Monitoring and early warning system for lithium battery energy storage

Abstract

The invention discloses a monitoring and early warning system for lithium battery energy storage, and relates to the technical field of lithium battery energy storage detection, and the system comprises a data collection module which is used for collecting all operation parameters of a lithium battery in real time; the data analysis module is connected with the data acquisition module and is used for receiving and analyzing the operation parameters; the early warning module is connected with the data analysis module, and when the data analysis module evaluates that the running state of the lithium battery exceeds a preset safety threshold range, an early warning signal of a corresponding level is sent out; and the communication module is used for transmitting the collected operation parameters, the analysis result and the early warning information to a remote monitoring terminal or a cloud platform. Through comprehensive data acquisition, innovative formula analysis, precise early warning and various communication and control means, the battery state is accurately evaluated, early warning is performed in time, intelligent regulation and control are performed, the service life of the battery is prolonged, safety is guaranteed, the energy utilization efficiency is improved, and efficient and stable operation of the lithium battery energy storage system is assisted.

Description

Technical Field

[0001] The present invention relates to the technical field of power battery energy storage, and in particular to a monitoring and early warning system for lithium battery energy storage. Background Art

[0002] With the continuous growth of energy demand and the increasing emphasis on renewable energy, lithium battery energy storage technology has been widely used in many fields such as power systems, electric vehicles, communication base stations, etc. Lithium batteries have the advantages of high energy density, long cycle life, and low self-discharge rate, but they also face some challenges and safety risks during use.

[0003] First of all, the performance and safety of lithium batteries are closely related to their operating status. During the charging and discharging process, the battery's voltage, current, temperature and other parameters will change. If these parameters exceed the normal range, it may cause the battery performance to decline, shorten its life, and even cause safety accidents such as overheating, combustion, and explosion. For example, overcharging will cause the chemical reaction inside the battery to get out of control, generate a large amount of gas and heat, which may cause the battery to swell and rupture; over-discharging will damage the battery's electrode structure and affect the battery's capacity and cycle life. In addition, the battery's internal resistance will gradually increase with the increase in usage time, which will not only reduce the battery's energy efficiency, but may also cause local overheating and increase safety hazards.

[0004] Secondly, as the scale of lithium battery energy storage systems continues to expand and the application scenarios become increasingly complex, higher requirements are placed on battery management and monitoring. Large energy storage power stations often contain hundreds or thousands of lithium battery cells, and the performance differences and inconsistencies in working conditions between these cells need to be effectively monitored and managed. Traditional manual inspection methods are not only inefficient, but also difficult to detect potential battery problems in real time. At the same time, for distributed energy storage systems, such as battery packs in electric vehicles, due to the diversity and complexity of their use environments, an intelligent, remotely monitorable monitoring and early warning system is needed to ensure the safe and reliable operation of the battery.

[0005] At present, although some lithium battery monitoring systems already exist, they still have some shortcomings in terms of function and performance. The monitoring parameters of many existing systems are not comprehensive enough, and they may only focus on a few parameters such as voltage, current and temperature, while ignoring important information such as internal resistance and power state. In terms of data analysis, the algorithms of some systems are not advanced enough, and the accuracy of the assessment of battery health status and remaining service life is not high, making it difficult to predict battery failure and failure in advance. In addition, the early warning function of some monitoring systems is not sensitive enough, and accurate early warning signals cannot be issued in time, or the early warning method is single and cannot meet the needs of different scenarios. In terms of communication, the communication methods of some systems are not flexible enough, and the stability and reliability of data transmission need to be improved, making it difficult to achieve remote real-time monitoring. Moreover, the existing systems also have problems in compatibility with lithium battery energy storage systems of different types and brands and other power equipment, which is not conducive to the integration and promotion of the system.

[0006] In summary, in order to ensure the safe and efficient operation of lithium battery energy storage systems and improve the service life and performance of batteries, it is of great practical significance and urgency to develop a comprehensive, superior, and intelligent monitoring and early warning system for lithium battery energy storage. This system needs to be able to collect various operating parameters of lithium batteries in real time and accurately, use advanced algorithms for data analysis and status evaluation, issue reliable early warning signals in a timely manner, and take effective control measures. At the same time, it should also have good compatibility and scalability to meet the needs of different scales and application scenarios. Summary of the invention

[0007] The present invention proposes a monitoring and early warning system for lithium battery energy storage to solve the problems mentioned in the above-mentioned prior art.

