries available for shipment.

[0075] S402, adjust the recommended number of batteries to be corrected based on the number of battery compartments to obtain the recommended number of batteries.

[0076] Specifically, in this embodiment, if the number of batteries to be corrected is greater than or equal to the number of battery compartments, the number of batteries to be corrected is assigned a value based on the number of battery compartments; if the number of batteries to be corrected is less than the number of battery compartments, the number of batteries to be corrected is assigned a value based on the number of batteries to be corrected.

[0077] Furthermore, in some embodiments of the present invention, the preset model of the battery quantity configuration method is as follows:

[0078] Y = ceil(a*s_n + b*now_b)

[0079] Where Y represents the number of batteries configured in the current time period, s_n represents the suggested number of batteries, now_b represents the number of batteries that can be shipped out at present, a and b represent the model parameters respectively, the size of the model parameters is related to the size of the number of batteries that can be shipped out at present, and ceil() represents the rounding up function.

[0080] Furthermore, in one specific embodiment of the present invention, such as Figure 5As shown, after obtaining the suggested number of batteries to be corrected for the current period, the suggested number of batteries to be corrected and the number of battery storage slots are compared. If the suggested number of batteries to be corrected is greater than or equal to the number of battery storage slots, the suggested number of batteries is assigned a value based on the number of battery storage slots. If the suggested number of batteries to be corrected is less than the number of battery storage slots, the suggested number of batteries is assigned a value based on the suggested number of batteries to be corrected. Then, the suggested number of batteries and the number of batteries currently available for distribution are compared. If the suggested number of batteries is greater than or equal to the number of batteries currently available for distribution, the battery configuration quantity for the current period is assigned a value based on the suggested number of batteries. If the suggested number of batteries is less than the number of batteries currently available for distribution, the current available battery quantity with a preset multiple and a first difference are compared. If the current available battery quantity with the preset multiple is greater than or equal to the first difference, the battery configuration quantity for the current period is assigned a value based on the suggested number of batteries. If the current available battery quantity with the preset multiple is less than the first difference, the battery configuration quantity for the current period is calculated according to a preset model. The preset multiple can preferably be 0.2 times, and the preset model is as follows:

[0081] Y = ceil(a*s_n + b*now_b)

[0082] Where Y represents the current battery configuration quantity, s_n represents the suggested battery quantity, now_b represents the current available battery quantity, and a and b represent model parameters, the magnitude of which is related to the current available battery quantity. If the current available battery quantity is greater than or equal to the preset quantity, then a can be preferably 0.75 and b can be preferably 0.2; if the current available battery quantity is less than the preset quantity, then a can be preferably 0.6 and b can be preferably 0.32. The preset quantity can be preferably 5. It should be noted that... Figure 5 In this context, s_n1 represents the suggested number of batteries to be corrected, s_n represents the suggested number of batteries, M represents the number of battery slots, now_b represents the number of batteries currently available for distribution, st_n represents the number of batteries currently available for distribution at a preset multiple, co_n represents the first difference between the suggested number of batteries and the number of batteries currently available for distribution, and ceil() represents the round-up function.

[0083] In summary, the battery quantity configuration method according to embodiments of the present invention acquires historical operation datasets of the battery swapping station, divides these datasets into subsets corresponding to multiple time periods, and then determines the maximum operating load rate of the battery swapping station in the current time period based on the subset of historical operation data corresponding to the current time period. This allows for the acquisition of the number of battery bays and the number of batteries currently available for shipment at the battery swapping station. Finally, based on the maximum operating load rate, the number of battery bays, and the number of batteries currently available for shipment, the battery configuration quantity for the current time period is determined. This enables accurate prediction and automated scheduling of battery management, significantly improves the scientific nature and operational efficiency of battery configuration, significantly reduces operating costs, and ensures a smooth transition and efficient utilization of battery resources.

[0084] Based on the battery quantity configuration method proposed in the foregoing embodiments of the present invention, the present invention also proposes a computer-readable storage medium storing a battery quantity configuration program thereon. When the battery quantity configuration program is executed by a processor, it implements the battery quantity configuration method of the above embodiments of the present invention.

