Energy storage battery utilization planning method and system

Abstract

The present invention provides a method and system for planning the utilization of energy storage batteries, which relates to data processing technology. The method includes: determining a power supply device that supplies power to an electric device, and obtaining device data corresponding to the power supply device; determining the power data and charge-discharge data corresponding to each different battery unit included in the power supply device based on the device data, and determining each estimated health factor corresponding to each battery unit based on the power data and charge-discharge data; obtaining operation plan data corresponding to the electric device, and performing data analysis based on the operation plan data, and determining the operation plan corresponding to the electric device based on the analysis result; performing use planning for each battery unit based on each estimated health factor, obtaining planning data adapted to the operation plan, and controlling the power supply device to supply power to the electric device based on the planning data. The present invention at least improves energy utilization efficiency.

Description

Technical Field

[0001] The present invention relates to data processing technology, and in particular to a method and system for planning the utilization of energy storage batteries. Background Art

[0002] In the rapid development of modern energy storage devices, batteries have become key energy storage components. In order to improve the service life and performance of batteries, battery management units (BMS) need to effectively manage each unit of the battery pack. Energy storage battery utilization planning methods, as a technical means to optimize battery pack performance, are gaining increasing attention.

[0003] The inventors found in their research that a battery pack is usually composed of multiple battery cells connected in series or in parallel. During the charging and discharging process, the voltage and capacity of the battery cells may differ due to manufacturing differences, usage conditions, and aging effects. These differences can cause some battery cells to over-discharge or over-charge, thus affecting the efficiency and life of the entire battery pack; therefore, it is necessary to find a method to achieve power balancing for battery packs with differences. Summary of the invention

[0004] Based on the above problems, the present invention is proposed to provide a method and system for energy storage battery utilization planning that overcomes the above problems or at least partially solves the above problems.

[0005] According to one aspect of the present invention, there is provided a method for planning energy storage battery utilization, comprising the following steps:

[0006] Determine a power supply device that supplies power to the power-consuming device, and obtain device data corresponding to the power supply device;

[0007] Determine the power data and charge-discharge data corresponding to each different battery unit included in the power supply device based on the device data, and determine each estimated health factor corresponding to each battery unit based on the power data and charge-discharge data;

[0008] Acquiring operation plan data corresponding to the electric equipment, performing data analysis based on the operation plan data, and determining an operation plan corresponding to the electric equipment based on the analysis result;

[0009] Based on each estimated health factor, use planning is performed on each battery unit to obtain planning data that is compatible with the operation plan, and based on the planning data, the power supply device is controlled to supply power to the power-consuming device.

[0010] Optionally, in the method according to the present invention, determining the power data and charge-discharge data respectively corresponding to each different battery unit included in the power supply device based on the device data, and determining each estimated health factor respectively corresponding to each battery unit based on the power data and charge-discharge data, including:

[0011] Splitting the device data to obtain battery data corresponding to different battery units included in the power supply device, wherein the battery data includes power data and charge and discharge data;

[0012] Determine the coefficient of the power data corresponding to each battery cell based on a preset power coefficient determination strategy, and calculate the product of the obtained power health coefficient and the retrieved power weight to obtain first fusion data;

[0013] Determine the coefficient of the charge and discharge data corresponding to each battery cell based on a preset charge and discharge coefficient determination strategy, and calculate the product of the obtained charge and discharge health coefficient and the retrieved charge and discharge weight to obtain second fusion data;

[0014] The first fused data and the second fused data are fused and calculated to obtain estimated health coefficients corresponding to each battery cell.

[0015] Optionally, in the method according to the present invention, the coefficient of the power data corresponding to each battery cell is determined based on a preset power coefficient determination strategy, including:

[0016] Determine the rated peak power and rated internal resistance corresponding to the battery cell based on any power data, and retrieve the historical peak power and historical internal resistance corresponding to the battery cell;

[0017] Comparing the historical power peak value with the rated power peak value, and determining the peak reduction rate corresponding to the battery unit based on the comparison result;

[0018] Comparing the peak values ​​of the historical internal resistance with the rated internal resistance, and determining the internal resistance increase rate corresponding to the battery cell based on the comparison result;

[0019] The reference power coefficient corresponding to the battery cell is reduced based on the peak reduction rate and the internal resistance increase rate to obtain a power health coefficient corresponding to the battery cell.

[0020] Optionally, in the method according to the present invention, the coefficient determination is performed on the charge and discharge data corresponding to each battery cell based on a preset charge and discharge coefficient determination strategy, including:

[0021] Determine the rated charge and discharge times and the rated energy conversion efficiency corresponding to the battery cell based on any charge and discharge data, and retrieve the historical charge and discharge times and the historical energy conversion efficiency corresponding to the battery cell;

[0022] Comparing the historical charge and discharge times with the rated charge and discharge times, and determining a times remaining rate corresponding to the battery cell based on the comparison result;

[0023] Comparing the historical energy conversion efficiency with the rated energy conversion efficiency, and determining the efficiency reduction rate corresponding to the battery cell based on the comparison result;

[0024] The reference charge and discharge coefficient corresponding to the battery cell is reduced based on the number of remaining rates and the efficiency reduction rate to obtain a charge and discharge health coefficient corresponding to the battery cell.

[0025] Optionally, in the method according to the present invention, the method further comprises:

[0026] Obtaining an actual health factor of the battery cell based on the management end, and comparing the actual health factor corresponding to the same battery cell with the estimated health factor;

[0027] When the actual health coefficient is greater than the estimated health coefficient, the power weight and the charge and discharge weight are increased respectively;

[0028] When the actual health factor is less than the estimated health factor, the power weight and the charge and discharge weight are respectively trained to be reduced;

[0029] The power weight and charge and discharge weight after training are obtained through the following formula:

[0030] ;

[0031] in, The power weight Increase the number of training sessions. The power weight The training constant value of The power weight Reduce the number of training sessions. is the power weight after training, is the charge and discharge weight Increase the number of training sessions. is the charge and discharge weight The training constant value of is the charge and discharge weight Increase or decrease the number of training sessions. is the charge and discharge weight after training.

[0032] Optionally, in the method according to the present invention, the operation plan data is navigation setting data, and the electric device includes an electric vehicle;

[0033] Acquiring operation plan data corresponding to the electric device, performing data analysis based on the operation plan data, and determining an operation plan corresponding to the electric device based on the analysis result, including:

[0034] Receiving navigation setting data sent by the electric device;

[0035] In response to the navigation setting data respectively including target location data corresponding to the target end point and current starting data corresponding to the starting location, generating an operation plan corresponding to the electrical equipment based on the current starting data and the target location data;

[0036] or,

[0037] In response to the navigation setting data only including current starting data corresponding to the starting position, retrieving real-time map data, and determining a real-time road where the starting position is located based on the real-time map data,

[0038] The real-time road is divided along the extension direction of the real-time road to obtain a divided road with the starting position as a starting point, and the divided road is determined as an operation plan corresponding to the electric equipment.

