Intelligent management system and method applied to long-time energy storage of novel lithium battery

Abstract

The invention discloses an intelligent management system and method applied to long-time energy storage of a novel lithium battery, relates to the technical field of big data analysis, and realizes effective monitoring of the equalization compensation amount of a single lithium battery under the condition of ensuring that the capacity attenuation of each battery in a lithium battery pack is consistent. Therefore, the use safety and stability of the lithium battery are comprehensively improved, and the service life of the lithium battery is prolonged. Current signals of the lithium batteries are strictly monitored by means of a current sensor, subjective interference is effectively avoided, it is ensured that discharge cycle division has high accuracy and objectivity, and a cycle equalization compensation quantity set is constructed, and a single lithium battery serves as a basic unit; a neural network model is combined with equalization compensation amount data from battery performance degradation to a fault state, an equalization compensation amount threshold value is accurately set, instantaneous and fixed equalization compensation amounts are integrated, the maximum equalization compensation amount of a single lithium battery is predicted and calculated, and threshold value early warning is combined, so that intelligent management of long-time energy storage of the novel lithium battery is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of battery energy storage management, and specifically to an intelligent management system and method applied to long-term energy storage of new lithium batteries. Background Art

[0002] Lithium batteries are crucial in the field of long-term energy storage. As the core energy storage component, with high energy density, long cycle life, and good charge and discharge performance, they ensure the stable and continuous power supply of the long-term energy storage system, provide key support for various scenarios relying on long-term stable power supply, and are the cornerstone for promoting the development and application of long-term energy storage technology.

[0003] During the operation of long-term energy storage of lithium-ion battery packs, the battery management system (BMS) plays a crucial role. However, its equalization control function has caused a major problem. Due to the influence of BMS equalization control, the accurate judgment of abnormal capacity decay of lithium-ion batteries is hindered. This lack of accuracy means that in the next charge and discharge cycle of lithium-ion batteries, the equalization compensation amount may exceed the threshold. Once this happens, it may lead to out-of-control regulation of the lithium-ion battery pack. Summary of the Invention

[0004] The purpose of the present invention is to provide an intelligent management system and method applied to long-term energy storage of new lithium batteries to solve the problems raised in the prior art.

[0005] To achieve the above purpose, the present invention provides the following technical solution: An intelligent management method applied to long-term energy storage of new lithium batteries, the intelligent management method includes the following steps: Step S1: Take the moment when the lithium battery is connected to the circuit and starts to output electrical energy as the starting point, and the moment when the lithium battery stops outputting electrical energy as the ending point, and divide it into a discharge cycle; Monitor the current signal of the lithium battery through a current sensor. When the current sensor obtains the current signal of the lithium battery, it is judged that the lithium battery outputs electrical energy; take the moment when the current starts to be obtained as the starting point. When the current sensor cannot obtain the current signal of the lithium battery, it is judged that the electrical energy output ends, and take the moment when the lithium battery current signal cannot be obtained as the ending point; divide the time interval between the starting point and the ending point into a discharge cycle of the lithium battery; The current sensor is a key component for accurately monitoring the current signal of a lithium battery to divide the discharge cycle. It mainly includes a Hall effect current sensor, which is based on the Hall effect and can measure AC, DC, and pulsed currents. It has good electrical isolation, fast response, but is susceptible to magnetic field interference and has a high price. It is commonly used in industrial and battery management systems; a current transformer type current sensor, which is based on the principle of electromagnetic induction and is suitable for measuring large AC currents. It has a simple structure and low cost, but can only measure AC and is used in power systems; a shunt resistor, which utilizes Ohm's law, has a simple structure and high accuracy, and can measure AC and DC, but has power loss and is used in lithium battery charge and discharge tests; an optical fiber current sensor, which is based on the Faraday magneto-optic effect, has good insulation and anti-interference performance, high accuracy, and can measure AC and DC. It has a complex structure and high cost and is used in high-voltage and high-precision measurement fields.

[0006] Using a current sensor to monitor the current signal of a lithium battery to divide the discharge cycle can accurately define the start and end times of the lithium battery outputting electrical energy, ensuring the accuracy and objectivity of the discharge cycle division. This judgment method based on the actual current state avoids the interference of subjective factors and provides a reliable and accurate time range basis for subsequent lithium battery performance analysis, data collection, and management.

