Thermal safety management system and method for battery energy storage

Abstract

The present invention relates to the field of battery control management technology, and in particular to a thermal safety management system and method for battery energy storage. The method comprises the following steps: obtaining a battery energy storage device; dividing the battery energy storage device into battery groups to generate a set of energy storage battery groups; detecting the internal temperature of the battery groups of the energy storage battery group set to obtain the internal temperature of the battery groups; performing quantitative statistics on the temperature values ​​of the internal temperature of the battery groups to generate battery group temperature statistics; performing temperature anomaly judgment on the battery group temperature statistics, and marking the battery groups to obtain temperature abnormal battery groups. The present invention realizes battery cell segmentation monitoring of the battery energy storage device through data processing technology, pattern recognition technology and deep learning technology, and evaluates the degree of thermal runaway of the battery by monitoring multiple parameters of the energy storage battery, thereby realizing dynamic thermal safety control of the battery energy storage device, thereby improving the thermal safety management efficiency of the battery energy storage.

Description

Technical Field

[0001] The present invention relates to the technical field of battery control management, and in particular to a thermal safety management system and method for battery energy storage. Background Art

[0002] Early energy storage batteries focused on energy density and cycle life, but with the application of energy storage batteries in electric vehicles and large-scale energy storage systems, thermal safety issues have gradually become the focus of research; energy storage batteries generate heat during the charging and discharging process. If the temperature is not properly controlled, it will lead to battery performance degradation or even thermal runaway, causing safety accidents; therefore, energy storage battery thermal management technology came into being, aiming to control battery temperature through effective heat exchange means to ensure safe operation of the battery; energy storage battery thermal management technology requires monitoring the battery operating status according to the battery management system and performing graded thermal safety management. However, the existing thermal safety management technology for battery energy storage fails to monitor the battery cells of the battery energy storage device, making it difficult to accurately perform thermal management of the battery cells; and fails to evaluate the degree of thermal runaway of the battery by monitoring multiple parameters of the energy storage battery, resulting in low timeliness and efficiency of thermal safety management of battery energy storage. Summary of the invention

[0003] Based on this, it is necessary to provide a thermal safety management system and method for battery energy storage to solve at least one of the above technical problems.

[0004] To achieve the above object, a thermal safety management method for battery energy storage is provided, the method comprising the following steps: Step S1: obtaining a battery energy storage device; dividing the battery energy storage device into battery groups to generate a set of energy storage battery groups; detecting the internal temperature of the battery groups of the set of energy storage battery groups to obtain the internal temperature of the battery groups; Step S2: quantify and count the temperature values ​​inside the battery pack to generate battery pack temperature statistics; determine the temperature anomaly of the battery pack temperature statistics and mark the battery pack to obtain a battery pack with abnormal temperature; perform battery cell internal resistance detection on the battery pack with abnormal temperature to generate a battery cell internal resistance value; perform battery pack diffusion gas monitoring on the battery pack with abnormal temperature to obtain diffusion gas characteristics; Step S3: Record the change of the internal resistance of the battery cell to obtain the internal resistance change data; perform temperature abnormality detection on the temperature abnormal battery pack according to the internal resistance change data to generate the temperature abnormality change data; evaluate the degree of thermal runaway of the battery based on the diffusion gas characteristics and the temperature abnormality change data to obtain the degree of thermal runaway of the battery; perform dynamic thermal safety control on the temperature abnormal battery pack according to the degree of thermal runaway of the battery to generate thermal safety control measures; Step S4: monitor the battery energy storage device in real time to obtain real-time monitoring data of the battery; perform thermal runaway warning on the real-time monitoring data of the battery to generate a thermal runaway warning signal; and perform thermal safety control measures on the battery energy storage device based on the thermal runaway warning signal to complete the thermal safety management operation of the battery energy storage.

[0005] The present invention obtains a battery energy storage device and divides it into battery groups to generate a collection of energy storage battery groups, thereby having a clear understanding of the structure of the battery energy storage device and providing a basis for subsequent temperature detection and abnormal judgment; the internal temperature of the battery group of the energy storage battery group collection is detected and the internal temperature of the battery group is obtained, providing an accurate data basis for temperature value quantification statistics and abnormal judgment, thereby ensuring the safe operation of the battery energy storage device. The temperature value of the internal temperature of the battery group is quantified and statistics are performed to clarify the temperature distribution of the battery group; the temperature abnormality judgment is performed on the battery group temperature statistics, and the battery group is marked to obtain a temperature abnormal battery group, which can timely discover the safety hazards existing in the battery energy storage device; the battery cell internal resistance detection and battery group diffusion gas monitoring are performed on the temperature abnormal battery group, and the battery cell internal resistance value and diffusion gas characteristics are generated, which provide the necessary parameters for the evaluation of the degree of thermal runaway of the battery and enhance the safety monitoring capability of the battery energy storage device. The internal resistance value of the battery cell is recorded to change the battery internal resistance, so as to monitor the performance change of the battery cell and provide data support for the subsequent abnormal temperature change detection; the abnormal temperature change of the temperature abnormal battery pack is detected according to the internal resistance change data, and the abnormal temperature change data is generated to accurately grasp the temperature dynamics of the battery pack and provide real-time data for the evaluation of the degree of thermal runaway of the battery; the degree of thermal runaway of the battery is evaluated based on the diffusion gas characteristics and the abnormal temperature change data, which can scientifically evaluate the safety status of the battery energy storage device and provide a basis for dynamic thermal safety control; the temperature abnormal battery pack is dynamically controlled according to the degree of thermal runaway of the battery, and thermal safety control measures are generated to ensure that the battery energy storage device can be handled promptly and effectively under abnormal conditions, thereby improving the safety performance of the battery energy storage device. Real-time monitoring of the battery energy storage device is performed to obtain real-time monitoring data of the battery, and the operating status of the battery energy storage device is continuously tracked to provide real-time data for thermal runaway warning; thermal runaway warning is performed on the real-time monitoring data of the battery, and a warning can be issued in time to remind relevant personnel to take action; thermal safety control measures are executed on the battery energy storage device based on the thermal runaway warning signal to complete the thermal safety management of the battery energy storage, ensuring that the battery energy storage device can be effectively controlled and processed when facing the risk of thermal runaway, and ensuring the safe and stable operation of the battery energy storage device. Therefore, the present invention realizes the subdivision monitoring of the battery unit of the battery energy storage device through data processing technology, pattern recognition technology and deep learning technology, and evaluates the degree of thermal runaway of the battery by monitoring multiple parameters of the energy storage battery, so as to realize dynamic thermal safety control of the battery energy storage device, thereby improving the thermal safety management efficiency of the battery energy storage.

[0006] Preferably, step S1 comprises the following steps: Step S11: Acquire a battery energy storage device; Step S12: determining the energy storage battery area of ​​the battery energy storage device to obtain the energy storage battery area; calculating the area of ​​the energy storage battery area to generate battery area data; Step S13: Divide the battery area data into multiple battery areas to obtain battery group division data; encode and merge the battery group division data to obtain an energy storage battery group set; Step S14: Detect the battery pack area temperature of the energy storage battery pack set to obtain the battery pack area temperature; extract the internal temperature of the battery pack area temperature to obtain the internal temperature of the battery pack.

[0007] The acquisition of the battery energy storage device in the present invention is the starting point of the entire battery energy storage management process, ensuring the direct control of the battery energy storage device and the basis for subsequent operations; the comprehensive management and monitoring of the battery energy storage device provides the necessary prerequisites for subsequent operations such as area determination and temperature detection; the energy storage battery area of ​​the battery energy storage device is determined, and the energy storage battery area is obtained, which provides a clear definition for the spatial layout of the battery energy storage device and accurately identifies and manages each battery area; the area of ​​the energy storage battery area is measured, and the battery area area data is generated, which provides an important parameter basis for the subsequent battery group division and thermal management; the battery area area data is divided into multiple component battery areas, and the battery group division data is obtained to achieve battery The refined management of the internal structure of the energy storage device enables each battery area to be individually identified and monitored; the battery group division data is encoded and merged to obtain a storage battery group set, and the information of each battery area is integrated by encoding to form a complete battery energy storage device data set; the battery group area temperature of the energy storage battery group set is detected, and the battery group area temperature is obtained, which provides basic data for temperature monitoring of the battery energy storage device and ensures real-time control of the thermal state of the battery energy storage device; the battery group area temperature is extracted from the group temperature, and the internal temperature of the battery group is obtained, which further refines the temperature data, so that the internal temperature of each battery group can be accurately monitored, providing accurate temperature data for subsequent temperature abnormality judgment and thermal safety control.

[0008] Preferably, step S2 comprises the following steps: Step S21: quantifying the temperature values ​​within each battery pack to obtain the temperature values ​​within each battery pack; summarizing and counting the temperature values ​​within each battery pack to generate battery pack temperature statistics; Step S22: mapping the temperature characteristics of each battery pack of the energy storage battery pack set based on the battery pack temperature statistics to obtain the temperature mapping characteristics of each group; generating a temperature heat map for the temperature mapping characteristics of each group to obtain the battery pack temperature heat map; Step S23: determining temperature anomalies on the battery pack temperature thermodynamic map to obtain abnormal blocks on the thermodynamic map; marking the energy storage battery packs based on the abnormal blocks on the thermodynamic map to obtain abnormal temperature battery packs; Step S24: monitoring the battery cell voltage of the battery pack with abnormal temperature to obtain the battery cell voltage value; monitoring the battery cell current of the battery pack with abnormal temperature to obtain the battery cell current value; Step S25: Calculating the internal resistance of the battery cell based on the battery cell voltage value and the battery cell current value to generate the internal resistance value of the battery cell; Step S26: monitoring the battery pack diffusion gas for the battery pack with abnormal temperature to obtain the diffusion gas characteristics.

[0009] The present invention quantifies the temperature values ​​within each battery pack to obtain the temperature values ​​within each group, providing accurate data support for the temperature monitoring of the battery pack, so that the temperature status of each battery pack can be analyzed in detail; the temperature values ​​within each group are summarized and counted to generate battery pack temperature statistics, and the temperature data of all battery packs are specifically summarized to provide comprehensive temperature distribution information for subsequent temperature feature mapping and abnormality judgment; based on the battery pack temperature statistics, the temperature characteristics of each battery pack of the energy storage battery pack set are mapped, so that the temperature data is converted into feature information, which provides a basis for the generation of temperature heat maps; the temperature heat map is generated for the temperature mapping characteristics of each group to obtain a battery pack temperature heat map, and the temperature distribution of the battery pack is displayed in a visual manner, so that the temperature abnormality area is more intuitive and easy to identify; the temperature abnormality judgment is performed on the battery pack temperature heat map, and the temperature area with problems is quickly located by analyzing the abnormal blocks of the heat map; based on The abnormal block of the thermal map marks the battery pack of the energy storage battery pack, provides a clear abnormal battery pack identification for subsequent battery cell monitoring and safety control, and improves the safety management efficiency of the battery energy storage device; the battery cell voltage is monitored for the battery pack with abnormal temperature to clearly evaluate the working status of the battery cell; the battery cell current is monitored for the battery pack with abnormal temperature, which provides data support for the current characteristic analysis of the battery cell, so as to further diagnose the abnormal situation of the battery cell; the battery cell internal resistance is calculated based on the battery cell voltage value and the battery cell current value, and the internal resistance of the battery cell is obtained by calculation, which provides key parameters for the health status evaluation and performance prediction of the battery cell, and timely discovers the abnormal problems of the battery cell; the battery pack diffusion gas is monitored for the battery pack with abnormal temperature. Specifically, the monitoring of the diffusion gas inside the battery pack can analyze the chemical reaction state of the battery pack, and provide important information for the thermal runaway risk assessment of the battery pack, thereby preventing the thermal runaway event of the battery pack.

