Battery energy storage management method and system based on data center

Abstract

The invention is suitable for the technical field of energy storage management, and particularly relates to a battery energy storage management method and system based on a data center, and the method comprises the steps: obtaining the electric quantity information of each energy storage module in a battery pack, and dividing the energy storage module into a basic energy storage module and a dynamic energy storage module; charging the basic energy storage module, acquiring charging parameter information, and predicting the charging duration of the basic energy storage module; scheduling the basic energy storage module with short charging time based on the charging time length, and performing dynamic replacement through the dynamic energy storage module; and carrying out statistics on the replacement times of each energy storage module, carrying out abnormity identification, and determining an abnormal energy storage module. According to the method, the energy storage modules are divided, so that the energy storage modules which are being charged are dynamically replaced in the charging process to ensure that the charging speed of the whole battery pack is kept consistent, the situation that the electric quantities of the energy storage modules in the battery pack are not consistent is avoided, and the performance uniformity of the energy storage modules is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of energy storage management, and particularly relates to a battery energy storage management method and system based on a data center. Background Art

[0002] A battery energy storage management system is a technical system for effectively monitoring, controlling, and maintaining a battery energy storage system. It ensures the safe operation of the battery by real-time monitoring of the battery's state parameters such as voltage, current, temperature, and state of charge, etc., while optimizing the charging and discharging process to extend the battery life and improve energy efficiency. This system is of great significance for improving the utilization efficiency of renewable energy, balancing the power grid load, providing emergency backup power, etc.

[0003] In the current battery energy storage management process, due to the differences in energy storage performance of different energy storage units, it is easy to have differences in the energy storage time of energy storage units, resulting in overcharging of some energy storage modules and undercharging of some other energy storage units. Summary of the Invention

[0004] The purpose of the present invention is to provide a battery energy storage management method based on a data center, aiming to solve the problem that due to the differences in energy storage performance of different energy storage units, it is easy to have differences in the energy storage time of energy storage units, resulting in overcharging of some energy storage modules and undercharging of some other energy storage units.

[0005] The present invention is implemented as follows. The battery energy storage management method based on a data center includes: Obtain the power information of each energy storage module in the battery pack, divide the energy storage modules into basic energy storage modules and dynamic energy storage modules, and the ratio of the number of dynamic energy storage modules to the number of basic energy storage modules is a preset value; Charge the basic energy storage modules, obtain the charging parameter information, and predict the charging duration of the basic energy storage modules based on the charging parameter information; Schedule the basic energy storage modules with short charging times based on the charging duration, and perform dynamic replacement through the dynamic energy storage modules; Count the replacement times of each energy storage module, select the energy storage modules with replacement times lower than the preset value for anomaly identification, and determine the energy storage modules with anomalies.

[0006] Preferably, the step of charging the basic energy storage modules, obtaining the charging parameter information, and predicting the charging duration of the basic energy storage modules based on the charging parameter information specifically includes: Charge all the basic energy storage modules, monitor the charging process of each basic energy storage module in real time, and record the corresponding charging parameter information. The charging parameter information at least includes charging time, charging temperature, and charging current; Construct a time-temperature curve and a temperature-current curve based on the charging parameter information, and perform function simulation to obtain a time-temperature function and a temperature-current function; Predict the charging amount according to the time-temperature function and the temperature-current function, and predict the charging duration according to the remaining power of the basic energy storage module.

[0007] Preferably, the step of scheduling the basic energy storage modules with short charging times based on the charging duration and dynamically replacing them through the dynamic energy storage modules includes: Query the charging duration of each basic energy storage module at preset time intervals, and calculate the maximum difference in the charging duration; Compare the maximum difference in the charging duration with the preset duration value. If it is greater than the preset duration value, replace the basic energy storage module with the longest charging duration with a group of dynamic energy storage modules; Re-determine the query time interval based on the maximum difference in the charging duration, and the new query time interval takes effect immediately.

[0008] Preferably, the step of counting the replacement times of each energy storage module, selecting the energy storage modules with replacement times lower than the preset value for anomaly identification, and determining the abnormal energy storage modules specifically includes: Count the replacement times of each energy storage module. If within the preset charging duration, the replacement times of a single energy storage module exceed the preset number of times, it is determined that anomaly identification is to be performed; Select the energy storage modules with replacement times less than the set number of times, perform abnormal heating determination based on the relative position relationship of the energy storage modules, and mark the abnormal energy storage modules; During the charging process, perform real-time monitoring, record the charging records of individual energy storage modules, store them in the data center, and analyze the charging amount distribution of the energy storage modules through the data center.

