A lithium-ion battery fire detection method and system

Abstract

The present invention discloses a lithium-ion battery fire detection method and system, and relates to the field of battery fire detection. The lithium-ion battery fire detection method obtains historical state data and real-time state data of the lithium-ion battery when it is working, and performs comprehensive analysis to obtain the current voltage change rate, current current change rate, current surface temperature change rate, current chemical gas concentration change rate, current electrochemical impedance change rate, and current electrolyte state change rate of the lithium-ion battery when it is working, and performs comprehensive analysis in combination with the historical state data to obtain the current voltage change evaluation index and current current change evaluation index of the lithium-ion battery when it is working. The present invention can monitor and evaluate the state of the battery in real time by comprehensively analyzing historical and real-time data, quickly discover abnormal changes, and issue a fire warning in advance. Compared with traditional single parameter monitoring, it is more comprehensive, can effectively avoid misjudgment caused by parameter changes, and ensure the accuracy and timeliness of the warning.

Description

Technical Field

[0001] The present invention relates to the field of battery fire detection, and in particular to a lithium ion battery fire detection method and system. Background Art

[0002] With the transformation of energy structure and the improvement of environmental protection requirements, lithium-ion batteries have been widely used in electric vehicles, portable electronic devices, aerospace and large-scale energy storage systems due to their high energy density, long cycle life and good charge and discharge performance. However, lithium-ion batteries have many safety risks during use, such as overcharge, over-discharge, internal short circuit, mechanical damage and thermal runaway, the most serious of which are battery fire and explosion accidents. These accidents may not only cause significant property losses, but also threaten personnel safety and environmental safety.

[0003] Currently, safety monitoring technology for lithium-ion batteries mainly relies on the battery management system (BMS), which prevents the battery from operating beyond the safe range by monitoring battery parameters such as voltage, current and temperature. However, existing monitoring technologies often cannot fully predict and prevent all types of failures, especially those caused by electrolyte leakage, battery aging or physical damage, such as internal short circuits and thermal runaway.

[0004] Prior art, such as the invention patent application with announcement number: CN117523809B, discloses a new energy station AGC comprehensive performance evaluation method for a lithium-ion battery energy storage station fire monitoring evaluation management method, which includes the following steps: establishing a fire monitoring area in the lithium-ion battery energy storage station, and deploying a space particle monitoring system, a deformation monitoring system, and a temperature monitoring system in the fire monitoring area; collecting the output voltage and output current of the lithium-ion battery module, and calculating the fluctuation value of the output voltage and output current; calculating the fire risk coefficient of the lithium-ion battery module; evaluating the possible fire situation of the lithium-ion battery module according to the fire risk coefficient; evaluating the fire level of the lithium-ion battery module, forming different levels of fire signals or fault signals, and executing different fire extinguishing, cooling, and fault repair procedures. The present invention adopts the principle of "early detection and early disposal" for the lithium-ion battery energy storage station fire monitoring evaluation management method, and performs advanced detection and early warning of the primary stage of thermal runaway of lithium batteries in the energy storage module, so as to extinguish the fire in the bud.

[0005] Based on the above scheme, it is found that the limitations of the existing technology include at least the following problems. First, in the implementation of the existing technology, it is often limited to the real-time monitoring of a single or a small number of parameters, and lacks an in-depth understanding of the overall state of the lithium-ion battery, which can easily lead to insufficient monitoring of potential risks of the battery and difficulty in comprehensively predicting and preventing safety accidents such as fire. Secondly, the existing technology often ignores the importance of historical data and fails to use these data to enhance the prediction accuracy of the battery status, which can easily lead to in actual operation. Even when abnormal key parameters are monitored, it is difficult to accurately judge their actual impact on the battery health status, thereby significantly insufficient in ensuring battery safety and effectiveness. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides a lithium-ion battery fire detection method and system, which solves the problem that in the implementation of the prior art, the real-time monitoring of a single or a small number of parameters is often limited, and there is a lack of in-depth understanding of the overall state of the lithium-ion battery, which easily leads to insufficient monitoring of potential risks of the battery, and it is difficult to comprehensively predict and prevent safety accidents such as fire. Secondly, the prior art often ignores the importance of historical data and fails to use these data to enhance the prediction accuracy of the battery state, which easily leads to the problem that in actual operation, even when abnormal key parameters are monitored, it is difficult to accurately judge their actual impact on the battery health state, thereby significantly insufficient in ensuring the safety and effectiveness of the battery.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: a lithium-ion battery fire detection method, comprising the following steps: obtaining historical status data and real-time status data of the lithium-ion battery when it is working, the historical status data specifically being historical voltage data, historical current data, historical surface temperature data, historical chemical gas concentration data, historical electrochemical impedance data, and historical electrolyte status data, the real-time status data specifically being voltage value, current value, surface temperature value, chemical gas concentration value, electrochemical impedance value, and electrolyte status data at the current time point and the previous time point; performing a comprehensive analysis on the real-time status data of the lithium-ion battery when it is working, obtaining the current voltage change rate, current current change rate, current surface temperature change rate, current chemical gas concentration change rate, current electrochemical impedance change rate, and current electrolyte status change rate of the lithium-ion battery when it is working, and combining A comprehensive analysis is performed on the historical status data to obtain the current voltage change assessment index, the current current change assessment index, the current surface temperature change assessment index, the current chemical gas concentration change assessment index, the current electrochemical impedance change assessment index, and the current electrolyte state change assessment index when the lithium-ion battery is working; a comprehensive analysis is performed on the current voltage change assessment index, the current current change assessment index, the current surface temperature change assessment index, the current chemical gas concentration change assessment index, the current electrochemical impedance change assessment index, and the current electrolyte state change assessment index when the lithium-ion battery is working to obtain the current fire risk assessment index when the lithium-ion battery is working; it is determined whether the current fire risk assessment index when the lithium-ion battery is working is within a preset fire assessment range, and when the current fire risk assessment index is outside the preset fire assessment range, a fire prediction alarm is sent at the same time.

[0008] Further, the historical voltage data is specifically the historical voltage value at each historical time point each time the lithium-ion battery has worked in history, the historical current data is specifically the historical current value at each historical time point each time the lithium-ion battery has worked in history, the historical surface temperature data is specifically the historical surface temperature value at each historical time point each time the lithium-ion battery has worked in history, the historical chemical gas concentration data is specifically the historical chemical gas concentration value at each historical time point each time the lithium-ion battery has worked in history, the historical electrochemical impedance data is specifically the historical electrochemical impedance value at each historical time point each time the lithium-ion battery has worked in history, the historical electrolyte state data is specifically the historical conductivity value, historical viscosity value and historical pH value of the electrolyte at each historical time point each time the lithium-ion battery has worked in history, and the electrolyte state data is specifically the conductivity value, viscosity value and pH value at the current time point and the previous time point.