[0010] Preferably, step S26 includes the following steps: Step S261: monitoring the battery pack diffusion condition of the battery pack with abnormal temperature to obtain the diffusion monitoring condition; identifying the diffusion gas based on the diffusion monitoring condition to generate diffusion gas condition data; Step S262: performing gas color judgment on the diffused gas condition data to obtain diffused gas color; performing gas concentration determination on the diffused gas condition data based on the diffused gas color to generate a gas concentration state; Step S263: performing gas composition identification on the diffused gas condition data according to the gas concentration state to obtain gas composition data; performing diffusion pattern identification on the gas composition data to generate a gas diffusion pattern; performing gas diffusion range detection on the gas diffusion pattern to obtain a gas diffusion range; Step S264: Integrate the gas concentration state, gas diffusion mode and gas diffusion range into the battery pack diffusion gas characteristics to obtain the diffusion gas characteristics.

[0011] The present invention monitors the diffusion of battery packs with abnormal temperature, can track the diffusion changes inside the battery pack in real time, and provide key information for battery safety monitoring; identifies the diffusion gas for the diffusion monitoring, and can accurately capture the chemical changes inside the battery pack by identifying the diffusion gas; judges the gas color of the diffusion gas situation data, and preliminarily judges the nature and chemical composition of the gas by analyzing the gas color; determines the gas concentration of the diffusion gas situation data based on the diffusion gas color, and can evaluate the activity of the chemical reaction inside the battery pack by determining the gas concentration; identifies the gas composition of the diffusion gas situation data according to the gas concentration state, and can deeply understand the chemical reaction process inside the battery pack by analyzing the gas composition; identifies the diffusion pattern of the gas composition data, and clarifies the propagation path of the gas inside the battery pack by identifying the gas diffusion pattern; detects the gas diffusion range of the gas diffusion pattern, and can evaluate the safety hazard area inside the battery pack by detecting the gas diffusion range; integrates the gas concentration state, gas diffusion pattern and gas diffusion range into the battery pack diffusion gas characteristics to obtain the diffusion gas characteristics. This step forms a comprehensive description of the battery pack diffusion gas characteristics by integrating key gas parameters, and provides data support for safety monitoring and risk assessment of the battery pack.

[0012] Preferably, step S3 comprises the following steps: Step S31: continuously monitoring the internal resistance of the battery cell to obtain battery internal resistance monitoring data; marking the monitoring time period of the battery internal resistance monitoring data to generate an internal resistance monitoring time period; Step S32: recording the resistance value of the internal resistance of the battery cell in the initial period based on the internal resistance monitoring period to obtain the resistance value in the initial period; recording the resistance value of the internal resistance of the battery cell in the final period based on the internal resistance monitoring period to obtain the resistance value in the final period; Step S33: subtract the internal resistance value in the final period from the internal resistance value in the initial period to generate internal resistance change data; Step S34: performing temperature abnormality detection on the temperature abnormality battery pack according to the internal resistance change data, and generating temperature abnormality change data; Step S35: evaluating the degree of thermal runaway of the battery based on the diffusion gas characteristics and the abnormal temperature change data to obtain the degree of thermal runaway of the battery; Step S36: Perform dynamic thermal safety control on the battery pack with abnormal temperature according to the degree of thermal runaway of the battery, and generate thermal safety control measures.

[0013] The present invention continuously monitors the internal resistance of a battery cell, can track the change of the internal resistance of the battery cell in real time, mark the monitoring time period for the battery internal resistance monitoring data, and identify the trend of the change of battery performance by marking the internal resistance data of different time periods; based on the internal resistance monitoring time period, the resistance value of the battery cell in the initial time period is recorded, which provides a reference point for the baseline of the battery performance and clearly evaluates the starting state of the battery performance; based on the internal resistance monitoring time period, the resistance value of the battery cell in the final time period is recorded, which provides data for the final state of the battery performance, thereby evaluating the change and degradation of the battery performance. The resistance value in the final time period is subtracted from the resistance value in the initial time period. By calculating the change in internal resistance, the degree of degradation of battery performance can be quantified, providing a key indicator for the evaluation of battery health status; abnormal temperature changes are detected for temperature-abnormal battery packs based on internal resistance change data, and abnormal temperature changes of battery packs can be identified by analyzing the relationship between internal resistance change and temperature anomaly; the degree of battery thermal runaway is evaluated based on diffusion gas characteristics and temperature anomaly change data, and the risk of battery thermal runaway can be accurately evaluated by comprehensively considering gas diffusion and temperature anomaly data; dynamic thermal safety control is performed on temperature-abnormal battery packs based on the degree of battery thermal runaway. Specifically, by implementing corresponding thermal safety control measures based on the assessment results of thermal runaway risk, the occurrence of battery thermal runaway events can be prevented and controlled, and the safe and stable operation of battery energy storage devices can be ensured.

[0014] Preferably, step S34 includes the following steps: Step S341: performing frequency domain conversion on the internal resistance change data to obtain internal resistance change frequency data; performing frequency jitter feature recognition on the internal resistance change frequency data to generate internal resistance frequency jitter features; Step S342: performing jitter time mapping on the internal resistance monitoring time period according to the internal resistance frequency jitter characteristics to obtain the internal resistance frequency jitter time; Step S343: performing temperature pattern recognition on the battery pack with abnormal temperature based on the internal resistance frequency jitter time to obtain a frequency jitter-temperature pattern; performing temperature sensitivity judgment on the battery pack based on the frequency jitter-temperature pattern to generate temperature sensitivity data; Step S344: recording the duration of abnormal temperature change of the battery pack with abnormal temperature according to the temperature sensitivity data to obtain the duration of abnormal temperature change; monitoring the abnormal temperature change value of the battery pack with abnormal temperature based on the temperature sensitivity data to obtain the abnormal temperature change degree value; Step S345: integrating the abnormal temperature change duration and the abnormal temperature change degree value into the abnormal temperature change characteristics to generate abnormal temperature change data.

[0015] The present invention performs frequency domain conversion on the internal resistance change data, and by converting the time domain data into frequency domain data, it can reveal the periodic characteristics of the battery internal resistance change; the frequency jitter feature recognition is performed on the internal resistance change frequency data, and by identifying the frequency jitter in the internal resistance change, it can capture the subtle dynamics of the battery performance change; the jitter time mapping is performed on the internal resistance monitoring time period according to the internal resistance frequency jitter feature, and by associating the frequency jitter feature with the specific time point, it can determine the specific moment of the battery performance change, providing accurate time information for real-time monitoring and early warning of the battery status; the temperature pattern recognition is performed on the temperature-abnormal battery pack based on the internal resistance frequency jitter time, and by analyzing the relationship between the internal resistance frequency jitter and the temperature change, the temperature change pattern of the battery pack can be identified, providing an important reference basis for battery thermal management; the frequency jitter The dynamic-temperature mode is used to judge the temperature sensitivity of the battery pack. By evaluating the sensitivity of the battery pack to temperature changes, key parameters can be provided for the thermal stability evaluation of the battery pack. The duration of abnormal temperature changes of the temperature-abnormal battery pack is recorded according to the temperature sensitivity data. By recording the duration of abnormal temperature, the stability and safety of the battery pack under abnormal conditions can be evaluated. The temperature abnormality change value of the temperature-abnormal battery pack is monitored based on the temperature sensitivity data, and by monitoring the degree of abnormal temperature change, the severity of the temperature abnormality of the battery pack can be quantified. The duration of abnormal temperature change and the degree of abnormal temperature change are integrated into the temperature abnormality change characteristics. By integrating the duration and degree of temperature abnormality, the temperature abnormality characteristics of the battery pack can be fully described, thereby enhancing the temperature abnormality management capability of the battery energy storage device.

[0016] Preferably, step S35 includes the following steps: Step S351: determining the gas concentration of the diffused gas feature to obtain the diffused gas concentration; identifying the diffusion mode type of the diffused gas feature to obtain the gas diffusion mode type; Step S352: performing gas diffusion space range detection on the diffusion gas characteristics based on the diffusion gas concentration and the gas diffusion mode type, and generating diffusion space distribution data; Step S353: performing gas diffusion influence weight matching on the battery pack with abnormal temperature according to the diffusion space distribution data, and generating a gas diffusion influence weight value; Step S354: determining the abnormal temperature change period of the abnormal temperature change data to obtain the abnormal temperature change period; calculating the abnormal temperature deviation value of the abnormal temperature change data to generate the abnormal temperature deviation value; Step S355: performing temperature abnormality change impact weight matching on the temperature abnormal battery pack based on the abnormal temperature change cycle and the temperature abnormality deviation value, and generating a temperature change impact weight value; Step S356: Calculate the battery thermal runaway weight according to the gas diffusion influence weight value and the temperature change influence weight value to obtain the battery thermal runaway weight scoring data; divide the battery thermal runaway weight scoring data into runaway degrees to obtain the battery thermal runaway degree.

[0017] The present invention determines the gas concentration of the diffuse gas characteristics, and can accurately quantify the concentration level of the gas; identifies the diffusion mode type of the diffuse gas characteristics, and by identifying the gas diffusion mode, clarifies the propagation characteristics of the gas in the battery pack; detects the gas diffusion space range of the diffuse gas characteristics based on the diffuse gas concentration and the gas diffusion mode type, and by combining the gas concentration and the diffusion mode, can determine the spatial distribution of the gas in the battery pack; matches the gas diffusion degree influence weight of the temperature abnormal battery pack according to the diffusion space distribution data, and by matching the spatial distribution of gas diffusion with the temperature abnormality of the battery pack, can quantify the influence of gas diffusion on the thermal safety of the battery, and provide important weight data for the risk assessment of thermal runaway of the battery; determines the abnormal temperature change period of the abnormal temperature change data, and by determining the periodicity of the temperature abnormality, can identify the regularity of the battery temperature abnormality, which is important for predicting and controlling the temperature. The abnormal temperature deviation value is calculated for the abnormal temperature change data to generate the abnormal temperature deviation value. By calculating the temperature deviation, the degree of temperature abnormality can be quantified. The abnormal temperature change impact weight is matched for the abnormal temperature battery pack based on the abnormal temperature change cycle and the abnormal temperature deviation value. By combining the cycle and deviation of the abnormal temperature, the comprehensive impact of the abnormal temperature on the battery performance can be evaluated, and the temperature weight data is provided for the risk assessment of battery thermal runaway. The battery thermal runaway weight is calculated according to the gas diffusion impact weight value and the temperature change impact weight value. Taking into account the impact of gas diffusion and temperature change, the comprehensive risk score of battery thermal runaway can be obtained, which provides a quantitative risk assessment for battery safety management. The battery thermal runaway weight score data is divided into the degree of out-of-control, which can provide clear guidance for the safe management and maintenance of the battery pack and ensure the safe operation of the battery energy storage device.

