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

Abstract

The application discloses an intelligent management system and method applied to long-time energy storage of new lithium batteries, 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 that the capacity attenuation of each battery in the lithium battery pack is consistent, so that the safety and stability of the lithium battery are comprehensively improved, and the service life of the lithium battery is prolonged. With the help of the current sensor, the lithium battery current signal is strictly monitored, subjective interference is effectively avoided, the discharge cycle division is ensured to have high accuracy and objectivity, a cycle equalization compensation amount set is constructed, a single lithium battery is taken as a basic unit, a neural network model is combined with equalization compensation amount data of battery performance deterioration to a fault state, an equalization compensation amount threshold value is accurately set, instantaneous and fixed equalization compensation amounts are comprehensively considered, maximum equalization compensation amount of a single lithium battery is predicted and calculated in combination with threshold value early warning, and the intelligent management of long-time energy storage of new lithium batteries is realized.

Description

Technical Field

[0001] This invention relates to the field of battery energy storage management technology, specifically to an intelligent management system and method for long-term energy storage of novel lithium batteries. Background Technology

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

[0003] In the long-term energy storage operation of lithium-ion battery packs, the Battery Management System (BMS) plays a crucial role. However, its equalization control function raises a significant issue. The accurate assessment of abnormal capacity decay in lithium-ion batteries is hampered by the influence of BMS equalization control. This lack of precision means that the equalization compensation amount may exceed the threshold in the next charge-discharge cycle of the lithium-ion battery. If this occurs, it can lead to uncontrolled regulation of the lithium-ion battery pack. Summary of the Invention

[0004] The purpose of this invention is to provide an intelligent management system and method for long-term energy storage of novel lithium batteries, in order to solve the problems raised in the prior art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: an intelligent management method for long-term energy storage of novel lithium batteries, the intelligent management method comprising 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 one discharge cycle. The lithium battery current signal is monitored by a current sensor. When the current sensor acquires the current signal of the lithium battery, it is determined that the lithium battery is outputting electrical energy. The moment when the current is acquired is taken as the starting point. When the current sensor no longer acquires the current signal of the lithium battery, it is determined that the electrical energy output has ended. The moment when the current signal of the lithium battery is no longer acquired is taken as the cutoff point. The time interval between the starting point and the cutoff point is divided into one discharge cycle of the lithium battery. Current sensors are key components for accurately monitoring lithium battery current signals to divide discharge cycles. They mainly include: Hall effect current sensors, which, based on the Hall effect, can measure AC, DC, and pulse currents; they offer good electrical isolation and fast response, but are susceptible to magnetic field interference and are expensive; they are commonly used in industrial applications and battery management systems. Current transformer sensors, based on the principle of electromagnetic induction, are suitable for measuring large AC currents; they have a simple structure and low cost, but can only measure AC, and are used in power systems. Shunt sensors, utilizing Ohm's law, have a simple structure, high accuracy, and can measure AC and DC, but have power losses; they are used for lithium battery charge and discharge testing. Fiber optic current sensors, based on the Faraday magneto-optical effect, offer good insulation and anti-interference capabilities, high accuracy, and can measure AC and DC; they have a complex structure and high cost, and are used in high-voltage and high-precision measurement fields.

[0006] Using a current sensor to monitor the lithium battery current signal to divide the discharge cycle can accurately define the moments when the lithium battery begins and ends its power output, ensuring the accuracy and objectivity of the discharge cycle division. This method of judgment based on the actual current state avoids interference from subjective factors and provides a reliable and accurate time range for subsequent lithium battery performance analysis, data acquisition, and management.

