Mobile battery replacement energy storage data control method based on artificial intelligence

Abstract

The invention discloses a mobile battery replacement energy storage data control method based on artificial intelligence, and particularly relates to the technical field of mobile battery replacement, and the method comprises the steps: S1, battery replacement data collection: collecting battery operation parameters and battery replacement station operation parameters; s2, battery replacement data analysis: obtaining a mobile battery replacement operation state analysis result; s3, mobile power conversion demand analysis: obtaining a mobile power conversion demand; s4, formulating an energy storage strategy: formulating the energy storage strategy of the battery swap station, and controlling an energy storage device to carry out energy storage operation; s5, monitoring the running state of the energy storage device: monitoring the running parameters of the energy storage device; s6, analyzing the running state of the energy storage device to obtain a state evaluation value of the energy storage device; and S7, dynamically adjusting the energy storage strategy: dynamically adjusting the energy storage strategy of the battery swap station. The energy supply demand of the battery swap station is monitored in real time, the charging priority of each type of battery is set, the operation state of the energy storage device in the charging process is monitored in real time, the operation difficulty and time cost of the battery swap station are effectively reduced, the overall operation efficiency is reduced, and the charging efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of mobile battery replacement technology, and more specifically, to a mobile battery replacement energy storage data control method based on artificial intelligence. Background Art

[0002] Under the general trend of global energy transformation, the electric vehicle market has shown explosive growth, and the problems of range anxiety and charging time have become increasingly prominent. The energy storage system can flexibly adjust resources and has the advantages of flexibility, scalability, environmental protection, and high efficiency. Mobile battery swapping refers to a service method of providing electric vehicles with rapid battery replacement through mobile battery swapping service vehicles. With the development of artificial intelligence technology, real-time monitoring, prediction and optimization of energy storage systems can be achieved. With the development of smart grids and energy Internet, mobile battery swapping energy storage systems, as an important part of energy Internet, work efficiently with the power grid, realize orderly charging and discharging of batteries through data control methods, optimize power grid load, and improve the operation efficiency and stability of the power grid.

[0003] However, there are still some shortcomings in its actual use. First, resources are unevenly allocated. When the energy storage priorities of the existing mobile battery swap technology are not divided, the battery swap station may not be able to reasonably allocate resources according to the battery status and needs. This may cause some batteries that urgently need to be charged to not receive timely battery swap services, while some batteries in good condition are replaced prematurely, resulting in waste of resources. Due to the lack of energy storage priority division, the operators of the battery swap station may not be able to quickly and accurately determine which batteries need to be given priority, effectively reducing the operating difficulty and time cost of the battery swap station, and reducing the overall operating efficiency.

[0004] Second, there are high safety risks. The existing mobile battery replacement technology cannot monitor charging parameters in real time, which means that it is impossible to detect abnormal conditions in the battery charging process in time, such as overcharging, over-discharging, abnormal temperature, etc. These abnormal conditions may cause battery performance to decline, shorten life, and even cause battery failure or safety accidents. If real-time monitoring is not possible, the charging process may not be able to be dynamically adjusted according to the actual state of the battery, resulting in low charging efficiency. Summary of the invention

[0005] In view of this, an embodiment of the present invention provides an artificial intelligence-based mobile battery exchange energy storage data control method, which effectively solves the problems of uneven resource allocation and high safety hazards in the existing mobile battery exchange process raised in the background technology by real-time monitoring of the energy supply demand of the battery exchange station, establishing charging priorities for various types of batteries, and real-time monitoring of the operating status of the energy storage device during the charging process.