[0018] Preferably, step S36 includes the following steps: Step S361: Compare the battery thermal runaway degree with a preset thermal runaway degree index. If the battery thermal runaway degree is greater than the preset thermal runaway degree index, mark it as the battery thermal runaway severity. Step S362: locating the thermal runaway battery cells of the battery pack with abnormal temperature based on the severity of the battery thermal runaway, and generating a thermal runaway battery cell area; Step S363: Cutting off the battery cell circuit in the thermal runaway battery cell area and generating circuit cutting measures; Step S364: evacuating the thermal runaway battery cell area with diffusion gas, and generating diffusion gas evacuation measures; Step S365: activating a battery cooling device for the thermal runaway battery cell area and generating cooling device activation measures; Step S366: Integrate the circuit cut-off measures, diffusion gas evacuation measures and cooling device startup measures for thermal safety control to generate thermal safety control measures.

[0019] The present invention compares the degree of thermal runaway of the battery with a preset thermal runaway degree index. If the degree of thermal runaway of the battery is greater than the preset thermal runaway degree index, it is marked as the severity of thermal runaway of the battery. By setting a threshold to judge the thermal runaway risk level of the battery, a clear warning can be provided for battery safety management to ensure that corresponding emergency measures are taken when the risk of thermal runaway of the battery is high. The thermal runaway battery cells of the battery pack with abnormal temperature are located based on the severity of the thermal runaway of the battery. By accurately locating the thermal runaway battery cells, the battery area that needs emergency treatment can be quickly identified. The battery cell circuit of the thermal runaway battery cell area is cut off. By cutting off the circuit connected to the thermal runaway battery cell, the current flow can be stopped immediately to prevent the thermal runaway phenomenon from further spreading and protect other parts of the battery pack from damage. The diffusion gas is evacuated in the thermal runaway battery cell area, and diffusion gas evacuation measures are generated. By evacuating the diffusion gas in the thermal runaway battery cell area, the risk of explosion caused by gas accumulation can be reduced, and the internal pressure of the battery can be reduced, providing additional protection for the safety of the battery pack; the battery cooling device is started in the thermal runaway battery cell area, and cooling device start-up measures are generated. By starting the cooling device to cool the thermal runaway battery cell, the battery temperature can be effectively controlled and reduced, the thermal runaway phenomenon can be prevented from further deteriorating, and the battery pack structure and function can be protected from damage; by comprehensively considering the three measures of circuit cutting, gas evacuation and cooling start-up, a complete set of thermal safety control solutions is formed, which can systematically respond to battery thermal runaway events, minimize the impact of thermal runaway on the battery energy storage device, and ensure the thermal safety of the battery energy storage device.

[0020] Preferably, step S4 comprises the following steps: Step S41: monitoring the state of the energy storage battery of the battery energy storage device in real time to obtain real-time monitoring data of the battery; Step S42: identifying the abnormal battery temperature state of the battery real-time monitoring data to obtain the abnormal battery temperature state; determining the battery thermal runaway mode of the abnormal battery temperature state to generate the battery thermal runaway mode; Step S43: Perform a thermal runaway warning on the battery thermal runaway mode and generate a thermal runaway warning signal; Step S44: based on the thermal runaway warning signal, locate the thermal runaway battery pack of the battery energy storage device to obtain the location information of the thermal runaway battery pack; perform thermal safety control measures on the location information of the thermal runaway battery pack to complete the thermal safety management operation of the battery energy storage.

[0021] The present invention monitors the state of the energy storage battery of the battery energy storage device in real time to obtain the real-time monitoring data of the battery. By continuously collecting the operating state information of the battery energy storage device, it can ensure the real-time grasp of the battery performance and safety state; and timely discover battery abnormalities to provide a data basis, which is a key link in battery safety management; the battery temperature abnormality state is identified based on the real-time monitoring data of the battery, and by analyzing the monitoring data, it can quickly identify whether the battery has temperature abnormalities, providing an early warning for battery thermal safety management; the battery thermal runaway mode is determined for the battery temperature abnormality state, and by determining the thermal runaway mode, the thermal runaway risk of the battery can be accurately evaluated; the battery thermal runaway state is determined based on the battery thermal runaway state. The thermal runaway warning is carried out in the control mode, and by issuing a warning signal, relevant personnel or systems can be notified in time to take emergency measures to prevent the occurrence or further deterioration of thermal runaway events and protect the safety of the battery energy storage device; the thermal runaway battery pack of the battery energy storage device is located based on the thermal runaway warning signal. By accurately locating the thermal runaway battery pack, it can ensure that emergency measures are carried out in a targeted manner and improve the efficiency of responding to thermal runaway events; thermal safety control measures are implemented based on the location information of the thermal runaway battery pack to complete the thermal safety management of battery energy storage. By executing specific thermal safety control measures, thermal runaway events can be effectively controlled and handled to ensure the safe and stable operation of the battery energy storage device.

[0022] In this specification, a thermal safety management system for battery energy storage is provided, which is used to execute the thermal safety management method for battery energy storage described above. The thermal safety management system for battery energy storage includes: The battery energy storage device temperature detection module is used to obtain the battery energy storage device; divide the battery energy storage device into battery groups to generate a set of energy storage battery groups; detect the internal temperature of the battery groups of the energy storage battery group set to obtain the internal temperature of the battery groups; The battery cell abnormality analysis module is used to quantify the temperature value of the internal temperature of the battery pack and generate the battery pack temperature statistics; to judge the temperature abnormality of the battery pack temperature statistics and mark the battery pack to obtain the temperature abnormal battery pack; to detect the battery cell internal resistance of the temperature abnormal battery pack and generate the battery cell internal resistance value; to monitor the battery pack diffusion gas of the temperature abnormal battery pack and obtain the diffusion gas characteristics; The battery thermal safety control module is used to record the change of the internal resistance of the battery unit and obtain the internal resistance change data; detect the abnormal temperature change of the temperature-abnormal battery pack based on the internal resistance change data and generate the abnormal temperature change data; evaluate the degree of thermal runaway of the battery based on the diffusion gas characteristics and the abnormal temperature change data and obtain the degree of thermal runaway of the battery; perform dynamic thermal safety control on the temperature-abnormal battery pack according to the degree of thermal runaway of the battery and generate thermal safety control measures; The thermal runaway warning execution module is used to monitor the battery energy storage device in real time to obtain real-time monitoring data of the battery; to issue a thermal runaway warning to the real-time monitoring data of the battery and generate a thermal runaway warning signal; and to execute thermal safety control measures on the battery energy storage device based on the thermal runaway warning signal to complete the thermal safety management of the battery energy storage.

[0023] The present invention obtains the battery energy storage device and divides it into battery groups through the battery energy storage device temperature detection module, generates a collection of energy storage battery groups, has a clear understanding of the structure of the battery energy storage device, and provides a basis for subsequent temperature detection and abnormal judgment; detects the internal temperature of the battery group of the energy storage battery group collection and obtains the internal temperature of the battery group, which provides an accurate data basis for temperature value quantification statistics and abnormal judgment, thereby ensuring the safe operation of the battery energy storage device. Through the battery cell abnormality analysis module, the temperature value of the internal temperature of the battery group is quantified and statistics are performed to clarify the temperature distribution of the battery group; the temperature abnormality judgment is performed on the battery group temperature statistics, and the battery group is marked to obtain the temperature abnormal battery group, which can timely discover the safety hazards existing in the battery energy storage device; the battery cell internal resistance detection and battery group diffusion gas monitoring are performed on the temperature abnormal battery group, and the battery cell internal resistance value and diffusion gas characteristics are generated, which provide the necessary parameters for the evaluation of the degree of thermal runaway of the battery, and enhance the safety monitoring capability of the battery energy storage device. Through the battery thermal safety control module, the internal resistance value of the battery unit is recorded for the change of the battery internal resistance, so that the performance change of the battery unit can be monitored, providing data support for the subsequent abnormal temperature change detection; the abnormal temperature change of the temperature abnormal battery pack is detected according to the internal resistance change data, and the abnormal temperature change data is generated to accurately grasp the temperature dynamics of the battery pack and provide real-time data for the evaluation of the degree of thermal runaway of the battery; the degree of thermal runaway of the battery is evaluated based on the diffusion gas characteristics and the abnormal temperature change data, which can scientifically evaluate the safety status of the battery energy storage device and provide a basis for dynamic thermal safety control; dynamic thermal safety control is performed on the abnormal temperature battery pack according to the degree of thermal runaway of the battery, and thermal safety control measures are generated to ensure that the battery energy storage device can be handled promptly and effectively under abnormal conditions, thereby improving the safety performance of the battery energy storage device. Through the thermal runaway warning execution module, the battery energy storage device is monitored in real time to obtain real-time monitoring data of the battery, and the operating status of the battery energy storage device is continuously tracked to provide real-time data for thermal runaway warning; thermal runaway warning is performed on the real-time monitoring data of the battery, and a warning can be issued in time to remind relevant personnel to take action; thermal safety control measures are executed on the battery energy storage device based on the thermal runaway warning signal to complete the thermal safety management of the battery energy storage, ensuring that the battery energy storage device can be effectively controlled and processed when facing the risk of thermal runaway, and ensuring the safe and stable operation of the battery energy storage device. Therefore, the present invention realizes the subdivision monitoring of the battery unit of the battery energy storage device through data processing technology, pattern recognition technology and deep learning technology, and evaluates the degree of thermal runaway of the battery by monitoring multiple parameters of the energy storage battery, so as to realize dynamic thermal safety control of the battery energy storage device, thereby improving the thermal safety management efficiency of the battery energy storage. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A schematic flow chart of the steps of a thermal safety management method for battery energy storage; Figure 2 for Figure 1 Detailed implementation steps of step S3 in FIG. Figure 3 for Figure 2 Detailed implementation steps of step S35; The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0025] The technical method of the present invention is described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are 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 technicians in this field without creative work are within the scope of protection of the present invention.