[0007] Step S2: Divide the lithium battery pack into individual lithium batteries that are monitored; obtain and analyze the historical data of the monitored lithium batteries, including the historical equalization compensation amount and discharge cycle of the monitored lithium batteries; extract the equalization compensation amount for each discharge cycle based on the historical data of the monitored lithium batteries to construct a set of cycle equalization compensation amounts, where the equalization compensation amount represents the ability to maintain the output performance of multiple lithium batteries working together while ensuring that the capacity decay of each lithium battery in the lithium battery pack is consistent. Step S2-1: Divide the lithium battery pack into units using a single lithium battery as the basic unit. The lithium battery pack is represented as a power combination that works together by multiple lithium batteries. Monitor each lithium battery in the battery pack and take 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 set of cycle equalization compensation amounts. The set of cycle equalization compensation amounts represents the equalization compensation amount in each historical discharge cycle of the monitored lithium battery. The set of cycle equalization compensation amounts is stored in a key-value pair storage method, with 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. The system ID of the monitored lithium battery represents a unique ID randomly generated by the system when the monitored lithium battery stores data, which is used to identify the primary key of the lithium battery data. Dividing lithium battery packs and constructing a set of periodic equalization compensation values ​​offers significant advantages. Dividing and monitoring individual lithium batteries as basic units allows for a focus on the specific condition of each battery, enabling precise understanding of its status. By extracting the equalization compensation values ​​from historical discharge cycles and storing them as key-value pairs with the system ID as the primary key, data can be efficiently organized and managed. This facilitates the traceability and analysis of the equalization compensation status of individual batteries, providing a solid data foundation for subsequent battery performance evaluation, capacity degradation prediction, and optimization of battery management strategies.

[0008] Step S3: Construct a trend chart of the change in the equalization compensation amount of the monitored lithium battery based on the set of periodic equalization compensation amounts; select the discharge cycle with the smallest period in the historical discharge cycles as the trend change analysis duration and the discharge cycle with the largest period as the trend change limitation duration based on the historical discharge cycle data of the monitored lithium battery; calculate the instantaneous equalization compensation amount of the monitored lithium battery based on the trend change analysis duration, and calculate the fixed equalization compensation amount of the monitored lithium battery based on the trend chart of the change in equalization compensation amount. Step S3-1: Read the data of the cycle equalization compensation amount set according to the system ID of the monitored lithium battery, and iterate through the equalization compensation amount of each discharge cycle. Step S3-2: Slice and combine the equalization 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: Combine data according to the timestamp of the equalization compensation amount in chronological order; Step S3-2-2: Delete the time periods without equalization compensation and retain the timestamps with equalization compensation. Step S3-3: Read the equalization compensation amount after the slice combination and construct a trend chart of the change of equalization compensation amount based on the timestamp. Construct the horizontal axis with the timestamp as the X-axis and the vertical axis with the equalization compensation amount as the Y-axis. Step S3-4: Extract the discharge cycle based on the historical data of the monitored lithium battery, and obtain the minimum discharge cycle and maximum discharge cycle of the monitored lithium battery by combining the bubble algorithm. Use the minimum discharge cycle as the trend change analysis duration and the maximum discharge cycle as the trend change limitation duration. Step S3-5: Calculate the change value of the balance compensation amount based on the trend change analysis time of the balance compensation amount as the instantaneous balance compensation amount. The instantaneous balance compensation amount is expressed as the change of the balance compensation amount of the monitored lithium battery during the minimum discharge cycle. Calculate the average value of the change of the balance compensation amount of the monitored lithium battery based on the balance compensation amount change trend graph as the fixed balance compensation amount.

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

[0010] The fixed balance compensation amount is calculated using the following formula: ; In the formula, J fix Represented as a fixed equalization compensation amount, i.e., the average equalization compensation amount of the monitored lithium battery; T max The longest discharge cycle in the historical discharge cycle is represented as the duration of the trend change; m represents the duration of the trend change within the specified time T. max The number of valid time intervals within; J represents the change in the equilibrium compensation amount within the j-th time interval; j Let the equilibrium compensation amount at time point j be denoted as ; satisfying the following condition: ; Constructing a trend chart of the equalization compensation amount can intuitively present the changing trend of the battery's equalization compensation amount over time, providing a clear visual basis for subsequent analysis. The minimum and maximum discharge cycles are selected as the trend change analysis duration and limit duration, accurately grasping 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 cycle, accurately measuring the battery's dynamic compensation characteristics over a short period; the fixed equalization compensation amount formula integrates the compensation amount changes at various time intervals within the trend change limit duration, reflecting the battery's average compensation over a longer period.