[0039] Optionally, the performing use planning for each battery unit based on each estimated health coefficient to obtain planning data adapted to the operation plan, and controlling the power supply device to supply power to the power-consuming device based on the planning data, includes:

[0040] Ranking each battery unit from high to low based on each estimated health factor to obtain a battery sequence;

[0041] Determine the estimated driving time based on the operation plan and obtain the current time;

[0042] Determine a trip end time based on the current time and the estimated driving duration, and obtain a current outdoor temperature and a future outdoor temperature corresponding to the current time and the trip end time respectively;

[0043] Calculating the average value of the current outdoor temperature and the future outdoor temperature to obtain an estimated reference temperature, and determining a power consumption coefficient based on the estimated reference temperature;

[0044] Determining a predicted power value based on the operation plan, and determining an actual power value corresponding to the operation plan based on the predicted power value and the power consumption coefficient;

[0045] Determine the remaining capacity of each battery corresponding to each battery cell based on each power data corresponding to each battery cell, and determine each battery cell whose sum of remaining capacity is greater than or equal to the actual power value as a discharge battery group along the forward arrangement order of the battery sequence;

[0046] The battery cells in the discharge battery pack are controlled to supply power to the electric vehicle based on the forward arrangement order of the battery sequence.

[0047] Optionally, in the method according to the present invention, the method further comprises:

[0048] In response to a charging preparation signal generated by the power-consuming device, establishing a charging display interface, wherein the charging display interface includes a battery display area;

[0049] Determine the battery remaining rates corresponding to the battery cells based on the battery remaining capacity and the rated capacity peak value corresponding to the same battery cell, and establish initial battery slots arranged in a line along a preset direction with the same number as the battery cells in the battery display area;

[0050] Filling each initial battery slot based on the remaining rate of each battery along the forward arrangement order of the battery sequence to obtain a current battery slot corresponding to each battery unit;

[0051] Obtaining the estimated charge capacity sent by the power-consuming device, and determining each battery unit whose sum of remaining battery capacity is greater than or equal to the estimated charge capacity as a rechargeable battery group along the forward arrangement order of the battery sequence;

[0052] Dividing each battery slot located in the battery display area based on the number of batteries in each battery unit located in the rechargeable battery pack to obtain a charging slot group corresponding to the rechargeable battery pack and a vacant slot group;

[0053] The battery display area is divided into regions, and the obtained regional contour of the charging sub-region corresponding to the charging slot group is configured with pixels of a first pixel value, and the obtained regional contour of the vacant sub-region corresponding to the vacant slot group is configured with pixels of a second pixel value.

[0054] Optionally, the method further comprises:

[0055] In response to a charging start signal generated by an electric device, a charging progress bar corresponding to the charging battery pack is created in the charging sub-area, wherein the charging progress bar includes node models corresponding to the battery cells in the charging battery pack and node connection segments for connecting the node models at adjacent positions;

[0056] The charging progress bar is configured to be in an invisible state, and based on the acquired charging progress of each battery unit in the rechargeable battery pack, a corresponding portion of the charging progress bar is dynamically displayed by converting the invisible state into a display state.

[0057] According to another aspect of the present invention, there is provided an energy storage battery utilization planning system, comprising:

[0058] The device determination module is configured to determine the power supply device that supplies power to the power-consuming device and obtain device data corresponding to the power supply device;

[0059] a coefficient estimation module, configured to determine, based on the device data, power data and charge-discharge data corresponding to different battery cells included in the power supply device, and determine, based on the power data and charge-discharge data, each estimated health coefficient corresponding to each battery cell;

[0060] a route acquisition module, configured to acquire operation plan data corresponding to the electric device, perform data analysis based on the operation plan data, and determine an operation plan corresponding to the electric device based on the analysis result;

[0061] The power supply planning module is configured to plan the use of each battery unit based on the estimated health coefficient, obtain planning data adapted to the operation plan, and control the power supply equipment to supply power to the power-consuming equipment based on the planning data.

[0062] According to the solution of the present invention, first determine the power supply device that supplies power to the power-consuming device, and obtain the device data corresponding to the power supply device; analyze the power and charging and discharging conditions of the battery unit based on the obtained device data to determine the corresponding estimated health factor, and complete the real-time evaluation of the health of each battery unit; then determine the planning data by obtaining and analyzing the operation plan of the power-consuming device, so that the use plan of the battery unit can be formulated based on the estimated health factor and planning data, and the power supply device can be adjusted accordingly to perform battery balancing to achieve efficient power supply to the power-consuming device. This method can improve the utilization efficiency of the battery unit, extend the battery life, and ensure the stable operation of the power-consuming device, thereby improving the energy utilization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 A flow chart of a method for planning energy storage battery utilization according to an embodiment of the present invention is shown;

[0064] Figure 2 The figure shows a schematic diagram of the charging display interface in this embodiment;

[0065] Figure 3It shows a structural block diagram of an energy storage battery utilization planning system according to another embodiment of the present invention;

[0066] Figure 4 A flow chart of a battery SOC and temperature balancing algorithm based on fuzzy control according to yet another embodiment of the present invention is shown. DETAILED DESCRIPTION

[0067] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0068] In the rapid development of modern energy storage devices, batteries have become key energy storage components. In order to improve the service life and performance of batteries, battery management units (BMS) need to effectively manage each unit of the battery pack. Energy storage battery utilization planning methods, as a technical means to optimize battery pack performance, are gaining increasing attention.

[0069] The inventors found in their research that a battery pack is usually composed of multiple battery cells connected in series or in parallel. During the charging and discharging process, the voltage and capacity of the battery cells may differ due to manufacturing differences, usage conditions, and aging effects. These differences can cause some battery cells to over-discharge or over-charge, thus affecting the efficiency and life of the entire battery pack; therefore, it is necessary to find a method to achieve power balancing for battery packs with differences.

[0070] In order to solve the above problems existing in the prior art, the inventor proposes the solution of the present invention.

[0071] Figure 1 FIG. 4 shows a flow chart of a method for planning energy storage battery utilization according to an embodiment of the present invention. Figure 1 As shown, the method starts at step S101, and in step S101, the following contents are included:

[0072] A power supply device that supplies power to an electrical device is determined, and device data corresponding to the power supply device is acquired.

