A lithium battery management system for mining

Abstract

This application discloses a mining lithium battery management system, belonging to the field of battery management technology, comprising: a data acquisition module; a feature processing module, which obtains the lithium battery database after coding and classification; a state prediction model, which uses the data in the coded and classified lithium battery database to obtain the lithium battery state prediction model through a neural network to predict the future state of the lithium battery, the future state of the lithium battery including the health state of the lithium battery; and a charge and discharge balancing module, which is used to manage the charge and discharge of the lithium battery according to the future state of the lithium battery. If the health state of a battery cell in the lithium battery is poor or there is a risk of overcharging and discharging, the lithium battery is set to a suspended working state or the lithium battery is controlled to undergo balancing. The present invention can reduce risks and extend the service life of mining lithium batteries.

Description

Technical Field

[0001] The present application relates to a mining lithium battery management system, which belongs to the technical field of battery management. Background Art

[0002] A mining lithium battery management system is an electronic system designed specifically for mining lithium batteries. Its core task is to monitor and manage various battery operating parameters to ensure safe, stable, and efficient operation in mining environments. While most domestic and international research on battery management systems (BMS) focuses on the electric vehicle industry, there are relatively few management systems specifically designed for large-capacity lithium-ion battery packs used in mining. The requirements for mining lithium-ion power supplies require strict control over remaining charge, cell voltage, cell temperature, and battery pack current. However, some currently used battery management systems can overcharge and over-discharge during use, posing significant safety risks. Therefore, a mining lithium battery management system is needed to mitigate these risks and extend the service life of mining lithium batteries. Summary of the Invention

[0003] According to one aspect of the present application, a mining lithium battery management system is provided, which predicts the future state of the lithium battery and manages the charging and discharging of the lithium battery based on the future state of the lithium battery.

[0004] A mining lithium battery management system, characterized by comprising:

[0005] The data acquisition module acquires the specific working environment and real-time status data of the mining lithium battery to form a lithium battery database; the specific working environment includes temperature environment, humidity environment and vibration environment; the real-time status data of the battery includes charging voltage, charging current, charging temperature, operating temperature and charge state;

[0006] a feature processing module, which codes and classifies the property data of the lithium battery database according to the state property classification, and obtains the coded and classified lithium battery database;

[0007] A state prediction model is obtained by using the data in the coded and classified lithium battery database through a neural network to predict the future state of the lithium battery, wherein the future state of the lithium battery includes the health state of the lithium battery;

[0008] The charge and discharge balancing module is used to manage the charge and discharge of the lithium battery according to the future state of the lithium battery. If the health state of a battery cell in the lithium battery is poor or there is a risk of overcharge and overdischarge, the lithium battery is set to a suspended working state or the lithium battery is controlled to perform balancing processing.

[0009] Furthermore, the state properties include environmental state properties and working state properties;

[0010] Using the environmental state properties, encoding the property data of the lithium battery database for the specific working environment to obtain specific working environments with different codes;

[0011] Using the working state properties, the property data of the lithium battery database is used to encode the battery real-time state data to obtain the battery real-time state with different codes;

[0012] Among them, different coded specific working environments correspond to different coded real-time battery states.

[0013] Furthermore, the property data of the lithium battery database is used to encode the real-time battery status data to obtain real-time battery status with different encodings, including:

[0014] The real-time battery status data is divided into n data sets, where n is a positive integer, and each data set includes at least one real-time battery status data.

[0015] Encoding each of the data sets, configuring the encoding to have a marking pointer set in a time-oriented manner, wherein the marking pointer sequentially marks the data sets and makes them have a specific direction;

[0016] The real-time status of the battery with different codes having specific time directions and orderly arrangement is obtained.

[0017] Furthermore, if a battery cell in the lithium battery is in a poor health state or has a risk of overcharge and overdischarge, the lithium battery is set to a suspended working state or the lithium battery is controlled to perform equalization processing, including:

[0018] When the health status of the battery cell is poor and the capacity decay is serious or there is a safety hazard, the working state of the lithium battery is set to a suspended working state;

[0019] When the battery cell has a risk of overcharge and overdischarge, the lithium battery is controlled to perform equalization processing.

[0020] Furthermore, the balancing process includes adjusting current, voltage and temperature to reduce risk and extend the service life of the lithium battery.