[0011] Step S4: Analyze the historical data of n lithium batteries and set the equalization compensation threshold according to the equalization compensation amount when the battery performance deteriorates to the state of a faulty battery. Based on the equalization compensation data of n lithium batteries from the start of performance degradation to the point of failure, the equalization compensation threshold J is calculated using a neural network model. max .

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

[0013] Step S5: Based on the trend change and the time limit, the maximum balance compensation amount of the monitored lithium battery is predicted and calculated by combining the instantaneous balance compensation amount and the fixed balance compensation amount. The monitoring lithium battery is then given an early warning based on the balance 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 The instantaneous and fixed equilibrium compensation quantities are weighted and combined with a trend change time limit to calculate the equilibrium compensation quantity of the monitored lithium battery, which is then used as the predicted equilibrium compensation quantity 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 combine it with the equalization compensation amount threshold to issue an early warning for the monitored lithium battery. The process is as follows: When J < J max When the change in the balance compensation amount within the time limit of the trend change is determined to be no more than the balance compensation amount threshold, the working conditions of the lithium battery pack for the next operation are met. When J≥J max If the system determines that the change in the balance compensation amount within the time limit of the trend change will exceed the balance compensation amount threshold and does not meet the working conditions of the lithium battery pack for the next time, it will read the system ID of the monitored lithium battery and issue a capacity abnormality warning signal.

[0015] By calculating and predicting the equalization compensation amount and the maximum equalization compensation amount, and combining this with an equalization compensation amount threshold for early warning, significant advantages are achieved. Obtaining the current equalization compensation amount and combining it with instantaneous and fixed equalization compensation amounts to calculate the predicted value takes into account the short-term and long-term performance changes of the battery, enabling a more accurate prediction of the battery's future equalization compensation situation. Early warning judgments based on comparisons with thresholds can detect potential capacity anomalies in lithium batteries in advance. When operating conditions are determined to be unmet, an early warning signal is issued and the system ID is read, allowing for rapid location of the problematic battery. This facilitates 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 potential risks caused by battery failures.

[0016] Furthermore, an intelligent management system for long-term energy storage of novel lithium batteries is provided, comprising 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 set of equalization compensation amounts; the compensation amount calculation module is used to calculate the compensation amount change trend and 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 of the discharge cycle division module is electrically connected to the input of the data acquisition set construction module; the output of the data acquisition set construction module is electrically connected to the input of the compensation amount calculation module; the output of the compensation amount calculation module is electrically connected to the input of the threshold setting module; and the output of the threshold setting module is electrically connected to the input 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 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 partitioning and monitoring unit and a compensation amount set construction unit; the battery partitioning and monitoring unit is used to partition lithium battery packs and select the monitored batteries; 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 trend of the equilibrium compensation amount change; the instantaneous and fixed amount calculation unit is used to calculate the instantaneous and fixed equilibrium compensation amounts; 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 based on the data. The early warning module includes a prediction compensation calculation unit and an early warning judgment and execution unit; the prediction compensation calculation unit is used to calculate the prediction equilibrium 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. This invention uses a current sensor to monitor the lithium battery current signal to divide the discharge cycle, accurately defining the start and end times of discharge, ensuring the accuracy and objectivity of the discharge cycle division. It avoids interference from subjective factors and provides a precise and reliable time range for subsequent lithium battery performance analysis, data collection, and management, making battery state assessment more scientific and reasonable.

[0018] 2. This invention constructs a set of periodic equalization compensation values, monitors individual lithium batteries as units, and stores data using key-value pairs, enabling efficient organization and management of information. This facilitates the analysis of equalization compensation for individual batteries, providing a solid data foundation for evaluating battery performance, predicting capacity degradation, and optimizing management strategies, thereby improving the precision of battery management.