[0008] In order to achieve the above object, the present invention adopts the following technical solution: a monitoring and early warning system for lithium battery energy storage, comprising: Data acquisition module, used to collect various operating parameters of lithium batteries in real time, including but not limited to voltage, current, temperature, internal resistance and power status; A data analysis module, connected to the data acquisition module, receives and analyzes the operating parameters, and evaluates the operating status of the lithium battery through a preset algorithm and model; An early warning module is connected to the data analysis module, and when the data analysis module evaluates that the operating state of the lithium battery exceeds a preset safety threshold range, an early warning signal of a corresponding level is issued; Communication module, used to transmit the collected operating parameters, analysis results and warning information to the remote monitoring terminal or cloud platform to achieve remote monitoring and management; A control module, interacting with the warning module and the communication module, and taking corresponding control measures according to the level of the warning signal, such as adjusting the charging or discharging strategy, starting or shutting down the heat dissipation device; Introduce the comprehensive evaluation index formula of battery health status: ,in Indicates the battery health status. Indicates the current battery capacity. Indicates the rated battery capacity, Indicates the current internal resistance of the battery. Indicates the internal resistance of a new battery. Indicates the current battery energy. represents the initial battery energy, , , It is a weight coefficient, which is adjusted according to actual conditions. It is used to comprehensively consider the impact of battery capacity, internal resistance, and energy factors on the health status, and more accurately evaluate the battery health status.

[0009] Introduce the temperature change rate warning formula: ,in represents the rate of temperature change, Indicates the current temperature. Indicates the temperature at the last moment. Indicates a time interval. When the set threshold is exceeded, an early warning of possible thermal runaway risks is issued and timely heat dissipation measures are taken to ensure battery safety.

[0010] Introduce the remaining service life prediction correction formula: ,in Indicates the remaining useful life. is the initial prediction value based on the basic algorithm, is the i-th factor affecting the remaining life (such as the number of charge and discharge cycles, temperature history data, current fluctuations), is the weight coefficient of the corresponding factor, The correction factor is used to correct the initial prediction value by comprehensively considering the impact of multiple factors on the remaining service life, thereby improving the accuracy of the remaining service life prediction.

[0011] The data analysis module includes: The data preprocessing unit performs filtering, denoising, and calibration preprocessing operations on the collected original operating parameters to remove abnormal data and interference signals to ensure the accuracy and reliability of the data; The state assessment algorithm unit uses machine learning algorithms or physical model-based algorithms to assess and predict the health state (SOH), remaining useful life (RUL) and current charge and discharge state of the lithium battery based on preprocessed data. The assessment error of the health state is within ±5%, and the prediction error of the remaining useful life is within ±10%. The fault diagnosis unit, based on historical fault data and real-time operating parameters, uses pattern recognition algorithms or expert systems to diagnose whether the lithium battery has potential faults, such as short circuit, open circuit, overcharge, over discharge, thermal runaway, and can locate the location of the fault. The fault diagnosis accuracy rate is over 90%; The early warning module comprises: The threshold setting unit sets different levels of safety thresholds for various operating parameters according to the type, specification and application scenario of the lithium battery, including normal range, warning range and danger range; The warning signal generation unit generates a warning signal of the corresponding level when the operating status parameters evaluated by the data analysis module exceed the warning range. The warning signal includes multiple forms such as sound alarm, flashing lights and SMS notifications, and the warning signals of different levels have obvious distinctions; The warning level adjustment unit dynamically adjusts the level of the warning signal according to the changing trend and severity of the lithium battery operating status to ensure the timeliness and accuracy of the warning.

[0012] The communication module comprises: Wired communication interface, supporting RS485, Ethernet common wired communication protocols, used to connect with local monitoring equipment or short-distance data transmission network, the data transmission rate is not less than 10Mbps, ensuring the stability and reliability of data transmission; The wireless communication unit uses Bluetooth, Wi-Fi, ZigBee or mobile network (such as 4G, 5G) wireless communication technology to wirelessly connect the monitoring and early warning system with the remote monitoring terminal or cloud platform to realize remote data transmission and monitoring. The transmission distance of wireless communication depends on the application scenario. In open space, the Bluetooth transmission distance is not less than 10 meters, and the Wi-Fi transmission distance is not less than 50 meters. The mobile network coverage depends on the operator's network signal strength, and the packet loss rate of data transmission is within 5%.