[0026] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0027] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0028] To achieve this, please refer to Figures 1 to 3 , a thermal safety management method for battery energy storage, the method comprising the following steps: Step S1: obtaining a battery energy storage device; dividing the battery energy storage device into battery groups to generate a set of energy storage battery groups; detecting the internal temperature of the battery groups of the set of energy storage battery groups to obtain the internal temperature of the battery groups; Step S2: quantify and count the temperature values ​​inside the battery pack to generate battery pack temperature statistics; determine the temperature anomaly of the battery pack temperature statistics and mark the battery pack to obtain a battery pack with abnormal temperature; perform battery cell internal resistance detection on the battery pack with abnormal temperature to generate a battery cell internal resistance value; perform battery pack diffusion gas monitoring on the battery pack with abnormal temperature to obtain diffusion gas characteristics; Step S3: Record the change of the internal resistance of the battery cell to obtain the internal resistance change data; perform temperature abnormality detection on the temperature abnormal battery pack according to the internal resistance change data to generate the temperature abnormality change data; evaluate the degree of thermal runaway of the battery based on the diffusion gas characteristics and the temperature abnormality change data to obtain the degree of thermal runaway of the battery; perform dynamic thermal safety control on the temperature abnormal battery pack according to the degree of thermal runaway of the battery to generate thermal safety control measures; Step S4: monitor the battery energy storage device in real time to obtain real-time monitoring data of the battery; perform thermal runaway warning on the real-time monitoring data of the battery to generate a thermal runaway warning signal; and perform thermal safety control measures on the battery energy storage device based on the thermal runaway warning signal to complete the thermal safety management operation of the battery energy storage.

[0029] The present invention obtains a battery energy storage device and divides it into battery groups to generate a collection of energy storage battery groups, thereby having a clear understanding of the structure of the battery energy storage device and providing a basis for subsequent temperature detection and abnormal judgment; the internal temperature of the battery group of the energy storage battery group collection is detected and the internal temperature of the battery group is obtained, providing an accurate data basis for temperature value quantification statistics and abnormal judgment, thereby ensuring the safe operation of the battery energy storage device. The temperature value of the internal temperature of the battery group is quantified and statistics are performed to clarify the temperature distribution of the battery group; the temperature abnormality judgment is performed on the battery group temperature statistics, and the battery group is marked to obtain a temperature abnormal battery group, which can timely discover the safety hazards existing in the battery energy storage device; the battery cell internal resistance detection and battery group diffusion gas monitoring are performed on the temperature abnormal battery group, and the battery cell internal resistance value and diffusion gas characteristics are generated, which provide the necessary parameters for the evaluation of the degree of thermal runaway of the battery and enhance the safety monitoring capability of the battery energy storage device. The internal resistance value of the battery cell is recorded to change the battery internal resistance, so as to monitor the performance change of the battery cell and provide data support for the subsequent abnormal temperature change detection; the abnormal temperature change of the temperature abnormal battery pack is detected according to the internal resistance change data, and the abnormal temperature change data is generated to accurately grasp the temperature dynamics of the battery pack and provide real-time data for the evaluation of the degree of thermal runaway of the battery; the degree of thermal runaway of the battery is evaluated based on the diffusion gas characteristics and the abnormal temperature change data, which can scientifically evaluate the safety status of the battery energy storage device and provide a basis for dynamic thermal safety control; the temperature abnormal battery pack is dynamically controlled according to the degree of thermal runaway of the battery, and thermal safety control measures are generated to ensure that the battery energy storage device can be handled promptly and effectively under abnormal conditions, thereby improving the safety performance of the battery energy storage device. Real-time monitoring of the battery energy storage device is performed to obtain real-time monitoring data of the battery, and the operating status of the battery energy storage device is continuously tracked to provide real-time data for thermal runaway warning; thermal runaway warning is performed on the real-time monitoring data of the battery, and a warning can be issued in time to remind relevant personnel to take action; thermal safety control measures are executed on the battery energy storage device based on the thermal runaway warning signal to complete the thermal safety management of the battery energy storage, ensuring that the battery energy storage device can be effectively controlled and processed when facing the risk of thermal runaway, and ensuring the safe and stable operation of the battery energy storage device. Therefore, the present invention realizes the subdivision monitoring of the battery unit of the battery energy storage device through data processing technology, pattern recognition technology and deep learning technology, and evaluates the degree of thermal runaway of the battery by monitoring multiple parameters of the energy storage battery, so as to realize dynamic thermal safety control of the battery energy storage device, thereby improving the thermal safety management efficiency of the battery energy storage.

[0030] In the embodiment of the present invention, reference Figure 1 FIG. 1 is a schematic flow chart of a thermal safety management method for battery energy storage according to the present invention. In this example, the thermal safety management method for battery energy storage includes the following steps: Step S1: obtaining a battery energy storage device; dividing the battery energy storage device into battery groups to generate a set of energy storage battery groups; detecting the internal temperature of the battery groups of the set of energy storage battery groups to obtain the internal temperature of the battery groups; In the embodiment of the present invention, the information of the battery energy storage device is obtained through high-voltage cascade technology, and specifically through power electronic design, a 6-35kV grid-connected voltage can be achieved without passing through a transformer; wherein the energy storage system is a 12.5MW / 25MWh system, consisting of three phases A, B, and C, each phase containing 42 H-bridge power units and 42 battery clusters, a total of 126 H-bridge power units and 126 battery clusters in the three phases, storing a total of 25.288MWh of electricity. The battery energy storage device is divided into battery groups. According to the high-voltage cascade scheme, each battery cluster contains 224 cells connected in series. The specific system electrical structure is similar to high-voltage SVG, consisting of three phases A, B, and C, and each phase contains 42 H-bridge power units and 42 battery clusters. It is divided according to 42 battery clusters per phase, with a total of 126 battery clusters to form an energy storage battery group set. The internal temperature of the battery group of the energy storage battery group set is detected, and the electrochemical impedance spectroscopy (EIS) technology is used to monitor the battery internal resistance, double-layer capacitance and diffusion. As a non-destructive and non-implantable method, EIS avoids the temperature delay phenomenon of using surface temperature sensors. In addition, the internal temperature monitoring technology of lithium batteries based on NTC temperature sensors detects abnormal temperature rise conditions inside the battery in real time and with high precision during the battery operation process. Specifically, multiple temperature probes are fixed at preset positions inside the battery, and each temperature probe is connected to an external temperature recorder through a temperature line. The temperature data of the preset position inside the battery is collected in real time by the external temperature recorder to realize the temperature detection inside the battery, thereby obtaining the internal temperature of the battery group.

[0031] Step S2: quantify and count the temperature values ​​inside the battery pack to generate battery pack temperature statistics; determine the temperature anomaly of the battery pack temperature statistics and mark the battery pack to obtain a battery pack with abnormal temperature; perform battery cell internal resistance detection on the battery pack with abnormal temperature to generate a battery cell internal resistance value; perform battery pack diffusion gas monitoring on the battery pack with abnormal temperature to obtain diffusion gas characteristics; In an embodiment of the present invention, the temperature value of the internal temperature of the battery pack is quantitatively counted. Specifically, the temperature data collected from 24 temperature sensors installed in the battery pack is quantitatively counted through cloud data preprocessing technology; taking the ternary lithium battery pack as an example, each battery module includes 5 parallel single cells to form a parallel unit, and then multiple parallel units are connected in series to form a module, with a total of 91 large single cells connected in series; through data preprocessing, the temperature data of the temperature sensor number corresponding to the battery number in each module is calculated, and the battery pack temperature statistics are obtained by statistics; the battery pack temperature statistics are judged to be abnormal, and the battery pack is marked; specifically, a temperature acquisition abnormality judgment method based on temperature difference calculation is adopted to extract the temperature data TN collected by N temperature sensors within a time period t, calculate the sum SN of the changes in all adjacent temperature data TN collected by each sensor, and based on the sum SN, the calibration parameter K and the set threshold S0, judge the temperature sensor with abnormal temperature acquisition to obtain a temperature abnormal battery pack; perform battery cell internal resistance detection on the temperature abnormal battery pack to generate the battery cell internal resistance value. The four-terminal measurement method is used to detect the internal resistance of the battery cell. This method is based on measuring the voltage drop across the battery and providing a constant test current at the same time. Specifically, a constant current is provided to the battery cell, the voltage drop across the battery is measured, and the internal resistance is calculated using Ohm's law. If the battery voltage drop is 0.2V and the test current is 10A, the internal resistance value is 0.2V / 10A=0.02 ohms. The battery pack diffusion gas is monitored for battery packs with abnormal temperature to obtain the diffusion gas characteristics, and the gas signal monitoring technology is used to evaluate the change in target gas concentration through the gas sensor S2. Specifically, the COMSOL built-in model is used for simulation. Compared with surface temperature monitoring, the gas sensing method can detect battery thermal runaway long before the critical time for thermal runaway propagation. For example, in a 55-gallon cylindrical space, through simulation and experimental verification, the gas sensing method can detect battery thermal runaway in about 85 seconds, while the critical time for thermal runaway propagation is about 710 seconds, and the diffusion gas characteristics are obtained.

[0032] Step S3: Record the change of the internal resistance of the battery cell to obtain the internal resistance change data; perform temperature abnormality detection on the temperature abnormal battery pack according to the internal resistance change data to generate the temperature abnormality change data; evaluate the degree of thermal runaway of the battery based on the diffusion gas characteristics and the temperature abnormality change data to obtain the degree of thermal runaway of the battery; perform dynamic thermal safety control on the temperature abnormal battery pack according to the degree of thermal runaway of the battery to generate thermal safety control measures; In the embodiment of the present invention, the internal resistance change of the battery cell is recorded to obtain the internal resistance change data; the battery internal resistance, double layer capacitance and diffusion parameters are monitored by electrochemical impedance spectroscopy (EIS) technology; specifically, the 2.8Ah ion battery is tested using Princeton PowerStrong electrochemical technology to record the battery internal resistance value under different charge and discharge states; for example, the battery internal resistance is 5m ohms in the initial state, and after 100 charge and discharge cycles, the internal resistance value change is recorded as 6m ohms, indicating that the internal resistance has increased by 20%; the temperature abnormality battery pack is detected for temperature abnormality change according to the internal resistance change data, specifically using the relationship between the battery internal resistance and temperature, and inferring the abnormal temperature change by monitoring the change of the internal resistance, and detecting the impedance at a specific frequency is highly sensitive to the internal temperature of the battery and is related to SOC and SOH; in practical applications, if the internal resistance is monitored to increase from 6m ohms to 7m ohms, the battery is identified. The temperature inside the battery rises abnormally; the degree of thermal runaway of the battery is evaluated based on the diffusion gas characteristics and abnormal temperature change data to obtain the degree of thermal runaway of the battery; the gas signal monitoring technology is used to evaluate the concentration changes of the target gas (including CH4, C3H8 and CO) through the gas sensor; the degree of thermal runaway of the battery is evaluated in combination with abnormal temperature change data, such as the increase of internal resistance and the increase of temperature; if the gas sensor detects a sudden increase in CH4 concentration, while the internal resistance increases and the temperature rises, this indicates that the battery is in the early stage of thermal runaway; dynamic thermal safety control is performed on the temperature-abnormal battery pack according to the degree of thermal runaway of the battery, and the battery management system (BMS) is used in combination with traditional algorithms to detect the battery status, and monitors multiple battery states such as temperature, voltage, and state of charge (SOC); if the specific evaluation results show that the risk of thermal runaway of the battery is high, the BMS will start the cooling system to reduce the battery temperature and cut off the connection between the battery and the external circuit.