[0009] Furthermore, the specific steps for obtaining the current fire risk assessment index of the lithium-ion battery when it is working are as follows: normalizing the current voltage change assessment index, the current current change assessment index, the current surface temperature change assessment index, the current chemical gas concentration change assessment index, the current electrochemical impedance change assessment index, and the current electrolyte state assessment index when the lithium-ion battery is working; and comprehensively analyzing the normalized current voltage change assessment index, the current current change assessment index, the current surface temperature change assessment index, the current chemical gas concentration change assessment index, the current electrochemical impedance change assessment index, and the current electrolyte state assessment index when the lithium-ion battery is working to obtain the current fire risk assessment index when the lithium-ion battery is working.

[0010] Furthermore, the specific formula for calculating the current fire risk assessment index of the lithium-ion battery when it is working is as follows:

[0011] ;in, Current fire risk assessment index when working with lithium-ion batteries, It is the normalized current voltage change evaluation index of the lithium-ion battery during operation. is the voltage variation coefficient, It is the normalized current change evaluation index of the lithium-ion battery during operation. is the current variation coefficient, is the normalized current surface temperature change evaluation index of the lithium-ion battery during operation, is the surface temperature variation coefficient, It is the normalized evaluation index of the current chemical gas concentration change when the lithium-ion battery is working. is the coefficient of variation of chemical gas concentration, It is the normalized current electrochemical impedance change evaluation index of the lithium-ion battery during operation. is the electrochemical impedance variation coefficient, is the normalized evaluation index of the current electrolyte state of the lithium-ion battery during operation, is the electrolyte state change coefficient, is a natural constant, .

[0012] Furthermore, the specific steps of obtaining the current voltage change evaluation index of the lithium-ion battery when it is working are as follows: reading the historical voltage value at each time point of each historical operation of the lithium-ion battery and performing a comprehensive analysis to obtain several historical voltage change rates of the lithium-ion battery each time it is working in history; performing a mean analysis on several historical voltage change rates of the lithium-ion battery each time it is working in history in combination with the moving exponential average method to obtain an initial mean value of the historical voltage change rate of the lithium-ion battery each time it is working in history; performing a mean analysis on the initial mean value of the historical voltage change rate of the lithium-ion battery each time it is working in history to obtain a comprehensive mean value of the historical voltage change rate of the lithium-ion battery when it is working; performing a comprehensive analysis on the comprehensive mean value of the historical voltage change rate of the lithium-ion battery when it is working and the current voltage change rate to obtain the current voltage change evaluation index of the lithium-ion battery when it is working.

[0013] Furthermore, the specific formula for calculating the initial mean value of the historical voltage change rate of the lithium-ion battery at each historical operation, the comprehensive mean value of the historical voltage change rate of the lithium-ion battery at operation, and the current voltage change evaluation index is as follows: ;in, is the average voltage change rate when the lithium-ion battery is working, The first lithium-ion battery The initial average value of the historical voltage change rate during the first operation, The first lithium-ion battery The history of the first work The historical voltage change rate, The first lithium-ion battery The history of the first work The weighting coefficient of the historical voltage change rate is The first lithium-ion battery The history of the first work The historical voltage change rate, The first lithium-ion battery The history of the first work The weighting coefficient of the historical voltage change rate is It is the comprehensive average of the historical voltage change rate when the lithium-ion battery is working. , is the number of historical voltage change rates, , The number of times the lithium-ion battery has been operated. It is the current voltage change evaluation index when the lithium-ion battery is working. The current voltage change rate when working with lithium-ion batteries.

[0014] Furthermore, the specific steps of obtaining the current electrolyte state change evaluation index when the lithium-ion battery is working are as follows: weighted analysis is performed on the historical conductivity value, historical viscosity value, and historical pH value at each historical time point of each historical working of the lithium-ion battery to obtain the historical electrolyte state value at each historical time point of each historical working of the lithium-ion battery, and comprehensive analysis is performed to obtain several historical electrolyte state change rates of each historical working of the lithium-ion battery; weighted average method is used to perform mean analysis on several historical electrolyte state change rates of each historical working of the lithium-ion battery to obtain the initial mean value of the historical electrolyte state change rate of each historical working of the lithium-ion battery; mean analysis is performed on the initial mean value of the historical electrolyte state change rate of each historical working of the lithium-ion battery to obtain the comprehensive mean value of the historical electrolyte state change rate of the lithium-ion battery; comprehensive analysis is performed on the comprehensive mean value of the historical electrolyte state change rate of the lithium-ion battery and the current electrolyte state change rate to obtain the current electrolyte state evaluation index when the lithium-ion battery is working.

[0015] Furthermore, the specific formulas for calculating the historical electrolyte state value at each historical time point of each historical operation of the lithium-ion battery, the initial mean value of the historical electrolyte state change rate of each historical operation of the lithium-ion battery, the comprehensive mean value of the historical electrolyte state change rate of the lithium-ion battery when it is working, and the current electrolyte state evaluation index are as follows: ;in, The first lithium-ion battery The history of the first work The historical electrolyte state value at a time point, The first lithium-ion battery The history of the first work The historical conductivity value at each time point, is the conductivity coefficient stored in the database, The first lithium-ion battery The history of the first work The historical viscosity value at a time point, is the viscosity coefficient stored in the database, The first lithium-ion battery The history of the first work The historical pH value at a time point, is the PH coefficient stored in the database, , , is the number of time points, The first lithium-ion battery The initial mean value of the historical electrolyte state change rate during the first operation, The first lithium-ion battery The history of the first work The historical electrolyte state change rate, The first lithium-ion battery The history of the first work The weighted coefficient of the historical electrolyte state change rate, It is the comprehensive average of the historical electrolyte state change rate when the lithium-ion battery is working. The first lithium-ion battery The weighting coefficient of the initial mean value of the historical electrolyte state change rate during the first operation, It is an evaluation index of the current electrolyte state when the lithium-ion battery is working. is the current electrolyte state change rate when the lithium-ion battery is working, , is the number of historical voltage change rates, , It is the historical working times of lithium-ion battery.