[0013] The control module comprises: The charging control unit adjusts the charger output parameters, such as charging voltage and charging current, in real time according to the warning signal and the current status of the lithium battery to prevent overcharging and ensure the safety and efficiency of the charging process; The discharge control unit, when detecting abnormal conditions during the discharge of lithium batteries, promptly cuts off the discharge circuit or adjusts the discharge power to avoid damage to the lithium batteries caused by over-discharge, while ensuring the normal operation of the load; The heat dissipation control unit is linked with the temperature sensor and the heat dissipation device (such as fan, liquid cooling system). When the temperature of the lithium battery exceeds the set threshold, the heat dissipation device is automatically started to cool down the battery, so as to control the temperature within a reasonable range and improve the service life and performance of the lithium battery. The emergency handling unit initiates emergency protection measures, such as triggering the fire extinguishing device and cutting off the main power switch, to ensure the safety of personnel and equipment in the event of a serious fault or emergency, such as thermal runaway.

[0014] Preferably, the data acquisition module includes: Voltage sensor, used to accurately measure the single cell voltage and total voltage of lithium batteries, with a measurement accuracy within ±0.1%, and has good anti-interference ability, and can work stably in complex electromagnetic environments; The current sensor can monitor the charge and discharge current of the lithium battery in real time. The measurement range covers the normal operating current range of the lithium battery and the overcurrent situation in a short period of time. The measurement error does not exceed ±0.5%, and it can respond quickly to current changes. Temperature sensors are located in key parts of lithium batteries, such as the surface of the battery cell and the tabs. The measurement temperature range is -40°C to +80°C with an accuracy of ±0.5°C, which can accurately reflect the temperature changes of lithium batteries. The internal resistance measurement unit uses the AC injection method or the DC discharge method to accurately measure the internal resistance of the lithium battery. The measurement frequency is at least once per hour, and the repeatability error of the measurement result is within ±5%; The fuel gauge accurately monitors the remaining power of the lithium battery, using the coulomb counting method or other high-precision power estimation algorithms, with a power estimation error within ±3%.

[0015] Preferably, the monitoring and early warning system has good system integration and compatibility, and can be seamlessly connected with lithium battery energy storage systems of different types, specifications and brands and other related power equipment and monitoring systems to achieve data sharing and interaction without affecting the normal operation and performance of the original system.

[0016] Preferably, the monitoring and early warning system has a self-diagnosis function and can regularly detect and diagnose faults of its own hardware equipment (such as sensors, communication modules) and software programs. When a fault is found, it automatically locates and records the fault, and attempts to self-recover by restarting, switching to backup equipment, or repairing the software to ensure the continuous and stable operation of the system. The self-diagnosis cycle of the system does not exceed 24 hours, and the self-recovery success rate is above 80%.

[0017] Preferably, the monitoring and early warning system includes a data storage module for storing the collected lithium battery operating parameters, analysis results, early warning information and system operation log data. The data storage time is not less than 5 years, and it has data backup and recovery functions. At the same time, it provides a convenient and fast historical record query interface. Users can query and export historical data according to time and parameter type conditions to facilitate data analysis and fault tracing.

[0018] Preferably, the monitoring and early warning system is equipped with a human-machine interface (HMI) to display the real-time lithium battery operating status, monitoring data, early warning information and system operation prompts. The HMI interface is concise and intuitive, easy to operate, supports touch screen operation and multi-language display, and users can use the HMI to set system parameters, adjust thresholds, and query historical data. At the same time, the HMI also has a permission management function, and users of different levels have different operating permissions to ensure the security and reliability of the system.

[0019] Preferably, a method for a monitoring and early warning system using lithium battery energy storage comprises the following steps: Installation and configuration: Install the various sensors in the data acquisition module correctly at the corresponding positions of the lithium battery to ensure that the various operating parameters can be accurately collected. Configure the communication module to establish an effective connection with the remote monitoring terminal or cloud platform. Set the threshold and warning mode of the early warning module, as well as the relevant parameters of the control module.

[0020] Data acquisition and transmission: The data acquisition module collects the voltage, current, temperature, internal resistance and power status parameters of the lithium battery in real time, and transmits these data to the remote monitoring terminal or cloud platform through the communication module, and also transmits them to the data analysis module.

[0021] Data analysis and evaluation: The data preprocessing unit in the data analysis module processes the collected raw data to remove abnormal data and interference signals. The state evaluation algorithm unit uses formula algorithms to evaluate and predict the health status, remaining service life, and charge and discharge status of lithium batteries. The battery health status comprehensive evaluation index formula, temperature change rate warning formula, and remaining service life prediction correction formula are used for relevant calculations and analysis. The fault diagnosis unit diagnoses potential faults and locates the fault location based on historical fault data and real-time operating parameters.