[0021] Furthermore, the equalization processing includes:

[0022] If the lithium battery is in a discharging state, determining whether the discharge current of the battery cell is less than a preset current threshold, and if so, performing balancing for a first processing time;

[0023] If the lithium battery is in a charging state, determining whether the voltage of the battery cell is less than a preset voltage threshold, and if so, performing balancing with a second processing time, and if not, performing balancing with the first processing time;

[0024] If the battery cell is in a suspended working state, balancing is performed during the third processing time.

[0025] Furthermore, the processing speed of the second processing time is greater than the processing speed of the first processing time;

[0026] A processing speed of the third processing time is greater than a processing speed of the second processing time.

[0027] Furthermore, the first processing time is determined according to a difference between a discharge current of the battery cell and a preset current threshold;

[0028] determining the second processing time according to a difference between the voltage of the battery cell and a preset voltage threshold;

[0029] The third processing time is determined according to the discharge current of the battery cell when the battery cell is in the suspended operation state.

[0030] The beneficial effects of this application include:

[0031] The present application provides a mining lithium battery management system, which has a data acquisition module to obtain the specific working environment and real-time battery status data of the mining lithium battery, a feature processing module to encode and classify the property data of the lithium battery database, and obtain the encoded and classified lithium battery database, and a state prediction model to predict the future state of the lithium battery, which is of great significance for discovering potential battery problems in advance and preventing battery failures. The charge and discharge balancing module manages the charge and discharge of the lithium battery according to the future state of the lithium battery predicted by the state prediction model. If it is found that the health status of a battery cell is poor or there is a risk of overcharging and discharging, measures will be taken immediately, such as setting the lithium battery to a suspended working state, or starting the balancing processing mechanism to ensure the safety and stability of the battery pack. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 This is a schematic diagram of a mining lithium battery management system in one embodiment of the present application. DETAILED DESCRIPTION

[0033] The present application is described in detail below with reference to embodiments, but the present application is not limited to these embodiments.

[0034] See also Figure 1 , a mining lithium battery management system, characterized by comprising:

[0035] The data acquisition module acquires the specific working environment and real-time status data of the mining lithium battery to form a lithium battery database; the specific working environment includes temperature environment, humidity environment and vibration environment; the real-time status data of the battery includes charging voltage, charging current, charging temperature, operating temperature and charge state;

[0036] a feature processing module, which codes and classifies the property data of the lithium battery database according to the state property classification, and obtains the coded and classified lithium battery database;

[0037] A state prediction model is obtained by using the data in the coded and classified lithium battery database through a neural network to predict the future state of the lithium battery, wherein the future state of the lithium battery includes the health state of the lithium battery;

[0038] The charge and discharge balancing module is used to manage the charge and discharge of the lithium battery according to the future state of the lithium battery. If the health state of a battery cell in the lithium battery is poor or there is a risk of overcharge and overdischarge, the lithium battery is set to a suspended working state or the lithium battery is controlled to perform balancing processing.

[0039] Specifically, the data acquisition module collects data on the specific operating environments of mining lithium batteries, such as temperature, humidity, and vibration. This data is crucial for assessing battery operating conditions and potential risks. It also acquires key data such as charging voltage, charging current, charging temperature, operating temperature, and state of charge in real time. Together, these data form a lithium battery database, providing the foundation for subsequent analysis and prediction. The feature processing module preprocesses the collected data from the lithium battery database, including encoding and classifying the property data. This encoding and classification provides a clearer understanding of the data's properties, facilitating subsequent data analysis and model training. The state prediction model utilizes a neural network algorithm, combined with the encoded and classified data from the lithium battery database, to train a lithium battery state prediction model. This model predicts the future state of lithium batteries, including key indicators such as health status, which is crucial for proactively identifying potential battery issues and preventing battery failures. The charge and discharge balancing module manages the battery's charge and discharge based on the future state predicted by the state prediction model. If a battery cell is found to be in poor health or at risk of overcharge or overdischarge, immediate action is taken, such as suspending the battery or initiating balancing, to ensure the safety and stability of the battery pack.

[0040] This mining lithium battery management system also offers the following advantages: Through its data acquisition module, the system monitors the battery's operating status and environment in real time, ensuring accurate and timely data. Leveraging a neural network algorithm, the system intelligently predicts the battery's future state, providing a scientific basis for battery management. The charge and discharge balancing module precisely manages the battery based on its actual conditions, preventing overcharging and discharging and damage, thereby extending its service life. The system promptly identifies potential battery issues and takes appropriate measures to ensure the safety and stability of the battery pack, reducing the risk of mining equipment downtime due to battery failure.