[0016] Furthermore, the specific process of calculating the voltage variation coefficient, the current variation coefficient, the surface temperature variation coefficient, the chemical gas concentration variation coefficient, the electrochemical impedance variation coefficient, and the electrolyte state variation coefficient is as follows:

[0017] The comprehensive mean of the historical current change rate, the comprehensive mean of the historical surface temperature change rate, the comprehensive mean of the historical chemical gas concentration change rate, and the comprehensive mean of the historical electrochemical impedance change rate when the lithium-ion battery is working are obtained, and standardized with the comprehensive mean of the voltage change rate and the comprehensive mean of the historical electrolyte state change rate; the comprehensive mean of the voltage change rate, the comprehensive mean of the historical current change rate, the comprehensive mean of the historical surface temperature change rate, the comprehensive mean of the historical chemical gas concentration change rate, the comprehensive mean of the historical electrochemical impedance change rate, and the comprehensive mean of the historical electrolyte state change rate when the standardized lithium-ion battery is working are summed and analyzed to obtain the fire risk assessment value; the comprehensive mean of the voltage change rate, the comprehensive mean of the historical current change rate, the comprehensive mean of the historical surface temperature change rate, the comprehensive mean of the historical chemical gas concentration change rate, the comprehensive mean of the historical electrochemical impedance change rate, and the comprehensive mean of the historical electrolyte state change rate when the standardized lithium-ion battery is working are respectively analyzed with the fire risk assessment value, and the proportion analysis results are used as the corresponding coefficients.

[0018] A lithium-ion battery fire detection system comprises: a data acquisition module, an evaluation index calculation module, a comprehensive analysis module, and a judgment analysis module; the data acquisition module is used to acquire historical status data and real-time status data of the lithium-ion battery when it is working, the historical status data specifically includes historical voltage data, historical current data, historical surface temperature data, historical chemical gas concentration data, historical electrochemical impedance data, and historical electrolyte status data, and the real-time status data specifically includes voltage value, current value, surface temperature value, chemical gas concentration value, electrochemical impedance value, and electrolyte status data at the current time point and the previous time point; the evaluation index calculation module is used to perform a comprehensive analysis on the real-time status data of the lithium-ion battery when it is working, obtain the current voltage change rate, current current change rate, current surface temperature change rate, current chemical gas concentration change rate, current electrochemical impedance change rate, and current electrolyte status change rate when the lithium-ion battery is working, and A comprehensive analysis is performed in combination with the historical status data to obtain the current voltage change assessment index, current current change assessment index, current surface temperature change assessment index, current chemical gas concentration change assessment index, current electrochemical impedance change assessment index, and current electrolyte state change assessment index when the lithium-ion battery is working; the comprehensive analysis module is used to perform a comprehensive analysis on the current voltage change assessment index, current current change assessment index, current surface temperature change assessment index, current chemical gas concentration change assessment index, current electrochemical impedance change assessment index, and current electrolyte state change assessment index when the lithium-ion battery is working to obtain the current fire risk assessment index when the lithium-ion battery is working; the judgment analysis module is used to judge whether the current fire risk assessment index when the lithium-ion battery is working is within a preset fire assessment range, and when the current fire risk assessment index is outside the preset fire assessment range, a fire prediction alarm is sent at the same time.

[0019] The present invention has the following beneficial effects:

[0020] (1) This lithium-ion battery fire detection method can monitor and evaluate the battery status in real time by comprehensively analyzing historical and real-time data, quickly discover abnormal changes, and issue fire warnings in advance. Compared with traditional single parameter monitoring, it is more comprehensive and can effectively avoid misjudgments caused by parameter changes, ensuring the accuracy and timeliness of the warning.

[0021] (2) This lithium-ion battery fire detection method can not only predict and prevent fire risks by deeply analyzing the battery's history and current operating status, but also provide insights into battery performance degradation and help develop more effective maintenance strategies, which helps to extend battery life and reduce maintenance costs while maintaining the optimal performance of the battery system.

[0022] (3) This lithium-ion battery fire detection method greatly improves the safety performance of the battery system by instantly monitoring key safety parameters and quickly responding to potential fire risks. The automated risk assessment and early warning mechanism can effectively reduce human operating errors, ensure that measures are taken quickly when potential hazards are discovered, minimize the possibility and impact of accidents, and provide users and operators with a higher level of safety protection.

[0023] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 The present invention is a flow chart of a lithium-ion battery fire detection method.

[0025] Figure 2 The present invention is a flowchart of the steps in a lithium-ion battery fire detection method.

[0026] Figure 3 The present invention is a block diagram of a lithium-ion battery fire detection system. DETAILED DESCRIPTION

[0027] The embodiment of the present application provides a lithium-ion battery fire detection method and system to solve the problem that in the implementation of the prior art, the real-time monitoring of a single or a small number of parameters is often limited, and there is a lack of in-depth understanding of the overall state of the lithium-ion battery, which easily leads to insufficient monitoring of potential risks of the battery and difficulty in comprehensively predicting and preventing safety accidents such as fires. Secondly, the importance of historical data is often ignored in the prior art, and these data are not used to enhance the prediction accuracy of the battery state, which easily leads to the difficulty in accurately judging the actual impact of abnormal key parameters on the battery health state in actual operation, even when abnormal key parameters are monitored, resulting in significant deficiencies in ensuring battery safety and effectiveness.

[0028] The overall idea of ​​the problem in the embodiment of this application is as follows:

[0029] First, the system collects the voltage, current, surface temperature, chemical gas concentration, electrochemical impedance and electrolyte state data (including conductivity, viscosity and pH value) of the lithium-ion battery at various time points in the historical working cycle. At the same time, the system also collects the corresponding data at the current and previous time points to calculate the real-time state changes, and calculates the current change rate of the collected real-time data, such as the voltage change rate, current change rate, etc., and uses historical data to analyze and calculate the historical means of various indicators, and combine these historical means with the current change rate to generate the current evaluation index, such as the voltage change evaluation index, etc. All current evaluation indices are normalized and comprehensively analyzed to generate a comprehensive fire risk assessment index. The system determines whether the current fire risk assessment index exceeds the preset safety range, and sends a fire warning when it exceeds the range, and initiates corresponding safety measures.

[0030] See also Figure 1 The embodiment of the present invention provides a technical solution: a lithium-ion battery fire detection method, comprising the following steps: obtaining historical status data and real-time status data of the lithium-ion battery when it is working, the historical status data specifically being historical voltage data, historical current data, historical surface temperature data, historical chemical gas concentration data, historical electrochemical impedance data, and historical electrolyte status data, and the real-time status data specifically being voltage value, current value, surface temperature value, chemical gas concentration value, electrochemical impedance value, and electrolyte status data at the current time point and the previous time point; performing a comprehensive analysis on the real-time status data of the lithium-ion battery when it is working to obtain the current voltage change rate, current current change rate, current surface temperature change rate, current chemical gas concentration change rate, current electrochemical impedance change rate, and current electrolyte state change rate of the lithium-ion battery when it is working, and performing a comprehensive analysis in combination with the historical status data to obtain the current voltage change evaluation index, current current change evaluation index, and current surface temperature change evaluation index of the lithium-ion battery when it is working. The evaluation index, current chemical gas concentration change evaluation index, current electrochemical impedance change evaluation index, and current electrolyte state change evaluation index are calculated, wherein the calculation logic of each change rate is consistent, for example: current voltage change rate = (voltage value at the current time point - voltage value at the previous time point) / duration of the time point; the current voltage change evaluation index, current current change evaluation index, current surface temperature change evaluation index, current chemical gas concentration change evaluation index, current electrochemical impedance change evaluation index, and current electrolyte state change evaluation index when the lithium-ion battery is working are comprehensively analyzed to obtain the current fire risk assessment index when the lithium-ion battery is working; whether the current fire risk assessment index when the lithium-ion battery is working is within a preset fire assessment range, and when the current fire risk assessment index is outside the preset fire assessment range, a fire prediction alarm is sent to relevant staff, and abnormal identification is performed for each index, and the abnormal index is marked and sent to relevant staff at the same time.