[0007] Step S2: Divide the lithium battery pack. The single lithium battery under monitoring is used as the monitored lithium battery; obtain the historical data of the monitored lithium battery for analysis. The historical data includes the historical equalization compensation amount and discharge cycle of the monitored lithium battery; extract the equalization compensation amount of each discharge cycle from the historical data of the monitored lithium battery to construct a cycle equalization compensation amount set. The equalization compensation amount is expressed as the amount that can keep the output performance of multiple lithium batteries working together unchanged while making the capacity attenuation of each lithium battery in the lithium battery pack consistent. Step S2-1: Divide the lithium battery pack with a single lithium battery as the basic unit of the lithium battery pack. The lithium battery pack is a power combination formed by multiple lithium batteries working together. Monitor each lithium battery in the battery pack and use the monitored single lithium battery as the monitored lithium battery. Step S2-2: Extract the equalization compensation amount of each discharge cycle from the historical data of the monitored lithium battery to construct a cycle equalization compensation amount set. The cycle equalization compensation amount set represents the equalization compensation amount in each discharge cycle of the historical data of the monitored lithium battery. The storage method of the cycle equalization compensation amount set is a key-value pair storage method. The system ID of the monitored lithium battery is used as the primary key, and the equalization compensation amount of each discharge cycle of the monitored lithium battery is used as the value for storage. The system ID of the monitored lithium battery is a unique ID randomly generated by the system for encoding when the monitored lithium battery stores data and is used to identify the data primary key of the lithium battery. Dividing the lithium battery pack and constructing a set of periodic equalization compensation amounts has significant advantages. By dividing and monitoring each single lithium battery as the basic unit, it is possible to focus on the specific conditions of each battery and accurately grasp its state. By extracting the equalization compensation amounts of historical discharge cycles and storing them in the form of key-value pairs with the system ID as the primary key, data can be efficiently organized and managed, facilitating the traceability and analysis of the equalization compensation of individual batteries, providing a solid data foundation for subsequent evaluation of battery performance, prediction of capacity attenuation, optimization of battery management strategies, etc.

[0008] Step S3: Construct a trend graph of the equalization compensation amount of the monitored lithium battery according to the set of periodic equalization compensation amounts of the monitored lithium battery; select the discharge cycle with the smallest cycle in the historical discharge cycles as the analysis duration of trend change and the largest discharge cycle as the limiting duration of trend change based on the historical data of the monitored lithium battery; calculate the instantaneous equalization compensation amount of the monitored lithium battery according to the analysis duration of trend change, and calculate the fixed equalization compensation amount of the monitored lithium battery according to the trend graph of the equalization compensation amount. Step S3-1: Read the data of the set of periodic equalization compensation amounts according to the system ID of the monitored lithium battery, and traverse the equalization compensation amounts of each discharge cycle read. Step S3-2: Slice and combine the equalization compensation amount of the monitored lithium battery according to the time stamp of the discharge cycle. The specific process is as follows: Step S3-2-1: Combine the data in chronological order according to the time stamp of the equalization compensation amount. Step S3-2-2: Delete the time periods without equalization compensation amounts and retain the time stamps with equalization compensation amounts. Step S3-3: Read the equalization compensation amount after slicing and combination and construct a trend graph of the equalization compensation amount according to the time stamp. Construct the abscissa with the time stamp as the X-axis and the ordinate with the equalization compensation amount as the Y-axis. Step S3-4: Extract the discharge cycles according to the historical data of the monitored lithium battery, and combine with the bubble algorithm to obtain the minimum and maximum discharge cycles of the monitored lithium battery. Take the minimum discharge cycle as the analysis duration of trend change and the maximum discharge cycle as the limiting duration of trend change. Step S3-5: Calculate the change value of the equalization compensation amount as the instantaneous equalization compensation amount according to the change of the equalization compensation amount during the analysis duration of trend change. The instantaneous equalization compensation amount represents the change of the equalization compensation amount of the monitored lithium battery during the minimum discharge cycle; calculate the average value of the change of the equalization compensation amount of the monitored lithium battery as the fixed equalization compensation amount according to the trend graph of the equalization compensation amount. The fixed equalization compensation amount represents the average value of the equalization compensation amount of the monitored lithium battery.

[0009] Let the instantaneous equalization compensation amount be J inst , and the calculation formula is as follows: J inst = (J end - J start ) / T min ; Wherein, J end represents the equalization compensation amount at the start time of the minimum discharge period; J start represents the equalization compensation amount at the end time of the minimum discharge period; T min represents the duration of trend change analysis.