[0009] Preferably, in the step of performing abnormal heating determination based on the relative position relationship of the energy storage modules, construct a two-dimensional coordinate system based on the positions of the energy storage modules, and construct a module matrix in the two-dimensional coordinate system. Each element in the module matrix represents an energy storage module. Extract the elements of the energy storage modules with replacement times less than the set number of times. Each time, select an energy storage module with a replacement time less than the set number of times, turn off the energy storage module through an electronic fuse, continue normal charging, monitor the charging parameters of its adjacent elements. If the charging speed of the energy storage module corresponding to the adjacent element increases, it is determined that the turned-off energy storage module is in an abnormal state.

[0010] Another object of the present invention is to provide a battery energy storage management system based on a data center, and the system includes: The module division module is used to obtain the power information of each energy storage module in the battery pack, divide the energy storage modules into basic energy storage modules and dynamic energy storage modules, and the quantity ratio of the dynamic energy storage modules to the basic energy storage modules is a preset value; The charging parameter recording module is used to charge the basic energy storage modules, obtain the charging parameter information, and predict the charging duration of the basic energy storage modules based on the charging parameter information; The dynamic replacement module is used to schedule the basic energy storage modules with short charging durations based on the charging duration, and perform dynamic replacement through the dynamic energy storage modules; The anomaly identification module is used to count the replacement times of each energy storage module, select the energy storage modules with replacement times lower than the preset value for anomaly identification, and determine the energy storage modules with anomalies.

[0011] Preferably, the charging parameter recording module includes: The data recording unit is used to charge all the basic energy storage modules, monitor the charging process of each basic energy storage module in real time, and record the corresponding charging parameter information. The charging parameter information at least includes charging time, charging temperature, and charging current; The curve construction unit is used to construct a time-temperature curve and a temperature-current curve based on the charging parameter information, and perform function simulation to obtain a time-temperature function and a temperature-current function; The charging prediction unit is used to predict the charging amount according to the time-temperature function and the temperature-current function, and predict the charging duration according to the remaining power of the basic energy storage module.

[0012] Preferably, the dynamic replacement module includes: The charging duration statistics unit is used to query the charging duration of each basic energy storage module at preset time intervals and calculate the maximum difference in charging duration; The module replacement unit is used to compare the maximum difference in charging duration with the duration preset value. If it is greater than the duration preset value, the basic energy storage module with the longest charging duration is replaced with a group of dynamic energy storage modules; The time interval adjustment unit is used to re-determine the query time interval based on the maximum difference in charging duration, and the new query time interval takes effect immediately.

[0013] Preferably, the anomaly identification module includes: The replacement times statistics unit is used to count the replacement times of each energy storage module. If the replacement times of a single energy storage module exceed the times preset value within the preset charging duration, it is determined that anomaly identification is to be performed; The anomaly marking unit is used to select the energy storage modules with fewer replacement times, determine anomaly heating according to the relative position relationship of the energy storage modules, and mark the energy storage modules with anomalies; A data recording unit is used to perform real-time monitoring during the charging process, record the charging records of individual energy storage modules, store them in a data center, and analyze the charging amount distribution of the energy storage modules through the data center.

[0014] Preferably, in the step of determining abnormal heating according to the relative position relationship of the energy storage modules, a two-dimensional coordinate system is constructed based on the positions of the energy storage modules, and a module matrix is constructed in the two-dimensional coordinate system. Each element in the module matrix represents an energy storage module. The elements of the energy storage modules with the replacement times less than the set times are extracted. Each time, an energy storage module with the replacement times less than the set times is selected, and the energy storage module is turned off through an electronic fuse, and normal charging continues. The charging parameters of its adjacent elements are monitored. If the charging speed of the energy storage module corresponding to the adjacent element increases, it is determined that the turned-off energy storage module is in an abnormal state.

[0015] The battery energy storage management method based on a data center provided by the present invention divides the energy storage modules, so that during the charging process, the energy storage modules being charged are dynamically replaced to ensure that the overall charging speed of the battery pack remains consistent, avoid the situation of inconsistent battery levels of the energy storage modules in the battery pack, and improve the performance uniformity of the energy storage modules. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flowchart of the battery energy storage management method based on a data center provided by an embodiment of the present invention; Figure 2 It is a flowchart of the step of charging the basic energy storage module, obtaining charging parameter information, and predicting the charging duration of the basic energy storage module based on the charging parameter information provided by an embodiment of the present invention; Figure 3 It is a flowchart of the step of scheduling the basic energy storage module with a short charging time based on the charging duration and dynamically replacing it through a dynamic energy storage module provided by an embodiment of the present invention; Figure 4 It is a flowchart of the step of counting the replacement times of each energy storage module, selecting the energy storage module with the replacement times lower than the preset value for abnormal identification, and determining the abnormal energy storage module provided by an embodiment of the present invention; Figure 5 It is an architecture diagram of the battery energy storage management system based on a data center provided by an embodiment of the present invention; Figure 6 It is an architecture diagram of the charging parameter recording module provided by an embodiment of the present invention; Figure 7 It is an architecture diagram of the dynamic replacement module provided by an embodiment of the present invention; Figure 8 It is an architecture diagram of the abnormal identification module provided by an embodiment of the present invention. Detailed implementation manners