[0022] Early warning and control: When the data analysis module evaluates that the operating status of the lithium battery exceeds the preset safety threshold range, the early warning module issues an early warning signal of the corresponding level. The control module takes corresponding control measures according to the level of the early warning signal, such as adjusting the charging or discharging strategy, starting or shutting down the heat dissipation device.

[0023] Data storage and query: The data storage module stores the collected lithium battery operating parameters, analysis results, warning information, and system operation log data. Users can query and export historical data according to time and parameter type conditions through the human-computer interaction interface to perform data analysis and fault tracing.

[0024] System maintenance and update: Regularly maintain the monitoring and early warning system, including checking the accuracy of sensors and the stability of communication modules. Update and upgrade the system according to actual usage and technological development to improve the performance and functionality of the system.

[0025] Compared with the prior art, the present invention has the following beneficial effects: The present invention uses a high-precision data acquisition module to comprehensively and real-time collect key operating parameters such as voltage, current, temperature, internal resistance and power state of lithium batteries, ensuring accurate grasp of the battery state. This not only helps to timely discover abnormal changes in the battery during charging and discharging, such as overcharging, over-discharging, overheating, etc., but also provides an accurate data basis for subsequent data analysis, so that corresponding measures can be taken in advance, effectively extending the service life of the battery and reducing equipment downtime and maintenance costs caused by battery failure.

[0026] The innovative battery health status comprehensive evaluation index formula, temperature change rate warning formula, and remaining service life prediction correction formula in the data analysis module can more accurately evaluate the battery's health status, remaining service life, and potential thermal runaway risks. By comprehensively considering the impact of multiple factors on battery performance, the evaluation results are more accurate and reliable, providing users with a more scientific basis for battery management, helping to reasonably plan the battery's use and replacement cycle, and improving the battery's efficiency and economy.

[0027] According to the data analysis results, the early warning module can issue a variety of early warning signals with obvious differentiation, such as sound alarms, flashing lights, and SMS notifications, when the battery operating status exceeds the safety threshold range. At the same time, the early warning level adjustment unit can also dynamically adjust the early warning level according to the changing trend and severity of the battery operating status, ensuring the timeliness and accuracy of the early warning, allowing users to take measures at the first time to avoid accidents and ensure the safety of personnel and equipment.

[0028] The communication module uses a variety of wired and wireless communication technologies to achieve efficient and stable data transmission, ensuring that the remote monitoring terminal or cloud platform can obtain real-time battery operation information. Whether in local monitoring or remote management scenarios, it can ensure the speed and reliability of data transmission, reduce the risk of data loss and transmission delay, provide users with a convenient remote monitoring method, and improve management efficiency.

[0029] The control module can automatically take corresponding control measures according to the early warning signal, such as adjusting the charging or discharging strategy, starting or shutting down the cooling device, etc., realizing the intelligent management of the lithium battery energy storage system. This not only effectively avoids further damage to the battery due to abnormal conditions, but also improves the overall stability and reliability of the system, reduces energy waste, and improves energy utilization efficiency.

[0030] In summary, the monitoring and early warning system for lithium battery energy storage of the present invention has significant advantages in ensuring the safe operation of lithium batteries, improving battery life and performance, and realizing intelligent management, and provides strong technical support for the development of the lithium battery energy storage field. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 A schematic block diagram of a monitoring and early warning system for lithium battery energy storage proposed by the present invention; Figure 2 A schematic block diagram of a monitoring and early warning method for lithium battery energy storage proposed by the present invention. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0033] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise" and "counterclockwise" indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0034] In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined. In addition, the terms "installed", "connected" and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, and it can be the internal connection of two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances. The present invention will be further described in detail below in conjunction with the accompanying drawings.