[0010] The calculation of the fixed equalization compensation amount uses the following formula: ; Wherein, J fix represents the fixed equalization compensation amount, that is, the average value of the equalization compensation amount of the monitored lithium battery; T max represents the maximum discharge period in the historical discharge cycles, as the duration limit for trend change; m represents the number of effective time intervals within the duration limit for trend change T max ; represents the change in the equalization compensation amount within the j-th time interval; J j represents the equalization compensation amount at the j-th time point; satisfying the following conditions: ; Constructing a trend chart of the change in the equalization compensation amount can visually present the change trend of the battery equalization compensation amount over time, providing a clear visual basis for subsequent analysis. Selecting the minimum and maximum discharge cycles as the duration of trend change analysis and the duration limit can accurately grasp the performance change range of the battery at different time scales. The instantaneous equalization compensation amount formula considers the compensation amount change and duration within the minimum discharge period, and can accurately measure the dynamic compensation characteristics of the battery in a short time; the fixed equalization compensation amount formula comprehensively considers the compensation amount changes in each time interval within the duration limit of trend change, and can reflect the average compensation situation of the battery over a longer period.

[0011] Step S4: Obtain the historical data of n lithium batteries for analysis, and set the equalization compensation amount threshold according to the equalization compensation amount when the battery performance deteriorates to the faulty battery state; According to the equalization compensation amount data of n lithium batteries during the period from the start of battery performance deterioration to reaching the faulty battery state, combined with the neural network model analysis and calculation, obtain the equalization compensation amount threshold J max .

[0012] The powerful learning and adaptive capabilities of neural networks can accurately capture the potential relationships and patterns between battery performance degradation and the equalization compensation amount from a large amount of complex historical data. Through in-depth analysis of this data, the calculated threshold can better fit the actual operating conditions of lithium batteries, improving the scientific nature and accuracy of threshold setting. This helps to identify potential battery failures in advance and accurately, providing a reliable basis for the battery management system to take timely countermeasures, thereby enhancing the safety and stability of lithium battery use and extending the battery life.

[0013] Step S5: Based on the time limit combined with the trend change, and the instantaneous equalization compensation amount and the fixed equalization compensation amount, predict and calculate the maximum equalization compensation amount of the monitored lithium battery, and issue a warning for the monitored lithium battery in combination with the equalization compensation amount threshold.

[0014] Step S5-1: Obtain the equalization compensation amount at the end of the most recent discharge cycle of the monitored lithium battery as the current equalization compensation amount J new , and perform weighted combination of the instantaneous equalization compensation amount and the fixed equalization compensation amount with the time limit combined with the trend change to calculate the equalization compensation amount of the monitored lithium battery as the predicted equalization compensation amount J prediction ; Step S5-2: Calculate the maximum equalization compensation amount J of the monitored lithium battery. Add the current equalization compensation amount and the predicted equalization compensation amount, and issue a warning for the monitored lithium battery in combination with the equalization compensation amount threshold. The process is as follows: When J < J max , it is judged that the change in the equalization compensation amount within the time limit combined with the trend change will not exceed the equalization compensation amount threshold, meeting the next working condition of the lithium battery pack; When J ≥ J max , it is judged that the change in the equalization compensation amount within the time limit combined with the trend change will exceed the equalization compensation amount threshold, not meeting the next working condition of the lithium battery pack. Read the system ID of the monitored lithium battery and issue a capacity anomaly warning signal.

[0015] By calculating the predicted equalization compensation amount and the maximum equalization compensation amount, and issuing a warning in combination with the equalization compensation amount threshold, it has significant advantages. Obtaining the current equalization compensation amount and calculating the predicted value in combination with the instantaneous and fixed equalization compensation amounts takes into account the short-term and long-term performance change characteristics of the battery, and can more accurately estimate the future equalization compensation situation of the battery. By comparing with the threshold for warning judgment, potential capacity anomaly problems of lithium batteries can be detected in advance. When it is judged that the working condition is not met, a warning signal is issued and the system ID is read, which can quickly locate the problem battery, facilitating timely maintenance or replacement measures, ensuring the stable operation of the lithium battery pack, improving the reliability and safety of the energy storage system, and reducing the potential risks brought by battery failures.