[0033] Step S4: monitor the battery energy storage device in real time to obtain real-time monitoring data of the battery; perform thermal runaway warning on the real-time monitoring data of the battery to generate a thermal runaway warning signal; and perform thermal safety control measures on the battery energy storage device based on the thermal runaway warning signal to complete the thermal safety management operation of the battery energy storage.

[0034] In the embodiment of the present invention, the battery energy storage device is monitored in real time, and the battery energy storage system data management and status monitoring platform technical solution is used to achieve real-time monitoring of the battery energy storage device; specifically, the system frequency, energy storage SOC, energy storage working status, load information and other data and parameters are included; through the real-time monitoring function of the system, a unique monitoring and analysis function of the energy storage device is provided, such as power generation power, frequency, inverter information; SOC, SOH, charge and discharge capacity, charge and discharge power, battery consistency and other information of the energy storage battery; specific operations include real-time acquisition of the temperature of the battery pack through the temperature sensor, real-time acquisition of the total current of the battery pack through the current sensor, and real-time acquisition of the total energy of the battery pack through the voltage sensor; thermal runaway warning is performed on the real-time monitoring data of the battery, and a thermal runaway warning signal is generated; the gas-sensitive technology of thermal runaway monitoring and warning of lithium-ion batteries is used, and the concentration change of the target gas (including CH4, C3H8 and CO) is evaluated through the gas sensor to achieve early warning of thermal runaway; at the same time, combined with the diagnosis method of abnormal battery temperature acquisition, the parameters of the battery at different SOCs, different currents, different temperatures and different aging degrees are measured, including the ohmic internal resistance r0 and the polarization internal resistance r p , control the thermal dissipation of the battery, and calculate the heat generation and internal resistance change rate of the battery, so as to diagnose whether the battery collection temperature t is an abnormal value and generate a thermal runaway warning signal. Based on the thermal runaway warning signal, thermal safety control measures are implemented on the battery energy storage device, and according to the lithium battery thermal runaway warning technology based on multi-feature fusion, when the thermal runaway warning signal is triggered, thermal safety control measures are implemented; these measures include starting the cooling system to reduce the battery temperature and cutting off the connection between the battery and the external circuit to prevent the further spread of thermal runaway. Specifically, if the battery temperature is detected to be abnormally high, the system will automatically start the thermal management function in the battery management system (BMS), and control the battery temperature within a safe range by adjusting the charging and discharging plan, adjusting the battery working status, or starting the liquid cooling system, so as to ensure the safe operation of the battery energy storage device.

[0035] Preferably, step S1 comprises the following steps: Step S11: obtaining a battery energy storage device; Step S12: determining the energy storage battery area of ​​the battery energy storage device to obtain the energy storage battery area; calculating the area of ​​the energy storage battery area to generate battery area data; Step S13: Divide the battery area data into multiple battery areas to obtain battery group division data; encode and merge the battery group division data to obtain an energy storage battery group set; Step S14: Detect the battery pack area temperature of the energy storage battery pack set to obtain the battery pack area temperature; extract the internal temperature of the battery pack area temperature to obtain the internal temperature of the battery pack.

[0036] In the embodiment of the present invention, the location and quantity of the battery energy storage device are determined by the battery energy storage detection technology; the energy storage battery area of ​​the battery energy storage device is determined, and the battery area is specifically divided to determine the energy storage battery area; the battery is divided into multiple areas, each area corresponds to the service range of a battery group, and the service area of ​​each battery group is determined by the Voronoi diagram division method; and the area measurement technology is used to generate battery area data; the battery area area data is divided into multi-component battery areas, and the battery group division data is encoded and merged to obtain an energy storage battery group set; the electrochemical characteristics of batteries in different areas are analyzed using electrochemical measurement technology, such as the constant current intermittent titration method (GITT), and the battery area is divided into different battery groups according to the electrochemical specific surface area and the lithium ion chemical diffusion coefficient; each battery area is divided into different battery groups according to the battery area data. The service area of ​​the battery swap station is further divided into multiple battery groups, each of which has similar electrochemical characteristics; the data of these battery groups are then integrated through coding merging technology to form an energy storage battery group collection; the battery group area temperature of the energy storage battery group collection is detected, and a temperature detection circuit and a temperature detection method are used to arrange a thermistor for each battery module, and a bridge circuit is constructed; the resistance data is collected through the battery management unit and converted into temperature data; specifically, a thermistor is arranged for each battery module in the energy storage battery group collection, and they are connected into a bridge circuit; the resistance change of each thermistor is collected through the battery management unit, and the temperature data of each battery module is converted according to the resistance change, thereby obtaining the battery group area temperature; then the battery group area temperature is analyzed through the temperature anomaly detection method, and the internal temperature of each battery module is extracted.

[0037] Preferably, step S2 comprises the following steps: Step S21: quantifying the temperature values ​​within each battery pack to obtain the temperature values ​​within each battery pack; summarizing and counting the temperature values ​​within each battery pack to generate battery pack temperature statistics; Step S22: mapping the temperature characteristics of each battery pack of the energy storage battery pack set based on the battery pack temperature statistics to obtain the temperature mapping characteristics of each group; generating a temperature heat map for the temperature mapping characteristics of each group to obtain the battery pack temperature heat map; Step S23: determining temperature anomalies on the battery pack temperature thermodynamic map to obtain abnormal blocks on the thermodynamic map; marking the energy storage battery packs based on the abnormal blocks on the thermodynamic map to obtain abnormal temperature battery packs; Step S24: monitoring the battery cell voltage of the battery pack with abnormal temperature to obtain the battery cell voltage value; monitoring the battery cell current of the battery pack with abnormal temperature to obtain the battery cell current value; Step S25: Calculating the internal resistance of the battery cell based on the battery cell voltage value and the battery cell current value to generate the internal resistance value of the battery cell; Step S26: monitoring the battery pack diffusion gas for the battery pack with abnormal temperature to obtain the diffusion gas characteristics.

[0038] In an embodiment of the present invention, for a battery pack consisting of 100 battery cells, each battery cell is arranged with an NTC thermistor, and the resistance value of each thermistor is measured, and the resistance value is converted into a temperature value by using a table lookup method or a formula method to obtain the temperature value in each group; by summarizing these temperature values, the average temperature or the temperature distribution range is calculated to generate the battery pack temperature statistics; based on the battery pack temperature statistics, the temperature characteristics of each battery pack are mapped for the energy storage battery pack set, and the impedance characteristics of different battery packs at different temperatures are analyzed by using the electrochemical impedance spectroscopy (EIS) technology, and the temperature statistics are mapped to the characteristic parameters of the battery pack; then, the temperature mapping characteristics are displayed in a graphical manner by using the temperature heat map generation technology to form a battery pack temperature heat map, so as to intuitively display the temperature distribution of each area of ​​the battery energy storage device. The temperature anomaly is judged on the battery pack temperature thermogram to obtain the abnormal block of the thermogram; the battery pack of the energy storage battery pack is marked based on the abnormal block of the thermogram to obtain the abnormal temperature battery pack; by analyzing the high temperature area on the thermogram, combined with the early characteristics and early warning methods of thermal runaway of lithium-ion batteries, it is judged whether the battery pack has temperature anomaly; the temperature threshold is specifically set to 60°C, and the area exceeding the threshold is marked as an abnormal block; the battery packs corresponding to these abnormal blocks are marked to identify the abnormal temperature battery packs; the battery cell voltage of the abnormal temperature battery pack is monitored to obtain the battery cell voltage value; the battery cell current of the abnormal temperature battery pack is monitored to obtain the battery cell current value; the voltage sampling circuit and the AC The flow transmitter samples the voltage response signal and phase difference signal of the battery cell in real time; sends these signals to the microcontroller (MCU) through the wireless communication module, stores them in the internal resistance calculation module of the MCU, monitors the voltage and current of each battery cell in real time, and obtains the battery cell voltage value and current value; calculates the internal resistance of the battery cell based on the battery cell voltage value and the battery cell current value, and generates the internal resistance value of the battery cell; calculates the internal resistance of the battery cell through the internal resistance calculation module in the MCU using the voltage continuous sampling algorithm and the impedance formula; calculates the internal resistance of the battery cell based on Ohm's law and the phase relationship of the AC circuit; monitors the battery pack diffusion gas for abnormal temperature battery packs to obtain the diffusion gas characteristics. Use gas sensor technology to monitor the gases diffused from the battery pack, such as CH4, C3H8 and CO, to assess the risk of thermal runaway of the battery; assess the concentration change of the target gas through the gas sensor to obtain the diffusion gas characteristics.

[0039] Preferably, step S26 includes the following steps: Step S261: monitoring the battery pack diffusion condition of the battery pack with abnormal temperature to obtain the diffusion monitoring condition; identifying the diffusion gas based on the diffusion monitoring condition to generate diffusion gas condition data; Step S262: performing gas color judgment on the diffused gas condition data to obtain diffused gas color; performing gas concentration determination on the diffused gas condition data based on the diffused gas color to generate a gas concentration state; Step S263: performing gas composition identification on the diffused gas condition data according to the gas concentration state to obtain gas composition data; performing diffusion pattern identification on the gas composition data to generate a gas diffusion pattern; performing gas diffusion range detection on the gas diffusion pattern to obtain a gas diffusion range; Step S264: Integrate the gas concentration state, gas diffusion mode and gas diffusion range into the battery pack diffusion gas characteristics to obtain the diffusion gas characteristics.

[0040] In the embodiment of the present invention, the battery pack diffusion condition is monitored for the battery pack with abnormal temperature to obtain the diffusion monitoring condition; the diffusion gas is identified for the diffusion monitoring condition; the battery cell voltage and temperature are monitored by the battery cell management unit BMU in the BMS battery management system, and thermal management and abnormal alarm are performed; the concentration change of the target gas (including CH4, C3H8 and CO) is evaluated by using gas sensor technology, such as a gas sensor; specifically, a battery pack consisting of 100 battery cells is monitored, and the concentration change of each gas is identified and recorded by the gas sensor to generate diffusion gas condition data; the gas color is judged for the diffusion gas condition data to obtain the diffusion gas color; the mixed gas component detection and identification technology based on the nanosensor matrix is ​​adopted, and the concentration change of each gas is recorded by the nanosensor matrix The four gas components are distinguished by the promoting or inhibiting effect of the mixed gas in the array; the gas color is determined by analyzing the spectral characteristics of the diffused gas, and then the gas concentration state is determined according to the known gas concentration range corresponding to the color; the gas composition is identified on the diffused gas situation data according to the gas concentration state, and the gas diffusion range is detected on the gas diffusion pattern to obtain the gas diffusion range; the velocity streamlines and hydrogen concentration evolution of the airflow in the energy storage battery compartment are analyzed; the gas composition data is identified specifically through simulation and experimental data, and then the gas diffusion pattern is generated and the gas diffusion range is detected according to the speed and range of gas diffusion; the gas concentration state, gas diffusion pattern and gas diffusion range are integrated into the battery pack diffusion gas characteristics by using data integration technology to obtain the diffused gas characteristics.