[0035] Reference Figure 1-2 :A monitoring and early warning system for lithium battery energy storage, comprising: Data acquisition module, used to collect various operating parameters of lithium batteries in real time, including but not limited to voltage, current, temperature, internal resistance and power status; A data analysis module, connected to the data acquisition module, receives and analyzes the operating parameters, and evaluates the operating status of the lithium battery through a preset algorithm and model; An early warning module is connected to the data analysis module, and when the data analysis module evaluates that the operating state of the lithium battery exceeds a preset safety threshold range, an early warning signal of a corresponding level is issued; Communication module, used to transmit the collected operating parameters, analysis results and warning information to the remote monitoring terminal or cloud platform to achieve remote monitoring and management; A control module, interacting with the warning module and the communication module, and taking corresponding control measures according to the level of the warning signal, such as adjusting the charging or discharging strategy, starting or shutting down the heat dissipation device; Introduce the comprehensive evaluation index formula of battery health status: ,in Indicates the battery health status. Indicates the current battery capacity. Indicates the rated battery capacity, Indicates the current internal resistance of the battery. Indicates the internal resistance of a new battery. Indicates the current battery energy. represents the initial battery energy, , , It is a weight coefficient, which is adjusted according to actual conditions. It is used to comprehensively consider the impact of battery capacity, internal resistance, and energy factors on the health status, and more accurately evaluate the battery health status.

[0036] Introduce the temperature change rate warning formula: ,in represents the rate of temperature change, Indicates the current temperature. Indicates the temperature at the last moment. Indicates a time interval. When the set threshold is exceeded, an early warning of possible thermal runaway risks is issued and timely heat dissipation measures are taken to ensure battery safety.

[0037] Introduce the remaining service life prediction correction formula: ,in Indicates the remaining useful life. is the initial prediction value based on the basic algorithm, is the i-th factor affecting the remaining life (such as the number of charge and discharge cycles, temperature history data, current fluctuations), is the weight coefficient of the corresponding factor, The correction factor is used to correct the initial prediction value by comprehensively considering the impact of multiple factors on the remaining service life, thereby improving the accuracy of the remaining service life prediction.

[0038] The data analysis module includes: The data preprocessing unit performs filtering, denoising, and calibration preprocessing operations on the collected original operating parameters to remove abnormal data and interference signals to ensure the accuracy and reliability of the data; The state assessment algorithm unit uses machine learning algorithms or physical model-based algorithms to assess and predict the health state (SOH), remaining useful life (RUL) and current charge and discharge state of the lithium battery based on preprocessed data. The assessment error of the health state is within ±5%, and the prediction error of the remaining useful life is within ±10%. The fault diagnosis unit, based on historical fault data and real-time operating parameters, uses pattern recognition algorithms or expert systems to diagnose whether the lithium battery has potential faults, such as short circuit, open circuit, overcharge, over discharge, thermal runaway, and can locate the location of the fault. The fault diagnosis accuracy rate is over 90%; The early warning module comprises: The threshold setting unit sets different levels of safety thresholds for various operating parameters according to the type, specification and application scenario of the lithium battery, including normal range, warning range and danger range; The warning signal generation unit generates a warning signal of the corresponding level when the operating status parameters evaluated by the data analysis module exceed the warning range. The warning signal includes multiple forms such as sound alarm, flashing lights and SMS notifications, and the warning signals of different levels have obvious distinctions; The warning level adjustment unit dynamically adjusts the level of the warning signal according to the changing trend and severity of the lithium battery operating status to ensure the timeliness and accuracy of the warning.

[0039] The communication module comprises: Wired communication interface, supporting RS485, Ethernet common wired communication protocols, used to connect with local monitoring equipment or short-distance data transmission network, the data transmission rate is not less than 10Mbps, ensuring the stability and reliability of data transmission; The wireless communication unit uses Bluetooth, Wi-Fi, ZigBee or mobile network (such as 4G, 5G) wireless communication technology to wirelessly connect the monitoring and early warning system with the remote monitoring terminal or cloud platform to realize remote data transmission and monitoring. The transmission distance of wireless communication depends on the application scenario. In open space, the Bluetooth transmission distance is not less than 10 meters, and the Wi-Fi transmission distance is not less than 50 meters. The mobile network coverage depends on the operator's network signal strength, and the packet loss rate of data transmission is within 5%.

[0040] The control module comprises: The charging control unit adjusts the charger output parameters, such as charging voltage and charging current, in real time according to the warning signal and the current status of the lithium battery to prevent overcharging and ensure the safety and efficiency of the charging process; The discharge control unit, when detecting abnormal conditions during the discharge of lithium batteries, promptly cuts off the discharge circuit or adjusts the discharge power to avoid damage to the lithium batteries caused by over-discharge, while ensuring the normal operation of the load; The heat dissipation control unit is linked with the temperature sensor and the heat dissipation device (such as fan, liquid cooling system). When the temperature of the lithium battery exceeds the set threshold, the heat dissipation device is automatically started to cool down the battery, so as to control the temperature within a reasonable range and improve the service life and performance of the lithium battery. The emergency handling unit initiates emergency protection measures, such as triggering the fire extinguishing device and cutting off the main power switch, to ensure the safety of personnel and equipment in the event of a serious fault or emergency, such as thermal runaway.