[0073] The power supply equipment can be an energy storage battery in an energy storage station, an energy storage battery in an electric vehicle, or other power supply equipment using an energy storage battery. The power-consuming equipment in the energy storage station can be various types of equipment connected to the energy storage battery in the energy storage station, such as motors, air conditioners, monitoring equipment, etc.; the power-consuming equipment in electric vehicles can be motors, air conditioners, players, etc. Among them, the motor is generally one of the devices with large power consumption. The motor is driven based on the battery, and corresponding power balancing is required to ensure the efficiency and service life of the battery pack; therefore, the focus can be on obtaining the motor start signal. At this time, the power supply equipment that powers the motor can be determined based on the corresponding motor start signal, so as to further obtain the corresponding equipment data based on the power supply equipment, so as to understand the real-time equipment status of the power supply equipment based on the equipment data, and facilitate the subsequent battery balancing process.

[0074] In this embodiment, the above-mentioned “determining the power supply device that supplies power to the power-consuming device, and obtaining the device data corresponding to the power supply device” may include the following steps:

[0075] Receive the sensor data output by the signal sensor pre-set on the electrical equipment in real time, and clean the received sensor data to obtain signal data;

[0076] Performing feature analysis based on the signal data to obtain signal features corresponding to the signal data, wherein the signal features include signal frequency and signal waveform;

[0077] Retrieving a signal comparison table for comparison, wherein the signal comparison table includes different signal features corresponding to different device startup signals;

[0078] Determine the device start signal of the corresponding motor in the signal comparison table as the motor start signal, and traverse the signal comparison table to determine the device start signal corresponding to the signal feature of the signal data;

[0079] In response to the device start signal being a motor start signal, a power supply device for supplying power to the motor is determined in the power-consuming device, and a battery management unit is controlled to acquire device data of the power supply device.

[0080] For example, in this embodiment, the object is an energy storage station or a motor in an electric vehicle. Since there are many independent electrical equipment units with different functions, such as air conditioners, display screens, door and window controllers, surveillance videos, etc., when each equipment unit is turned on, the processor of the control system needs to send a corresponding equipment start signal to the corresponding equipment unit. In order to determine whether the equipment start signal is a motor start signal of the corresponding motor, the sensor data output by the preset signal sensor can be received in real time, and the sensor data can be further cleaned to clear the noise data and obtain the corresponding signal data; after obtaining the signal data, the signal data can be feature analyzed to obtain signal features corresponding to the signal data, wherein the signal features can include signal frequency and signal waveform, etc.; here, it needs to be explained What is interesting is that when the processor of the control system sends signals for turning on different equipment units, in order to be able to distinguish each signal, different signal frequencies and signal waveforms can be set for different signals; and after completing the feature analysis of the signal data, the signal comparison table can be further retrieved, wherein the signal comparison table includes different signal characteristics corresponding to different equipment start signals, for example, including signal characteristics corresponding to air-conditioning start signals, signal characteristics corresponding to display start signals, signal characteristics corresponding to wiper start signals, and signal characteristics corresponding to electric start signals; when the feature comparison of the signal data is completed and the obtained equipment start signal is the corresponding motor start signal, the power supply device that supplies power to the motor can be determined based on the motor start signal, and the corresponding battery management unit (BMS) can be controlled to obtain the equipment data of the power supply device.

[0081] In step S102, the following contents are included:

[0082] Based on the device data, power data and charge-discharge data corresponding to different battery cells included in the power supply device are determined, and based on the power data and charge-discharge data, each estimated health factor corresponding to each battery cell is determined.

[0083] For example, in the present embodiment, the device data of the corresponding power supply device includes power data and charge and discharge data corresponding to each different battery cell, wherein the power data is used to characterize the power capacity of a battery cell, and the charge and discharge data is used to characterize the charge and discharge condition of a battery cell; it should be noted that, under normal circumstances, the corresponding power capacity of any battery cell will decrease to varying degrees after a long period of use, and each battery cell also has a rated number of charge and discharge times due to its structure. Therefore, by obtaining the power data and charge and discharge data of the corresponding battery cell, the estimated health factor of the battery cell can be further determined, so that multiple battery cells can be further balanced based on the estimated health factor, thereby improving the use effect and service life of the power supply equipment.

[0084] Further, in this embodiment, the above-mentioned “determining the power data and the charge and discharge data corresponding to each different battery unit included in the power supply device based on the device data, and determining each estimated health factor corresponding to each battery unit based on the power data and the charge and discharge data” may also include the following steps:

[0085] Splitting the device data to obtain battery data corresponding to different battery units included in the power supply device, wherein the battery data includes power data and charge and discharge data;

[0086] Determine the coefficient of the power data corresponding to each battery cell based on a preset power coefficient determination strategy, and calculate the product of the obtained power health coefficient and the retrieved power weight to obtain first fusion data;

[0087] Determine the coefficient of the charge and discharge data corresponding to each battery cell based on a preset charge and discharge coefficient determination strategy, and calculate the product of the obtained charge and discharge health coefficient and the retrieved charge and discharge weight to obtain second fusion data;

[0088] The first fused data and the second fused data are fused and calculated to obtain estimated health coefficients corresponding to each battery cell.

[0089] For example, in this embodiment, since the device data is obtained based on the power supply device, in order to be able to perform battery balancing on multiple battery cells that constitute the power supply device, it is necessary to split the data based on the device data, so as to obtain battery data corresponding to each different battery cell, wherein the battery data may include power data and charge and discharge data; after obtaining the battery data corresponding to each battery cell, the battery data and charge and discharge data may be determined according to different preset power coefficient determination strategies and preset charge and discharge coefficient determination strategies to obtain corresponding power health coefficients and charge and discharge health coefficients; after obtaining the corresponding power health coefficient and charge and discharge health coefficient, the power health coefficient and the charge and discharge health coefficient may be multiplied by the retrieved power weight and the charge and discharge weight, respectively, and fused based on the obtained first fusion data and the second fusion coefficient. Based on the above calculation process, the estimated health coefficients corresponding to each battery cell may be determined.

[0090] Furthermore, in this embodiment, the above-mentioned “determining the coefficient of the power data corresponding to each battery cell based on the preset power coefficient determination strategy” may include the following steps:

[0091] Determine the rated peak power and rated internal resistance corresponding to the battery cell based on any power data, and retrieve the historical peak power and historical internal resistance corresponding to the battery cell;

[0092] Comparing the historical power peak value with the rated power peak value, and determining the peak reduction rate corresponding to the battery unit based on the comparison result;

[0093] Comparing the peak values ​​of the historical internal resistance with the rated internal resistance, and determining the internal resistance increase rate corresponding to the battery cell based on the comparison result;

[0094] The reference power coefficient corresponding to the battery cell is reduced based on the peak reduction rate and the internal resistance increase rate to obtain a power health coefficient corresponding to the battery cell.