[0041] In summary, the mining lithium battery management system has the advantages of real-time monitoring, intelligent prediction, precise management, safety and reliability, and can effectively improve the efficiency and safety of mining lithium batteries.

[0042] The state properties include environmental state properties and working state properties;

[0043] Using the environmental state properties, encoding the property data of the lithium battery database for the specific working environment to obtain specific working environments with different codes;

[0044] Using the working state properties, the property data of the lithium battery database is used to encode the battery real-time state data to obtain the battery real-time state with different codes;

[0045] Among them, different coded specific working environments correspond to different coded real-time battery states.

[0046] Specifically, the environmental state properties describe the external environmental conditions of the lithium battery, such as temperature, humidity, and vibration. This external environment has a significant impact on the performance and lifespan of the lithium battery. The operating state properties describe the internal state of the lithium battery during operation, such as charging voltage, charging current, charging temperature, operating temperature, and state of charge. This state data reflects the real-time performance and health of the lithium battery. Generally, the operating state properties of a lithium battery may vary under different external environmental conditions. Therefore, different operating states corresponding to different environments are handled here.

[0047] The environmental state properties are used to encode specific operating environment data in the lithium battery database. The resulting encoding is a specific operating environment with different codes, representing different combinations of environmental conditions. The operating state properties are also used to encode the real-time battery state data in the lithium battery database. The resulting encoding is a real-time battery state with different codes, representing different combinations of the lithium battery's internal states during operation. There is a correspondence between the different coded specific operating environments and the different coded real-time battery states. This correspondence reflects the different internal states that a lithium battery may exhibit under different environmental conditions.

[0048] By analyzing this correspondence, we can gain a deeper understanding of the impact of environmental factors on lithium battery performance and the behavioral characteristics of lithium batteries under different environmental conditions. This encoding method helps to convert complex lithium battery data into a form that is easy to analyze and process. By comparing the specific working environment and real-time battery status of different encodings, the key factors affecting lithium battery performance and life can be identified. This provides strong data support for the research and development, optimization and use of lithium batteries, and helps to improve the performance, safety and service life of lithium batteries. Therefore, using environmental state properties and working state properties to encode data in the lithium battery database is an effective data processing method that helps to deeply understand the performance characteristics and behavioral laws of lithium batteries.

[0049] Encoding the real-time battery status data using the property data of the lithium battery database to obtain real-time battery status with different codes includes:

[0050] The real-time battery status data is divided into n data sets, where n is a positive integer, and each data set includes at least one real-time battery status data.

[0051] Encoding each of the data sets, configuring the encoding to have a marking pointer set in a time-oriented manner, wherein the marking pointer sequentially marks the data sets and makes them have a specific direction;

[0052] The real-time status of the battery with different codes having specific time directions and orderly arrangement is obtained.

[0053] Specifically, the real-time battery status data is first divided into n data sets, where n is a positive integer. Each data set contains at least one real-time battery status data point, which may represent different battery cell states. Each data set is then encoded to convert the raw data into a form that is easy to process and analyze. The encoding can be a combination of numbers, letters, or symbols; the specific implementation is not limited here. During the encoding process, a time-based marker pointer is assigned to each data set. This marker pointer is used to sequentially label the data set and give it specific directionality. The marker pointer can be a timestamp, sequence number, or other marker that indicates the order and time of the data in the data set. By configuring the marker pointer, different encoded real-time battery status data with specific time references and ordered arrangement are obtained. These encoded data states are arranged in chronological order, facilitating subsequent analysis and processing. The specific time reference enables the system to accurately identify the time point corresponding to each data state, thereby more accurately assessing the battery's performance and status. This encoding and sorting method helps convert complex real-time battery status data into a structured form, facilitating subsequent analysis and processing. By analyzing the encoded data status, we can gain a deeper understanding of battery performance and status changes at different time points, providing strong data support for battery health management and maintenance. This also helps improve the efficiency and accuracy of data processing, providing strong technical support for the research, development, optimization, and use of lithium batteries. Therefore, dividing, encoding, and orderly arranging the real-time battery status data in the lithium battery database is an effective processing method that helps to deeply understand the performance characteristics and behavioral patterns of batteries, and provides strong data support for battery health management and maintenance.

[0054] If a battery cell in the lithium battery is in a poor health state or has a risk of overcharge and overdischarge, the lithium battery is set to a suspended working state or the lithium battery is controlled to perform equalization processing, including:

[0055] When the health status of the battery cell is poor and the capacity decay is serious or there is a safety hazard, the working state of the lithium battery is set to a suspended working state;

[0056] When the battery cell has a risk of overcharge and overdischarge, the lithium battery is controlled to perform equalization processing.