[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a mobile battery swap energy storage data control method based on artificial intelligence, comprising a battery monitoring terminal, a battery swap station operation monitoring terminal, an energy storage device monitoring terminal, a control center and an energy storage device, wherein the battery monitoring terminal, the battery swap station operation monitoring terminal, the energy storage device monitoring terminal and the energy storage device should be arranged at the battery swap station, and specifically comprises the following steps: S1: Battery swap data collection: The battery operating parameters and battery swap station operating parameters are collected in real time through the battery monitoring terminal and the battery swap station operation monitoring terminal, and the collected data is transmitted to the control center; S2: Battery swap data analysis: The control center analyzes the real-time collected battery operating parameters and battery swap station operating parameters to obtain the mobile battery swap operating status analysis results; S3: Mobile battery swap demand analysis: The control center performs mobile battery swap demand analysis based on the mobile battery swap operation status analysis results to obtain the mobile battery swap demand; S4: Energy storage strategy formulation: The control center formulates the energy storage strategy of the battery swap station according to the mobile battery swap demand, and controls the energy storage device to perform energy storage operations; S5: Energy storage device operation status monitoring: monitor the operation parameters of the energy storage device in real time through the energy storage device monitoring terminal, and transmit the collected data to the control center; S6: Energy storage device operating status analysis: The control center analyzes the energy storage device operating parameters collected in real time to obtain the energy storage device status evaluation value; S7: Dynamically adjust the energy storage strategy: The control center dynamically adjusts the energy storage strategy of the battery swap station according to the status evaluation value of the energy storage device.

[0007] Technical effects and advantages of the present invention: 1. The present invention collects battery operating parameters and battery swap station operating parameters in real time through the battery monitoring terminal and the battery swap station operation monitoring terminal, and performs data analysis on the battery operating parameters and the battery swap station operating parameters through the control center to obtain the total amount of electricity required to be replenished in a single time interval and the priority weight coefficients corresponding to each type of battery, and accordingly sets the energy supply demand and charging priority of each type of battery in a single time interval of the battery swap station. The battery swap station can reasonably allocate resources according to the status and demand of the battery to avoid waste of resources. The operators of the battery swap station can quickly and accurately determine which batteries need to be processed first, reduce the difficulty and time cost of operation, and improve the overall operation efficiency; The present invention monitors the operating parameters of the energy storage device in real time through the energy storage device monitoring terminal, and performs data analysis on the operating parameters of the energy storage device through the control center to obtain the energy storage device state evaluation value, and establish the energy storage device state evaluation standard value, and compares the energy storage device state evaluation value with the energy storage device state evaluation standard value to judge the real-time operating state of the energy storage device, which helps to timely discover abnormal conditions in the battery charging process and reduce the possibility of safety accidents. The charging process can be dynamically adjusted according to the actual state of the battery to improve the charging efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 It is a schematic diagram of the method steps of the present invention.

[0009] Figure 2 It is a schematic diagram of the overall structure of the present invention.

[0010] Figure 3 It is a schematic diagram of the battery replacement data analysis steps of the present invention. DETAILED DESCRIPTION

[0011] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0012] As attached Figure 1 The shown method is a mobile battery swap energy storage data control method based on artificial intelligence, including a battery monitoring terminal, a battery swap station operation monitoring terminal, an energy storage device monitoring terminal, a control center and an energy storage device. The battery monitoring terminal, the battery swap station operation monitoring terminal, the energy storage device monitoring terminal and the energy storage device should be set at the battery swap station.

[0013] What needs to be specifically explained in this embodiment is that the battery monitoring terminal is used to monitor and collect battery operating parameters in real time, including the battery power, charging speed, charging efficiency, and battery quantity. Real-time collection of battery operating parameters helps ensure that the battery swap station has sufficient power reserves to maintain normal battery swap services. Excessive discharge or long periods of idleness can cause damage to the battery. By monitoring the battery power, the battery swap station can charge the battery in time when it is close to being exhausted to avoid excessive discharge. Monitoring the charging speed helps improve the efficiency of battery swapping. The battery swap station can formulate different battery swapping strategies based on the power and charging needs of different batteries.