[0016] Furthermore, an intelligent management system for long-term energy storage of a new type of lithium battery, the intelligent management system includes a discharge cycle division module, a data acquisition set construction module, a compensation amount calculation module, a threshold setting module, and an early warning module; The discharge cycle division module is used to divide the discharge cycle of the lithium battery; the data acquisition set construction module is used to collect data and construct an equalization compensation amount set; the compensation amount calculation module is used to calculate the change trend of the compensation amount and the instantaneous and fixed compensation amounts; the threshold setting module is used to set the equalization compensation amount threshold; the early warning module is used to predict the maximum compensation amount and combine it with the threshold for early warning; The output end of the discharge cycle division module is electrically connected to the input end of the data acquisition set construction module; the output end of the data acquisition set construction module is electrically connected to the input end of the compensation amount calculation module; the output end of the compensation amount calculation module is electrically connected to the input end of the threshold setting module; the output end of the threshold setting module is electrically connected to the input end of the early warning module; The discharge cycle division module includes a start and end point determination unit and a cycle division execution unit; the start and end point determination unit is used to determine the start and end times of the lithium battery discharge; the cycle division execution unit is used to divide the discharge cycle according to the start and end times; The data acquisition set construction module includes a battery division and monitoring unit and a compensation amount set construction unit; the battery division and monitoring unit is used to divide the lithium battery pack and select the battery to be monitored; the compensation amount set construction unit is used to construct a cycle equalization compensation amount set; The compensation amount calculation module includes a trend calculation unit and an instantaneous and fixed amount calculation unit; the trend calculation unit is used to calculate the change trend of the equalization compensation amount; the instantaneous and fixed amount calculation unit is used to calculate the instantaneous and fixed equalization compensation amounts; The threshold setting module includes a data collection unit and a threshold calculation unit; the data collection unit is used to collect the compensation amount data from battery deterioration to failure; the threshold calculation unit is used to calculate the compensation amount threshold in combination with the data; The early warning module includes a predicted compensation amount calculation unit and an early warning judgment and execution unit; the predicted compensation amount calculation unit is used to calculate the predicted equalization compensation amount; the early warning judgment and execution unit is used to judge and issue an early warning signal.

[0017] Compared with the prior art, the beneficial effects of the present invention are: 1. The present invention divides the discharge cycle by monitoring the lithium battery current signal through a current sensor, which can accurately define the start and end times of the discharge, ensuring the accuracy and objectivity of the discharge cycle division. Avoiding subjective factors interference provides an accurate and reliable time range basis for subsequent lithium battery performance analysis, data collection, and management, making the battery state assessment more scientific and reasonable.

[0018] 2. The present invention constructs a set of cycle balance compensation amounts, monitors each single lithium battery as a unit, and stores data using key-value pairs, which can efficiently organize and manage information. It is convenient to analyze the balance compensation of a single battery, providing a solid data basis for evaluating battery performance, predicting capacity attenuation, and optimizing management strategies, and improving the refinement level of battery management.

[0019] 3. The present invention sets the balance compensation amount threshold by combining a neural network model, and uses its powerful learning and adaptive capabilities to capture the relationship between battery performance deterioration and compensation amount from complex data. The calculated threshold is more in line with the actual situation, can accurately identify faults in advance, provides a reliable basis for battery management, improves the safety and stability of lithium battery use, and extends the service life. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 is a schematic flow chart of an intelligent management method for long-term energy storage of a new type of lithium battery according to the present invention; Figure 2 is a schematic structural diagram of an intelligent management system for long-term energy storage of a new type of lithium battery according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0021] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0022] Embodiment 1: As Figure 1 shown, the present invention provides a technical solution, an intelligent management method for long-term energy storage of a new type of lithium battery, and the intelligent management method includes the following steps: Step S1: Take the moment when the lithium battery is connected to the circuit and starts to output electric energy as the starting point, and the moment when the lithium battery terminates the output of electric energy as the cut-off point, and divide it into a discharge cycle; Monitor the current signal of the lithium battery through a current sensor. When the current sensor obtains the current signal of the lithium battery, it is judged that the lithium battery outputs electric energy; take the moment when the current is first obtained as the starting point. When the current sensor fails to obtain the current signal of the lithium battery, it is judged that the electric energy output ends, and take the moment when the lithium battery current signal cannot be obtained as the cut-off point; divide the time interval between the starting point and the cut-off point into a discharge cycle of the lithium battery.

[0023] In specific implementation, the operating principle is as follows: The current sensor is used to monitor the current signal of the lithium battery in real time. When the sensor detects a current signal, it means that the lithium battery is connected to the circuit and starts to output electrical energy, and this moment is recorded as the starting point of the discharge cycle. As the discharge process progresses, when the sensor can no longer obtain a current signal, it indicates that the output of electrical energy from the lithium battery terminates, and this instant is recorded as the cut-off point. Finally, the time interval between the starting point and the cut-off point is calculated to determine a complete discharge cycle.