[0031] The historical voltage data specifically refers to the historical voltage value at each historical time point each time the lithium-ion battery has worked in history, the historical current data specifically refers to the historical current value at each historical time point each time the lithium-ion battery has worked in history, the historical surface temperature data specifically refers to the historical surface temperature value at each historical time point each time the lithium-ion battery has worked in history, the historical chemical gas concentration data specifically refers to the historical chemical gas concentration value at each historical time point each time the lithium-ion battery has worked in history, the historical electrochemical impedance data specifically refers to the historical electrochemical impedance value at each historical time point each time the lithium-ion battery has worked in history, the historical electrolyte state data specifically refers to the historical conductivity value, historical viscosity value and historical pH value of the electrolyte at each historical time point each time the lithium-ion battery has worked in history, and the electrolyte state data specifically refers to the conductivity value, viscosity value and pH value at the current time point and the previous time point.

[0032] It should be explained that, among them, the voltage is obtained by using a high-precision voltage measuring instrument, the current is obtained by a current sensor installed in the battery circuit, the surface temperature is obtained by using a surface temperature sensor, the chemical gas concentration number is obtained by a chemical gas sensor, the electrochemical impedance is obtained by an electrochemical impedance spectrometer (EIS), the conductivity is obtained by a conductivity meter, the viscosity is obtained by a viscometer, such as a rotational viscometer, and the pH value is obtained by a pH meter.

[0033] Specifically, Figure 2 As shown, the specific steps for obtaining the current fire risk assessment index of the lithium-ion battery when it is working are as follows: normalize the current voltage change assessment index, the current current change assessment index, the current surface temperature change assessment index, the current chemical gas concentration change assessment index, the current electrochemical impedance change assessment index, and the current electrolyte state assessment index when the lithium-ion battery is working; and comprehensively analyze the normalized current voltage change assessment index, the current current change assessment index, the current surface temperature change assessment index, the current chemical gas concentration change assessment index, the current electrochemical impedance change assessment index, and the current electrolyte state assessment index when the lithium-ion battery is working to obtain the current fire risk assessment index when the lithium-ion battery is working.

[0034] The specific formula for calculating the current fire risk assessment index when lithium-ion batteries are working is as follows: ;in, Current fire risk assessment index when working with lithium-ion batteries, It is the normalized current voltage change evaluation index of the lithium-ion battery during operation. is the voltage variation coefficient, It is the normalized current change evaluation index of the lithium-ion battery during operation. is the current variation coefficient, is the normalized current surface temperature change evaluation index of the lithium-ion battery during operation, is the surface temperature variation coefficient, It is the normalized evaluation index of the current chemical gas concentration change when the lithium-ion battery is working. is the coefficient of variation of chemical gas concentration, It is the normalized current electrochemical impedance change evaluation index of the lithium-ion battery during operation. is the electrochemical impedance variation coefficient, is the normalized evaluation index of the current electrolyte state of the lithium-ion battery during operation, is the electrolyte state change coefficient, is a natural constant, .

[0035] In this embodiment, by integrating the change rates of multiple key parameters (voltage, current, surface temperature, chemical gas concentration, electrochemical impedance and electrolyte state) and normalizing these change rates, the method can dynamically evaluate the fire risk of lithium-ion batteries at any given time point. This comprehensive analysis takes into account multiple aspects of the battery state and provides a comprehensive risk profile, providing more comprehensive safety protection than monitoring a single or a few parameters. The method analyzes the battery's operating data in real time and quickly responds to any changes that may cause safety problems, providing data support for timely warnings. For example, if the change rate of a parameter suddenly increases, the system can immediately calculate An updated fire risk assessment index is generated, and an alarm is sounded when the index exceeds the safe range. This real-time monitoring and immediate response mechanism greatly improves the efficiency of handling potential safety threats and reduces possible damage and risks. The normalization and coefficient weighting methods allow the contribution of different parameters to the overall risk assessment to be adjusted according to their importance. For example, if experimental and empirical data show that a small change in the electrolyte state has a greater impact on safety, this can be reflected by adjusting the corresponding coefficient. This provides battery managers with a powerful decision support tool to help them formulate operating strategies, optimize maintenance plans, and implement necessary safety measures based on real-time data and precise risk assessments.

[0036] Specifically, the specific steps of obtaining the current voltage change evaluation index when the lithium-ion battery is working are as follows: reading the historical voltage value at each time point in the history of each working of the lithium-ion battery and performing a comprehensive analysis to obtain several historical voltage change rates in the history of each working of the lithium-ion battery; performing a mean analysis on several historical voltage change rates in the history of each working of the lithium-ion battery in combination with the moving exponential average method to obtain an initial mean value of the historical voltage change rate in the history of each working of the lithium-ion battery; performing a mean analysis on the initial mean value of the historical voltage change rate in the history of each working of the lithium-ion battery to obtain a comprehensive mean value of the historical voltage change rate in the history of the lithium-ion battery; performing a comprehensive analysis on the comprehensive mean value of the historical voltage change rate in the history of the lithium-ion battery and the current voltage change rate to obtain the current voltage change evaluation index when the lithium-ion battery is working.

[0037] The specific formula for calculating the initial mean value of the historical voltage change rate of the lithium-ion battery at each historical operation, the comprehensive mean value of the historical voltage change rate of the lithium-ion battery at operation, and the current voltage change evaluation index is as follows: ;in, is the average voltage change rate when the lithium-ion battery is working, The first lithium-ion battery The initial average value of the historical voltage change rate during the first operation, The first lithium-ion battery The history of the first work The historical voltage change rate, The first lithium-ion battery The history of the first work The weighting coefficient of the historical voltage change rate is The first lithium-ion battery The history of the first work The historical voltage change rate, The first lithium-ion battery The history of the first work The weighting coefficient of the historical voltage change rate is It is the comprehensive average of the historical voltage change rate when the lithium-ion battery is working. , is the number of historical voltage change rates, , The number of times the lithium-ion battery has been operated. It is the current voltage change evaluation index when the lithium-ion battery is working. The current voltage change rate when working with lithium-ion batteries.