[0017] In order to make the objectives, technical solutions and advantages of the present invention more clear and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0018] As Figure 1 shown, it is a flowchart of a battery energy storage management method based on a data center provided by an embodiment of the present invention. The method includes: S100. Obtain the power information of each energy storage module in the battery pack, divide the energy storage modules into basic energy storage modules and dynamic energy storage modules, and the quantity ratio of the dynamic energy storage modules to the basic energy storage modules is a preset value.

[0019] In this step, obtain the power information of each energy storage module in the battery pack. When charging, number all the energy storage modules in the battery pack, read the remaining power in each energy storage module, and select a part of the energy storage modules as dynamic energy storage modules. The ratio of the number of dynamic energy storage modules to the total number of energy storage modules is a preset value, such as 3%. When the battery pack includes 100 energy storage modules, three energy storage modules are selected as dynamic energy storage modules, and the remaining energy storage modules are used as basic energy storage modules. When charging, first charge the basic energy storage modules and use the dynamic energy storage modules for charging adjustment.

[0020] S200. Charge the basic energy storage modules, obtain the charging parameter information, and predict the charging duration of the basic energy storage modules based on the charging parameter information.

[0021] In this step, charge the basic energy storage modules. By charging the basic energy storage modules, record the data generated during the charging process, that is, obtain the charging parameter information. The energy storage modules are connected in parallel. When charging, they have the same charging voltage. However, due to different losses of different energy storage modules, their internal resistances are also different, so the charging currents are also different. Record the above information, and estimate the charging duration required for each basic energy storage module to be fully charged according to the real-time charging amount of the basic energy storage modules. Due to different losses and differences in remaining power of the basic energy storage modules, this will lead to differences in the charging durations of different basic energy storage modules. The energy storage modules with more remaining power and faster charging speed have shorter corresponding charging durations, and vice versa. If charging is carried out synchronously, some energy storage modules are already fully charged while the remaining energy storage modules are still undercharged.

[0022] S300. Schedule the basic energy storage modules with short charging times based on the charging duration, and perform dynamic replacement through the dynamic energy storage modules.

[0023] In this step, the basic energy storage modules with short charging times are scheduled based on the charging duration. An electronic fuse is set on each energy storage module, and the on / off of each energy storage module can be controlled through the electronic fuse. The electronic fuse can be used to control the connection of the energy storage module to the charging system or its disconnection from the charging. During the charging process, if the charging durations of different energy storage modules vary greatly, the energy storage module with the longest charging duration is disconnected. At the same time, the corresponding number of dynamic energy storage modules are connected. During this process, since the number of energy storage modules in the charging state is the same, when the charging voltage remains unchanged, the charging current of each energy storage module is ensured to be stable. After charging for a certain period of time, the dynamic energy storage modules are replaced with the disconnected energy storage modules to reduce the difference in charging duration between different energy storage modules, so that different energy storage modules can be fully charged at the same time.

[0024] S400. Count the replacement times of each energy storage module, select the energy storage modules with replacement times lower than the preset value for anomaly identification, and determine the energy storage modules with anomalies.

[0025] In this step, count the replacement times of each energy storage module. When some energy storage modules are abnormal, their charging speed will become slower. For example, when the energy storage module ages, its internal resistance increases, and it will generate heat during charging, affecting the charging efficiency. At this time, the charging duration of this energy storage module will increase. To maintain the charging balance, the normally charged energy storage modules will be temporarily replaced. Therefore, the more the replacement times of an energy storage module, the faster its charging speed. On the contrary, the fewer the replacement times of an energy storage module, the slower its charging speed. Then, an anomaly determination is made to determine the energy storage modules with anomalies.

[0026] As Figure 2 shown, as a preferred embodiment of the present invention, the step of charging the basic energy storage module, obtaining the charging parameter information, and predicting the charging duration of the basic energy storage module based on the charging parameter information specifically includes: S201. Charge all the basic energy storage modules, monitor the charging process of each basic energy storage module in real time, and record the corresponding charging parameter information. The charging parameter information at least includes charging time, charging temperature, and charging current.