[0024] Step S2: Divide the lithium battery pack. The single lithium battery to be monitored is used as the monitored lithium battery. Obtain the historical data of the monitored lithium battery for analysis. The historical data includes the historical equalization compensation amount and discharge cycle of the monitored lithium battery. Extract the equalization compensation amount of each discharge cycle from the historical data of the monitored lithium battery to construct a cycle equalization compensation amount set. The equalization compensation amount is expressed as the amount that can keep the output performance of multiple lithium batteries working together unchanged while making the capacity attenuation of each lithium battery in the lithium battery pack consistent. Step S2-1: Divide the lithium battery pack with a single lithium battery as the basic unit of the lithium battery pack. The lithium battery pack is a power combination formed by multiple lithium batteries working together. Monitor each lithium battery in the battery pack, and use the monitored single lithium battery as the monitored lithium battery. Step S2-2: Extract the equalization compensation amount of each discharge cycle from the historical data of the monitored lithium battery to construct a cycle equalization compensation amount set. The cycle equalization compensation amount set represents the equalization compensation amount in each discharge cycle of the monitored lithium battery's history. The storage method of the cycle equalization compensation amount set is the key-value pair storage method. Use the system ID of the monitored lithium battery as the primary key and the equalization compensation amount of each discharge cycle of the monitored lithium battery as the value for storage. The system ID of the monitored lithium battery is a unique ID randomly generated by the system during data storage of the monitored lithium battery and is used to identify the data primary key of the lithium battery.

[0025] In specific implementation, first divide the lithium battery pack composed of multiple lithium batteries working together with a single lithium battery as the basic unit, monitor each battery in the group, and select one of them as the monitored lithium battery. Then, extract the equalization compensation amount of each discharge cycle from the historical data of the monitored lithium battery. This equalization compensation amount can ensure the stable output performance of the lithium battery pack and the consistent capacity attenuation of each battery. Finally, use the key-value pair storage method, with the unique system ID randomly generated by the system as the primary key and the equalization compensation amount of each discharge cycle as the value, to construct and store the cycle equalization compensation amount set.

[0026] Step S3: Construct a trend chart of the equalization compensation amount of the monitored lithium battery based on the set of cycle equalization compensation amounts of the monitored lithium battery; screen out the discharge cycle with the smallest cycle in the historical discharge cycles of the monitored lithium battery as the analysis duration of trend change, and the largest discharge cycle as the limiting duration of trend change according to the historical data of the monitored lithium battery; calculate the instantaneous equalization compensation amount of the monitored lithium battery based on the analysis duration of trend change, and calculate the fixed equalization compensation amount of the monitored lithium battery according to the trend chart of equalization compensation amount. Step S3-1: Read the data of the set of cycle equalization compensation amounts according to the system ID of the monitored lithium battery, and traverse the equalization compensation amounts of each discharge cycle read. Step S3-2: Slice and combine the equalization compensation amount of the monitored lithium battery according to the time stamp of the discharge cycle. The specific process is as follows: Step S3-2-1: Combine the data in chronological order according to the time stamp of the equalization compensation amount. Step S3-2-2: Delete the time periods without equalization compensation amount, and retain the time stamps with equalization compensation amount. Step S3-3: Read the equalization compensation amount after slice combination and construct a trend chart of equalization compensation amount according to the time stamp. Construct the abscissa with the time stamp as the X-axis and the ordinate with the equalization compensation amount as the Y-axis. Step S3-4: Extract the discharge cycles according to the historical data of the monitored lithium battery, and combine with the bubble algorithm to obtain the minimum discharge cycle and the maximum discharge cycle of the monitored lithium battery. Take the minimum discharge cycle as the analysis duration of trend change and the maximum discharge cycle as the limiting duration of trend change. Step S3-5: Calculate the change value of the equalization compensation amount as the instantaneous equalization compensation amount according to the change of the equalization compensation amount during the analysis duration of trend change. The instantaneous equalization compensation amount represents the change of the equalization compensation amount of the monitored lithium battery during the minimum discharge cycle; calculate the average value of the change of the equalization compensation amount of the monitored lithium battery according to the trend chart of equalization compensation amount as the fixed equalization compensation amount. The fixed equalization compensation amount represents the average value of the equalization compensation amount of the monitored lithium battery.

[0027] For example, the limiting duration of trend change is T max There are m = 5 effective time intervals within it, and the equalization compensation data corresponding to each time interval is as follows: The order of time points j: 1, 2, 3, 4, 5, 6; Equalization compensation amount J j : 10, 12, 15, 18, 20, 22; When j = 1, the change of the equalization compensation amount within the first time interval is: 12 - 10 = 2; When j = 2, the change of the equalization compensation amount within the second time interval is: 15 - 12 = 3; When j = 3, the change in the equalization compensation amount within the third time interval is: 18 - 15 = 3; When j = 4, the change in the equalization compensation amount within the fourth time interval is: 20 - 18 = 2; When j = 5, the change in the equalization compensation amount within the fifth time interval is: 22 - 20 = 2; According to the fixed equalization compensation amount calculation formula: ; Substituting the above data, we get: J fix = 12 / 5 = 2.4; Step S4: Obtain the historical data of n lithium batteries for analysis, and set the equalization compensation amount threshold according to the equalization compensation amount when the battery performance deteriorates to the faulty battery state; According to the equalization compensation amount data of n lithium batteries from the start of battery performance deterioration until reaching the faulty battery state, combined with the neural network model analysis and calculation to obtain the equalization compensation amount threshold J max .