[0038] It needs to be explained that the specific formulas for calculating the initial mean value of the historical current change rate, the initial mean value of the historical surface temperature change rate, the initial mean value of the historical chemical gas concentration change rate, and the initial mean value of the historical electrochemical impedance change rate for each historical operation of the lithium-ion battery use the same logic as the specific formula for calculating the initial mean value of the historical voltage change rate for each historical operation of the lithium-ion battery.

[0039] The specific formulas for calculating the comprehensive mean of the historical current change rate, the comprehensive mean of the historical surface temperature change rate, the comprehensive mean of the historical chemical gas concentration change rate, and the comprehensive mean of the historical electrochemical impedance change rate when the lithium-ion battery is working use the same logic as the specific formula for calculating the comprehensive mean of the historical voltage change rate when the lithium-ion battery is working.

[0040] The specific formulas for calculating the current current change assessment index, the current surface temperature change assessment index, the current chemical gas concentration change assessment index, and the current electrochemical impedance change assessment index when the lithium-ion battery is working are consistent with the logic used in the specific formula for calculating the current voltage change assessment index when the lithium-ion battery is working.

[0041] and, , The specific calculation process is as follows: The history of the first work , The historical voltage change rates are added together to obtain the lithium-ion battery history The historical voltage change rate and value when the lithium-ion battery is working for the first time, and then the The history of the first work , The historical voltage change rates are respectively calculated by ratio with the historical voltage change rates and values, and the ratio results are used as the corresponding weighting coefficients.

[0042] In this implementation scheme, by comprehensively analyzing the historical voltage change rate and calculating the initial mean and the comprehensive mean, the method can accurately track the performance trend of the battery under different working conditions. This trend analysis helps to predict possible future behavior patterns, especially when voltage fluctuations may indicate battery performance degradation or potential failures. Accurate predictions can not only warn of potential fire risks in advance, but also provide a scientific basis for battery maintenance and replacement decisions. By combining the analysis results of the historical voltage change rate with the real-time voltage change rate, the battery status can be monitored in real time and abnormal situations can be responded to quickly. This real-time monitoring mechanism allows the operation team to take immediate measures when abnormal voltage fluctuations occur, such as adjusting the charging strategy, suspending use, or initiating safety protocols, thereby significantly reducing accidents. The risks of occurrence and potential equipment damage, the use of moving exponential average method and other statistical techniques to analyze the voltage change rate, not only helps in real-time risk assessment, but also can optimize the battery usage strategy to keep the battery in the best working condition. For example, by identifying the specific working mode or external conditions that cause voltage fluctuations, the battery's operating parameters can be adjusted to reduce hardware stress, thereby extending the battery's service life and improving its overall performance. This method provides a data-based decision support tool that enables the operations team to make more informed decisions based on detailed historical data and real-time performance analysis. By continuously monitoring and evaluating voltage changes, the behavior of the battery and potential safety hazards can be better understood, thereby implementing more effective risk management and emergency response strategies in daily operations.

[0043] Specifically, the specific steps of obtaining the current electrolyte state change evaluation index when the lithium-ion battery is working are as follows: weighted analysis is performed on the historical conductivity value, historical viscosity value, and historical pH value at each historical time point of each historical working time of the lithium-ion battery to obtain the historical electrolyte state value at each historical time point of each historical working time of the lithium-ion battery, and comprehensive analysis is performed to obtain several historical electrolyte state change rates of each historical working time of the lithium-ion battery; weighted average method is used to perform mean analysis on several historical electrolyte state change rates of each historical working time of the lithium-ion battery to obtain the initial mean value of the historical electrolyte state change rate of each historical working time of the lithium-ion battery; mean analysis is performed on the initial mean value of the historical electrolyte state change rate of each historical working time of the lithium-ion battery to obtain the comprehensive mean value of the historical electrolyte state change rate of the lithium-ion battery; comprehensive analysis is performed on the comprehensive mean value of the historical electrolyte state change rate of the lithium-ion battery and the current electrolyte state change rate to obtain the current electrolyte state evaluation index when the lithium-ion battery is working.

[0044] The specific formulas for calculating the historical electrolyte state value at each time point in the history of each operation of the lithium-ion battery, the initial mean value of the historical electrolyte state change rate in each operation of the lithium-ion battery, the comprehensive mean value of the historical electrolyte state change rate when the lithium-ion battery is working, and the current electrolyte state evaluation index are as follows: ;in, The first lithium-ion battery The history of the first work The historical electrolyte state value at a time point, The first lithium-ion battery The history of the first work The historical conductivity value at each time point, is the conductivity coefficient stored in the database, The first lithium-ion battery The history of the first work The historical viscosity value at a time point, is the viscosity coefficient stored in the database, The first lithium-ion battery The history of the first work The historical pH value at a time point, is the PH coefficient stored in the database, , , is the number of time points, The first lithium-ion battery The initial mean value of the historical electrolyte state change rate during the first operation, The first lithium-ion battery The history of the first work The historical electrolyte state change rate, The first lithium-ion battery The history of the first work The weighted coefficient of the historical electrolyte state change rate, It is the comprehensive average of the historical electrolyte state change rate when the lithium-ion battery is working. The first lithium-ion battery The weighting coefficient of the initial mean value of the historical electrolyte state change rate during the first operation, It is an evaluation index of the current electrolyte state when the lithium-ion battery is working. is the current electrolyte state change rate when the lithium-ion battery is working, , is the number of historical voltage change rates, and , , It is the historical working times of lithium-ion battery.

[0045] It needs to be explained that , , The specific calculation process is as follows: read the historical conductivity value, historical viscosity value, and historical pH value at each time point in the history of each working of the lithium-ion battery, and perform mean analysis in combination with the weighted average method to obtain the initial mean value of the historical conductivity, the initial mean value of the historical viscosity, and the initial mean value of the historical pH of the lithium-ion battery each time it works in history; perform mean analysis on the initial mean value of the historical conductivity, the initial mean value of the historical viscosity, and the initial mean value of the historical pH of the lithium-ion battery each time it works in history, and obtain the comprehensive mean value of the historical conductivity, the comprehensive mean value of the historical viscosity, and the comprehensive mean value of the historical pH of the lithium-ion battery when it works; sum and analyze the comprehensive mean values ​​of the historical conductivity, the comprehensive mean value of the historical viscosity, and the comprehensive mean value of the historical pH of the lithium-ion battery when it works to obtain the electrolyte sum value; perform proportion analysis on the comprehensive mean values ​​of the historical conductivity, the comprehensive mean value of the historical viscosity, and the comprehensive mean value of the historical pH of the lithium-ion battery when it works, respectively, and the electrolyte sum value to obtain the conductivity coefficient, viscosity coefficient, and pH coefficient.