[0014] The battery swap station operation monitoring terminal is used to monitor the operating parameters of the battery swap equipment in real time, such as the battery swap time, battery swap frequency, and number of battery swap vehicles of different battery models. It can remotely monitor and collect data of the battery swap station by establishing remote monitoring, and collect the operating parameters of the battery swap station in real time. In addition, the battery swap station operation monitoring terminal can collect some data that cannot be directly collected by sensors through manual detection and input, such as vehicle fault information, battery appearance inspection, etc., as a supplement to the operating parameters of the battery swap station, and provide more comprehensive information on the operation of the battery swap station.

[0015] The energy storage device monitoring terminal is used to monitor the operating parameters of the energy storage device in the battery swap station in real time, such as the voltage, current, power and frequency of the energy storage device. By monitoring the performance parameters of the energy storage device in real time, it is helpful to timely discover potential safety hazards such as overheating, overcharging, and over-discharging of the equipment, so as to take timely measures to avoid accidents. Monitoring the performance parameters of the energy storage device is of great significance in ensuring the safe operation of the equipment, optimizing system performance, extending the life of the equipment, supporting decision-making, and improving user experience.

[0016] The control center analyzes the data monitored and collected by the above-mentioned battery monitoring terminal, battery swap station operation monitoring terminal and energy storage device monitoring terminal, and controls the energy storage device to perform relevant operations based on the analysis results.

[0017] Energy storage devices are devices that can store electrical energy and release it when needed. Energy storage devices are usually used to store electrical energy obtained from the power grid and renewable resources, and provide electrical energy when electric vehicles need to be replaced. Energy storage devices specifically include chemical energy storage devices and physical energy storage devices. Chemical energy storage devices include lithium-ion batteries and nickel-metal hydride batteries, and physical energy storage devices include supercapacitors and flywheel batteries.

[0018] For the connection method of the above-mentioned battery monitoring terminal, battery swap station operation monitoring terminal, energy storage device monitoring terminal, control center and energy storage device, see Figure 2 .

[0019] The specific implementation of the present invention comprises the following steps: S1: Battery swap data collection: The battery operating parameters and battery swap station operating parameters are collected in real time through the battery monitoring terminal and the battery swap station operation monitoring terminal, and the collected data is transmitted to the control center.

[0020] Furthermore, the battery operating parameters collected in real time by the battery monitoring terminal include the remaining power Q, charging speed v, number of batteries n and capacity C of each battery in the battery swap station. The battery swap station operating parameters collected in real time by the battery swap station operation monitoring terminal specifically include the battery swap time t.

[0021] It should be specifically explained in this embodiment that the battery monitoring terminal in the above steps specifically refers to the battery management system (BMS) of the battery swap station. The battery management system monitors the battery charging power, battery power, expected full time and battery quantity in real time. The battery management system accurately calculates the remaining battery power through complex algorithms and sensor networks, and monitors the battery charging speed based on the data provided by the battery management system. The battery swap station operation monitoring terminal in the above steps monitors every link of the battery swap process in real time through the monitoring system of the battery swap station, including the removal of the battery, the installation of the new battery and the vehicle status monitoring. Through the time recording function of the monitoring system, the battery swap time required for each type of battery can be accurately measured.

[0022] S2: Battery swap data analysis: The control center performs data analysis on the battery operating parameters and battery swap station operating parameters collected in real time to obtain the mobile battery swap operating status analysis results.

[0023] Further, the steps of battery swap data analysis are as follows: A1: Set a time interval, monitor the number of batteries in the battery swap station in a single time interval in real time through the battery monitoring terminal, and classify the battery types, marking them as a, b and c, and count the number n of each type of battery; What needs to be specifically explained in this embodiment is that the time interval can be one day, one week and one month. By monitoring the number of batteries used for mobile battery replacement in the battery swap station within a unit time length, the electricity consumed in the battery swap station in one day can be better analyzed. It should be noted that the single time interval selected in this embodiment should be able to represent the average level of the battery swap station.