[0095] For example, in this embodiment, the battery capacity of any battery cell can be determined based on the rated peak power and the rated internal resistance, that is, the rated peak power and the rated content corresponding to the battery cell are determined by the power data, and the historical peak power and the historical internal resistance corresponding to the battery cell are retrieved at the same time, where the historical peak power and the historical internal resistance can be obtained based on the historical charging conditions; it should be noted that the higher the difference between the historical peak power and the rated peak power, the higher the service life of the battery cell is reduced, and the higher the difference between the historical internal resistance and the rated internal resistance, it can also be indicated that the utilization efficiency of the battery cell is also significantly reduced; based on this, the rated data can be compared with the historical values ​​to determine the peak reduction rate and the internal resistance increase rate of the corresponding battery cell; and further based on the peak reduction rate and the internal resistance increase rate, the benchmark power coefficient corresponding to the battery cell is reduced by a coefficient, so as to obtain each power health coefficient corresponding to each battery cell.

[0096] It should be noted that, in this embodiment, the above-mentioned reference power coefficient can be set based on a battery cell in a healthy state, that is, a battery cell with no reduction in efficiency and service life.

[0097] Similarly, in this embodiment, the above-mentioned “determining the coefficient of the charge and discharge data corresponding to each battery cell based on the preset charge and discharge coefficient determination strategy” may include the following steps:

[0098] Determine the rated charge and discharge times and the rated energy conversion efficiency corresponding to the battery cell based on any charge and discharge data, and retrieve the historical charge and discharge times and the historical energy conversion efficiency corresponding to the battery cell;

[0099] Comparing the historical charge and discharge times with the rated charge and discharge times, and determining a times remaining rate corresponding to the battery cell based on the comparison result;

[0100] Comparing the historical energy conversion efficiency with the rated energy conversion efficiency, and determining the efficiency reduction rate corresponding to the battery cell based on the comparison result;

[0101] The reference charge and discharge coefficient corresponding to the battery cell is reduced based on the number of remaining rates and the efficiency reduction rate to obtain a charge and discharge health coefficient corresponding to the battery cell.

[0102] For example, in this embodiment, the charge and discharge conditions of any battery cell can be determined based on the rated charge and discharge times and the rated energy conversion efficiency, that is, the rated charge and discharge times and the rated energy conversion efficiency corresponding to the battery cell are determined by the charge and discharge data, and the historical charge and discharge times and the historical energy conversion efficiency corresponding to the battery cell are retrieved at the same time, where the historical charge and discharge times and the historical energy conversion efficiency can be obtained based on the historical charging conditions; it should be noted that when the difference between the historical charge and discharge times and the rated charge and discharge times is higher, it indicates that the service life of the battery cell is reduced more, and when the difference between the historical energy conversion efficiency and the rated energy conversion efficiency is higher, it can also indicate that the use efficiency of the battery cell has also decreased significantly; based on this, the rated data can be compared with the historical values ​​accordingly to determine the number of remaining rates and the efficiency reduction rate of the corresponding battery cell; and further based on the number of remaining rates and the internal efficiency reduction rate, the benchmark charge and discharge coefficient corresponding to the battery cell is reduced by a coefficient, so as to obtain the charge and discharge health coefficients corresponding to each battery cell.

[0103] It should be noted that, in this embodiment, the above-mentioned reference charge and discharge coefficient can be set based on a battery cell in a healthy state, that is, a battery cell that has no reduced efficiency or service life.

[0104] Here, the estimated health factor of the corresponding battery cell obtained based on the present embodiment is obtained through data evaluation. Therefore, the estimated health factor determined through data evaluation may deviate from the actual situation to a certain extent. In order to improve the corresponding determination accuracy, the corresponding power weights and charge and discharge weights can be updated and trained in real time to realize the process of updating and iterating the power weights and charge and discharge weights, thereby continuously improving the corresponding evaluation accuracy.

[0105] Here, the update iteration of the quantity weight and the charge and discharge weight can be achieved through the following steps:

[0106] ;

[0107] in, The power weight Increase the number of training sessions. The power weight The training constant value of The power weight Reduce the number of training sessions. is the power weight after training, is the charge and discharge weight Increase the number of training sessions. is the charge and discharge weight The training constant value of is the charge and discharge weight Increase or decrease the number of training sessions. is the charge and discharge weight after training.

[0108] In step S103, the following contents are included:

[0109] Operation plan data corresponding to the electric device is obtained, and data analysis is performed based on the operation plan data, and an operation plan corresponding to the electric device is determined based on the analysis result.

[0110] For example, in this embodiment, taking an electric car as an example, the operation plan data is navigation setting data. After the electric car generates a corresponding motor start signal, the power supply device corresponding to the motor will supply power to the motor, that is, the corresponding battery cells will perform a corresponding discharge process, so that the electric car moves under the drive of the motor. In order to be able to plan the use of each battery cell based on the movement process of the electric car, the navigation setting data corresponding to the electric car can be obtained, and the operation plan corresponding to the electric car can be further determined based on data analysis, thereby improving the use efficiency and service life of the power supply equipment and realizing dynamic adjustment of the power supply equipment.

[0111] Further, in this embodiment, the above-mentioned “obtaining operation plan data corresponding to the electric device, performing data analysis based on the operation plan data, and determining the operation plan corresponding to the electric device based on the analysis result” may include the following steps:

[0112] Receiving navigation setting data of the electric vehicle;

[0113] In response to the navigation setting data respectively including target position data corresponding to the target end point and current starting data corresponding to the starting position, generating an operation plan corresponding to the electric vehicle based on the current starting data and the target position data;

[0114] or,

[0115] In response to the navigation setting data only including current starting data corresponding to the starting position, retrieving real-time map data, and determining a real-time road where the starting position is located based on the real-time map data,

[0116] The real-time road is divided along the extension direction of the real-time road to obtain a divided road with the starting position as a starting point, and the divided road is determined as an operation plan corresponding to the electric vehicle.

[0117] For example, in this embodiment, since the vehicle unit provided on the electric vehicle is generally pre-configured with corresponding navigation software, when performing route planning based on the electric vehicle, the corresponding target destination can be selected through the vehicle unit, so that the generated operation plan data, i.e., the navigation setting data, can simultaneously include the target position data corresponding to the target destination and the current starting data corresponding to the starting position of the electric vehicle. If route planning is not performed based on the electric vehicle, the generated operation plan data only includes the current starting data corresponding to the starting position. Based on these two different data situations, the operation plan corresponding to the electric vehicle can be determined based on different methods. Among them, for the operation plan data including both the current starting data and the target position data, the operation plan corresponding to the electric vehicle can be directly generated based on the corresponding starting position and the target destination. For the operation plan data including only the current starting data, the real-time road where the electric vehicle is located can be determined based on the real-time map data by retrieving the real-time map data, so that the real-time road can be divided based on the extension direction of the real-time road to obtain the divided road with the starting position as the starting point, so that the divided road can be further determined as the operation plan corresponding to the electric vehicle.