[0027] In this step, when charging all the basic energy storage modules, at the beginning of charging, only the remaining power of each energy storage module can be obtained, and its charging speed cannot be calculated. To determine its charging speed and estimate its charging time, the charging process of each basic energy storage module is monitored, and the charging parameter information is recorded. The charging parameter information at least includes charging time, charging temperature, and charging current. During the charging process, the energy storage module will generate heat. The greater its internal resistance, the greater the heat generated, and the lower the charging speed.

[0028] S202. Based on the charging parameter information, construct a time-temperature curve and a temperature-current curve, and perform function simulation to obtain a time-temperature function and a temperature-current function.

[0029] In this step, based on the charging parameter information, construct a time-temperature curve and a temperature-current curve. Construct two sets of two-dimensional coordinate systems. In one set of two-dimensional coordinate systems, construct a time-temperature curve with time as the abscissa and temperature as the ordinate. In the other set of two-dimensional coordinate systems, with temperature as the abscissa and current value as the ordinate, so as to obtain a set of time-temperature curves and a set of temperature-current curves. Use a function fitting tool to fit the two sets of curves into corresponding functions, and obtain the time-temperature function T(t) and the temperature-current curve I(T).

[0030] S203. Predict the charging amount according to the time-temperature function and the temperature-current function, and predict the charging duration according to the remaining power of the basic energy storage module.

[0031] In this step, predict the charging amount according to the time-temperature function and the temperature-current function. When making a prediction, predict the time-temperature function T(t) according to a preset time gradient. For example, set the time gradient as Δt, and increase the time by Δt each time. Substitute it into the time-temperature function T(t) to predict the temperature at the corresponding time. Then substitute this temperature into the temperature-current curve I(T) to predict the charging current at the corresponding moment. Calculate the charging amount based on the current and the time Δt, and calculate the charging duration required for each basic energy storage module to be fully charged accordingly.

[0032] As Figure 3 shown, as a preferred embodiment of the present invention, the step of scheduling the basic energy storage module with a short charging time based on the charging duration and dynamically replacing it through a dynamic energy storage module includes: S301. Query the charging duration of each basic energy storage module at a preset time interval, and calculate the maximum difference in the charging duration.

[0033] In this step, query the charging duration of each basic energy storage module at a preset time interval, sort the basic energy storage modules based on the charging duration. The basic energy storage module with the longest charging duration has the slowest charging speed. Calculate the difference between the longest charging duration and the shortest charging duration to obtain the maximum difference.

[0034] S302. Compare the maximum difference in the charging duration with a preset duration value. If it is greater than the preset duration value, replace the basic energy storage module with the longest charging duration with a set of dynamic energy storage modules.

[0035] In this step, compare the maximum difference in charging duration with the duration preset value. When the maximum difference in charging duration is greater than the duration preset value, it indicates that during this charging process, there is an uneven charging speed among the energy storage modules. To maintain the consistency of the charging speed, select the basic energy storage module with the maximum charging duration and disconnect it from the charging system. At the same time, connect a group of dynamic energy storage modules to the charging system to ensure that the total number of energy storage modules in the charging state remains unchanged. Repeat this process.

[0036] S303. Re-determine the query time interval based on the maximum difference in charging duration, and the new query time interval takes effect immediately.

[0037] In this step, re-determine the query time interval based on the maximum difference in charging duration. The larger the maximum difference, the greater the gap in charging duration during the previous round of dynamic adjustment, and the query time interval needs to be shortened to achieve a faster adjustment frequency. On the contrary, the larger the maximum difference, the stronger the charging consistency of the energy storage modules, and a larger query time interval can be adopted. The new query time interval takes effect immediately.

[0038] As Figure 4 shown, as a preferred embodiment of the present invention, the step of counting the replacement times of each energy storage module, selecting the energy storage module with the replacement times lower than the preset value for abnormal identification, and determining the abnormal energy storage module specifically includes: S401. Count the replacement times of each energy storage module. If within the preset charging duration, the replacement times of a single energy storage module exceed the number preset value, it is determined to perform abnormal identification.

[0039] In this step, count the replacement times of each energy storage module. If within the preset charging duration, the replacement times of a certain energy storage module exceed the number preset value, it indicates that during this charging process, the unevenness of the charging speed is extremely obvious, and there may be an abnormal energy storage module. For example, if a certain energy storage module abnormally heats up and its charging speed significantly decreases, then dynamic adjustment will be frequently performed, and abnormal identification is performed at this time.