[0019] 3. This invention combines a neural network model to set a threshold for the equalization compensation amount, leveraging its powerful learning and adaptive capabilities to capture the relationship between battery performance degradation and compensation amount from complex data. The calculated threshold is more realistic, enabling accurate early identification of faults, providing a reliable basis for battery management, improving the safety and stability of lithium battery use, and extending its service life. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating an intelligent management method for long-term energy storage of novel lithium batteries according to the present invention. Figure 2 This is a schematic diagram of the structure of an intelligent management system for long-term energy storage of novel lithium batteries according to the present invention. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] Example 1: As Figure 1 As shown, this invention provides a technical solution: an intelligent management method for long-term energy storage of novel 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 one discharge cycle. The lithium battery current signal is monitored by a current sensor. When the current sensor detects the current signal of the lithium battery, it is determined that the lithium battery is outputting electrical energy. The moment when the current is detected is taken as the starting point. When the current sensor fails to detect the current signal of the lithium battery, it is determined that the electrical energy output has ended. The moment when the current signal of the lithium battery is no longer detected is taken as the cutoff point. The time interval between the starting point and the cutoff point is divided into one discharge cycle of the lithium battery.

[0023] In practice, the operating principle is as follows: a current sensor monitors 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 begins to output electrical energy; this moment is recorded as the start point of the discharge cycle. As the discharge process progresses, when the sensor can no longer obtain a current signal, it indicates that the lithium battery's output of electrical energy has stopped; this moment is recorded as the cutoff point. Finally, the time interval between the start point and the cutoff point is calculated to determine a complete discharge cycle.

[0024] Step S2: Divide the lithium battery pack into individual lithium batteries that are monitored; obtain and analyze the historical data of the monitored lithium batteries, including the historical equalization compensation amount and discharge cycle of the monitored lithium batteries; extract the equalization compensation amount for each discharge cycle based on the historical data of the monitored lithium batteries to construct a set of cycle equalization compensation amounts, where the equalization compensation amount represents the ability to maintain the output performance of multiple lithium batteries working together while ensuring that the capacity decay of each lithium battery in the lithium battery pack is consistent. Step S2-1: Divide the lithium battery pack into units using a single lithium battery as the basic unit. The lithium battery pack is represented as a power combination that works together by multiple lithium batteries. Monitor each lithium battery in the battery pack and take 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 set of periodic equalization compensation amounts. The set of periodic equalization compensation amounts represents the equalization compensation amount in each historical discharge cycle of the monitored lithium battery. The set of periodic equalization compensation amounts is stored in a key-value pair format, with 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. The system ID of the monitored lithium battery is a unique ID randomly generated by the system during data storage and is used to identify the primary key of the lithium battery data.

[0025] In practice, the lithium battery pack, composed of multiple cooperating lithium batteries, is first divided into individual lithium batteries as basic units. Each battery within the pack is monitored, and one is selected as the monitored lithium battery. Next, the equalization compensation amount for each discharge cycle is extracted from the historical data of this monitored lithium battery. This equalization compensation amount ensures stable output performance of the lithium battery pack and consistent capacity decay across all batteries. Finally, a key-value pair storage method is used, with a unique system ID randomly generated by the system as the primary key and the equalization compensation amount for each discharge cycle as the value, to construct and store a set of cycle equalization compensation amounts.