[0041] As an example of the present invention, refer to Figure 2 As shown, in this example, step S3 includes: Step S31: continuously monitoring the internal resistance of the battery cell to obtain battery internal resistance monitoring data; marking the monitoring time period of the battery internal resistance monitoring data to generate an internal resistance monitoring time period; Step S32: recording the resistance value of the internal resistance of the battery cell in the initial period based on the internal resistance monitoring period to obtain the resistance value in the initial period; recording the resistance value of the internal resistance of the battery cell in the final period based on the internal resistance monitoring period to obtain the resistance value in the final period; Step S33: subtract the internal resistance value in the final period from the internal resistance value in the initial period to generate internal resistance change data; Step S34: performing temperature abnormality detection on the temperature abnormality battery pack according to the internal resistance change data, and generating temperature abnormality change data; Step S35: evaluating the degree of thermal runaway of the battery based on the diffusion gas characteristics and the abnormal temperature change data to obtain the degree of thermal runaway of the battery; Step S36: Perform dynamic thermal safety control on the battery pack with abnormal temperature according to the degree of thermal runaway of the battery, and generate thermal safety control measures.

[0042] In an embodiment of the present invention, the internal resistance of the battery cell is continuously monitored to obtain the battery internal resistance monitoring data; the internal resistance monitoring function in the BMS (battery management system) is used to measure the internal resistance of the battery by real-time monitoring the voltage and current of the battery cell; for example, the BMS detects abnormal conditions of the battery cell in time through voltage monitoring, current monitoring and internal resistance monitoring; specifically, the BMS records the internal resistance value of each battery cell at a specific time point, such as once every 5 minutes, to generate an internal resistance monitoring time period; based on the internal resistance monitoring time period, the internal resistance value of the battery cell is recorded in the initial time period, and the internal resistance value of the battery cell is recorded in the final time period according to the internal resistance monitoring time period; at the beginning of monitoring, the initial internal resistance value of the battery cell is recorded, such as recording the internal resistance value within the first minute from the beginning of monitoring; at the end of monitoring, the internal resistance value of the final time period is recorded, such as recording the internal resistance value within the last minute before the end of monitoring; the internal resistance value of the final time period is subtracted from the internal resistance value of the initial time period to generate an internal resistance change number data; and by calculating the difference between the resistance value in the final time period and the resistance value in the initial time period, the internal resistance change data is obtained; specifically, if the resistance value in the initial time period is 50m ohms and the resistance value in the final time period is 55m ohms, the internal resistance change data is an increase of 5m ohms; according to the internal resistance change data, the temperature abnormality battery pack is detected for temperature abnormality change, and the internal resistance change data is used in combination with the temperature monitoring data of the battery to detect the abnormal temperature change of the battery pack; specifically, if the increase in internal resistance is accompanied by an abnormal increase in temperature, this indicates that the battery pack is at risk of thermal runaway; based on the characteristics of the diffused gas and the temperature abnormal change data, the degree of thermal runaway of the battery is evaluated to obtain the degree of thermal runaway of the battery; by analyzing the characteristics of the diffused gas and the temperature abnormal change data, the degree of thermal runaway of the battery is evaluated; for example, by monitoring the gases diffused from the battery pack, such as CH4, C3H8 and CO, the risk of thermal runaway of the battery is evaluated; dynamic thermal safety control is performed on the temperature abnormal battery pack according to the degree of thermal runaway of the battery, and thermal safety control measures are generated. Utilizing the thermal management function of the BMS, corresponding thermal safety control measures are executed according to the degree of thermal runaway of the battery; for example, if the risk of thermal runaway of the battery is high, the BMS will start the cooling system to reduce the battery temperature and at the same time cut off the connection between the battery and the external circuit to prevent further spread of thermal runaway.

[0043] Preferably, step S34 includes the following steps: Step S341: performing frequency domain conversion on the internal resistance change data to obtain internal resistance change frequency data; performing frequency jitter feature recognition on the internal resistance change frequency data to generate internal resistance frequency jitter features; Step S342: performing jitter time mapping on the internal resistance monitoring time period according to the internal resistance frequency jitter characteristics to obtain the internal resistance frequency jitter time; Step S343: performing temperature pattern recognition on the battery pack with abnormal temperature based on the internal resistance frequency jitter time to obtain a frequency jitter-temperature pattern; performing temperature sensitivity judgment on the battery pack based on the frequency jitter-temperature pattern to generate temperature sensitivity data; Step S344: recording the duration of abnormal temperature change of the battery pack with abnormal temperature according to the temperature sensitivity data to obtain the duration of abnormal temperature change; monitoring the abnormal temperature change value of the battery pack with abnormal temperature based on the temperature sensitivity data to obtain the abnormal temperature change degree value; Step S345: integrating the abnormal temperature change duration and the abnormal temperature change degree value into the abnormal temperature change characteristics to generate abnormal temperature change data.

[0044] In an embodiment of the present invention, a frequency domain method is used to convert a time domain signal into a frequency domain signal through Fourier transform, so as to identify the frequency characteristics of the internal resistance change; specifically, a fast Fourier transform (FFT) algorithm is used to perform frequency domain conversion on the battery internal resistance change data to obtain the internal resistance change frequency data; then, the key technology of identifying the test modal parameters is used through the frequency domain method to identify the frequency jitter characteristics in the internal resistance change frequency data, and generate the internal resistance frequency jitter characteristics; by analyzing the distribution of the internal resistance frequency jitter characteristics in the frequency domain, combined with the time-frequency mapping technology, the jitter time is determined to obtain the internal resistance frequency jitter time; based on the internal resistance frequency jitter time, the temperature mode of the battery pack with abnormal temperature is identified to obtain the frequency jitter-temperature mode; the frequency jitter-temperature mode is identified by using the correlation between the internal resistance frequency jitter time and the battery pack temperature data; specifically, by analyzing the internal resistance frequency The correlation between the jitter time and the battery pack temperature data is used to identify the temperature pattern, and the temperature sensitivity of the pattern is judged to generate temperature sensitivity data; the duration of abnormal temperature changes of the temperature-abnormal battery pack is recorded according to the temperature sensitivity data to obtain the duration of abnormal temperature changes; specifically according to the temperature sensitivity data, the abnormal temperature changes of the battery pack in a specific time period are monitored and recorded to obtain the duration of abnormal temperature changes and the degree of abnormal temperature changes; the duration of abnormal temperature changes and the degree of abnormal temperature changes are integrated with the abnormal temperature change characteristics to generate abnormal temperature change data; complete abnormal temperature change data are formed by integrating the duration and degree of abnormal temperature changes; specifically, the duration of abnormal temperature changes and the degree of abnormal temperature changes are integrated to generate abnormal temperature change data, providing key parameters for battery thermal runaway assessment.

[0045] As an example of the present invention, refer to Figure 3 As shown, in this example, step S35 includes: Step S351: determining the gas concentration of the diffused gas feature to obtain the diffused gas concentration; identifying the diffusion mode type of the diffused gas feature to obtain the gas diffusion mode type; Step S352: performing gas diffusion space range detection on the diffusion gas characteristics based on the diffusion gas concentration and the gas diffusion mode type, and generating diffusion space distribution data; Step S353: performing gas diffusion influence weight matching on the battery pack with abnormal temperature according to the diffusion space distribution data, and generating a gas diffusion influence weight value; Step S354: determining the abnormal temperature change period of the abnormal temperature change data to obtain the abnormal temperature change period; calculating the abnormal temperature deviation value of the abnormal temperature change data to generate the abnormal temperature deviation value; Step S355: performing temperature abnormality change impact weight matching on the temperature abnormal battery pack based on the abnormal temperature change cycle and the temperature abnormality deviation value, and generating a temperature change impact weight value; Step S356: Calculate the battery thermal runaway weight according to the gas diffusion influence weight value and the temperature change influence weight value to obtain the battery thermal runaway weight scoring data; divide the battery thermal runaway weight scoring data into runaway degrees to obtain the battery thermal runaway degree.

[0046] In the embodiment of the present invention, the gas concentration of the diffused gas characteristic is determined to obtain the diffused gas concentration; the diffusion pattern type of the diffused gas characteristic is identified to obtain the gas diffusion pattern type; the concentration of the gas diffused from the battery pack is determined and the diffusion pattern type is identified through a gas sensor array and a pattern recognition algorithm, such as a back propagation artificial neural network (BP-ANN); specifically, a high-resolution gas detection device is used to identify and quantify the gas components, and the BP-ANN algorithm is applied to classify and identify the gas concentration and diffusion pattern through the data collected by the sensor array; the diffused gas characteristic is gas-identified based on the diffused gas concentration and the gas diffusion pattern type. Diffusion space range detection, generating diffusion space distribution data; combining gas concentration and diffusion mode type, determine the diffusion space range of gas in the battery pack through simulation and experimental data; specifically, by analyzing the relationship between CO2 diffusion coefficient and effective diffusion coefficient and time, calculate the diffusion path and range of gas molecules in coal, and generate diffusion space distribution data; match the gas diffusion degree influence weights for temperature abnormal battery packs according to diffusion space distribution data, and generate gas diffusion influence weight values; use time series analysis methods in statistics, such as smoothing techniques (such as moving average, exponential smoothing), to analyze the diffusion space distribution data to determine the gas diffusion degree on the battery pack. Impact weight; specifically, by analyzing the spatial distribution data of gas diffusion, the contribution of gas diffusion to the thermal runaway risk of the battery pack is calculated, and the gas diffusion impact weight is generated; the abnormal temperature change cycle is determined for the abnormal temperature change data, and the temperature distribution of the new energy battery pack is monitored in real time using infrared thermal imaging technology. By detecting the temperature difference inside the battery pack, the abnormal temperature change cycle and the abnormal temperature deviation value are determined; specifically, the temperature of the battery pack is monitored by an infrared thermal imaging module, and the time series of the temperature data is analyzed to determine the abnormal temperature change cycle and the abnormal temperature deviation value; the abnormal temperature change cycle and the abnormal temperature deviation value are analyzed to determine the impact of abnormal temperature on the thermal runaway risk of the battery pack The influence weight of the temperature abnormality change data is processed by statistical analysis methods to calculate the contribution of temperature abnormality to the thermal runaway risk of the battery pack and generate the temperature change influence weight value; the battery thermal runaway weight is calculated according to the gas diffusion influence weight value and the temperature change influence weight value to obtain the battery thermal runaway weight score data; the weight score data of the battery thermal runaway is calculated by combining the gas diffusion influence weight value and the temperature change influence weight value, and the degree of runaway is divided; specifically, by evaluating the battery thermal runaway risk and combining multiple parameters (such as temperature, gas concentration, voltage, internal resistance, etc.) for early warning, the accuracy and sensitivity of the early warning system are effectively improved, and the degree of battery thermal runaway is finally determined.