[0057] The balancing process includes adjusting current, voltage, and temperature to reduce risk and extend the service life of the lithium battery.

[0058] Specifically, when a single cell in a lithium-ion battery is detected to be in poor health, experiencing severe capacity degradation, or presenting a safety hazard, the system should immediately set the lithium-ion battery's operating state to a suspended state. This is to prevent further deterioration of the cell, avoid possible safety incidents, and protect the performance and safety of the entire battery pack. When a cell is detected to be at risk of overcharging or overdischarging, the system should implement balancing measures. Balancing is a method of actively managing the status of each cell within a battery pack, aiming to reduce performance differences between cells and improve the overall performance and safety of the battery pack.

[0059] By adjusting the charge or discharge current, the charge and discharge rates of the battery cells are made consistent, preventing some cells from overcharging or discharging. By adjusting the voltage of the battery cells to maintain it within a reasonable range, damage to the battery caused by excessively high or low voltage is prevented. Temperature is a key factor affecting the performance and lifespan of lithium-ion batteries. Adjusting temperature is also a crucial step in the balancing process. Because each battery cell in the battery pack generates heat during the charge and discharge process, temperature differences can further exacerbate imbalances between the cells. Therefore, measures are needed to reduce temperature differences in the battery pack to improve balance between the cells. This process involves implementing an effective heat dissipation system to reduce the temperature of the battery pack.

[0060] It's worth noting that the primary purpose of balancing is to reduce performance variations between battery cells and improve the overall performance and safety of the battery pack. By adjusting parameters such as current, voltage, and temperature, the battery cells can be more evenly balanced, extending the lifespan of the lithium-ion battery and reducing potential safety hazards caused by performance variations between cells.

[0061] Therefore, by monitoring the status of battery cells in real time and taking timely countermeasures, further deterioration of the cells can be avoided, protecting the performance and safety of the entire battery pack, and extending the service life of the lithium battery. This is of great significance for improving the reliability and economic efficiency of lithium batteries, and will help promote the application and development of lithium batteries in various fields.

[0062] The equalization process includes:

[0063] If the lithium battery is in a discharging state, determining whether the discharge current of the battery cell is less than a preset current threshold, and if so, performing balancing for a first processing time;

[0064] If the lithium battery is in a charging state, determining whether the voltage of the battery cell is less than a preset voltage threshold, and if so, performing balancing with a second processing time, and if not, performing balancing with the first processing time;

[0065] If the battery cell is in a suspended working state, balancing is performed during the third processing time.

[0066] Specifically, when a lithium-ion battery is discharging, it is first determined whether the discharge current of the battery cell is less than a preset current threshold. If the discharge current is less than the preset current threshold, it indicates that the battery cell is discharging slowly, potentially leading to performance differences or uneven charge. At this point, balancing is performed for the first processing time, aiming to achieve a more balanced charge between the battery cells by adjusting the discharge rate or other parameters. If the discharge current is not less than the preset current threshold (i.e., the battery cell is discharging normally or rapidly), immediate balancing may not be necessary, or the effect of balancing may not be significant. In this case, the decision to perform balancing can be made based on the actual situation, or a more appropriate time can be waited for.

[0067] When a lithium-ion battery is charging, a determination is made as to whether the voltage of the battery cell is less than a preset voltage threshold. If the battery cell voltage is less than the preset voltage threshold, this indicates that the battery cell is undercharged or charging slowly. At this point, equalization is performed for the second processing time, adjusting the charging current, voltage, or other parameters to increase the charging rate of the battery cell and keep it consistent with the other battery cells. If the battery cell voltage is not less than the preset voltage threshold (i.e., the battery cell is charging normally or rapidly), equalization is performed for the first processing time. The "first processing time" here may be a relatively short period of time used to fine-tune the charging status between battery cells to ensure overall charging balance.

[0068] When a battery cell is in a suspended state (e.g., temporarily disabled due to poor health or when the lithium battery is not in operation), balancing is performed for a third processing time. Balancing during a suspended state can be a maintenance charge or discharge of the battery cell to adjust its internal state and prepare for subsequent normal operation. The third processing time may be relatively long to ensure the adequacy and effectiveness of the balancing process.