[0085] According to embodiments of the present invention, a computer-readable storage medium, by executing a battery quantity configuration program through a processor, can achieve accurate prediction and automated scheduling of battery management, significantly improve the scientific nature and operational efficiency of battery configuration, significantly reduce operating costs, and ensure a smooth transition and efficient utilization of battery resources.

[0086] Figure 6 This is a block diagram of a battery quantity configuration device according to an embodiment of the present invention.

[0087] Specifically, battery quantity configuration devices are used in battery swapping stations, such as... Figure 3 As shown, the battery quantity configuration device 100 includes a first acquisition module 10, a processing module 20, a first determination module 30, a second acquisition module 40, and a second determination module 50.

[0088] The first acquisition module 10 is used to acquire the historical operation dataset of the battery swapping station; the processing module 20 is used to divide the historical operation dataset into multiple historical operation data subsets corresponding to different time periods; the first determination module 30 is used to determine the maximum operating load rate of the battery swapping station in the current time period based on the historical operation data subset corresponding to the current time period; the second acquisition module 40 is used to acquire the number of battery bays and the number of batteries that can be shipped out at the current time period; and the second determination module 50 is used to determine the number of batteries configured in the current time period based on the maximum operating load rate, the number of battery bays, and the number of batteries that can be shipped out at the current time period.

[0089] In some embodiments of the present invention, the subset of historical operational data includes the number of historical battery swapping orders and the number of historical batteries available for shipment at the battery swapping station.

[0090] In some embodiments of the present invention, the first determining module 30 is specifically used to determine the set of operating load rates corresponding to the current time period based on the number of historical battery swapping orders and the number of historical batteries available for shipment; calculate the average value and standard deviation of the set of operating load rates; and determine the maximum value of the operating load rate of the battery swapping station in the current time period based on the average value and standard deviation.

[0091] In some embodiments of the present invention, the processing module 20 is also used to clean the historical operation dataset to filter out invalid historical battery swapping orders and data corresponding to historical batteries that can be shipped out of the warehouse with a SOC less than a preset SOC threshold.

[0092] In some embodiments of the present invention, the second determining module 50 is specifically used to determine the recommended number of batteries for the current period based on the maximum operating load rate, the number of battery bays, and the number of batteries that can be shipped out at the current time; calculate the first difference between the recommended number of batteries and the number of batteries that can be shipped out at the current time; and determine the battery configuration number for the current period based on the recommended number of batteries, the number of batteries that can be shipped out at the current time, and the first difference.

[0093] In some embodiments of the present invention, the second determining module 50 is further configured to calculate the recommended number of batteries to be corrected for the current period based on the maximum operating load rate for the current period and the current number of batteries available for delivery; and to correct the recommended number of batteries to be corrected based on the number of battery storage spaces to obtain the recommended number of batteries.

[0094] In some embodiments of the present invention, the second determining module 50 is further configured to assign a value to the battery recommendation quantity based on the number of battery compartments if the recommended number of batteries to be corrected is greater than or equal to the number of battery compartments; and to assign a value to the battery recommendation quantity based on the recommended number of batteries to be corrected if the recommended number of batteries to be corrected is less than the number of battery compartments.

[0095] In some embodiments of the present invention, the second determining module 50 is further configured to: if the suggested battery quantity is greater than or equal to the current number of batteries that can be shipped out, assign a value to the battery configuration quantity for the current period based on the suggested battery quantity; if the suggested battery quantity is less than the current number of batteries that can be shipped out, determine the current number of batteries that can be shipped out and a first difference; if the current number of batteries that can be shipped out is a preset multiple greater than or equal to the first difference, assign a value to the battery configuration quantity for the current period based on the suggested battery quantity, wherein the preset multiple is a positive number less than one; if the current number of batteries that can be shipped out is a preset multiple less than the first difference, calculate the battery configuration quantity for the current period based on a preset model.