[0046] And, the specific calculation process of is: add up each historical electrolyte state change rate of the lithium-ion battery when it works for the time in history, and obtain the historical electrolyte state change sum value of the lithium-ion battery when it works for the time in history, and then calculate the ratio of the historical electrolyte state change rate of the lithium-ion battery when it works for the time in history to the historical electrolyte state change sum value of the lithium-ion battery when it works for the time in history, and the result is the corresponding weighting coefficient.

[0047] And, the specific calculation process of is: add up the initial mean values ​​of the historical electrolyte state change rate of the lithium-ion battery for each historical working time to obtain the total value of the historical electrolyte state change of the lithium-ion battery for the th working time in history, and then calculate the ratio of the initial mean value of the historical electrolyte state change rate of the lithium-ion battery for the th working time in history to the total value of the historical electrolyte state change, and the result is the corresponding weighting coefficient.

[0048] In this embodiment, a comprehensive electrolyte status analysis is provided by integrating historical and real-time conductivity, viscosity and pH data. This comprehensive analysis helps to more fully understand the health of the electrolyte, because the status of the electrolyte has a direct impact on the overall performance and safety of the battery. For example, changes in conductivity can indicate changes in ion concentration, changes in viscosity may reflect chemical degradation of the electrolyte, and changes in pH can indicate potential chemical imbalances. Through continuous monitoring and in-depth analysis of the electrolyte status, the method can identify changes that may lead to battery performance degradation or safety risks in advance. For example, by tracking historical changes in electrolyte viscosity and pH, problems caused by electrolyte degradation, such as internal short circuits or overheating, can be predicted and prevented, thereby effectively preventing fires and other safety accidents. The data provided by this evaluation method can help operators The operation team can make more scientific maintenance decisions, such as when to replace the electrolyte or take other maintenance measures to maintain the optimal operating state of the battery. By analyzing the trend of the electrolyte state, the battery life and performance can be optimized and the risk of unexpected downtime can be reduced. This method can also help optimize the management and performance of the battery. By continuously monitoring the state of the electrolyte and combining it with other operating data of the battery (such as voltage, current and temperature), the battery's charge and discharge strategy can be adjusted more accurately to ensure that the battery operates within safe operating parameters, thereby improving energy efficiency and extending the battery's service life. Through regular and systematic electrolyte state assessment, problems that may be caused by the electrolyte can be discovered and resolved in a timely manner, greatly enhancing the safety of the system. This preventive measure reduces the possibility of fire and other safety risks caused by electrolyte degradation, and provides a higher level of protection for users and equipment.

[0049] Specifically, the specific process of calculating the voltage variation coefficient, the current variation coefficient, the surface temperature variation coefficient, the chemical gas concentration variation coefficient, the electrochemical impedance variation coefficient, and the electrolyte state variation coefficient is as follows: obtaining the comprehensive mean of the historical current variation rate, the comprehensive mean of the historical surface temperature variation rate, the comprehensive mean of the historical chemical gas concentration variation rate, and the comprehensive mean of the historical electrochemical impedance variation rate when the lithium-ion battery is working, and standardizing them with the comprehensive mean of the voltage variation rate and the comprehensive mean of the historical electrolyte state variation rate; standardizing the comprehensive mean of the voltage variation rate, the comprehensive mean of the historical current variation rate, and the historical electrolyte state variation rate when the lithium-ion battery is working. The comprehensive mean of historical surface temperature change rate, the comprehensive mean of historical chemical gas concentration change rate, the comprehensive mean of historical electrochemical impedance change rate, and the comprehensive mean of historical electrolyte state change rate are summed up and analyzed to obtain the fire risk assessment and value; the comprehensive mean of voltage change rate of standardized lithium-ion batteries during operation, the comprehensive mean of historical current change rate, the comprehensive mean of historical surface temperature change rate, the comprehensive mean of historical chemical gas concentration change rate, the comprehensive mean of historical electrochemical impedance change rate, and the comprehensive mean of historical electrolyte state change rate are respectively analyzed with the fire risk assessment and value, and the results of the proportion analysis are used as the corresponding coefficients.

[0050] In this implementation scheme, by standardizing and summing the change rates of various key parameters (such as voltage, current, surface temperature, etc.), this method provides a quantitative way to assess the overall fire risk. This quantitative risk management allows operators to understand the risk level through specific numbers rather than relying solely on subjective judgment, thereby providing a more scientific and accurate risk assessment method. By calculating the contribution of each parameter to the overall fire risk (i.e., proportion analysis), the operation and maintenance team can determine which factors have the greatest impact on safety, so as to prioritize resources for monitoring and intervention. For example, if it is found that the current change rate has the highest contribution, then it may be necessary to strengthen the control and monitoring of the charging and discharging process. , to prevent the risk of fire caused by overcharging or over-discharging. By integrating multiple change rate indicators, this method can comprehensively reflect the battery status and potential risks, which can not only improve the accuracy of the early warning system, but also issue an alarm in time before the risk actually takes shape. This is crucial to preventing fires and other safety accidents, especially in key battery-dependent applications such as electric vehicles and energy storage systems. This evaluation method also provides a basis for continuous improvement. By regularly analyzing the impact and proportion of each change rate, the design, use and maintenance strategies of the battery can be continuously optimized. For example, if the analysis finds that a particular batch of batteries exhibits a higher risk under specific conditions, the manufacturing process or usage guidelines can be adjusted accordingly.

[0051] See also Figure 3The embodiment of the present invention provides a technical solution: a lithium-ion battery fire detection system, including: a data acquisition module, an evaluation index calculation module, a comprehensive analysis module, and a judgment analysis module; the data acquisition module is used to obtain historical status data and real-time status data of the lithium-ion battery when it is working, the historical status data is specifically historical voltage data, historical current data, historical surface temperature data, historical chemical gas concentration data, historical electrochemical impedance data, and historical electrolyte status data, and the real-time status data is specifically the voltage value, current value, surface temperature value, chemical gas concentration value, electrochemical impedance value, and electrolyte status data at the current time point and the previous time point; the evaluation index calculation module is used to comprehensively analyze the real-time status data of the lithium-ion battery when it is working, and obtain the current voltage change rate, current current change rate, current surface temperature change rate, current chemical gas concentration change rate, current electrochemical impedance change rate, current electrolyte status data, and the evaluation index calculation module. The state change rate is calculated, and a comprehensive analysis is performed in combination with the historical state data to obtain the current voltage change assessment index, the current current change assessment index, the current surface temperature change assessment index, the current chemical gas concentration change assessment index, the current electrochemical impedance change assessment index, and the current electrolyte state change assessment index when the lithium-ion battery is working; a comprehensive analysis module is used to comprehensively analyze the current voltage change assessment index, the current current change assessment index, the current surface temperature change assessment index, the current chemical gas concentration change assessment index, the current electrochemical impedance change assessment index, and the current electrolyte state change assessment index when the lithium-ion battery is working to obtain the current fire risk assessment index when the lithium-ion battery is working; a judgment analysis module is used to judge whether the current fire risk assessment index when the lithium-ion battery is working is within a preset fire assessment range, and when the current fire risk assessment index is outside the preset fire assessment range, a fire prediction alarm is sent at the same time.