[0024] What needs to be specifically explained in this embodiment is that the type of battery configured in the battery swap station depends on the type and brand of electric vehicles served by the battery swap station. The type of battery in the battery swap station can be classified according to the voltage platform, battery type and battery capacity. According to the voltage platform, it can be specifically divided into 400V platform batteries and 800V platform batteries. The capacity of the 400V platform battery includes 70 / 75 degrees, 100 degrees and 150 degrees, which is suitable for electric vehicles on high voltage platforms, such as Weilai's NT1 / 2 series; the capacity of the 800V platform battery includes 60 degrees, 85 degrees, 102 degrees and 120 degrees, which is suitable for electric vehicles on high voltage platforms, such as Weilai's Ledao series. According to the battery type, it can be specifically divided into lithium batteries and lead-acid batteries. Lithium batteries are the type used by most battery swap stations. They have the advantages of high energy density and short charging time. They specifically include ternary lithium batteries, ternary hybrid batteries and lithium iron phosphate batteries; lead-acid batteries are traditional electric vehicle batteries and are less used. According to the battery capacity, it can be specifically divided into standard batteries, lightweight batteries and large-capacity batteries. Standard batteries are suitable for small electric vehicles to meet daily use needs; lightweight batteries are suitable for small vehicles such as light electric vehicles and folding electric vehicles to meet short-distance travel needs, and are suitable for large electric vehicles and commercial electric vehicles to meet long-distance travel and heavy-load transportation needs.

[0025] A2: Use the battery monitoring terminal to collect the remaining power Q of any battery within the time interval i , collect the charging speed v corresponding to each type of battery, and obtain the capacity C of each type of battery through the battery monitoring terminal; What needs to be specifically explained in this embodiment is that any battery within the time interval includes all batteries stored in the battery swap station for mobile battery swapping. The storage quantity of each type of battery should be related to the type of vehicle served by the battery swap station. The batteries stored in the battery swap station are set according to the demand quantity of each type of battery by the battery swap station, and each type of battery has a rated charging speed.

[0026] A3: Process and analyze the real-time collected battery swap data to obtain the total amount of electricity required to be replenished within a single time interval of the battery swap station Q s ; Furthermore, by calculating the difference between the capacity of each type of battery and the remaining power of any battery, the amount of power required to be replenished for any battery can be obtained, including Q ai , Q bi and Q ci Three types, accumulate the amount of electricity that needs to be replenished for any battery and use the formula Calculate the total amount of electricity required for a single time interval Q s , C a , C b and C c Respectively represent the capacities of three types of batteries: a, b, and c, na 、n b and n c Respectively represent the number of three types of batteries: a, b and c; What needs to be specifically explained in this embodiment is that by real-time monitoring of the remaining power of any battery swap battery within a single time interval, and using the total capacity of each type of battery swap battery to calculate the amount of power that the battery swap station needs to replenish for the battery within the time interval, it provides strong data support for the selection of charging methods in subsequent steps.

[0027] A4: The battery monitoring terminal is used to monitor the battery replacement time t required for each type of battery within a single time interval in real time, and the battery replacement data are processed to obtain the priority weight coefficient ρ of each type of battery.

[0028] Furthermore, the charging time t required for a single battery is obtained by dividing the difference between the rated capacity C and the remaining capacity Qi of any battery in a single time interval by the charging speed v corresponding to each type of battery. 1 , the charging time required for the same type of batteries in a single time interval is accumulated and divided by the number of batteries of this type n to obtain the average charging time of the battery of this type. The battery replacement time t required for each type of battery collected in real time by the battery monitoring terminal in a single time interval is accumulated and divided by the number of batteries of this type n to obtain the average battery replacement time of this type of battery. The average charging time and average battery replacement time of each type of battery are added in a fixed ratio using the formula Get the weight time t of each type of battery w , μ 1 and μ 2 are the proportional coefficients of the average charging time and the average battery replacement time, and the weighted time t corresponding to a, b and the three types of batteries are calculated respectively. wa ,t wb and t wc , and calculate the proportion of each type of battery, using the formula Calculate the priority weight coefficient ρ corresponding to each type of battery k , subscript k indicates the type of battery, including a, b and c, σ 1 and σ 2 Respectively represent the weight time and the proportional coefficient of each type of battery.