[0118] It should be noted that in this embodiment, the determination of the operation plan can be based on two different application scenarios, thereby achieving flexibility in determining the operation plan, and further achieving corresponding battery balancing for different application scenarios, so as to improve the utilization efficiency and service life of the corresponding power supply equipment, thereby increasing universality.

[0119] In step S104, the following contents are included:

[0120] Based on each estimated health factor, use planning is performed on each battery unit to obtain planning data that is compatible with the operation plan, and based on the planning data, the power supply device is controlled to supply power to the power-consuming device.

[0121] For example, according to the above content, after completing the acquisition of the estimated health factor of the battery cell and the determination of the corresponding operation plan of the electric vehicle, the use of the different battery cells that make up the same power supply equipment can be planned based on the estimated health factor, and based on the obtained planning data that is adapted to the operation plan, the power supply equipment can be further controlled based on the planning data to provide corresponding power supply to the electric vehicle, thereby helping to improve the use efficiency and service life of the battery cells.

[0122] Further, in this embodiment, the above-mentioned “planning the use of each battery unit based on each estimated health factor, obtaining planning data adapted to the operation plan, and controlling the power supply device to supply power to the power-consuming device based on the planning data” may also include the following steps:

[0123] Ranking each battery unit from high to low based on each estimated health factor to obtain a battery sequence;

[0124] Determine the estimated driving time based on the operation plan and obtain the current time;

[0125] Determine a trip end time based on the current time and the estimated driving duration, and obtain a current outdoor temperature and a future outdoor temperature corresponding to the current time and the trip end time respectively;

[0126] Calculating the average value of the current outdoor temperature and the future outdoor temperature to obtain an estimated reference temperature, and determining a power consumption coefficient based on the estimated reference temperature;

[0127] Determining a predicted power value based on the operation plan, and determining an actual power value corresponding to the operation plan based on the predicted power value and the power consumption coefficient;

[0128] Determine the remaining capacity of each battery corresponding to each battery cell based on each power data corresponding to each battery cell, and determine each battery cell whose sum of remaining capacity is greater than or equal to the actual power value as a discharge battery group along the forward arrangement order of the battery sequence;

[0129] The battery cells in the discharge battery pack are controlled to supply power to the electric vehicle based on the forward arrangement order of the battery sequence.

[0130] For example, in this embodiment, after obtaining the estimated health coefficients of the battery cells constituting the power supply device, the battery cells can be ranked according to the health of each battery cell, thereby obtaining a corresponding battery sequence. For example, when there are three battery cells, and the estimated health coefficients of the three battery cells are 1.1 (battery A), 0.8 (battery B), and 0.9 (battery C), respectively, after sorting from high to low based on the estimated health coefficients, the obtained battery sequence corresponds to: battery A-battery C-battery B; then, based on the characteristics of the battery cells, it can be known that the battery capacity corresponding to the battery cells under different temperature conditions is The amount of electricity consumed will be affected by the environment. For example, for hot and cold temperature conditions, the battery capacity of the same battery unit under hot temperature conditions will be greater than that under cold temperature conditions. Therefore, when planning the operation of electric vehicles to calculate the corresponding power consumption, the impact of temperature conditions must be considered. Based on this, the estimated driving time can be determined according to the operation plan, and the current time can be obtained. By superimposing the current time with the estimated driving time, the corresponding driving end time can be determined. Here, the driving end time can be understood as the electric The time point at which the electric vehicle travels from the starting position to the target terminal based on the operation plan; then, after completing the acquisition of the travel end time, the corresponding current outdoor temperature and future outdoor temperature can be determined based on the current time and the travel end time, and the corresponding estimated reference temperature needs to be calculated based on the average of the current outdoor temperature and the future outdoor temperature to obtain the corresponding estimated reference temperature, so as to determine the corresponding power consumption coefficient through the estimated reference temperature; then, the predicted power value not affected by the temperature is determined according to the operation plan, and the actual power value corresponding to the operation plan is determined based on the corresponding predicted power value and the power consumption coefficient; finally, the remaining battery capacity of each battery cell can be determined according to the obtained power data corresponding to each battery cell, so that the battery cells whose sum of remaining battery capacity is greater than or equal to the actual power value can be determined in the battery sequence according to the actual power value as the discharge battery group, that is, the battery cells used to power the electric vehicle; it should be noted that by ranking the battery cells based on the estimated health coefficient, the relatively healthy battery cells can be found in the power supply equipment to complete the power supply of the electric vehicle, so that the health of each battery cell can be balanced to improve the use efficiency and service life of the power supply equipment.

[0131] Through the above content, the battery balancing of the power supply device in the process of supplying power to the electric vehicle can be achieved. It can be known that a general battery unit includes two reversible power processes, namely a charging process and a discharging process. In this embodiment, in order to achieve corresponding battery balancing in the charging process of the power supply device, the following method steps can be used to achieve it:

[0132] In response to a charging preparation signal generated by the electric vehicle, a charging display interface is established, wherein the charging display interface includes a battery display area;

[0133] Determine the battery remaining rates corresponding to the battery cells based on the battery remaining capacity and the rated capacity peak value corresponding to the same battery cell, and establish initial battery slots arranged in a line along a preset direction with the same number as the battery cells in the battery display area;

[0134] Filling each initial battery slot based on the remaining rate of each battery along the forward arrangement order of the battery sequence to obtain a current battery slot corresponding to each battery unit;

[0135] Obtaining the estimated charge capacity sent by the electric vehicle, and determining each battery unit whose sum of remaining battery capacity is greater than or equal to the estimated charge capacity as a rechargeable battery group along the forward arrangement order of the battery sequence;

[0136] Dividing each battery slot located in the battery display area based on the number of batteries in each battery unit located in the rechargeable battery pack to obtain a charging slot group corresponding to the rechargeable battery pack and a vacant slot group;

[0137] The battery display area is divided into regions, and the obtained regional contour of the charging sub-region corresponding to the charging slot group is configured with pixels of a first pixel value, and the obtained regional contour of the vacant sub-region corresponding to the vacant slot group is configured with pixels of a second pixel value.

[0138] For example, in this embodiment, when the electric vehicle is ready to charge the power supply device, the electric vehicle will generate a corresponding charging preparation signal. At this time, in order to display the charging process, a corresponding charging display interface can be established, wherein the charging display interface can include a corresponding battery display area;

[0139] Next, based on the above-determined battery remaining capacity and rated power peak value corresponding to the same battery unit, the battery remaining rates corresponding to each battery unit can be determined. At the same time, initial battery slots arranged in a line along a preset direction can be established in the battery display area based on the battery quantity of each battery unit corresponding to the power supply device. Here, the preset direction can include horizontal and vertical directions.