[0052] In summary, this application has at least the following effects:

[0053] By comprehensively analyzing historical and real-time data, it is possible to monitor and evaluate the status of the battery in real time, quickly discover abnormal changes, and issue fire warnings in advance. Compared with traditional single parameter monitoring, it is more comprehensive and can effectively avoid misjudgments caused by parameter changes, ensuring the accuracy and timeliness of the warning.

[0054] By deeply analyzing the battery’s history and current operating status, it is not only possible to predict and prevent fire risks, but also provide insights into battery performance degradation to help develop more effective maintenance strategies, which helps extend battery life and reduce maintenance costs while maintaining optimal performance of the battery system.

[0055] By real-time monitoring of key safety parameters and rapid response to potential fire risks, the safety performance of the battery system is greatly improved. The automated risk assessment and early warning mechanism can effectively reduce human operational errors, ensure that measures are taken quickly when potential dangers are discovered, minimize the possibility and impact of accidents, and provide users and operators with a higher level of safety protection.

[0056] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0057] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A lithium-ion battery fire detection method, characterized in that: The following steps are involved: Acquire historical status data and real-time status data of the lithium-ion battery when it is working, the historical status data specifically includes historical voltage data, historical current data, historical surface temperature data, historical chemical gas concentration data, historical electrochemical impedance data, and historical electrolyte status data, and the real-time status data specifically includes voltage value, current value, surface temperature value, chemical gas concentration value, electrochemical impedance value, and electrolyte status data at the current time point and the previous time point; Comprehensively analyze the real-time status data of the lithium-ion battery when it is working, and obtain the current voltage change rate, current current change rate, current surface temperature change rate, current chemical gas concentration change rate, current electrochemical impedance change rate, and current electrolyte state change rate of the lithium-ion battery when it is working, and conduct a comprehensive analysis in combination with the historical status data to obtain the current voltage change evaluation index, current current change evaluation index, current surface temperature change evaluation index, current chemical gas concentration change evaluation index, current electrochemical impedance change evaluation index, and current electrolyte state change evaluation index when the lithium-ion battery is working; Comprehensively analyze the current voltage change assessment index, current current change assessment index, current surface temperature change assessment index, current chemical gas concentration change assessment index, current electrochemical impedance change assessment index, and current electrolyte state change assessment index when the lithium-ion battery is working, and obtain the current fire risk assessment index when the lithium-ion battery is working; Determine whether the current fire risk assessment index of the lithium-ion battery when it is working is within the preset fire assessment range, and send a fire prediction alarm when the current fire risk assessment index is outside the preset fire assessment range; The specific formula for calculating the current fire risk assessment index when lithium-ion batteries are working is as follows: ； in, Current fire risk assessment index when working with lithium-ion batteries, It is the normalized current voltage change evaluation index of the lithium-ion battery during operation. is the voltage variation coefficient, It is the normalized current change evaluation index of the lithium-ion battery during operation. is the current variation coefficient, is the normalized current surface temperature change evaluation index of the lithium-ion battery during operation, is the surface temperature variation coefficient, It is the normalized evaluation index of the current chemical gas concentration change when the lithium-ion battery is working. is the coefficient of variation of chemical gas concentration, It is the normalized current electrochemical impedance change evaluation index of the lithium-ion battery during operation. is the electrochemical impedance variation coefficient, is the normalized evaluation index of the current electrolyte state of the lithium-ion battery during operation, is the electrolyte state change coefficient, is a natural constant, ; The specific steps for obtaining the current voltage change evaluation index when the lithium-ion battery is working are as follows: Read the historical voltage value of each time point of each historical operation of the lithium-ion battery and conduct a comprehensive analysis to obtain several historical voltage change rates of each historical operation of the lithium-ion battery; Performing mean analysis on several historical voltage change rates of the lithium-ion battery at each historical operation by using the moving exponential average method, and obtaining the initial mean value of the historical voltage change rate of the lithium-ion battery at each historical operation; Performing mean analysis on the initial mean of the historical voltage change rate of the lithium-ion battery during each operation to obtain the comprehensive mean of the historical voltage change rate of the lithium-ion battery during operation; The comprehensive average of the historical voltage change rates of the lithium-ion battery when it is working and the current voltage change rate are comprehensively analyzed to obtain the current voltage change evaluation index of the lithium-ion battery when it is working.

2. The lithium-ion battery fire detection method according to claim 1, characterized in that: The historical voltage data specifically refers to the historical voltage value at each historical time point each time the lithium-ion battery has worked in history, the historical current data specifically refers to the historical current value at each historical time point each time the lithium-ion battery has worked in history, the historical surface temperature data specifically refers to the historical surface temperature value at each historical time point each time the lithium-ion battery has worked in history, the historical chemical gas concentration data specifically refers to the historical chemical gas concentration value at each historical time point each time the lithium-ion battery has worked in history, the historical electrochemical impedance data specifically refers to the historical electrochemical impedance value at each historical time point each time the lithium-ion battery has worked in history, the historical electrolyte state data specifically refers to the historical conductivity value, historical viscosity value and historical pH value of the electrolyte at each historical time point each time the lithium-ion battery has worked in history, and the electrolyte state data specifically refers to the conductivity value, viscosity value and pH value at the current time point and the previous time point.

3. The lithium-ion battery fire detection method according to claim 1, characterized in that: The specific steps for obtaining the current fire risk assessment index of lithium-ion batteries when working are as follows: Normalizing the current voltage change evaluation index, the current current change evaluation index, the current surface temperature change evaluation index, the current chemical gas concentration change evaluation index, the current electrochemical impedance change evaluation index, and the current electrolyte state evaluation index when the lithium-ion battery is working; A comprehensive analysis is performed on the normalized current voltage change assessment index, current current change assessment index, current surface temperature change assessment index, current chemical gas concentration change assessment index, current electrochemical impedance change assessment index, and current electrolyte state assessment index of the lithium-ion battery when working to obtain the current fire risk assessment index of the lithium-ion battery when working.