[0028] Step S5: According to the trend change limited time duration, combined with the instantaneous equalization compensation amount and the fixed equalization compensation amount, predict and calculate the maximum equalization compensation amount of the monitored lithium battery, and combine the equalization compensation amount threshold to give an early warning to the monitored lithium battery.

[0029] Step S5-1: Obtain the equalization compensation amount at the end of the most recent discharge cycle of the monitored lithium battery as the current equalization compensation amount J new , and perform weighted combination of the instantaneous equalization compensation amount and the fixed equalization compensation amount, combined with the trend change limited time duration to calculate the equalization compensation amount of the monitored lithium battery as the predicted equalization compensation amount J prediction ; Step S5-2: Calculate the maximum equalization compensation amount J of the monitored lithium battery, add the current equalization compensation amount and the predicted equalization compensation amount, and combine the equalization compensation amount threshold to give an early warning to the monitored lithium battery. The process is as follows: When J < J max , it is determined that the change in the equalization compensation amount within the trend change limited time duration will not exceed the equalization compensation amount threshold, meeting the next working condition of the lithium battery pack; When J ≥ J max , it is determined that the change in the equalization compensation amount within the trend change limited time duration will exceed the equalization compensation amount threshold, not meeting the next working condition of the lithium battery pack. Read the system ID of the monitored lithium battery and send out a capacity anomaly warning signal.

[0030] Example 2, as Figure 2As shown in the figure, the present invention provides an intelligent management system for long-term energy storage of a new type of lithium battery. The intelligent management system includes a discharge cycle division module, a data acquisition set construction module, a compensation amount calculation module, a threshold setting module, and an early warning module; The discharge cycle division module is used to divide the discharge cycle of the lithium battery; the data acquisition set construction module is used to collect data and construct an equalization compensation amount set; the compensation amount calculation module is used to calculate the change trend of the compensation amount and the instantaneous and fixed compensation amounts; the threshold setting module is used to set the equalization compensation amount threshold; the early warning module is used to predict the maximum compensation amount and combine it with the threshold for early warning; The output end of the discharge cycle division module is electrically connected to the input end of the data acquisition set construction module; the output end of the data acquisition set construction module is electrically connected to the input end of the compensation amount calculation module; the output end of the compensation amount calculation module is electrically connected to the input end of the threshold setting module; the output end of the threshold setting module is electrically connected to the input end of the early warning module; The discharge cycle division module includes a start and end point determination unit and a cycle division execution unit; the start and end point determination unit is used to determine the start and end times of the lithium battery discharge; the cycle division execution unit is used to divide the discharge cycle according to the start and end times; The data acquisition set construction module includes a battery division and monitoring unit and a compensation amount set construction unit; the battery division and monitoring unit is used to divide the lithium battery pack and select the monitored battery; the compensation amount set construction unit is used to construct a cycle equalization compensation amount set; The compensation amount calculation module includes a trend calculation unit and an instantaneous and fixed amount calculation unit; the trend calculation unit is used to calculate the change trend of the equalization compensation amount; the instantaneous and fixed amount calculation unit is used to calculate the instantaneous and fixed equalization compensation amounts; The threshold setting module includes a data collection unit and a threshold calculation unit; the data collection unit is used to collect the compensation amount data from battery deterioration to failure; the threshold calculation unit is used to calculate the compensation amount threshold in combination with the data; The early warning module includes a predicted compensation amount calculation unit and an early warning judgment and execution unit; the predicted compensation amount calculation unit is used to calculate the predicted equalization compensation amount; the early warning judgment and execution unit is used to judge and issue an early warning signal.

[0031] It is obvious to those skilled in the art that the present invention is not limited to the details of the above-described exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention. Therefore, in any respect, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the appended claims rather than the above description. Accordingly, all changes that fall within the meaning and scope of the equivalent elements of the claims are intended to be embraced within the present invention. Any reference signs in the claims should not be construed as limiting the claims concerned.