[0140] Next, since the electric vehicle generally first determines the corresponding estimated charge capacity when charging, the battery cells whose sum of remaining battery capacity is greater than or equal to the estimated charge capacity can be selected from the battery sequence based on the estimated charge capacity to determine as the charging battery group;

[0141] Then, after obtaining the corresponding rechargeable battery pack, each battery slot can be divided based on the number of batteries in each battery unit in the rechargeable battery pack, so as to obtain a charging slot group corresponding to the rechargeable battery pack and an empty slot group corresponding to all other remaining battery units;

[0142] Finally, after completing the division of each battery slot, the battery display area can be divided into corresponding charging sub-areas and vacant sub-areas. In order to be able to distinguish different sub-areas based on visual dimensions, the area contours corresponding to different sub-areas can be configured with pixels of first pixel values ​​and second pixel values ​​respectively, so that when the charging display interface is displayed on the display screen of the electric vehicle, the corresponding users can distinguish it and improve the corresponding recognition.

[0143] It should be noted that, here, with regard to the charging process, relatively healthy battery cells can be found in the power supply equipment to complete the charging of the electric vehicle, so that the health of each battery cell can be balanced to improve the efficiency and service life of the power supply equipment.

[0144] Furthermore, in this embodiment, in order to dynamically display the charging process of each battery unit, the following method steps may be included:

[0145] In response to a charging start signal generated by the electric vehicle, a charging progress bar corresponding to the charging battery pack is created in the charging sub-area, wherein the charging progress bar includes node models corresponding to the battery cells in the charging battery pack and node connection segments for connecting the node models at adjacent positions;

[0146] The charging progress bar is configured to be in an invisible state, and based on the acquired charging progress of each battery unit in the rechargeable battery pack, a corresponding portion of the charging progress bar is dynamically displayed by converting the invisible state into a display state.

[0147] For example, Figure 2 is the corresponding charging display interface, where Figure 2In the figure, the charging sub-area includes battery cell A, battery cell B and battery cell C, and the vacant sub-area includes battery cell D and battery cell E; at the same time, exemplarily, the charging display interface also includes node model a, node model b, and node model c corresponding to battery cell A, battery cell B, and battery cell C respectively.

[0148] It can be explained that, in the present embodiment, after completing the usage planning for the charging process based on the different health levels of each battery cell, the electric vehicle can be charged based on the usage planning, and in response to obtaining the charging start signal generated by the electric vehicle, a charging progress bar corresponding to the charging battery pack can be created in the charging sub-area, and the charging progress bar can be configured to be invisible in the initial state. When charging the power supply equipment, the corresponding part of the charging progress bar can be dynamically displayed based on the charging progress of each battery cell in the charging battery pack, that is, converted from the initial invisible state to the corresponding display state, so as to better visually identify the charging progress and improve the corresponding user experience.

[0149] In summary, in this embodiment, when performing battery balancing for the power supply equipment, first, after receiving the motor start signal, the relevant data of the power supply equipment can be identified and obtained; then, the power and charge and discharge conditions of the battery unit are analyzed according to the obtained equipment data to determine the corresponding estimated health coefficient, and complete the real-time evaluation of the health of each battery unit; finally, the planning data is determined by obtaining and analyzing the operation plan of the power-consuming equipment, so that the use plan of the battery unit can be formulated based on the estimated health coefficient and planning data, and the power supply equipment can be adjusted accordingly to achieve efficient power supply to the power-consuming equipment. This method can improve the utilization efficiency of the battery unit, extend the battery life, and ensure the stable operation of the power-consuming equipment, thereby improving the energy utilization efficiency.

[0150] Another embodiment of the present invention provides a system for planning energy storage battery utilization. Figure 3 As the corresponding system block diagram, the system includes:

[0151] The device determination module is configured to determine the power supply device that supplies power to the power-consuming device and obtain device data corresponding to the power supply device;

[0152] a coefficient estimation module, configured to determine, based on the device data, power data and charge-discharge data corresponding to different battery cells included in the power supply device, and determine, based on the power data and charge-discharge data, each estimated health coefficient corresponding to each battery cell;

[0153] a route acquisition module, configured to acquire operation plan data corresponding to the electric device, perform data analysis based on the operation plan data, and determine an operation plan corresponding to the electric device based on the analysis result;

[0154] The power supply planning module is configured to plan the use of each battery unit based on the estimated health coefficient, obtain planning data adapted to the operation plan, and control the power supply equipment to supply power to the power-consuming equipment based on the planning data.

[0155] Another embodiment of the present invention also provides a battery SOC and temperature balancing algorithm based on fuzzy control, wherein the overall flow chart of the method is as follows: Figure 4 As shown in the figure, taking the balancing of six batteries as an example, the six batteries B1, B2, B3, B4, B5 and B6 are divided into two groups. B1, B2 and B3 are divided into one group, named Group 1, and B4, B5 and B6 are divided into one group, named Group 2. First, the voltage, current and temperature of each battery cell are collected, and the SOC is estimated through the state estimation module to find out whether the SOC difference between each battery cell is greater than the balancing start threshold. If it is less than the balancing threshold, there is no need to start balancing; if it is greater than the balancing threshold, balancing is started. The mean-difference method is used for balancing between groups; fuzzy control considering temperature and SOC is used for balancing within the group. The fuzzy control outputs a variable balancing current according to the changes in SOC and temperature. Through pi modulation, the actual current in the circuit is changed to achieve balancing and temperature rise restrictions. When the SOC variance of the six batteries is Stop balancing.

[0156] Among them, through Figure 4 It can be seen that step 1 (S1) is the process of collecting battery information, estimating the SOC state, and judging whether to start balancing. It includes collecting battery status (S11), estimating the SOC state (S12), and judging whether to start balancing (S13).

[0157] Battery information collection (S11): The sensor and information collection module include: voltage sensor, current sensor and temperature sensor. The voltage sensor is used to collect the voltage information of each battery cell and pass it to the state estimation module. The current sensor is used to collect the current information of each battery cell and pass it to the state estimation module. The temperature sensor is used to collect the temperature information of each battery cell and pass it to the state estimation module and the fuzzy control module.

[0158] SOC state estimation (S12): The state estimation module estimates the SOC state of the single cell based on the collected battery voltage, current and temperature information based on the ampere-hour integration method, the characterization parameter-based method, the model-based method or the data-driven method.

[0159] Determine whether to start balancing (S13): compare the estimated battery cell SOCs and find out the maximum battery cell SOC. , the minimum battery cell SOC is , and find the difference between the two. If the balance is enabled, equalization is enabled. Otherwise, no equalization is required.

[0160] Step 2 (S2) is the battery balancing process. It includes inter-group balancing (S21), intra-group fuzzy control balancing (S22), and balancing stop judgment (S23).