[0029] In this embodiment, it is necessary to specifically explain the ratio coefficient μ between the average charging time and the average battery replacement time in the above steps. 1 and μ 2 The sum should be 1. The proportional coefficient needs to be obtained by specifically analyzing the importance of the battery charging time and battery replacement time at the battery swap station and setting it according to the requirements of the battery swap station. The proportional coefficient σ of the weight time and quantity of each type of battery in the above steps 1 and σ2 The sum should be 1, and the proportional coefficient should be set by the battery swap station based on historical battery swap data.

[0030] What needs to be specifically explained in this embodiment is that in the above steps, the average charging time and average battery replacement time of different types of batteries are calculated to reflect the weighted time required for the battery as a whole, and the processing priority of each type of battery in the battery replacement station is specifically analyzed by analyzing the weighted time and quantity ratio required for different batteries.

[0031] S3: Mobile battery swap demand analysis: The control center conducts mobile battery swap demand analysis based on the mobile battery swap operation status analysis results to obtain the mobile battery swap demand.

[0032] Furthermore, the mobile battery swap demand analysis includes the following steps: The control center sets the energy supply demand within a single time interval of the battery swap station based on the total amount of electricity required to be replenished within a single time interval obtained from the battery swap data analysis, and sets the energy supply index. It also determines the charging priority of each type of battery in the battery swap station based on the priority weight coefficients of each type of battery obtained from the battery swap data analysis.

[0033] Furthermore, the energy supply index should be divided into three levels, including small demand power supply standard, medium demand power supply standard and large demand power supply standard, marked as Q 1 , Q 2 and Q 3 , where Q 1 =1 / 3Q 3 ,Q 2 =2 / 3Q 3 .

[0034] In this embodiment, it should be specifically explained that in order to avoid a large amount of power loss at the power supply station, the power supply demand set by the power swap station should be the sum of the total amount of power required to be replenished in a single time interval and the floating power value of the power swap station. When determining the charging priority according to the weight coefficient of each type of battery, it should be noted that the larger the priority weight coefficient of each type, the longer the charging and swapping time required for this type of battery or the more batteries there are, and the higher the charging priority of this type of battery should be, for example, a < b < c , indicating that the priority weight coefficient of class A batteries is smaller than the priority weight coefficient of class B batteries, which is smaller than the priority weight coefficient of class C batteries. Correspondingly, the charging priority of class C batteries should be higher than that of class B batteries, and the charging priority of class B batteries should be higher than that of class A batteries.

[0035] S4: Energy storage strategy formulation: The control center formulates the energy storage strategy of the battery swap station according to the mobile battery swap demand, and controls the energy storage device to perform energy storage operations.

[0036] Furthermore, the formulation of energy storage strategies requires the control center to compare the energy supply demand and functional indicators obtained from the mobile battery swap demand analysis, determine the energy supply level required for the battery swap station, select the charging method based on the energy supply level, and determine the order of charging each type of battery based on the charging priority of each type of battery obtained from the mobile battery swap demand analysis.

[0037] What needs to be specifically explained in this embodiment is that when the energy supply demand is less than the small demand power supply standard, it means that the battery swap station belongs to the small demand power supply and needs to provide less power. The fine charging method can be used to charge the battery. This method can give priority to solar charging and energy storage battery charging methods to power the battery, and use a small current for trickle charging to avoid overcharging and battery damage; when the energy supply demand is greater than the small demand power supply standard and less than the medium demand power supply standard, it means that the battery swap station belongs to the medium demand power supply and needs to provide moderate power. The conventional charging method can be used to charge the battery. This method is suitable for conventional AC charging in the power grid, with moderate charging speed and less damage to the battery; when the functional demand is greater than the medium demand power supply standard and less than the high demand power supply standard, the fast charging method can be used to charge the battery. This method usually uses the power grid for DC fast charging, which can replenish a large amount of power to the battery in a relatively short time.