4. The lithium-ion battery fire detection method according to claim 1, characterized in that: The specific formula for calculating the initial mean value of the historical voltage change rate of the lithium-ion battery at each historical operation, the comprehensive mean value of the historical voltage change rate of the lithium-ion battery at operation, and the current voltage change evaluation index is as follows: ; in, is the average voltage change rate when the lithium-ion battery is working, The first lithium-ion battery The initial average value of the historical voltage change rate during the first operation, The first lithium-ion battery The history of the first work The historical voltage change rate, The first lithium-ion battery The history of the first work The weighting coefficient of the historical voltage change rate is The first lithium-ion battery The history of the first work The historical voltage change rate, The first lithium-ion battery The history of the first work The weighting coefficient of the historical voltage change rate is It is the comprehensive average of the historical voltage change rate when the lithium-ion battery is working. , is the number of historical voltage change rates, , The number of times the lithium-ion battery has been operated. It is the current voltage change evaluation index when the lithium-ion battery is working. The current voltage change rate when working with lithium-ion batteries.

5. The lithium-ion battery fire detection method according to claim 4, characterized in that: The specific steps for obtaining the current electrolyte state change evaluation index when the lithium-ion battery is working are as follows: Perform weighted analysis on the historical conductivity value, historical viscosity value, and historical pH value at each historical time point of each historical operation of the lithium-ion battery to obtain the historical electrolyte state value at each historical time point of each historical operation of the lithium-ion battery, and perform comprehensive analysis to obtain several historical electrolyte state change rates of each historical operation of the lithium-ion battery; Performing mean analysis on several historical electrolyte state change rates of each operation of the lithium-ion battery using a weighted average method, and obtaining an initial mean value of the historical electrolyte state change rate of each operation of the lithium-ion battery; Performing mean analysis on the initial mean values ​​of the historical electrolyte state change rates during each operation of the lithium-ion battery, and obtaining the comprehensive mean value of the historical electrolyte state change rates during the operation of the lithium-ion battery; The comprehensive mean of the historical electrolyte state change rate when the lithium-ion battery is working and the current electrolyte state change rate are comprehensively analyzed to obtain the current electrolyte state evaluation index when the lithium-ion battery is working.

6. The lithium-ion battery fire detection method according to claim 5, characterized in that: The specific formulas for calculating the historical electrolyte state value at each time point in the history of each operation of the lithium-ion battery, the initial mean value of the historical electrolyte state change rate in each operation of the lithium-ion battery, the comprehensive mean value of the historical electrolyte state change rate when the lithium-ion battery is working, and the current electrolyte state evaluation index are as follows: ； in, The first lithium-ion battery The history of the first work The historical electrolyte state value at a time point, The first lithium-ion battery The history of the first work The historical conductivity value at each time point, is the conductivity coefficient stored in the database, The first lithium-ion battery The history of the first work The historical viscosity value at a time point, is the viscosity coefficient stored in the database, The first lithium-ion battery The history of the first work The historical pH value at a time point, is the PH coefficient stored in the database, , , is the number of time points, The first lithium-ion battery The initial mean value of the historical electrolyte state change rate during the first operation, The first lithium-ion battery The history of the first work The historical electrolyte state change rate, The first lithium-ion battery The history of the first work The weighted coefficient of the historical electrolyte state change rate, It is the comprehensive average of the historical electrolyte state change rate when the lithium-ion battery is working. The first lithium-ion battery The weighting coefficient of the initial mean value of the historical electrolyte state change rate during the first operation, It is an evaluation index of the current electrolyte state when the lithium-ion battery is working. is the current electrolyte state change rate when the lithium-ion battery is working, , is the number of historical voltage change rates, , It is the historical working times of lithium-ion battery.

7. The lithium-ion battery fire detection method according to claim 6, characterized in that: The specific process of calculating the voltage variation coefficient, current variation coefficient, surface temperature variation coefficient, chemical gas concentration variation coefficient, electrochemical impedance variation coefficient, and electrolyte state variation coefficient is as follows: Obtain the comprehensive mean of the historical current change rate, the comprehensive mean of the historical surface temperature change rate, the comprehensive mean of the historical chemical gas concentration change rate, and the comprehensive mean of the historical electrochemical impedance change rate when the lithium-ion battery is working, and perform standardization with the comprehensive mean of the voltage change rate and the comprehensive mean of the historical electrolyte state change rate; The standardized comprehensive mean of the voltage change rate of lithium-ion batteries during operation, the comprehensive mean of the historical current change rate, the comprehensive mean of the historical surface temperature change rate, the comprehensive mean of the historical chemical gas concentration change rate, the comprehensive mean of the historical electrochemical impedance change rate, and the comprehensive mean of the historical electrolyte state change rate are summed up and analyzed to obtain the fire risk assessment value; The comprehensive mean value of the voltage change rate of the standardized lithium-ion batteries during operation, the comprehensive mean value of the historical current change rate, the comprehensive mean value of the historical surface temperature change rate, the comprehensive mean value of the historical chemical gas concentration change rate, the comprehensive mean value of the historical electrochemical impedance change rate, and the comprehensive mean value of the historical electrolyte state change rate were respectively analyzed with the fire risk assessment value and the value, and the results of the proportion analysis were used as the corresponding coefficients.

8. A lithium-ion battery fire detection system, using the lithium-ion battery fire detection method according to any one of claims 1 to 7, characterized in that: include: Data acquisition module, evaluation index calculation module, comprehensive analysis module, judgment analysis module; The data acquisition module is used to acquire historical status data and real-time status data of the lithium-ion battery when it is working, the historical status data specifically includes historical voltage data, historical current data, historical surface temperature data, historical chemical gas concentration data, historical electrochemical impedance data, and historical electrolyte status data, and the real-time status data specifically includes voltage value, current value, surface temperature value, chemical gas concentration value, electrochemical impedance value, and electrolyte status data at the current time point and the previous time point; The evaluation index calculation module is used to comprehensively analyze the real-time status data of the lithium-ion battery when it is working, and obtain the current voltage change rate, current current change rate, current surface temperature change rate, current chemical gas concentration change rate, current electrochemical impedance change rate, and current electrolyte state change rate of the lithium-ion battery when it is working, and to perform a comprehensive analysis in combination with the historical status data to obtain the current voltage change evaluation index, current current change evaluation index, current surface temperature change evaluation index, current chemical gas concentration change evaluation index, current electrochemical impedance change evaluation index, and current electrolyte state change evaluation index when the lithium-ion battery is working; The comprehensive analysis module is used to comprehensively analyze the current voltage change assessment index, the current current change assessment index, the current surface temperature change assessment index, the current chemical gas concentration change assessment index, the current electrochemical impedance change assessment index, and the current electrolyte state change assessment index when the lithium-ion battery is working, to obtain the current fire risk assessment index when the lithium-ion battery is working; The judgment and analysis module is used to judge whether the current fire risk assessment index of the lithium-ion battery when it is working is within a preset fire assessment range, and to send a fire prediction alarm when the current fire risk assessment index is outside the preset fire assessment range.

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