Claims

1. An intelligent management method for long-term energy storage of new lithium batteries, characterized by: The intelligent management method comprises the following steps: Step S1, dividing the time when the lithium battery is connected to the circuit and starts to output electric energy as the starting point, and the time when the lithium battery stops outputting electric energy as the end point, into a discharge cycle; Step S2, dividing the lithium battery pack, and taking the monitored single lithium battery as the monitored lithium battery; obtaining historical data of the monitored lithium battery for analysis, wherein the historical data includes the historical balancing compensation amount and discharge cycle of the monitored lithium battery; extracting the balancing compensation amount of each discharge cycle according to the historical data of the monitored lithium battery to construct a set of period balancing compensation amounts, wherein the balancing compensation amount is expressed as maintaining the output performance of multiple lithium batteries working in collaboration unchanged while making the capacity decay of each lithium battery in the lithium battery pack consistent; Step S3, constructing a balanced compensation amount change trend graph of the monitored lithium battery according to the period balanced compensation amount set of the monitored lithium battery; selecting the discharge cycle with the smallest period in the historical discharge cycle as the trend change analysis duration, and the largest discharge cycle as the trend change limit duration according to the historical data of the monitored lithium battery; calculating the instantaneous balanced compensation amount of the monitored lithium battery according to the trend change analysis duration, and calculating the fixed balanced compensation amount of the monitored lithium battery according to the balanced compensation amount change trend graph; Step S4, obtaining historical data of n lithium batteries for analysis, and setting a threshold of equalization compensation amount according to the equalization compensation amount when the battery performance deteriorates to a faulty battery state; Step S5: Calculate the maximum equalization compensation amount of the monitored lithium battery according to the trend change limit time combined with the instantaneous equalization compensation amount and the fixed equalization compensation amount prediction, and issue an early warning to the monitored lithium battery in combination with the equalization compensation amount threshold.

2. According to claim 1, an intelligent management method for long-term energy storage of a novel lithium battery is characterized in that: In step S1, the current signal of the lithium battery is monitored by a current sensor. When the current sensor obtains the current signal of the lithium battery, it is determined that the lithium battery outputs electrical energy; The moment when the current starts to be obtained is taken as the starting point. When the current sensor cannot obtain the current signal of the lithium battery, it is judged that the power output has ended, and the moment when the lithium battery current signal cannot be obtained is taken as the cutoff point; the time interval between the starting point and the cutoff point is divided into a discharge cycle of the lithium battery.

3. According to claim 2, an intelligent management method for long-term energy storage of a novel lithium battery is characterized in that: The specific steps of step S2 are as follows: Step S2-1, dividing the lithium battery pack with a single lithium battery as the basic unit of the lithium battery pack, wherein the lithium battery pack is represented as a power supply combination composed of multiple lithium batteries working together, monitoring each lithium battery in the battery pack, and taking the monitored single lithium battery as the monitored lithium battery; Step S2-2, extracting the balancing compensation amount of each discharge cycle in the historical data of the monitored lithium battery to construct a cycle balancing compensation amount set, wherein the cycle balancing compensation amount set is represented by the balancing compensation amount in each historical discharge cycle of the monitored lithium battery, and the storage method of the cycle balancing compensation amount set is a key-value pair storage method, with the system ID of the monitored lithium battery as the primary key and the balancing compensation amount of each discharge cycle of the monitored lithium battery as the value for storage, and the system ID of the monitored lithium battery is represented by a unique ID randomly generated by the system when the monitored lithium battery is stored, and is used to identify the data primary key of the lithium battery.

4. According to claim 3, an intelligent management method for long-term energy storage of a novel lithium battery is characterized in that: The specific steps of step S3 are as follows: Step S3-1, reading the data of the cycle balancing compensation amount set according to the system ID of the monitored lithium battery, and traversing the read balancing compensation amount of each discharge cycle; Step S3-2: Slice and combine the balanced compensation amount of the monitored lithium battery according to the timestamp of the discharge cycle. The specific process is as follows: Step S3-2-1, combining data in chronological order according to the timestamps of the equalization compensation amounts; Step S3-2-2, delete the time period without the balanced compensation amount, and keep the time stamp with the balanced compensation amount; Step S3-3, read the balanced compensation amount after the slice combination, and construct a balanced compensation amount change trend diagram according to the timestamp, with the timestamp as the X-axis to construct the horizontal coordinate and the balanced compensation amount as the Y-axis to construct the vertical coordinate.