[0038] In this embodiment, it should be specifically explained that when various batteries need to be charged at the same time, the control center will set the charging order of the batteries according to the charging priority of each type of battery. For example, when the charging priority of type C batteries should be higher than that of type B batteries, and the charging priority of type B batteries should be higher than that of type A batteries, type C batteries should be charged first, and when there is an empty charging device, type B batteries will be charged, and so on, and finally type A batteries will be charged.

[0039] S5: Energy storage device operation status monitoring: The energy storage device operation parameters are monitored in real time through the energy storage device monitoring terminal, and the collected data is transmitted to the control center.

[0040] Furthermore, the operating parameters of the energy storage device specifically include the real-time voltage U and the real-time current I during the charging process of the energy storage device.

[0041] What needs to be specifically explained in this embodiment is that the real-time voltage of the energy storage device during charging is too high, which may exceed the rated voltage of the energy storage device, causing damage to the device or performance degradation, or even leading to safety accidents. The voltage level will also affect the charging efficiency. Under the appropriate voltage, the energy storage device can receive and store electrical energy more efficiently. If the voltage is too low, it may cause slow charging speed and affect charging efficiency; while excessive voltage may cause unnecessary energy loss and heating of the device; the real-time current during the charging process of the energy storage device directly determines the charging rate of the energy storage device. At the same voltage, the greater the current, the faster the charging speed. However, excessive current may cause problems such as equipment overheating and battery polarization, thereby affecting charging efficiency and equipment life.

[0042] S6: Analysis of the operating status of the energy storage device: The control center analyzes the operating parameters of the energy storage device collected in real time to obtain an evaluation value of the energy storage device status.

[0043] Furthermore, the calculation steps of the energy storage device state evaluation value are as follows: B1: Set a monitoring interval for the charging process of an energy storage device and divide it into individual sub-time zones of equal time length, marked as 1, 2, ..., j, ..., m; It should be specifically explained in this embodiment that the establishment of the energy storage device charging process monitoring interval must include at least the entire battery charging process, and each battery charging process is carried out in parallel according to the number of idle charging devices. An energy storage device charging process monitoring interval can be 5 hours, and sub-time areas are divided according to a time length of 5 minutes.

[0044] B2: The real-time voltage U in any sub-time zone is obtained through the energy storage device monitoring terminal. j , and calculate the voltage mean through the real-time voltage in any sub-time zone, calculate the difference between the real-time voltage and the voltage mean in any sub-time zone, add up the squares of the difference between the real-time voltage and the voltage mean in any sub-time zone, divide by the number of m-1 sub-time zones and take the square root, and get the voltage fluctuation value of the user in the monitoring time zone, and use the same method to calculate the current fluctuation value, add the voltage fluctuation value and the current fluctuation value according to a fixed proportional coefficient and use the formula Calculate the energy storage device status assessment value D, ω 1 and ω 2 Respectively represent the proportionality coefficients of voltage fluctuation value and current fluctuation value.

[0045] In this embodiment, it is necessary to specifically explain the proportionality coefficient ω between the voltage fluctuation value and the current fluctuation value. 1 and ω 2 The sum should be 1. It is necessary to analyze and process the status of the energy storage device during a large number of charging processes through the battery swap station, and set the corresponding proportional coefficient based on the analysis results.

[0046] S7: Dynamically adjust the energy storage strategy: The control center dynamically adjusts the energy storage strategy of the battery swap station according to the status evaluation value of the energy storage device.

[0047] Furthermore, the energy storage device status assessment standard value D is set 标 , compare the energy storage device status evaluation value with the energy storage device status evaluation standard value, judge the real-time operating status of the energy storage device, and dynamically adjust the energy storage strategy based on the real-time operating status of the energy storage device.