[0040] S402. Select the energy storage modules with the replacement times less than the set number, determine abnormal heating according to the relative position relationship of the energy storage modules, and mark the abnormal energy storage modules.

[0041] In this step, select the energy storage modules with the number of replacements less than the set number. Construct a two-dimensional coordinate system based on the positions of the energy storage modules, and construct a module matrix in the two-dimensional coordinate system. Each element in the module matrix represents an energy storage module. Extract the elements of the energy storage modules with the number of replacements less than the set number. Each time, select an energy storage module with the number of replacements less than the set number, turn off the energy storage module through an electronic fuse, continue normal charging, and monitor the charging parameters of its adjacent elements. If the charging speed of the energy storage module corresponding to the adjacent element increases, it is determined that the turned-off energy storage module is in an abnormal state.

[0042] S403. During the charging process, conduct real-time monitoring, record the charging records of individual energy storage modules, store them in the data center, and analyze the charging amount distribution of the energy storage modules through the data center.

[0043] In this step, during the charging process, conduct real-time monitoring. In order to analyze the working conditions of each energy storage module, record all the charging records in the data center. The data in the data center is updated regularly. Analyze the charging amount of each group of energy storage modules each time to construct a charging amount prediction function, and use the charging amount prediction function to estimate its lifespan and provide maintenance suggestions for the users.

[0044] As Figure 5 shown, the battery energy storage management system based on the data center provided by the embodiment of the present invention includes: A module division module 100, configured to obtain the power information of each energy storage module in the battery pack, divide the energy storage modules into basic energy storage modules and dynamic energy storage modules, and the quantity ratio of the dynamic energy storage modules to the basic energy storage modules is a preset value.

[0045] In this system, the module division module 100 obtains the power information of each energy storage module in the battery pack. During charging, number all the energy storage modules in the battery pack, read the remaining power in each energy storage module, and select a part of the energy storage modules as dynamic energy storage modules. The ratio of the number of dynamic energy storage modules to the total number of energy storage modules is a preset value, such as 3%. When the battery pack contains 100 energy storage modules, three energy storage modules are selected as dynamic energy storage modules, and the remaining energy storage modules are used as basic energy storage modules. During charging, first charge the basic energy storage modules and use the dynamic energy storage modules for charging adjustment.

[0046] A charging parameter recording module 200, configured to charge the basic energy storage modules, obtain charging parameter information, and predict the charging duration of the basic energy storage modules based on the charging parameter information.

[0047] In this system, the charging parameter recording module 200 charges the basic energy storage module group. By charging the basic energy storage module group, the data generated during the charging process is recorded, that is, the charging parameter information is obtained. The energy storage modules are connected in parallel. During charging, they have the same charging voltage. However, due to different losses of different energy storage modules, their internal resistances are also different, so the charging currents will also be different. The above information is recorded, and the charging duration required for each basic energy storage module to be fully charged is estimated based on the real-time charging amount of the basic energy storage module group. Due to different losses and different remaining power levels of the basic energy storage modules, the charging durations of different basic energy storage modules will vary. The energy storage module with more remaining power and faster charging speed will have a shorter corresponding charging duration, and vice versa. If charging is carried out simultaneously, some energy storage modules will be fully charged while the remaining energy storage modules are still undercharged.

[0048] The dynamic replacement module 300 is used to schedule the basic energy storage modules with short charging durations based on the charging duration, and perform dynamic replacement through the dynamic energy storage modules.

[0049] In this system, the dynamic replacement module 300 schedules the basic energy storage modules with short charging durations based on the charging duration. An electronic fuse is set on each energy storage module. Through the electronic fuse, the on / off of each energy storage module can be controlled. The electronic fuse can be used to control the connection of the energy storage module to the charging system or disconnection from the charging. During the charging process, if the charging durations of different energy storage modules vary greatly, the energy storage module with the longest charging duration is disconnected. At the same time, the corresponding number of dynamic energy storage modules are connected. During this process, since the number of energy storage modules in the charging state is the same, when the charging voltage remains unchanged, the charging currents of all energy storage modules are ensured to be stable. After charging for a certain period of time, the dynamic energy storage modules are replaced back with the disconnected energy storage modules to reduce the difference in charging durations between different energy storage modules, so that different energy storage modules can be fully charged simultaneously.

[0050] The abnormal identification module 400 is used to count the replacement times of each energy storage module, select the energy storage modules with replacement times lower than the preset value for abnormal identification, and determine the energy storage modules with abnormalities.