[0069] In one embodiment, when the lithium battery is in a discharging state and the discharge current of a battery cell is less than a preset current threshold, balancing is performed for a first processing time. This time period may be relatively short, as balancing in the discharging state primarily aims to adjust for differences in charge between battery cells and prevent over-discharge of some cells. The specific time period may vary depending on the battery type, capacity, and performance of the balancing equipment, but may generally range from a few minutes to several hours. When the lithium battery is in a charging state and the battery cell voltage is less than a preset voltage threshold, balancing is performed for a second processing time. This time period may be relatively long, as balancing in the charging state must ensure that the battery cells are fully charged while avoiding safety issues such as overcharging and overheating. The specific time period depends on the battery charging rate, the performance of the balancing equipment, and the system design requirements, but may generally range from a few hours to several tens of hours. If the battery cell voltage is not less than the preset voltage threshold, balancing is performed for the first processing time. In this case, balancing is primarily aimed at fine-tuning the charge state between battery cells to ensure overall charge balance. The time period may be relatively short, similar to balancing in the discharging state. When the battery cells are in a suspended state, balancing is performed for a third processing time. This period can be relatively long because the balancing process during the suspended state may require maintenance charging or discharging to adjust the internal state of the battery cells. The specific period depends on the type, capacity, health of the battery, and the performance of the balancing equipment, but it can typically range from a few hours to dozens of hours.

[0070] The processing speed of the second processing time is greater than the processing speed of the first processing time;

[0071] A processing speed of the third processing time is greater than a processing speed of the second processing time.

[0072] Specifically, processing speed refers to the rate at which the voltage or capacity differences between battery cells are reduced during the balancing process. A faster processing speed means a higher degree of balancing between battery cells within the same time.

[0073] The first processing time (T1) has a relatively slow processing speed. It's ideal for applications where cell differences are minimal or where slow, steady balancing is required. For example, at the end of a battery pack's discharge, when most cells are nearly depleted, balancing is primarily performed to fine-tune the remaining charge and prevent over-discharge of individual cells. The second processing time (T2) has a higher processing speed than the first. It's ideal for applications where cell differences are significant and rapid balancing is required. For example, during battery pack charging, if one or more cells charge significantly faster than others, the processing speed needs to be increased to ensure all cells are fully charged simultaneously. The third processing time (T3) has a higher processing speed than the second (i.e., faster) than the second. It's ideal for applications where deep balancing or maintenance balancing is required and cells are suspended. Since the cells are not actually charging or discharging, a higher processing speed is acceptable to quickly adjust for differences in cell state. However, it's important to note that excessively high processing speeds may result in excessive heat generation and battery loss, so a trade-off needs to be considered in practical applications.

[0074] It's worth noting that regardless of the processing speed or time period chosen, safety must be ensured during the balanced processing. This includes monitoring battery parameters such as temperature, voltage, and current to prevent safety issues like overcharging, over-discharging, and overheating. Faster processing speeds generally result in more efficient energy transfer or dissipation, but they can also lead to greater battery loss and heat generation. Therefore, a comprehensive balance between efficiency and loss is crucial when selecting a processing speed.

[0075] determining the first processing time according to a difference between a discharge current of the battery cell and a preset current threshold;

[0076] determining the second processing time according to a difference between the voltage of the battery cell and a preset voltage threshold;

[0077] The third processing time is determined according to the discharge current of the battery cell when the battery cell is in the suspended operation state.

[0078] Specifically, the first processing time (T1) is determined based on the difference between the discharge current of the battery cell and the preset current threshold. When the battery cell is in the discharge state, its discharge current is monitored in real time. The difference between the discharge current and the preset current threshold (ΔI = I 放电 - I 阈值The first processing time T1 is determined based on the difference ΔI using a preset mapping relationship or algorithm. For example, when ΔI is small, it means that the battery cell discharges more smoothly, and a longer T1 can be set; when ΔI is large, it means that the battery cell discharges faster and may require a faster processing speed, so a shorter T1 is set.

[0079] The second processing time (T2) is determined based on the difference between the voltage of the battery cell and the preset voltage threshold. When the battery cell is in the charging state, its voltage is monitored in real time. The difference between the voltage and the preset voltage threshold (ΔV = V 充电 -V 阈值 The second processing time T2 is determined based on the size of the difference ΔV using a preset mapping relationship or algorithm. For example, when ΔV is small, it means that the battery cell voltage is close to the preset value, and a longer T2 can be set for fine-tuning. When ΔV is large, it means that the battery cell voltage deviates significantly from the preset value, requiring a faster processing speed, so a shorter T2 is set.