[0161] Inter-group balancing (S21): The six batteries are divided into two groups. The SOC of each battery estimated by S12 is summed. B1, B2, and B3 are group 1, and the sum of the SOC of B1, B2, and B3 (the first three batteries) is ,Right now:

[0162] ( is the SOC of the first battery);

[0163] B4, B5, and B6 are group 2. The sum of the SOCs of B4, B5, and B6 (the last three batteries) is ,Right now . First and For comparison, assuming , find the average of the two groups as avgSOC, and then the inter-group balancing controller balances the inductance in the inter-group balancing circuit. Stop between-group balancing and then start within-group balancing.

[0164] Intra-group fuzzy control balancing (S22): The intra-group fuzzy control balancer starts the intra-group balancing circuit. The current on the inductor is the battery balancing current, and its size is related to the on-off time of the thyristor, and the on-off of the thyristor is controlled by the PWM pulse. The size of the traditional balancing current is determined by a fixed duty cycle, and the size of the balancing current cannot be flexibly adjusted according to the inconsistency of the battery. If a battery cell with too high a temperature appears in the battery pack, the balancing cannot be stopped in time or the balancing current cannot be reduced, which will affect the life of the battery and even cause a fire. Therefore, the size of the balancing current needs to be dynamically adjusted according to the inconsistency between the batteries and the temperature of the battery.

[0165] Internal temperature of the battery at any time of charging and discharging It can be expressed as the following formula (1), where is the thermal resistor, is the thermal time constant, is the ambient temperature, is the total heat (W) generated during charging or discharging, which can be expressed as the following formula (2), where T is the internal temperature of the battery, is the rated voltage at temperature T, is the actual voltage at temperature T, is the reversible voltage temperature coefficient, i is the battery charge and discharge current, s is a complex variable, is the inverse Laplace transform. From equations (1) and (2), we can see that the internal temperature of the battery at any time is related to its charge and discharge current:

[0166] (1);

[0167] (2);

[0168] In order to achieve fast and efficient balancing, a larger balancing current is usually used to improve the problem of battery inconsistency. However, this will cause energy loss on the internal resistance of the battery and cause the battery temperature to rise in a short period of time, thus limiting the balancing performance. In order to resolve the contradiction between balancing speed and energy loss, an algorithm based on fuzzy control is proposed. The algorithm combines the battery SOC and temperature as input variables, and outputs the appropriate balancing current size through a dynamic fuzzy controller to control the temperature rise and improve the energy utilization efficiency, thereby achieving fast and efficient balancing operation.

[0169] In the description provided herein, a large number of specific details are described. However, it is understood that embodiments of the present invention can be practiced without these specific details. In some instances, well-known methods, structures and techniques are not shown in detail so as not to obscure the understanding of this description.

[0170] Similarly, it should be understood that in order to streamline the present disclosure and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the present invention, various features of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof.

[0171] Those skilled in the art will appreciate that the modules or units or components of the devices in the examples disclosed herein may be arranged in the devices described in the embodiment, or alternatively may be located in one or more devices different from the devices in the examples. The modules in the foregoing examples may be combined into one module or may be divided into multiple submodules.

[0172] Those skilled in the art will appreciate that the modules in the devices in the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments may be combined into one module or unit or component, and furthermore may be divided into a plurality of submodules or subunits or subcomponents.

[0173] Furthermore, those skilled in the art will appreciate that although some embodiments described herein include certain features included in other embodiments but not other features, the combination of features from different embodiments is meant to be within the scope of the present invention and to form different embodiments.

Claims

1. A method for planning the utilization of energy storage batteries, characterized in that: The following steps are involved: Determine a power supply device that supplies power to the power-consuming device, and obtain device data corresponding to the power supply device; Determine the power data and charge-discharge data corresponding to each different battery unit included in the power supply device based on the device data, and determine each estimated health factor corresponding to each battery unit based on the power data and charge-discharge data; Acquiring operation plan data corresponding to the electric equipment, performing data analysis based on the operation plan data, and determining an operation plan corresponding to the electric equipment based on the analysis result; Performing usage planning for each battery unit based on each estimated health factor, obtaining planning data adapted to the operation plan, and controlling the power supply device to supply power to the power-consuming device based on the planning data; The operation plan data is navigation setting data; Acquiring operation plan data corresponding to the electric device, performing data analysis based on the operation plan data, and determining an operation plan corresponding to the electric device based on the analysis result, including: Receiving navigation setting data of electric equipment; In response to the navigation setting data respectively including target location data corresponding to the target end point and current starting data corresponding to the starting location, generating an operation plan corresponding to the electrical equipment based on the current starting data and the target location data; or, In response to the navigation setting data only including current starting data corresponding to the starting position, retrieving real-time map data, and determining a real-time road where the starting position is located based on the real-time map data, Dividing the real-time road along the extension direction of the real-time road to obtain a divided road starting from the starting position, and determining the divided road as an operation plan corresponding to the electric equipment; Based on each estimated health factor, use planning is performed on each battery unit to obtain planning data adapted to the operation plan, and based on the planning data, a power supply device is controlled to supply power to the power-consuming device, including: Ranking each battery unit from high to low based on each estimated health factor to obtain a battery sequence; Determine the estimated driving time based on the operation plan and obtain the current time; Determine a trip end time based on the current time and the estimated driving duration, and obtain a current outdoor temperature and a future outdoor temperature corresponding to the current time and the trip end time respectively; Calculating the average value of the current outdoor temperature and the future outdoor temperature to obtain an estimated reference temperature, and determining a power consumption coefficient based on the estimated reference temperature; Determining a predicted power value based on the operation plan, and determining an actual power value corresponding to the operation plan based on the predicted power value and the power consumption coefficient; Determine the remaining capacity of each battery corresponding to each battery cell based on each power data corresponding to each battery cell, and determine each battery cell whose sum of remaining capacity is greater than or equal to the actual power value as a discharge battery group along the forward arrangement order of the battery sequence; The battery cells in the discharge battery pack are controlled to supply power to the power-consuming device based on the forward arrangement order of the battery sequence.

2. The energy storage battery utilization planning method according to claim 1, characterized in that: Determining the power data and charge-discharge data corresponding to each different battery unit included in the power supply device based on the device data, and determining each estimated health factor corresponding to each battery unit based on the power data and charge-discharge data, including: Splitting the device data to obtain battery data corresponding to different battery units included in the power supply device, wherein the battery data includes power data and charge and discharge data; Determine the coefficient of the power data corresponding to each battery cell based on a preset power coefficient determination strategy, and calculate the product of the obtained power health coefficient and the retrieved power weight to obtain first fusion data; Determine the coefficient of the charge and discharge data corresponding to each battery cell based on a preset charge and discharge coefficient determination strategy, and calculate the product of the obtained charge and discharge health coefficient and the retrieved charge and discharge weight to obtain second fusion data; The first fused data and the second fused data are fused and calculated to obtain estimated health coefficients corresponding to each battery cell.