[0096] In some embodiments of the present invention, the preset model is as follows:

[0097] Y = ceil(a*s_n + b*now_b)

[0098] Where Y represents the number of batteries configured in the current time period, s_n represents the suggested number of batteries, now_b represents the number of batteries that can be shipped out at present, and a and b represent the model parameters, the size of which is related to the size of the number of batteries that can be shipped out at present.

[0099] It should be noted that other specific implementations of the battery quantity configuration device proposed in the embodiments of the present invention can be found in the specific implementations of the battery quantity configuration method described in the foregoing embodiments of the present invention. To reduce redundancy, they will not be repeated here.

[0100] In summary, the battery quantity configuration device according to embodiments of the present invention acquires historical operation datasets of the battery swapping station through a first acquisition module, divides the historical operation datasets into multiple historical operation data subsets corresponding to different time periods through a processing module, and then determines the maximum operating load rate of the battery swapping station in the current time period through a first determination module based on the historical operation data subset corresponding to the current time period. The device also acquires the number of battery bays and the number of batteries currently available for shipment through a second acquisition module, and then determines the battery configuration quantity for the current time period through the second determination module based on the maximum operating load rate, the number of battery bays, and the number of batteries currently available for shipment. This enables accurate prediction and automated scheduling of battery management, significantly improves the scientific nature and operational efficiency of battery configuration, significantly reduces operating costs, and ensures a smooth transition and efficient utilization of battery resources.

[0101] Figure 7 This is a block diagram of a power swapping device according to an embodiment of the present invention.

[0102] like Figure 7 As shown, the battery swapping equipment 1000 includes a battery quantity configuration device 100 according to the above-described embodiment of the present invention.

[0103] According to the vehicle of the present invention, by adopting the battery quantity configuration device of the above embodiments of the present invention, accurate prediction and automated scheduling of battery management can be achieved, significantly improving the scientific nature and operational efficiency of battery configuration, significantly reducing operating costs, and ensuring a smooth transition and efficient utilization of battery resources.

[0104] Furthermore, other components and functions of the battery swapping equipment in this embodiment of the invention are known to those skilled in the art, and will not be described in detail here to reduce redundancy.

[0105] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0106] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0107] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0108] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this invention and simplifying the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0109] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0110] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0111] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can mean that the first feature is in direct contact with the second feature, or that the first feature is in indirect contact with the second feature through an intermediate medium. Furthermore, "above," "over," and "on top" of the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply that the first feature is at a lower horizontal level than the second feature.

[0112] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method of configuring a number of batteries, characterized by, The method is applied to a battery swap station, and the method comprises the following steps: obtaining a historical operation data set of the battery swap station; dividing the historical operation data set into historical operation data subsets corresponding to multiple time periods; determining a maximum operation load rate of the battery swap station in a current time period according to a historical operation data subset corresponding to the current time period; obtaining a number of battery bays of the battery swap station and a number of currently available batteries; determining a battery configuration number of the current time period according to the maximum operation load rate of the current time period, the number of battery bays and the number of currently available batteries; determining a battery configuration number of the current time period according to the maximum operation load rate of the current time period, the number of battery bays and the number of currently available batteries, comprising: determining a battery recommendation number of the current time period according to the maximum operation load rate of the current time period and the number of currently available batteries; calculating a first difference value of the battery recommendation number and the number of currently available batteries; determining the battery configuration number of the current time period according to the battery recommendation number, the number of currently available batteries and the first difference value; determining the battery configuration number of the current time period according to the battery recommendation number, the number of currently available batteries and the first difference value, comprising: if the battery recommendation number is greater than or equal to the number of currently available batteries, assigning the battery configuration number of the current time period according to the battery recommendation number; if the battery recommendation number is less than the number of currently available batteries, judging the number of currently available batteries and the first difference value; if a preset multiple of the number of currently available batteries is greater than or equal to the first difference value, assigning the battery configuration number of the current time period according to the battery recommendation number, wherein the preset multiple is a positive number less than one; if a preset multiple of the number of currently available batteries is less than the first difference value, calculating the battery configuration number of the current time period according to a preset model.