[0041] In the present invention, the data acquisition module includes: Voltage sensor, used to accurately measure the single cell voltage and total voltage of lithium batteries, with a measurement accuracy within ±0.1%, and has good anti-interference ability, and can work stably in complex electromagnetic environments; The current sensor can monitor the charge and discharge current of the lithium battery in real time. The measurement range covers the normal operating current range of the lithium battery and the overcurrent situation in a short period of time. The measurement error does not exceed ±0.5%, and it can respond quickly to current changes. Temperature sensors are located in key parts of lithium batteries, such as the surface of the battery cell and the tabs. The measurement temperature range is -40°C to +80°C with an accuracy of ±0.5°C, which can accurately reflect the temperature changes of lithium batteries. The internal resistance measurement unit uses the AC injection method or the DC discharge method to accurately measure the internal resistance of the lithium battery. The measurement frequency is at least once per hour, and the repeatability error of the measurement result is within ±5%; The fuel gauge accurately monitors the remaining power of the lithium battery, using the coulomb counting method or other high-precision power estimation algorithms, with a power estimation error within ±3%.

[0042] In the present invention, the monitoring and early warning system has good system integration and compatibility, and can be seamlessly connected with lithium battery energy storage systems of different types, specifications and brands and other related power equipment and monitoring systems to achieve data sharing and interaction without affecting the normal operation and performance of the original system.

[0043] In the present invention, the monitoring and early warning system has a self-diagnosis function, and can regularly detect and diagnose faults of its own hardware equipment (such as sensors, communication modules) and software programs. When a fault is found, it automatically locates and records the fault, and attempts to self-recover by restarting, switching to backup equipment or repairing the software to ensure the continuous and stable operation of the system. The self-diagnosis cycle of the system does not exceed 24 hours, and the self-recovery success rate is above 80%.

[0044] In the present invention, the monitoring and early warning system includes a data storage module for storing the collected lithium battery operating parameters, analysis results, early warning information and system operation log data. The data storage time is not less than 5 years, and it has data backup and recovery functions. At the same time, it provides a convenient and fast historical record query interface. Users can query and export historical data according to time and parameter type conditions to facilitate data analysis and fault tracing.

[0045] In the present invention, the monitoring and early warning system is equipped with a human-machine interface (HMI) to display the real-time lithium battery operating status, monitoring data, early warning information and system operation prompts. The HMI interface is concise and intuitive, easy to operate, supports touch screen operation and multi-language display, and users can set system parameters, adjust thresholds, and query historical data through the HMI. At the same time, the HMI also has a permission management function, and users of different levels have different operating permissions to ensure the security and reliability of the system.

[0046] The present invention also discloses a method for a monitoring and early warning system using lithium battery energy storage, comprising the following steps: Installation and configuration: Install the various sensors in the data acquisition module correctly at the corresponding positions of the lithium battery to ensure that the various operating parameters can be accurately collected. Configure the communication module to establish an effective connection with the remote monitoring terminal or cloud platform. Set the threshold and warning mode of the early warning module, as well as the relevant parameters of the control module.

[0047] Data acquisition and transmission: The data acquisition module collects the voltage, current, temperature, internal resistance and power status parameters of the lithium battery in real time, and transmits these data to the remote monitoring terminal or cloud platform through the communication module, and also transmits them to the data analysis module.

[0048] Data analysis and evaluation: The data preprocessing unit in the data analysis module processes the collected raw data to remove abnormal data and interference signals. The state evaluation algorithm unit uses formula algorithms to evaluate and predict the health status, remaining service life, and charge and discharge status of lithium batteries. The battery health status comprehensive evaluation index formula, temperature change rate warning formula, and remaining service life prediction correction formula are used for relevant calculations and analysis. The fault diagnosis unit diagnoses potential faults and locates the fault location based on historical fault data and real-time operating parameters.

[0049] Early warning and control: When the data analysis module evaluates that the operating status of the lithium battery exceeds the preset safety threshold range, the early warning module issues an early warning signal of the corresponding level. The control module takes corresponding control measures according to the level of the early warning signal, such as adjusting the charging or discharging strategy, starting or shutting down the heat dissipation device.

[0050] Data storage and query: The data storage module stores the collected lithium battery operating parameters, analysis results, warning information, and system operation log data. Users can query and export historical data according to time and parameter type conditions through the human-computer interaction interface to perform data analysis and fault tracing.