3. The energy storage battery utilization planning method according to claim 2, characterized in that: The coefficient of the power data corresponding to each battery cell is determined based on a preset power coefficient determination strategy, including: Determine the rated peak power and rated internal resistance corresponding to the battery cell based on any power data, and retrieve the historical peak power and historical internal resistance corresponding to the battery cell; Comparing the historical power peak value with the rated power peak value, and determining the peak reduction rate corresponding to the battery unit based on the comparison result; Comparing the peak values ​​of the historical internal resistance with the rated internal resistance, and determining the internal resistance increase rate corresponding to the battery cell based on the comparison result; The reference power coefficient corresponding to the battery cell is reduced based on the peak reduction rate and the internal resistance increase rate to obtain a power health coefficient corresponding to the battery cell.

4. The energy storage battery utilization planning method according to claim 2, characterized in that: The method of determining the coefficient of the charge and discharge data corresponding to each battery cell based on a preset charge and discharge coefficient determination strategy includes: Determine the rated charge and discharge times and the rated energy conversion efficiency corresponding to the battery cell based on any charge and discharge data, and retrieve the historical charge and discharge times and the historical energy conversion efficiency corresponding to the battery cell; Comparing the historical charge and discharge times with the rated charge and discharge times, and determining a times remaining rate corresponding to the battery cell based on the comparison result; Comparing the historical energy conversion efficiency with the rated energy conversion efficiency, and determining the efficiency reduction rate corresponding to the battery cell based on the comparison result; The reference charge and discharge coefficient corresponding to the battery cell is reduced based on the number of remaining rates and the efficiency reduction rate to obtain a charge and discharge health coefficient corresponding to the battery cell.

5. The energy storage battery utilization planning method according to claim 2, characterized in that: The method further comprises: Obtaining an actual health factor of the battery cell based on the management end, and comparing the actual health factor corresponding to the same battery cell with the estimated health factor; When the actual health coefficient is greater than the estimated health coefficient, the power weight and the charge and discharge weight are increased respectively; When the actual health factor is less than the estimated health factor, the power weight and the charge and discharge weight are respectively trained to be reduced; The power weight and charge and discharge weight after training are obtained through the following formula: ； in, The power weight Increase the number of training sessions. The power weight The training constant value of The power weight Reduce the number of training sessions. is the power weight after training, is the charge and discharge weight Increase the number of training sessions. is the charge and discharge weight The training constant value of is the charge and discharge weight Increase or decrease the number of training sessions. is the charge and discharge weight after training.

6. The energy storage battery utilization planning method according to claim 1, characterized in that: The method further comprises: In response to a charging preparation signal generated by the power-consuming device, establishing a charging display interface, wherein the charging display interface includes a battery display area; Determine the battery remaining rates corresponding to the battery cells based on the battery remaining capacity and the rated capacity peak value corresponding to the same battery cell, and establish initial battery slots arranged in a line along a preset direction with the same number as the battery cells in the battery display area; Filling each initial battery slot based on the remaining rate of each battery along the forward arrangement order of the battery sequence to obtain a current battery slot corresponding to each battery unit; Obtaining the estimated charge capacity sent by the power-consuming device, and determining each battery unit whose sum of remaining battery capacity is greater than or equal to the estimated charge capacity as a rechargeable battery group along the forward arrangement order of the battery sequence; Dividing each battery slot located in the battery display area based on the number of batteries in each battery unit located in the rechargeable battery pack to obtain a charging slot group corresponding to the rechargeable battery pack and a vacant slot group; The battery display area is divided into regions, and the obtained regional contour of the charging sub-region corresponding to the charging slot group is configured with pixels of a first pixel value, and the obtained regional contour of the vacant sub-region corresponding to the vacant slot group is configured with pixels of a second pixel value.

7. The energy storage battery utilization planning method according to claim 6, characterized in that: The method further comprises: In response to a charging start signal generated by an electric device, a charging progress bar corresponding to the charging battery pack is created in the charging sub-area, wherein the charging progress bar includes node models corresponding to the battery cells in the charging battery pack and node connection segments for connecting the node models at adjacent positions; The charging progress bar is configured to be in an invisible state, and based on the acquired charging progress of each battery unit in the rechargeable battery pack, a corresponding portion of the charging progress bar is dynamically displayed by converting the invisible state into a display state.

8. A system for planning energy storage battery utilization, characterized in that: include: A device determination module is configured to determine a power supply device that supplies power to the power-consuming device and obtain device data corresponding to the power supply device; a coefficient estimation module, configured to determine, based on the device data, power data and charge-discharge data corresponding to each different battery unit included in the power supply device, and determine, based on the power data and charge-discharge data, each estimated health coefficient corresponding to each battery unit; a route acquisition module, configured to acquire operation plan data corresponding to the electric device, perform data analysis based on the operation plan data, and determine an operation plan corresponding to the electric device based on the analysis result; A power supply planning module is configured to plan the use of each battery unit based on each estimated health coefficient, obtain planning data adapted to the operation plan, and control the power supply device to supply power to the power-consuming device based on the planning data; The operation plan data is navigation setting data; Acquiring operation plan data corresponding to the electric device, performing data analysis based on the operation plan data, and determining an operation plan corresponding to the electric device based on the analysis result, including: Receiving navigation setting data of electric equipment; In response to the navigation setting data respectively including target location data corresponding to the target end point and current starting data corresponding to the starting location, generating an operation plan corresponding to the electrical equipment based on the current starting data and the target location data; or, In response to the navigation setting data only including current starting data corresponding to the starting position, retrieving real-time map data, and determining a real-time road where the starting position is located based on the real-time map data, Dividing the real-time road along the extension direction of the real-time road to obtain a divided road starting from the starting position, and determining the divided road as an operation plan corresponding to the electric equipment; Based on each estimated health factor, use planning is performed on each battery unit to obtain planning data adapted to the operation plan, and based on the planning data, a power supply device is controlled to supply power to the power-consuming device, including: Ranking each battery unit from high to low based on each estimated health factor to obtain a battery sequence; Determine the estimated driving time based on the operation plan and obtain the current time; Determine a trip end time based on the current time and the estimated driving duration, and obtain a current outdoor temperature and a future outdoor temperature corresponding to the current time and the trip end time respectively; Calculating the average value of the current outdoor temperature and the future outdoor temperature to obtain an estimated reference temperature, and determining a power consumption coefficient based on the estimated reference temperature; Determining a predicted power value based on the operation plan, and determining an actual power value corresponding to the operation plan based on the predicted power value and the power consumption coefficient; Determine the remaining capacity of each battery corresponding to each battery cell based on each power data corresponding to each battery cell, and determine each battery cell whose sum of remaining capacity is greater than or equal to the actual power value as a discharge battery group along the forward arrangement order of the battery sequence; The battery cells in the discharge battery pack are controlled to supply power to the power-consuming device based on the forward arrangement order of the battery sequence.

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