2. The method of claim 1, wherein the number of batteries is configured by: The historical operation data subset comprises a historical number of battery swap orders and a historical number of available batteries of the battery swap station.

3. The method of claim 2, wherein the number of batteries is configured by: Determining the maximum operation load rate of the battery swap station in the current time period according to the historical operation data subset corresponding to the current time period, comprising: determining an operation load rate set corresponding to the current time period according to the historical number of battery swap orders and the historical number of available batteries; calculating a mean value and a standard deviation of the operation load rate set; determining the maximum operation load rate of the battery swap station in the current time period according to the mean value and the standard deviation.

4. The method of claim 2, wherein the number of batteries is configured by: After obtaining the historical operation data set of the battery swap station, comprising: cleaning the historical operation data set to filter out data corresponding to invalid historical battery swap orders and historical available batteries with a SOC less than a preset SOC threshold.

5. The method of claim 1, wherein the number of batteries is configured by: Determining the battery recommendation number of the current time period according to the maximum operation load rate of the current time period, the number of battery bays and the number of currently available batteries, comprising: calculating a to-be-corrected battery recommendation number of the current time period according to the maximum operation load rate of the current time period and the number of currently available batteries; The battery suggestion quantity to be corrected is corrected according to the battery position quantity to obtain the battery suggestion quantity.

6. The method of claim 5, wherein the number of batteries is configured by: The battery suggestion quantity to be corrected is corrected according to the battery position quantity, including: If the battery suggestion quantity to be corrected is greater than or equal to the battery position quantity, the battery suggestion quantity is assigned according to the battery position quantity; If the battery suggestion quantity to be corrected is less than the battery position quantity, the battery suggestion quantity is assigned according to the battery suggestion quantity to be corrected.

7. The method of claim 1, wherein the number of batteries is configured by a user. The preset model is: Wherein, Y represents the battery configuration quantity of the current period, s_n represents the battery suggestion quantity, now_b represents the current battery quantity available for delivery, and a and b respectively represent model parameters, the size of the model parameters being related to the size of the current battery quantity available for delivery.

8. A computer-readable storage medium, characterized in that, A processor executes the battery quantity configuration program stored on the storage medium to implement the battery quantity configuration method according to any one of claims 1-7.

9. A battery number configuration device, characterized by comprising: The device is applied to a battery swap station, and the device includes: A first obtaining module configured to obtain a historical operation data set of the battery swap station; A processing module configured to divide the historical operation data set into historical operation data subsets corresponding to multiple periods; A first determining module configured to determine a maximum operation load rate of the battery swap station in a current period according to a historical operation data subset corresponding to the current period; A second obtaining module configured to obtain a battery position quantity and a current battery quantity available for delivery of the battery swap station; A second determining module configured to determine a battery configuration quantity of the current period according to the maximum operation load rate of the current period, the battery position quantity, and the current battery quantity available for delivery; The second determining module is further configured to determine a battery suggestion quantity of the current period according to the maximum operation load rate of the current period, the battery position quantity, and the current battery quantity available for delivery; calculate a first difference between the battery suggestion quantity and the current battery quantity available for delivery; and determine the battery configuration quantity of the current period according to the battery suggestion quantity, the current battery quantity available for delivery, and the first difference. The second determining module is further configured to include: if the battery suggestion quantity is greater than or equal to the current battery quantity available for delivery, assigning the battery configuration quantity of the current period according to the battery suggestion quantity; if the battery suggestion quantity is less than the current battery quantity available for delivery, judging the current battery quantity available for delivery and the first difference; if a preset multiple of the current battery quantity available for delivery is greater than or equal to the first difference, assigning the battery configuration quantity of the current period according to the battery suggestion quantity, wherein the preset multiple is a positive number less than one; and if the preset multiple of the current battery quantity available for delivery is less than the first difference, calculating the battery configuration quantity of the current period according to a preset model.

10. A battery replacing device characterized by comprising: The battery quantity configuration device of claim 9 is included.

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