[0051] System maintenance and update: Regularly maintain the monitoring and early warning system, including checking the accuracy of sensors and the stability of communication modules. Update and upgrade the system according to actual usage and technological development to improve the performance and functionality of the system.

[0052] The above are only preferred specific implementation modes of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can replace or change the technical solution and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A monitoring and early warning system for lithium battery energy storage, characterized in that: include: Data acquisition module, used to collect various operating parameters of lithium batteries in real time, including voltage, current, temperature, internal resistance and power status; A data analysis module, connected to the data acquisition module, receives and analyzes the operating parameters, and evaluates the operating status of the lithium battery through a preset algorithm and model; An early warning module is connected to the data analysis module, and when the data analysis module evaluates that the operating state of the lithium battery exceeds a preset safety threshold range, an early warning signal of a corresponding level is issued; Communication module, used to transmit the collected operating parameters, analysis results and warning information to the remote monitoring terminal or cloud platform to achieve remote monitoring and management; A control module, interacting with the warning module and the communication module, and taking corresponding control measures according to the level of the warning signal, including adjusting the charging or discharging strategy, and starting or shutting down the heat dissipation device; Introduce the comprehensive evaluation index formula of battery health status: ,in Indicates the battery health status. Indicates the current battery capacity. Indicates the rated battery capacity, Indicates the current internal resistance of the battery. Indicates the internal resistance of a new battery. Indicates the current battery energy. represents the initial battery energy, , , is the weight coefficient; Introduce the temperature change rate warning formula: ,in represents the rate of temperature change, Indicates the current temperature. Indicates the temperature at the last moment. Indicates a time interval. When the set threshold is exceeded, early warning of thermal runaway risk is given; Introduce the remaining service life prediction correction formula: ,in Indicates the remaining useful life. is the initial prediction value based on the basic algorithm, The i-th factor affecting the remaining life includes the number of charge and discharge cycles, temperature history data, and current fluctuation. is the weight coefficient of the corresponding factor, is the correction factor; The data analysis module includes: The data preprocessing unit performs filtering, denoising, and calibration preprocessing operations on the collected original operating parameters to remove abnormal data and interference signals; The state assessment algorithm unit uses a machine learning algorithm or an algorithm based on a physical model to assess and predict the health state SOH, remaining service life RUL, and current charge and discharge state of the lithium battery based on preprocessed data. The assessment error of the health state is within ±5%, and the prediction error of the remaining service life is within ±10%. The fault diagnosis unit uses a pattern recognition algorithm to diagnose whether the lithium battery has potential faults based on historical fault data and real-time operating parameters, and locates the location of the fault. The fault diagnosis accuracy rate is over 90%; The early warning module comprises: The threshold setting unit sets different levels of safety thresholds for operating parameters according to the type, specification and application scenario of the lithium battery, including normal range, warning range and danger range; The warning signal generation unit generates a warning signal of a corresponding level when the operating status parameter evaluated by the data analysis module exceeds the warning range. The warning signal includes a sound alarm, flashing lights, and SMS notifications, and different levels of warning signals have distinguishability; The warning level adjustment unit dynamically adjusts the level of the warning signal according to the changing trend and severity of the lithium battery operating status to ensure the timeliness and accuracy of the warning; The communication module comprises: Wired communication interface, supporting RS485, Ethernet common wired communication protocols, used to connect with local monitoring equipment or short-distance data transmission network, the data transmission rate is not less than 10Mbps; The wireless communication unit uses Bluetooth, Wi-Fi, ZigBee or mobile network wireless communication technology to wirelessly connect the monitoring and early warning system with the remote monitoring terminal or cloud platform to achieve remote data transmission and monitoring. The transmission distance of wireless communication in open space is not less than 10 meters for Bluetooth transmission and not less than 50 meters for Wi-Fi transmission; The control module comprises: The charging control unit adjusts the output parameters of the charger, including charging voltage and charging current, in real time according to the warning signal and the current status of the lithium battery; The discharge control unit cuts off the discharge circuit or adjusts the discharge power when an abnormal situation is detected during the discharge process of the lithium battery; The heat dissipation control unit is linked with the temperature sensor and the heat dissipation device, including the fan and the liquid cooling system. When the temperature of the lithium battery exceeds the set threshold, the heat dissipation device is automatically started to cool down; The emergency handling unit initiates emergency protection measures, including triggering the fire extinguishing device and cutting off the main power switch, in the event of a serious failure or emergency, including thermal runaway.