[0047] Preferably, step S36 includes the following steps: Step S361: Compare the battery thermal runaway degree with a preset thermal runaway degree index. If the battery thermal runaway degree is greater than the preset thermal runaway degree index, mark it as the battery thermal runaway severity. Step S362: locating the thermal runaway battery cells of the battery pack with abnormal temperature based on the severity of the battery thermal runaway, and generating a thermal runaway battery cell area; Step S363: Cutting off the battery cell circuit in the thermal runaway battery cell area and generating circuit cutting measures; Step S364: evacuating the thermal runaway battery cell area with diffusion gas, and generating diffusion gas evacuation measures; Step S365: activating a battery cooling device for the thermal runaway battery cell area and generating cooling device activation measures; Step S366: Integrate the circuit cut-off measures, diffusion gas evacuation measures and cooling device startup measures for thermal safety control to generate thermal safety control measures.

[0048] In the embodiment of the present invention, the battery thermal runaway degree is compared with a preset thermal runaway degree index. If the battery thermal runaway degree is greater than the preset thermal runaway degree index, it is marked as the battery thermal runaway severity. A lithium battery safety evaluation method based on a thermal runaway risk index is adopted. By evaluating the battery thermal runaway risk index, the actual thermal runaway degree is compared with a preset safety threshold. For example, the preset thermal runaway degree indicator is that the battery temperature reaches 120°C. If the monitored battery temperature exceeds this value, it is marked as the battery thermal runaway severity. The thermal runaway battery cells of the battery pack with abnormal temperature are located based on the battery thermal runaway severity, and a thermal runaway battery cell area is generated. The online battery thermal runaway early warning method and system based on EIS parameter extraction are used to extract key parameters of the electrochemical impedance spectroscopy (EIS) to determine the specific location of the thermal runaway battery cell. Specifically, by analyzing the changes in the real and imaginary parts of the impedance, a specific battery cell area in the battery pack is located as the thermal runaway battery cell area. The battery cell circuit is cut off in the thermal runaway battery cell area, and a circuit cutoff measure is generated. According to the battery thermal runaway safety strategy, after determining the thermal runaway battery cell area, the circuit cutoff operation is immediately performed to prevent Stop the spread of thermal runaway; specifically, control the relay or fuse through the battery management system (BMS) to cut off the circuit connection with the thermal runaway battery cell area, and generate circuit cut-off measures; evacuate the thermal runaway battery cell area with diffusion gas, and generate diffusion gas evacuation measures; perform gas evacuation operations on the thermal runaway battery cell area to reduce the gas accumulation caused by thermal runaway; such as starting the gas evacuation system in the battery compartment to extract the gas in the thermal runaway battery cell area, and generate diffusion gas evacuation measures; start the battery cooling device in the thermal runaway battery cell area, and generate cooling device start-up measures; specifically start the battery cooling device to reduce the temperature of the thermal runaway battery cell area; such as cooling the thermal runaway battery cell area through the coolant circulation system, or using phase change materials for local cooling, and generate cooling device start-up measures; use data fusion technology to integrate the circuit cut-off measures, diffusion gas evacuation measures and cooling device start-up measures for thermal safety control, and generate thermal safety control measures.

[0049] Preferably, step S4 comprises the following steps: Step S41: monitoring the state of the energy storage battery of the battery energy storage device in real time to obtain real-time monitoring data of the battery; Step S42: identifying the abnormal battery temperature state of the battery real-time monitoring data to obtain the abnormal battery temperature state; determining the battery thermal runaway mode of the abnormal battery temperature state to generate the battery thermal runaway mode; Step S43: Perform a thermal runaway warning on the battery thermal runaway mode and generate a thermal runaway warning signal; Step S44: based on the thermal runaway warning signal, locate the thermal runaway battery pack of the battery energy storage device to obtain the location information of the thermal runaway battery pack; perform thermal safety control measures on the location information of the thermal runaway battery pack to complete the thermal safety management operation of the battery energy storage.

[0050] In the embodiment of the present invention, the state of the energy storage battery of the battery energy storage device is monitored in real time, and the battery management system (BMS) is specifically used to detect various state quantities in the battery operation process in real time, such as voltage, temperature, current, SOC, SOH, etc. In the specific embodiment, the BMS obtains the temperature frequency distribution table of each battery temperature probe through the temperature sensor arranged in the battery module; the battery temperature abnormal state is identified for the real-time monitoring data of the battery to obtain the battery temperature abnormal state; the battery thermal runaway mode is determined for the battery temperature abnormal state to generate the battery thermal runaway mode; the battery temperature abnormal state is identified by analyzing the battery temperature curve and interval division; if the temperature of the monitoring point reaches the maximum temperature specified by the manufacturer (generally 60°C), it is determined to be a battery thermal runaway mode; the battery thermal runaway mode is given a thermal runaway warning, and the multi-feature fusion lithium battery thermal runaway warning method of the abnormal temperature rise rate and the temperature drop after the safety valve is opened can timely and accurately find the opening time and position of the lithium battery safety valve, and generate a thermal runaway warning signal. Based on the thermal runaway warning signal, the battery energy storage device locates the thermal runaway battery pack and obtains the location information of the thermal runaway battery pack. Combined with the current temperature of the energy storage battery, the comprehensive risk estimation index of the energy storage battery during normal use is obtained, which reflects the degree of risk of the energy storage battery at present. Thermal safety control measures are implemented on the location information of the thermal runaway battery pack to complete the thermal safety management of the battery energy storage.

[0051] In this specification, a thermal safety management system for battery energy storage is provided, which is used to execute the thermal safety management method for battery energy storage described above. The thermal safety management system for battery energy storage includes: The battery energy storage device temperature detection module is used to obtain the battery energy storage device; divide the battery energy storage device into battery groups to generate a set of energy storage battery groups; detect the internal temperature of the battery groups of the energy storage battery group set to obtain the internal temperature of the battery groups; The battery cell abnormality analysis module is used to quantify the temperature value of the internal temperature of the battery pack and generate the battery pack temperature statistics; to judge the temperature abnormality of the battery pack temperature statistics and mark the battery pack to obtain the temperature abnormal battery pack; to detect the battery cell internal resistance of the temperature abnormal battery pack and generate the battery cell internal resistance value; to monitor the battery pack diffusion gas of the temperature abnormal battery pack and obtain the diffusion gas characteristics; The battery thermal safety control module is used to record the change of the internal resistance of the battery unit and obtain the internal resistance change data; detect the abnormal temperature change of the temperature-abnormal battery pack based on the internal resistance change data and generate the abnormal temperature change data; evaluate the degree of thermal runaway of the battery based on the diffusion gas characteristics and the abnormal temperature change data and obtain the degree of thermal runaway of the battery; perform dynamic thermal safety control on the temperature-abnormal battery pack according to the degree of thermal runaway of the battery and generate thermal safety control measures; The thermal runaway warning execution module is used to monitor the battery energy storage device in real time to obtain real-time monitoring data of the battery; to issue a thermal runaway warning to the real-time monitoring data of the battery and generate a thermal runaway warning signal; and to execute thermal safety control measures on the battery energy storage device based on the thermal runaway warning signal to complete the thermal safety management of the battery energy storage.

[0052] The present invention obtains the battery energy storage device and divides it into battery groups through the battery energy storage device temperature detection module, generates a collection of energy storage battery groups, has a clear understanding of the structure of the battery energy storage device, and provides a basis for subsequent temperature detection and abnormal judgment; detects the internal temperature of the battery group of the energy storage battery group collection and obtains the internal temperature of the battery group, which provides an accurate data basis for temperature value quantification statistics and abnormal judgment, thereby ensuring the safe operation of the battery energy storage device. Through the battery cell abnormality analysis module, the temperature value of the internal temperature of the battery group is quantified and statistics are performed to clarify the temperature distribution of the battery group; the temperature abnormality judgment is performed on the battery group temperature statistics, and the battery group is marked to obtain the temperature abnormal battery group, which can timely discover the safety hazards existing in the battery energy storage device; the battery cell internal resistance detection and battery group diffusion gas monitoring are performed on the temperature abnormal battery group, and the battery cell internal resistance value and diffusion gas characteristics are generated, which provide the necessary parameters for the evaluation of the degree of thermal runaway of the battery, and enhance the safety monitoring capability of the battery energy storage device. Through the battery thermal safety control module, the internal resistance value of the battery unit is recorded for the change of the battery internal resistance, so that the performance change of the battery unit can be monitored, providing data support for the subsequent abnormal temperature change detection; the abnormal temperature change of the temperature abnormal battery pack is detected according to the internal resistance change data, and the abnormal temperature change data is generated to accurately grasp the temperature dynamics of the battery pack and provide real-time data for the evaluation of the degree of thermal runaway of the battery; the degree of thermal runaway of the battery is evaluated based on the diffusion gas characteristics and the abnormal temperature change data, which can scientifically evaluate the safety status of the battery energy storage device and provide a basis for dynamic thermal safety control; dynamic thermal safety control is performed on the abnormal temperature battery pack according to the degree of thermal runaway of the battery, and thermal safety control measures are generated to ensure that the battery energy storage device can be handled promptly and effectively under abnormal conditions, thereby improving the safety performance of the battery energy storage device. Through the thermal runaway warning execution module, the battery energy storage device is monitored in real time to obtain real-time monitoring data of the battery, and the operating status of the battery energy storage device is continuously tracked to provide real-time data for thermal runaway warning; thermal runaway warning is performed on the real-time monitoring data of the battery, and a warning can be issued in time to remind relevant personnel to take action; thermal safety control measures are executed on the battery energy storage device based on the thermal runaway warning signal to complete the thermal safety management of the battery energy storage, ensuring that the battery energy storage device can be effectively controlled and processed when facing the risk of thermal runaway, and ensuring the safe and stable operation of the battery energy storage device. Therefore, the present invention realizes the subdivision monitoring of the battery unit of the battery energy storage device through data processing technology, pattern recognition technology and deep learning technology, and evaluates the degree of thermal runaway of the battery by monitoring multiple parameters of the energy storage battery, so as to realize dynamic thermal safety control of the battery energy storage device, thereby improving the thermal safety management efficiency of the battery energy storage.