[0026] Step S3: Construct a trend chart of the change in the equalization compensation amount of the monitored lithium battery based on the set of periodic equalization compensation amounts; select the discharge cycle with the smallest period in the historical discharge cycles as the trend change analysis duration and the discharge cycle with the largest period as the trend change limitation duration based on the historical discharge cycle data of the monitored lithium battery; calculate the instantaneous equalization compensation amount of the monitored lithium battery based on the trend change analysis duration, and calculate the fixed equalization compensation amount of the monitored lithium battery based on the trend chart of the change in equalization compensation amount. Step S3-1: Read the data of the cycle equalization compensation amount set according to the system ID of the monitored lithium battery, and iterate through the equalization compensation amount of each discharge cycle. Step S3-2: Slice and combine the equalization 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: Combine data according to the timestamp of the equalization compensation amount in chronological order; Step S3-2-2: Delete the time periods without equalization compensation and retain the timestamps with equalization compensation. Step S3-3: Read the equalization compensation amount after the slice combination and construct a trend chart of the change of equalization compensation amount based on the timestamp. Construct the horizontal axis with the timestamp as the X-axis and the vertical axis with the equalization compensation amount as the Y-axis. Step S3-4: Extract the discharge cycle based on the historical data of the monitored lithium battery, and obtain the minimum discharge cycle and maximum discharge cycle of the monitored lithium battery by combining the bubble algorithm. Use the minimum discharge cycle as the trend change analysis duration and the maximum discharge cycle as the trend change limitation duration. Step S3-5: Calculate the change value of the balance compensation amount based on the trend change analysis time of the balance compensation amount as the instantaneous balance compensation amount. The instantaneous balance compensation amount is expressed as the change of the balance compensation amount of the monitored lithium battery during the minimum discharge cycle. Calculate the average value of the change of the balance compensation amount of the monitored lithium battery based on the balance compensation amount change trend graph as the fixed balance compensation amount.

[0027] For example, the trend change is limited to a duration T. max There are m=5 valid time intervals, and the equalization compensation data corresponding to each time interval is as follows: The time sequence j: 1, 2, 3, 4, 5, 6; Balanced compensation quantity J j : 10, 12, 15, 18, 20, 22; When j=1, the change in the balance compensation amount in the first time interval is: 12-10=2; When j=2, the change in the balance compensation amount in the second time interval is: 15-12=3; When j=3, the change in the balance compensation amount in the third time interval is: 18-15=3; When j=4, the change in the balance compensation amount in the 4th time interval is: 20-18=2; When j=5, the change in the balance compensation amount in the 5th time interval is: 22-20=2; According to the formula for calculating the fixed equilibrium compensation amount: ; Substituting the above data, we get: J fix =12 / 5=2.4; Step S4: Analyze the historical data of n lithium batteries and set the equalization compensation threshold according to the equalization compensation amount when the battery performance deteriorates to the state of a faulty battery. Based on the equalization compensation data of n lithium batteries from the start of performance degradation to the point of failure, the equalization compensation threshold J is calculated using a neural network model. max .

[0028] Step S5: Based on the trend change and the time limit, the maximum balance compensation amount of the monitored lithium battery is predicted and calculated by combining the instantaneous balance compensation amount and the fixed balance compensation amount. The monitoring lithium battery is then given an early warning based on the balance compensation amount threshold.

[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 The instantaneous and fixed equilibrium compensation quantities are weighted and combined with a trend change time limit to calculate the equilibrium compensation quantity of the monitored lithium battery, which is then used as the predicted equilibrium compensation quantity 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 combine it with the equalization compensation amount threshold to issue an early warning for the monitored lithium battery. The process is as follows: When J < J max When the change in the balance compensation amount within the time limit of the trend change is determined to be no more than the balance compensation amount threshold, the working conditions of the lithium battery pack for the next operation are met. When J≥J max If the system determines that the change in the balance compensation amount within the time limit of the trend change will exceed the balance compensation amount threshold and does not meet the working conditions of the lithium battery pack for the next time, it will read the system ID of the monitored lithium battery and issue a capacity abnormality warning signal.