[0051] In this system, the anomaly recognition module 400 counts the replacement times of each energy storage module. When some energy storage modules are abnormal, their charging speed will become slower. For example, when the energy storage module ages, its internal resistance increases, and heat is generated during charging, which affects the charging efficiency. At this time, the charging duration of this energy storage module will increase. To maintain the charging balance, the normally charged energy storage modules will be temporarily replaced. Therefore, the more times an energy storage module is replaced, the faster its charging speed. Conversely, the fewer times an energy storage module is replaced, the slower its charging speed. Then, an anomaly determination is made to identify the abnormal energy storage module.

[0052] As Figure 6 shown, as a preferred embodiment of the present invention, the charging parameter recording module 200 includes: The data recording unit 201 is used to charge all basic energy storage modules, monitor the charging process of each basic energy storage module in real time, and record the corresponding charging parameter information. The charging parameter information at least includes charging time, charging temperature, and charging current.

[0053] In this module, the data recording unit 201 charges all basic energy storage modules. At the beginning of charging, only the remaining power of each energy storage module can be obtained, and its charging speed cannot be calculated. To determine its charging speed and estimate its charging time, the charging process of each basic energy storage module is monitored, and the charging parameter information is recorded. The charging parameter information at least includes charging time, charging temperature, and charging current. During the charging process, the energy storage module will generate heat. The greater its internal resistance, the greater the heat generation, and the lower the charging speed.

[0054] The curve construction unit 202 is used to construct a time-temperature curve and a temperature-current curve based on the charging parameter information, and perform function simulation to obtain a time-temperature function and a temperature-current function.

[0055] In this module, the curve construction unit 202 constructs a time-temperature curve and a temperature-current curve based on the charging parameter information, constructs two sets of two-dimensional coordinate systems. In one set of two-dimensional coordinate systems, a time-temperature curve is constructed, with time as the abscissa and temperature as the ordinate. In the other set of two-dimensional coordinate systems, temperature is used as the abscissa and current value as the ordinate, so as to obtain a set of time-temperature curves and a set of temperature-current curves. The two sets of curves are fitted into corresponding functions through a function fitting tool to obtain the time-temperature function T(t) and the temperature-current curve I(T).

[0056] The charging prediction unit 203 is used to predict the charging amount according to the time-temperature function and the temperature-current function, and predict the charging duration according to the remaining power of the basic energy storage module.

[0057] In this module, the charging prediction unit 203 predicts the charging amount according to the time-temperature function and the temperature-current function. When making the prediction, the time-temperature function T(t) is predicted according to a preset time gradient. For example, if the time gradient is set as Δt, the time Δt is increased each time and substituted into the time-temperature function T(t) to predict the temperature corresponding to the time. Subsequently, this temperature is substituted into the temperature-current curve I(T) to predict the charging current at the corresponding moment, and the charging amount is calculated based on the current and the time Δt. Based on this, the charging duration required for each basic energy storage module to be fully charged is calculated.

[0058] As Figure 7 shown, as a preferred embodiment of the present invention, the dynamic replacement module 300 includes: A charging duration statistics unit 301, configured to query the charging durations of each basic energy storage module at a preset time interval and calculate the maximum difference in the charging durations.

[0059] In this module, the charging duration statistics unit 301 queries the charging durations of each basic energy storage module at a preset time interval, sorts the basic energy storage modules based on the charging durations. The basic energy storage module with the longest charging duration has the slowest charging speed. The difference between the longest charging duration and the shortest charging duration is calculated to obtain the maximum difference.

[0060] A module replacement unit 302, configured to compare the maximum difference in the charging durations with a duration preset value. If it is greater than the duration preset value, the basic energy storage module with the longest charging duration is replaced with a group of dynamic energy storage modules.

[0061] In this module, the module replacement unit 302 compares the maximum difference in the charging durations with the duration preset value. When the maximum difference in the charging durations is greater than the duration preset value, it indicates that during this charging process, there is an uneven charging speed among the energy storage modules. To maintain the consistency of the charging speed, the basic energy storage module with the longest charging duration is selected and disconnected from the charging system. At the same time, a group of dynamic energy storage modules are connected to the charging system to ensure that the total number of energy storage modules in the charging state remains unchanged. This process is repeated.

[0062] A time interval adjustment unit 303, configured to re-determine the query time interval based on the maximum difference in the charging durations, and the new query time interval takes effect immediately.