[0048] It should be specifically explained in this embodiment that when the energy storage device state evaluation value is less than the energy storage device state evaluation standard value, it means that the energy storage device is in a normal operating state and no adjustment is required; when the energy storage device state evaluation value is greater than the energy storage device state evaluation standard value, it means that the energy storage device is in an abnormal operating state, and the battery being charged and the energy storage device should be checked immediately for abnormalities.

[0049] Secondly: In the drawings of the embodiments disclosed in the present invention, only the structures involved in the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the case of no conflict, the same embodiment and different embodiments of the present invention can be combined with each other; Finally: The above description is only the preferred embodiment of the present invention and is not used to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A mobile battery replacement energy storage data control method based on artificial intelligence, characterized in that: It includes a battery monitoring terminal, a battery swap station operation monitoring terminal, an energy storage device monitoring terminal, a control center and an energy storage device. The battery monitoring terminal, the battery swap station operation monitoring terminal, the energy storage device monitoring terminal and the energy storage device should be set up at the battery swap station, and specifically includes the following steps: S1: Battery swap data collection: The battery operating parameters and battery swap station operating parameters are collected in real time through the battery monitoring terminal and the battery swap station operation monitoring terminal, and the collected data is transmitted to the control center; S2: Battery swap data analysis: The control center analyzes the real-time collected battery operating parameters and battery swap station operating parameters to obtain the mobile battery swap operating status analysis results; S3: Mobile battery swap demand analysis: The control center performs mobile battery swap demand analysis based on the mobile battery swap operation status analysis results to obtain the mobile battery swap demand; S4: Energy storage strategy formulation: The control center formulates the energy storage strategy of the battery swap station according to the mobile battery swap demand, and controls the energy storage device to perform energy storage operations; S5: Energy storage device operation status monitoring: monitor the operation parameters of the energy storage device in real time through the energy storage device monitoring terminal, and transmit the collected data to the control center; S6: Energy storage device operating status analysis: The control center analyzes the energy storage device operating parameters collected in real time to obtain the energy storage device status evaluation value; S7: Dynamically adjust the energy storage strategy: The control center dynamically adjusts the energy storage strategy of the battery swap station according to the status evaluation value of the energy storage device.

2. According to the artificial intelligence-based mobile battery exchange energy storage data control method of claim 1, it is characterized by: The battery operating parameters collected in real time by the battery monitoring terminal include the remaining power Q, charging speed v, number of batteries n and capacity C of each battery in the battery swap station. The battery swap station operating parameters collected in real time by the battery swap station operation monitoring terminal specifically include the battery swap time t.

3. According to the artificial intelligence-based mobile battery replacement energy storage data control method of claim 1, it is characterized by: The steps for battery swap data analysis are as follows: A1: Set a time interval, monitor the number of batteries in the battery swap station in a single time interval in real time through the battery monitoring terminal, and classify the battery types, marking them as a, b and c, and count the number n of each type of battery; A2: Use the battery monitoring terminal to collect the remaining power Q of any battery within the time interval i , collect the charging speed v corresponding to each type of battery, and obtain the capacity C of each type of battery through the battery monitoring terminal; A3: Process and analyze the real-time collected battery swap data to obtain the total amount of electricity required to be replenished within a single time interval of the battery swap station Q s ; A4: The battery monitoring terminal is used to monitor the battery replacement time t required for each type of battery within a single time interval in real time, and the battery replacement data are processed to obtain the priority weight coefficient ρ of each type of battery.

4. According to claim 3, a method for controlling mobile battery replacement energy storage data based on artificial intelligence is characterized in that: The total amount of electricity required to be replenished within the single time interval is Q s It is obtained by calculating the difference between the capacity of each type of battery and the remaining power corresponding to any battery, including Q ai , Q bi and Q ci Three types, accumulate the amount of electricity that needs to be replenished for any battery and use the formula Calculate the total amount of electricity required for a single time interval Q s , C a , C b and C c Respectively represent the capacities of three types of batteries: a, b, and c, n a 、n b and n c Respectively represent the number of three types of batteries: a, b and c.