[0030] Example 2, as Figure 2As shown, the present invention provides an intelligent management system for long-term energy storage of novel lithium batteries. 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 set of equalization compensation amounts; the compensation amount calculation module is used to calculate the compensation amount change trend and 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 of the discharge cycle division module is electrically connected to the input of the data acquisition set construction module; the output of the data acquisition set construction module is electrically connected to the input of the compensation amount calculation module; the output of the compensation amount calculation module is electrically connected to the input of the threshold setting module; and the output of the threshold setting module is electrically connected to the input 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 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 partitioning and monitoring unit and a compensation amount set construction unit; the battery partitioning and monitoring unit is used to partition lithium battery packs and select the monitored batteries; 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 trend of the equilibrium compensation amount change; the instantaneous and fixed amount calculation unit is used to calculate the instantaneous and fixed equilibrium compensation amounts; 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 based on the data. The early warning module includes a prediction compensation calculation unit and an early warning judgment and execution unit; the prediction compensation calculation unit is used to calculate the prediction equilibrium compensation amount; the early warning judgment and execution unit is used to judge and issue an early warning signal.

[0031] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A smart management method for long-term energy storage of novel lithium batteries, characterized in that: 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 one discharge cycle. Step S2: Divide the lithium battery pack into individual lithium batteries that are monitored; obtain and analyze the historical data of the monitored lithium batteries, including the historical equalization compensation amount and discharge cycle of the monitored lithium batteries; extract the equalization compensation amount for each discharge cycle based on the historical data of the monitored lithium batteries to construct a set of cycle equalization compensation amounts, where the equalization compensation amount represents the ability to maintain the output performance of multiple lithium batteries working together while ensuring that the capacity decay of each lithium battery in the lithium battery pack is consistent. Step S3: Construct a trend chart of the change in the equalization compensation amount of the monitored lithium battery based on the set of periodic equalization compensation amounts; select the discharge cycle with the smallest period in the historical discharge cycles as the trend change analysis duration and the discharge cycle with the largest period as the trend change limitation duration based on the historical discharge cycle data of the monitored lithium battery; calculate the instantaneous equalization compensation amount of the monitored lithium battery based on the trend change analysis duration, and calculate the fixed equalization compensation amount of the monitored lithium battery based on the trend chart of the change in equalization compensation amount. Step S4: Analyze the historical data of n lithium batteries and set the equalization compensation threshold according to the equalization compensation amount when the battery performance deteriorates to the state of a faulty battery. Step S5: Based on the trend change and the time limit, the maximum balance compensation amount of the monitored lithium battery is predicted and calculated by combining the instantaneous balance compensation amount and the fixed balance compensation amount. The monitoring lithium battery is then given an early warning based on the balance compensation amount threshold.

2. The intelligent management method for long-term energy storage of novel lithium batteries according to claim 1, characterized in that: In step S1, the lithium battery current signal is monitored by a current sensor. When the current sensor obtains the lithium battery current signal, it is determined that the lithium battery is outputting electrical energy. The starting point is the moment when current is first acquired. When the current sensor no longer acquires a current signal from the lithium battery, it is determined that the power output has ended, and the moment when no current signal from the lithium battery is acquired is taken as the cutoff point. The time interval between the starting point and the cutoff point is divided into one discharge cycle of the lithium battery.

3. The intelligent management method for long-term energy storage of novel lithium batteries according to claim 2, characterized in that: The specific steps of step S2 are as follows: Step S2-1: Divide the lithium battery pack into units using a single lithium battery as the basic unit. The lithium battery pack is represented as a power combination that works together by multiple lithium batteries. Monitor each lithium battery in the battery pack and take 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 set of periodic equalization compensation amounts. The set of periodic equalization compensation amounts represents the equalization compensation amount in each historical discharge cycle of the monitored lithium battery. The set of periodic equalization compensation amounts is stored in a key-value pair format, with 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. The system ID of the monitored lithium battery is a unique ID randomly generated by the system during data storage and is used to identify the primary key of the lithium battery data.