[0080] The third processing time (T3) is determined based on the discharge current of the battery cell when it is suspended. When the battery cell is suspended, its discharge current is monitored (note that the discharge current may be very low or even zero at this time). If the discharge current is not zero, it indicates that the battery cell may be experiencing self-discharge or internal short circuit issues. In this case, the third processing time T3 should be determined based on the discharge current using a preset mapping relationship or algorithm. For example, a higher discharge current may require faster processing speed to correct the condition, so a shorter T3 may be set. If the discharge current is zero or near zero, it indicates that the battery cell is in a relatively stable state. In this case, a longer T3 can be set for maintenance balancing or deep balancing.

[0081] It is worth noting that this strategy should allow for dynamic adjustments based on the real-time status of the battery cells in practical applications. For example, when the status of a battery cell changes significantly, the balancing time can be recalculated and adjusted. Safety factors should always be considered when determining the balancing time. For example, avoiding excessively fast processing speeds that could cause battery overheating or damage. When determining the balancing time, a balance between efficiency and loss must also be considered. Excessively long processing times may result in increased energy losses, while too short processing times may not achieve sufficient balancing results.

[0082] The above descriptions are merely a few embodiments of the present application and do not constitute any form of limitation to the present application. Although the present application discloses the preferred embodiments as above, they are not intended to limit the present application. Any technical personnel familiar with the present profession, without departing from the scope of the technical solution of the present application, using the technical content disclosed above to make slight changes or modifications are equivalent to equivalent implementation cases and fall within the scope of the technical solution.

Claims

1. A mining lithium battery management system, characterized in that: include: The data acquisition module acquires the specific working environment and real-time status data of the mining lithium battery to form a lithium battery database; the specific working environment includes temperature environment, humidity environment and vibration environment; the real-time status data of the battery includes charging voltage, charging current, charging temperature, operating temperature and charge state; a feature processing module, which codes and classifies the property data of the lithium battery database according to the state property classification, and obtains the coded and classified lithium battery database; A state prediction model is obtained by using the data in the coded and classified lithium battery database through a neural network to predict the future state of the lithium battery, wherein the future state of the lithium battery includes the health state of the lithium battery; a charge-discharge balancing module, configured to manage the charge and discharge of the lithium battery according to the future state of the lithium battery, and to suspend the lithium battery or perform balancing on the lithium battery if the health state of a cell in the lithium battery is poor or there is a risk of overcharge or overdischarge; When the health status of the battery cell is poor and the capacity decay is serious or there is a safety hazard, the working state of the lithium battery is set to a suspended working state; When the battery cell is at risk of overcharge and overdischarge, controlling the lithium battery to perform equalization processing; The equalization process includes: If the lithium battery is in a discharging state, determining whether the discharge current of the battery cell is less than a preset current threshold, and if so, performing balancing for a first processing time; If the lithium battery is in a charging state, determining whether the voltage of the battery cell is less than a preset voltage threshold, and if so, performing balancing with a second processing time, and if not, performing balancing with the first processing time; If the battery cell is in a suspended working state, balancing is performed for a third processing time; The processing speed of the second processing time is greater than the processing speed of the first processing time; A processing speed of the third processing time is greater than a processing speed of the second processing time.

2. A mining lithium battery management system according to claim 1, characterized in that: The state properties include environmental state properties and working state properties; Using the environmental state properties, encoding the property data of the lithium battery database for the specific working environment to obtain specific working environments with different codes; Using the working state properties, the property data of the lithium battery database is used to encode the battery real-time state data to obtain the battery real-time state with different codes; Among them, different coded specific working environments correspond to different coded real-time battery states.

3. A mining lithium battery management system according to claim 1, characterized in that: Encoding the real-time battery status data using the property data of the lithium battery database to obtain real-time battery status with different codes includes: The real-time battery status data is divided into n data sets, where n is a positive integer, and each data set includes at least one real-time battery status data. Encoding each of the data sets, configuring the encoding to have a marking pointer set in a time-oriented manner, wherein the marking pointer sequentially marks the data sets and makes them have a specific direction; The real-time status of the battery with different codes having specific time directions and orderly arrangement is obtained.

4. A mining lithium battery management system according to claim 1, characterized in that: The balancing process includes adjusting current, voltage, and temperature to reduce risk and extend the service life of the lithium battery.

5. A mining lithium battery management system according to claim 1, characterized in that: determining the first processing time according to a difference between a discharge current of the battery cell and a preset current threshold; determining the second processing time according to a difference between the voltage of the battery cell and a preset voltage threshold; The third processing time is determined according to the discharge current of the battery cell when the battery cell is in the suspended operation state.

Images