5. According to claim 3, a method for controlling mobile battery storage data based on artificial intelligence is characterized in that: The charging time t1 required for a single battery is obtained by dividing the difference between the rated capacity C and the remaining power Qi of any battery in a single time interval by the charging speed v corresponding to each type of battery. The charging time required for batteries of the same type in a single time interval is accumulated and divided by the number of batteries of this type n to obtain the average charging time of batteries of this type. The battery replacement time t required for each type of battery collected in real time by the battery monitoring terminal in a single time interval is accumulated and divided by the number of batteries of this type n to obtain the average battery replacement time of batteries of this type. The average charging time and the average battery replacement time of each type of battery are added in a fixed ratio using the formula Get the weight time t of each type of battery w , μ1 and μ2 are the proportional coefficients of the average charging time and the average battery replacement time, respectively, and the weighted time t corresponding to a, b and the three types of batteries are calculated respectively wa ,t wb and t wc , and calculate the proportion of each type of battery, using the formula Calculate the priority weight coefficient ρ corresponding to each type of battery k , the subscript k represents the type of battery, including a, b and c, σ1 and σ2 represent the proportional coefficients of the weight time and quantity of each type of battery, respectively.

6. According to the artificial intelligence-based mobile battery replacement energy storage data control method of claim 1, it is characterized by: The mobile battery swap demand analysis includes the following steps: The control center sets the energy supply demand in a single time interval of the battery swap station according to the total amount of electricity required to be replenished in a single time interval obtained from the battery swap data analysis, and sets the energy supply index. The charging priority of each type of battery in the battery swap station is determined according to the priority weight coefficient of each type of battery obtained from the battery swap data analysis; Energy supply indicators should be divided into three levels, including small demand power supply standard, medium demand power supply standard and large demand power supply standard, marked as Q1, Q2 and Q3 respectively, where Q1=1 / 3Q3, Q2=2 / 3Q3.

7. According to claim 6, a method for controlling mobile battery storage data based on artificial intelligence is characterized in that: The formulation of the energy storage strategy requires the control center to compare the energy supply demand and functional indicators obtained from the mobile battery swap demand analysis, determine the energy supply level required by the battery swap station, select the charging method according to the energy supply level, and determine the order of charging each type of battery according to the charging priority of each type of battery obtained from the mobile battery swap demand analysis.

8. According to the artificial intelligence-based mobile battery replacement energy storage data control method of claim 1, it is characterized by: The operating parameters of the energy storage device specifically include the real-time voltage U and the real-time current I during the charging process of the energy storage device.

9. According to the artificial intelligence-based mobile battery replacement energy storage data control method of claim 1, it is characterized by: The calculation steps of the energy storage device state evaluation value are as follows: B1: Set a monitoring interval for the charging process of an energy storage device and divide it into individual sub-time zones of equal time length, marked as 1, 2, ..., j, ..., m; B2: The real-time voltage U in any sub-time zone is obtained through the energy storage device monitoring terminal. j , and calculate the voltage mean through the real-time voltage in any sub-time zone, calculate the difference between the real-time voltage and the voltage mean in any sub-time zone, add up the squares of the difference between the real-time voltage and the voltage mean in any sub-time zone, divide by the number of m-1 sub-time zones and take the square root, and get the voltage fluctuation value of the user in the monitoring time zone, and use the same method to calculate the current fluctuation value, add the voltage fluctuation value and the current fluctuation value according to a fixed proportional coefficient and use the formula The energy storage device state evaluation value D is calculated, and ω1 and ω2 represent the proportionality coefficients of the voltage fluctuation value and the current fluctuation value respectively.

10. The method for controlling mobile battery replacement energy storage data based on artificial intelligence according to claim 1 is characterized in that: The energy storage strategy is set by constructing the energy storage device state evaluation standard value D 标 , compare the energy storage device status evaluation value with the energy storage device status evaluation standard value, determine the real-time operating status of the energy storage device, and dynamically adjust the energy storage strategy according to the real-time operating status of the energy storage device.

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