4. The intelligent management method for long-term energy storage of novel lithium batteries according to claim 3, characterized in that: The specific steps of step S3 are as follows: Step S3-1: Read the data of the cycle equalization compensation amount set according to the system ID of the monitored lithium battery, and iterate through the equalization compensation amount of each discharge cycle. Step S3-2: Slice and combine the equalization 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: Combine data according to the timestamp of the equalization compensation amount in chronological order; Step S3-2-2: Delete the time periods without equalization compensation and retain the timestamps with equalization compensation. Step S3-3: Read the equalization compensation amount after the slice combination and construct a trend chart of the equalization compensation amount change based on the timestamp. Construct the horizontal axis with the timestamp as the X-axis and the vertical axis with the equalization compensation amount as the Y-axis.

5. The intelligent management method for long-term energy storage of novel lithium batteries according to claim 4, characterized in that: Step S3 also includes: Step S3-4: Extract the discharge cycle based on the historical data of the monitored lithium battery, and obtain the minimum discharge cycle and maximum discharge cycle of the monitored lithium battery by combining the bubble algorithm. Use the minimum discharge cycle as the trend change analysis duration and the maximum discharge cycle as the trend change limitation duration. Step S3-5: Calculate the change value of the balance compensation amount based on the trend change analysis time of the balance compensation amount as the instantaneous balance compensation amount. The instantaneous balance compensation amount is expressed as the change of the balance compensation amount of the monitored lithium battery during the minimum discharge cycle. Calculate the average value of the change of the balance compensation amount of the monitored lithium battery based on the balance compensation amount change trend graph as the fixed balance compensation amount.

6. The intelligent management method for long-term energy storage of novel lithium batteries according to claim 5, characterized in that: In step S4, based on the equalization compensation amount data of n lithium batteries from the start of battery performance degradation until they reach the faulty battery state, the equalization compensation amount threshold J is calculated by combining the analysis and calculation of the neural network model. max .

7. The intelligent management method for long-term energy storage of novel lithium batteries according to claim 6, characterized in that: The specific steps of step S5 are as follows: 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 The instantaneous and fixed equilibrium compensation quantities are weighted and combined with a trend change time limit to calculate the equilibrium compensation quantity of the monitored lithium battery, which is then used as the predicted equilibrium compensation quantity 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 combine it with the equalization compensation amount threshold to issue an early warning for the monitored lithium battery. The process is as follows: When J < J max When the change in the balance compensation amount within the time limit of the trend change is determined to be no more than the balance compensation amount threshold, the working conditions of the lithium battery pack for the next operation are met. When J≥J max If the system determines that the change in the balance compensation amount within the time limit of the trend change will exceed the balance compensation amount threshold and does not meet the working conditions of the lithium battery pack for the next time, it will read the system ID of the monitored lithium battery and issue a capacity abnormality warning signal.

8. An intelligent management system for long-term energy storage of novel lithium batteries, wherein the system is applied to the intelligent management method for long-term energy storage of novel lithium batteries as described in any one of claims 1-7, 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 set of equalization compensation amounts; the compensation amount calculation module is used to calculate the compensation amount change trend and 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 of the discharge cycle division module is electrically connected to the input of the data acquisition set construction module; the output of the data acquisition set construction module is electrically connected to the input of the compensation amount calculation module; the output of the compensation amount calculation module is electrically connected to the input of the threshold setting module; and the output of the threshold setting module is electrically connected to the input of the early warning module.

9. The intelligent management system for long-term energy storage of novel 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 times of 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 quantity set construction unit; the battery division and monitoring unit is used to divide lithium battery packs and select the monitored batteries; The compensation amount set construction unit is used to construct a periodic equilibrium 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 changing trend of the equilibrium compensation amount. The instantaneous and fixed quantity calculation unit is used to calculate the instantaneous and fixed balance compensation quantities.

10. The intelligent management system for long-term energy storage of novel 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 based on the data. The early warning module includes a prediction compensation calculation unit and an early warning judgment and execution unit; the prediction compensation calculation unit is used to calculate the prediction equilibrium compensation amount; the early warning judgment and execution unit is used to judge and issue an early warning signal.

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