2. A monitoring and early warning system for lithium battery energy storage according to claim 1, characterized in that: The data acquisition module comprises: Voltage sensor, used to measure the single cell voltage and total voltage of lithium battery, with measurement accuracy within ±0.1%; Current sensor, real-time monitoring of the charge and discharge current of lithium batteries. The measurement range covers the normal working current range of lithium batteries and overcurrent conditions in a short period of time, and the measurement error does not exceed ±0.5%; Temperature sensors are located in key parts of lithium batteries, including the cell surface and the tabs. The measurement temperature range is -40°C to +80°C with an accuracy of ±0.5°C. The internal resistance measurement unit uses the AC injection method or the DC discharge method to accurately measure the internal resistance of the lithium battery. The measurement frequency is at least once per hour, and the repeatability error of the measurement result is within ±5%; The fuel gauge monitors the remaining power of the lithium battery and estimates the power using the coulomb counting method. The power estimation error is within ±3%.

3. A monitoring and early warning system for lithium battery energy storage according to claim 1, characterized in that: The monitoring and early warning system seamlessly connects with lithium battery energy storage systems of different types, specifications and brands, as well as power equipment and monitoring systems, to achieve data sharing and interaction without affecting the normal operation and performance of the original system.

4. A monitoring and early warning system for lithium battery energy storage according to claim 1, characterized in that: The monitoring and early warning system has a self-diagnosis function, and regularly detects and diagnoses faults of its own hardware equipment, including sensors, communication modules and software programs. When a fault is found, it automatically locates and records the fault, and attempts to self-recover by restarting, switching to backup equipment or software repair. The system's self-diagnosis cycle does not exceed 24 hours, and the self-recovery success rate is above 80%.

5. A monitoring and early warning system for lithium battery energy storage according to claim 1, characterized in that: The monitoring and early warning system includes a data storage module for storing the collected lithium battery operating parameters, analysis results, early warning information and system operation log data. The data storage time is not less than 5 years, and it has data backup and recovery functions. At the same time, it provides a historical record query interface, and users can query and export historical data according to time and parameter type conditions.

6. A monitoring and early warning system for lithium battery energy storage according to claim 1, characterized in that: The monitoring and early warning system is equipped with a human-machine interaction interface HMI, which displays real-time lithium battery operating status, monitoring data, early warning information and system operation prompts. The HMI interface supports touch screen operation and multi-language display. Users can set system parameters, adjust thresholds, and query historical data through the HMI. At the same time, the HMI also has a permission management function. Users of different levels have different operating permissions to ensure the security and reliability of the system.

7. A method for using a monitoring and early warning system for lithium battery energy storage according to any one of claims 1 to 6, characterized in that: The following steps are involved: Installation and configuration: correctly install the various sensors in the data acquisition module at the corresponding positions of the lithium battery to ensure accurate collection of various operating parameters. Configure the communication module to establish an effective connection with the remote monitoring terminal or cloud platform, set the threshold and warning mode of the early warning module, and the relevant parameters of the control module; Data acquisition and transmission: The data acquisition module collects the voltage, current, temperature, internal resistance and power status parameters of the lithium battery in real time, and transmits these data to the remote monitoring terminal or cloud platform through the communication module, and also transmits them to the data analysis module; Data analysis and evaluation: The data preprocessing unit in the data analysis module processes the collected raw data to remove abnormal data and interference signals. The state evaluation algorithm unit uses formula algorithms to evaluate and predict the health status, remaining service life, and charging and discharging status of the lithium battery. The battery health status comprehensive evaluation index formula, temperature change rate warning formula, and remaining service life prediction correction formula are used for relevant calculations and analysis. The fault diagnosis unit diagnoses potential faults and locates the fault location based on historical fault data and real-time operating parameters. Early warning and control: When the data analysis module evaluates that the operating status of the lithium battery exceeds the preset safety threshold range, the early warning module sends out an early warning signal of the corresponding level, and the control module takes corresponding control measures according to the level of the early warning signal, including adjusting the charging or discharging strategy, starting or shutting down the heat dissipation device; Data storage and query: The data storage module stores the collected lithium battery operating parameters, analysis results, warning information and system operation log data. Users can query and export historical data according to time and parameter type conditions through the human-computer interaction interface to perform data analysis and fault tracing; System maintenance and update: Regularly maintain the monitoring and early warning system, including checking the accuracy of sensors and the stability of communication modules. Update and upgrade the system according to actual usage and technological development to improve system performance and functionality.

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