5. According to claim 4, an intelligent management method for long-term energy storage of a novel lithium battery is characterized in that: In step S3, it also includes: Step S3-4, extracting the discharge cycle according to the historical data of the monitored lithium battery, combining the bubbling algorithm to obtain the minimum discharge cycle and the maximum discharge cycle of the monitored lithium battery, taking the minimum discharge cycle as the trend change analysis duration, and taking the maximum discharge cycle as the trend change limit duration; Step S3-5, calculating the change value of the equalization compensation amount as the instantaneous equalization compensation amount according to the change of the equalization compensation amount during the trend change analysis time, and the instantaneous equalization compensation amount is represented by the change of the equalization compensation amount of the monitored lithium battery during the minimum discharge cycle; calculating the average value of the change of the equalization compensation amount of the monitored lithium battery according to the equalization compensation amount change trend diagram as the fixed equalization compensation amount, and the fixed equalization compensation amount is represented as the average value of the equalization compensation amount of the monitored lithium battery.

6. According to claim 5, an intelligent management method for long-term energy storage of a novel lithium battery is characterized in that: In step S4, the equalization compensation threshold J is calculated based on the equalization compensation data of n lithium batteries from the time when the battery performance begins to deteriorate until the battery reaches the faulty battery state, combined with the neural network model analysis. max .

7. The intelligent management method for long-term energy storage of a novel lithium battery according to claim 6, characterized in that: The specific steps of step S5 are as follows: Step S5-1, obtaining the balanced compensation amount at the end of the most recent discharge cycle of the monitored lithium battery as the current balanced compensation amount J new The instantaneous balance compensation amount and the fixed balance compensation amount are weighted and combined with the trend change time limit to calculate the balance compensation amount of the monitored lithium battery as the predicted balance compensation amount J prediction ; Step S5-2, calculate the maximum equalization compensation amount J of the monitored lithium battery, add the current equalization compensation amount to the predicted equalization compensation amount, and use the equalization compensation amount threshold to warn the monitored lithium battery. The process is as follows: When J<J max When the equalization compensation amount is determined to be within the limited time of the trend change, the change will not exceed the equalization compensation amount threshold, and the next working condition of the lithium battery pack is met; When J ≥ J max When the balance compensation amount is judged to exceed the balance compensation amount threshold within the limited time of trend change, the next working condition of the lithium battery pack is not met, the system ID of the monitored lithium battery is read, and a capacity abnormality warning signal is issued.

8. An intelligent management system for long-term energy storage of a novel lithium battery, which is applied to an intelligent management method for long-term energy storage of a novel lithium battery as claimed in any one of claims 1 to 7, characterized in that: The intelligent management system includes a discharge cycle division module, a data acquisition set construction module, a compensation amount calculation module, a threshold setting module and an early warning module; The discharge cycle division module is used to divide the discharge cycle of the lithium battery; the data acquisition set construction module is used to collect data and construct a balanced compensation amount set; the compensation amount calculation module is used to calculate the compensation amount change trend and the instantaneous and fixed compensation amounts; the threshold setting module is used to set the balanced compensation amount threshold; the warning module is used to predict the maximum compensation amount and combine the threshold warning; The output end of the discharge cycle division module is electrically connected to the input end of the data acquisition set construction module; the output end of the data acquisition set construction module is electrically connected to the input end of the compensation amount calculation module; the output end of the compensation amount calculation module is electrically connected to the input end of the threshold setting module; the output end of the threshold setting module is electrically connected to the input end of the early warning module.

9. The intelligent management system for long-term energy storage of new lithium batteries according to claim 8, characterized in that: The discharge cycle division module includes a start and end point determination unit and a cycle division execution unit; the start and end point determination unit is used to determine the start and end time of lithium battery discharge; the cycle division execution unit is used to divide the discharge cycle according to the start and end time; The data acquisition set building module includes a battery division and monitoring unit and a compensation amount set building unit; the battery division and monitoring unit is used to divide the lithium battery group and select the monitored battery; The compensation amount set construction unit is used to construct a periodic equalization compensation amount set; The compensation amount calculation module includes a trend calculation unit and an instantaneous and fixed amount calculation unit; the trend calculation unit is used to calculate the change trend of the balanced compensation amount; The instantaneous and fixed amount calculation unit is used to calculate the instantaneous and fixed equalization compensation amounts.

10. The intelligent management system for long-term energy storage of new lithium batteries according to claim 8, characterized in that: The threshold setting module includes a data collection unit and a threshold calculation unit; the data collection unit is used to collect compensation amount data of battery degradation to failure; the threshold calculation unit is used to calculate the compensation amount threshold in combination with the data; The early warning module includes a predicted compensation amount calculation unit and an early warning judgment and execution unit; the predicted compensation amount calculation unit is used to calculate the predicted equilibrium compensation amount; the early warning judgment and execution unit is used to judge and issue an early warning signal.

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