[0063] In this module, the time interval adjustment unit 303 re - determines the query time interval based on the maximum difference in charging duration. The larger the maximum difference, the greater the gap in charging duration during the previous round of dynamic adjustment, and the query time interval needs to be shortened to achieve a faster adjustment frequency. Conversely, the larger the maximum difference, the stronger the charging consistency of the energy storage module group, and a larger query time interval can be adopted. The new query time interval takes effect immediately.

[0064] As Figure 8 shown, as a preferred embodiment of the present invention, the anomaly recognition module 400 includes: A replacement times statistical unit 401, which is used to count the replacement times of each energy storage module. If the replacement times of a single energy storage module exceed the preset number of times within the preset charging duration, it is determined that anomaly recognition is to be performed.

[0065] In this module, the replacement times statistical unit 401 counts the replacement times of each energy storage module. If the replacement times of a certain energy storage module exceed the preset number of times within the preset charging duration, it indicates that the imbalance of the charging speed is extremely obvious during this charging process, and there may be an abnormal energy storage module. For example, if an energy storage module abnormally heats up and its charging speed significantly decreases, then dynamic adjustment will be frequently performed, and at this time, anomaly recognition is carried out.

[0066] An anomaly marking unit 402, which is used to select the energy storage modules with replacement times less than the set number of times, determine abnormal heating according to the relative position relationship of the energy storage modules, and mark the abnormal energy storage modules.

[0067] In this module, the anomaly marking unit 402 selects the energy storage modules with replacement times less than the set number of times, constructs a two - dimensional coordinate system based on the positions of the energy storage modules, and constructs a module matrix in the two - dimensional coordinate system. Each element in the module matrix represents an energy storage module. Extract the elements of the energy storage modules with replacement times less than the set number of times. Each time, select an energy storage module with replacement times less than the set number of times, turn off the energy storage module through an electronic fuse, continue normal charging, monitor the charging parameters of its adjacent elements. If the charging speed of the energy storage module corresponding to the adjacent element increases, it is determined that the turned - off energy storage module is in an abnormal state.

[0068] A data recording unit 403, which is used to perform real - time monitoring during charging, record the charging records of individual energy storage modules, store them in the data center, and analyze the charging amount distribution of the energy storage modules through the data center.

[0069] In this module, the data recording unit 403 conducts real-time monitoring during the charging process. To analyze the working conditions of each energy storage module, all charging records are recorded in the data center. The data in the data center is updated regularly, and the charging amount of each group of energy storage modules each time is analyzed to construct a charging amount prediction function. The charging amount prediction function is used to estimate its lifespan and provide maintenance suggestions for the users.

[0070] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A battery energy storage management method based on a data center, characterized in that: The method comprises: Obtaining power information of each energy storage module in the battery pack, dividing the energy storage modules into basic energy storage modules and dynamic energy storage modules, and the number ratio of dynamic energy storage modules to basic energy storage modules is a preset value; charging the basic energy storage module, obtaining charging parameter information, and predicting the charging time of the basic energy storage module based on the charging parameter information; Based on the charging time, the basic energy storage modules with short charging time are scheduled and dynamically replaced by dynamic energy storage modules; The replacement times of each energy storage module are counted, and energy storage modules with replacement times lower than a preset value are selected for abnormality identification to determine the energy storage module with the abnormality.

2. The battery energy storage management method based on data center according to claim 1 is characterized in that: The steps of charging the basic energy storage module, acquiring charging parameter information, and predicting the charging time of the basic energy storage module based on the charging parameter information specifically include: Charge all basic energy storage modules, monitor the charging process of each basic energy storage module in real time, and record corresponding charging parameter information, wherein the charging parameter information at least includes charging time, charging temperature, and charging current; Based on the charging parameter information, a time-temperature curve and a temperature-current curve are constructed, and a function simulation is performed to obtain a time-temperature function and a temperature-current function; The charging amount is predicted based on the time-temperature function and the temperature-current function, and the charging time is predicted based on the remaining power of the basic energy storage module.

3. The battery energy storage management method based on data center according to claim 1 is characterized in that: The step of scheduling the basic energy storage module with short charging time based on the charging time and dynamically replacing it with the dynamic energy storage module includes: Query the charging time of each basic energy storage module at preset time intervals and calculate the maximum difference in charging time; The maximum difference in charging time is compared with a preset time value. If the maximum difference in charging time is greater than the preset time value, the basic energy storage module with the longest charging time is replaced with a group of dynamic energy storage modules. The query time interval is re-determined based on the maximum difference in charging time, and the new query time interval takes effect immediately.