[0053] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0054] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A thermal safety management method for battery energy storage, characterized in that: The following steps are involved: Step S1: obtaining a battery energy storage device; dividing the battery energy storage device into battery groups to generate a set of energy storage battery groups; Detecting the internal temperature of a battery pack of an energy storage battery pack to obtain the internal temperature of the battery pack; Step S2: quantifying and counting the internal temperature of the battery pack to generate a battery pack temperature statistic; determining temperature anomalies on the battery pack temperature statistic, and marking the battery pack to obtain a battery pack with abnormal temperature; Perform battery cell internal resistance detection on battery packs with abnormal temperature to generate battery cell internal resistance values; perform battery pack diffusion gas monitoring on battery packs with abnormal temperature to obtain diffusion gas characteristics; Step S3: recording the change of the internal resistance of the battery cell to obtain the internal resistance change data; performing temperature abnormality change detection on the temperature abnormal battery pack according to the internal resistance change data to generate the temperature abnormality change data; The battery thermal runaway degree is evaluated based on the diffusion gas characteristics and abnormal temperature change data to obtain the battery thermal runaway degree; dynamic thermal safety control is performed on the temperature abnormal battery pack according to the battery thermal runaway degree to generate thermal safety control measures; Step S4: monitor the battery energy storage device in real time to obtain real-time monitoring data of the battery; perform thermal runaway warning on the real-time monitoring data of the battery to generate a thermal runaway warning signal; Based on the thermal runaway warning signal, thermal safety control measures are implemented on the battery energy storage device to complete the thermal safety management of the battery energy storage.

2. The thermal safety management method for battery energy storage according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: Acquire a battery energy storage device; Step S12: determining the energy storage battery area of ​​the battery energy storage device to obtain the energy storage battery area; calculating the area of ​​the energy storage battery area to generate battery area data; Step S13: Divide the battery area data into multiple battery areas to obtain battery group division data; encode and merge the battery group division data to obtain an energy storage battery group set; Step S14: Detect the battery pack area temperature of the energy storage battery pack set to obtain the battery pack area temperature; extract the internal temperature of the battery pack area temperature to obtain the internal temperature of the battery pack.

3. The thermal safety management method for battery energy storage according to claim 1, characterized in that: Step S2 includes the following steps: Step S21: quantifying the temperature values ​​within each battery pack to obtain the temperature values ​​within each battery pack; summarizing and counting the temperature values ​​within each battery pack to generate battery pack temperature statistics; Step S22: mapping the temperature characteristics of each battery pack of the energy storage battery pack set based on the battery pack temperature statistics to obtain the temperature mapping characteristics of each group; generating a temperature heat map for the temperature mapping characteristics of each group to obtain the battery pack temperature heat map; Step S23: determining temperature anomalies on the battery pack temperature thermodynamic map to obtain abnormal blocks on the thermodynamic map; marking the energy storage battery packs based on the abnormal blocks on the thermodynamic map to obtain abnormal temperature battery packs; Step S24: monitoring the battery cell voltage of the battery pack with abnormal temperature to obtain the battery cell voltage value; monitoring the battery cell current of the battery pack with abnormal temperature to obtain the battery cell current value; Step S25: Calculating the internal resistance of the battery cell based on the battery cell voltage value and the battery cell current value to generate the internal resistance value of the battery cell; Step S26: monitoring the battery pack diffusion gas for the battery pack with abnormal temperature to obtain the diffusion gas characteristics.

4. The thermal safety management method for battery energy storage according to claim 3, characterized in that: Step S26 includes the following steps: Step S261: monitoring the battery pack diffusion condition of the battery pack with abnormal temperature to obtain the diffusion monitoring condition; identifying the diffusion gas based on the diffusion monitoring condition to generate diffusion gas condition data; Step S262: performing gas color judgment on the diffused gas condition data to obtain diffused gas color; performing gas concentration determination on the diffused gas condition data based on the diffused gas color to generate a gas concentration state; Step S263: performing gas composition identification on the diffused gas condition data according to the gas concentration state to obtain gas composition data; performing diffusion pattern identification on the gas composition data to generate a gas diffusion pattern; performing gas diffusion range detection on the gas diffusion pattern to obtain a gas diffusion range; Step S264: Integrate the gas concentration state, gas diffusion mode and gas diffusion range into the battery pack diffusion gas characteristics to obtain the diffusion gas characteristics.

5. The thermal safety management method for battery energy storage according to claim 1, characterized in that: Step S3 includes the following steps: Step S31: continuously monitoring the internal resistance of the battery cell to obtain battery internal resistance monitoring data; marking the monitoring time period of the battery internal resistance monitoring data to generate an internal resistance monitoring time period; Step S32: recording the resistance value of the internal resistance of the battery cell in the initial period based on the internal resistance monitoring period to obtain the resistance value in the initial period; recording the resistance value of the internal resistance of the battery cell in the final period based on the internal resistance monitoring period to obtain the resistance value in the final period; Step S33: subtract the internal resistance value in the final period from the internal resistance value in the initial period to generate internal resistance change data; Step S34: performing temperature abnormality detection on the temperature abnormality battery pack according to the internal resistance change data, and generating temperature abnormality change data; Step S35: evaluating the degree of thermal runaway of the battery based on the diffusion gas characteristics and the abnormal temperature change data to obtain the degree of thermal runaway of the battery; Step S36: Perform dynamic thermal safety control on the battery pack with abnormal temperature according to the degree of thermal runaway of the battery, and generate thermal safety control measures.

6. The thermal safety management method for battery energy storage according to claim 5, characterized in that: Step S34 includes the following steps: Step S341: performing frequency domain conversion on the internal resistance change data to obtain internal resistance change frequency data; performing frequency jitter feature recognition on the internal resistance change frequency data to generate internal resistance frequency jitter features; Step S342: performing jitter time mapping on the internal resistance monitoring time period according to the internal resistance frequency jitter characteristics to obtain the internal resistance frequency jitter time; Step S343: performing temperature pattern recognition on the battery pack with abnormal temperature based on the internal resistance frequency jitter time to obtain a frequency jitter-temperature pattern; performing temperature sensitivity judgment on the battery pack based on the frequency jitter-temperature pattern to generate temperature sensitivity data; Step S344: recording the duration of abnormal temperature change of the battery pack with abnormal temperature according to the temperature sensitivity data to obtain the duration of abnormal temperature change; monitoring the abnormal temperature change value of the battery pack with abnormal temperature based on the temperature sensitivity data to obtain the abnormal temperature change degree value; Step S345: integrating the abnormal temperature change duration and the abnormal temperature change degree value into the abnormal temperature change characteristics to generate abnormal temperature change data.

7. The thermal safety management method for battery energy storage according to claim 5, characterized in that: Step S35 includes the following steps: Step S351: determining the gas concentration of the diffused gas feature to obtain the diffused gas concentration; identifying the diffusion mode type of the diffused gas feature to obtain the gas diffusion mode type; Step S352: performing gas diffusion space range detection on the diffusion gas characteristics based on the diffusion gas concentration and the gas diffusion mode type, and generating diffusion space distribution data; Step S353: performing gas diffusion influence weight matching on the battery pack with abnormal temperature according to the diffusion space distribution data, and generating a gas diffusion influence weight value; Step S354: determining the abnormal temperature change period of the abnormal temperature change data to obtain the abnormal temperature change period; calculating the abnormal temperature deviation value of the abnormal temperature change data to generate the abnormal temperature deviation value; Step S355: performing temperature abnormality change impact weight matching on the temperature abnormal battery pack based on the abnormal temperature change cycle and the temperature abnormality deviation value, and generating a temperature change impact weight value; Step S356: Calculate the battery thermal runaway weight according to the gas diffusion influence weight value and the temperature change influence weight value to obtain the battery thermal runaway weight scoring data; divide the battery thermal runaway weight scoring data into runaway degrees to obtain the battery thermal runaway degree.

8. The thermal safety management method for battery energy storage according to claim 5, characterized in that: Step S36 includes the following steps: Step S361: Compare the battery thermal runaway degree with a preset thermal runaway degree index. If the battery thermal runaway degree is greater than the preset thermal runaway degree index, mark it as the battery thermal runaway severity. Step S362: locating the thermal runaway battery cells of the battery pack with abnormal temperature based on the severity of the battery thermal runaway, and generating a thermal runaway battery cell area; Step S363: Cutting off the battery cell circuit in the thermal runaway battery cell area and generating circuit cutting measures; Step S364: evacuating the thermal runaway battery cell area with diffusion gas, and generating diffusion gas evacuation measures; Step S365: activating a battery cooling device for the thermal runaway battery cell area and generating cooling device activation measures; Step S366: Integrate the circuit cut-off measures, diffusion gas evacuation measures and cooling device startup measures for thermal safety control to generate thermal safety control measures.

9. The thermal safety management method for battery energy storage according to claim 1, characterized in that: Step S4 includes the following steps: Step S41: monitoring the state of the energy storage battery of the battery energy storage device in real time to obtain real-time monitoring data of the battery; Step S42: identifying the abnormal battery temperature state of the battery real-time monitoring data to obtain the abnormal battery temperature state; determining the battery thermal runaway mode of the abnormal battery temperature state to generate the battery thermal runaway mode; Step S43: Perform a thermal runaway warning on the battery thermal runaway mode and generate a thermal runaway warning signal; Step S44: based on the thermal runaway warning signal, locate the thermal runaway battery pack of the battery energy storage device to obtain the location information of the thermal runaway battery pack; perform thermal safety control measures on the location information of the thermal runaway battery pack to complete the thermal safety management operation of the battery energy storage.

10. A thermal safety management system for battery energy storage, characterized in that: Used to execute the thermal safety management method of battery energy storage as claimed in claim 1, the thermal safety management system of battery energy storage comprises: The battery energy storage device temperature detection module is used to obtain the battery energy storage device; divide the battery energy storage device into battery groups to generate a set of energy storage battery groups; detect the internal temperature of the battery group of the energy storage battery group set to obtain the internal temperature of the battery group; The battery cell abnormality analysis module is used to quantify the temperature value of the internal temperature of the battery pack and generate the battery pack temperature statistics; to judge the temperature abnormality of the battery pack temperature statistics and mark the battery pack to obtain the temperature abnormal battery pack; to detect the battery cell internal resistance of the temperature abnormal battery pack and generate the battery cell internal resistance value; to monitor the battery pack diffusion gas of the temperature abnormal battery pack and obtain the diffusion gas characteristics; The battery thermal safety control module is used to record the change of the internal resistance of the battery unit and obtain the internal resistance change data; detect the abnormal temperature change of the temperature-abnormal battery pack based on the internal resistance change data and generate the abnormal temperature change data; evaluate the degree of thermal runaway of the battery based on the diffusion gas characteristics and the abnormal temperature change data and obtain the degree of thermal runaway of the battery; perform dynamic thermal safety control on the temperature-abnormal battery pack according to the degree of thermal runaway of the battery and generate thermal safety control measures; The thermal runaway warning execution module is used to monitor the battery energy storage device in real time to obtain real-time monitoring data of the battery; to issue a thermal runaway warning to the real-time monitoring data of the battery and generate a thermal runaway warning signal; and to execute thermal safety control measures on the battery energy storage device based on the thermal runaway warning signal to complete the thermal safety management of the battery energy storage.

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