4. The battery energy storage management method based on data center according to claim 1, characterized in that: The step of counting the number of replacements of each energy storage module, selecting energy storage modules with replacement times lower than a preset value for abnormality identification, and determining the energy storage module with abnormality specifically includes: The number of replacements of each energy storage module is counted. If the number of replacements of a single energy storage module exceeds the preset value within the preset charging time, an abnormality identification is performed; Select the energy storage modules that have been replaced less than the set number of times, make abnormal heating determination based on the relative position relationship of the energy storage modules, and mark the energy storage modules with abnormalities; Real-time monitoring is carried out during the charging process, and the charging records of individual energy storage modules are recorded and stored in the data center. The charging distribution of the energy storage modules is analyzed through the data center.

5. The battery energy storage management method based on data center according to claim 4 is characterized in that: In the step of determining abnormal heating according to the relative position relationship of the energy storage modules, a two-dimensional coordinate system is constructed based on the position of the energy storage modules, and a module matrix is ​​constructed in the two-dimensional coordinate system, each element in the module matrix represents an energy storage module, and elements of energy storage modules whose replacement times are less than the set times are extracted, and each time an energy storage module whose replacement times are less than the set times is selected, the energy storage module is turned off by an electronic insurance, and normal charging continues, and the charging parameters of the adjacent elements are monitored. If the charging speed of the energy storage modules corresponding to the adjacent elements is increased, it is determined that the turned-off energy storage module is in an abnormal state.

6. The battery energy storage management system based on the data center is characterized by: The system comprises: A module division module is used to obtain the power information of each energy storage module in the battery pack, and divide the energy storage modules into basic energy storage modules and dynamic energy storage modules, wherein the ratio of the number of dynamic energy storage modules to the basic energy storage modules is a preset value; A charging parameter recording module is used to charge the basic energy storage module, obtain charging parameter information, and predict the charging time of the basic energy storage module based on the charging parameter information; A dynamic replacement module is used to schedule basic energy storage modules with short charging time based on charging time, and dynamically replace them through dynamic energy storage modules; The abnormality identification module is used to count the replacement times of each energy storage module, select energy storage modules with replacement times lower than a preset value for abnormality identification, and determine the energy storage modules with abnormalities.

7. The data center-based battery energy storage management system according to claim 6, characterized in that: The charging parameter recording module includes: A data recording unit, used to charge all basic energy storage modules, monitor the charging process of each basic energy storage module in real time, and record corresponding charging parameter information, wherein the charging parameter information at least includes charging time, charging temperature, and charging current; A curve construction unit, used to construct a time-temperature curve and a temperature-current curve based on the charging parameter information, and perform function simulation to obtain a time-temperature function and a temperature-current function; The charging prediction unit is used to predict the charging amount according to the time-temperature function and the temperature-current function, and to predict the charging time according to the remaining power of the basic energy storage module.

8. The data center-based battery energy storage management system according to claim 6, characterized in that: The dynamic replacement module comprises: A charging time statistics unit is used to query the charging time of each basic energy storage module according to a preset time interval and calculate the maximum difference in charging time; A module replacement unit, used to compare the maximum difference in charging time with a preset time value, and if the maximum difference is greater than the preset time value, replace the basic energy storage module with the longest charging time with a group of dynamic energy storage modules; The time interval adjustment unit is used to re-determine the query time interval based on the maximum difference in charging time, and the new query time interval takes effect immediately.

9. The data center-based battery energy storage management system according to claim 6, characterized in that: The abnormality identification module comprises: A replacement times counting unit is used to count the replacement times of each energy storage module. If the replacement times of a single energy storage module exceeds a preset value within a preset charging time, an abnormality identification is performed; An abnormal marking unit is used to select an energy storage module that has been replaced less than a set number of times, make an abnormal heating determination based on the relative position relationship of the energy storage modules, and mark the energy storage module with the abnormality; The data recording unit is used to perform real-time monitoring during the charging process, record the charging records of a single energy storage module, store them in the data center, and analyze the charging distribution of the energy storage module through the data center.

10. The data center-based battery energy storage management system according to claim 9, characterized in that: In the step of determining abnormal heating according to the relative position relationship of the energy storage modules, a two-dimensional coordinate system is constructed based on the position of the energy storage modules, and a module matrix is ​​constructed in the two-dimensional coordinate system, each element in the module matrix represents an energy storage module, and elements of energy storage modules whose replacement times are less than the set times are extracted, and each time an energy storage module whose replacement times are less than the set times is selected, the energy storage module is turned off by an electronic insurance, and normal charging continues, and the charging parameters of the adjacent elements are monitored. If the charging speed of the energy storage modules corresponding to the adjacent elements is increased, it is determined that the turned-off energy storage module is in an abnormal state.

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