Lithium battery thermal runaway early warning method and device

Abstract

The invention discloses a lithium battery thermal runaway early warning method and device, and belongs to the field of battery thermal runaway early warning, and the method comprises the steps: obtaining a plurality of groups of set feature data of a lithium battery in real time through a preset collection mode; based on a preset alarm threshold value and a duration threshold value corresponding to the set feature data, independently judging an abnormal level of each set of set feature data; according to a preset abnormality level-score mapping rule, converting the abnormality level of each group of set feature data into a corresponding score, and calculating a total score through a weighted scoring method in combination with a preset index weight; and determining and outputting a final early warning grade of the thermal runaway of the lithium battery according to the total score and a preset abnormal grade-score mapping rule. The problems that in an existing lithium battery thermal runaway multi-feature fusion early warning technology, feature integration logic is not uniform, the obtaining mode is not clear, graded early warning is lacked, and consequently early warning accuracy and practicability are insufficient are solved.

Description

Technical Field

[0001] This invention belongs to the field of battery thermal runaway early warning, specifically relating to a method and device for early warning of lithium battery thermal runaway. Background Technology

[0002] Lithium-ion batteries, with their advantages of high energy density and long cycle life, have been widely used in energy storage systems and various electronic devices. However, thermal runaway, as the most serious safety hazard of lithium-ion batteries, causes sudden temperature rises, gas releases, and even combustion and explosions, seriously threatening equipment safety and human lives. Therefore, accurate and reliable thermal runaway early warning technology has become a core requirement in the industry.

[0003] Currently, there are various methods for early warning of thermal runaway in lithium batteries. Among them, the multi-feature fusion early warning method has become the mainstream research direction because it can integrate multiple feature information such as temperature, voltage, and gas composition to comprehensively reflect the internal state of the battery. Compared with the single feature monitoring method, it is more accurate.

[0004] However, existing multi-feature fusion early warning technologies still have significant shortcomings. First, there is a lack of a unified and efficient solution for feature integration logic, with various methods differing greatly and failing to fully consider the weight of different features on the early warning, resulting in insufficient reliability of the early warning. Second, there are no clear specifications for feature acquisition methods, such as the specific implementation methods for voltage difference calculation and sensor installation layout, which affect the replicability and application effect of the technology. Third, most technologies only output a single alarm signal without classifying early warning levels, making it difficult to support the control system to take differentiated protection actions and limiting the practical application value. Summary of the Invention

[0005] To address this issue, the present invention provides a method and apparatus for early warning of thermal runaway in lithium batteries, which solves the problems of inconsistent feature integration logic, unclear acquisition methods, and lack of hierarchical early warning in existing multi-feature fusion early warning technologies for thermal runaway in lithium batteries, resulting in insufficient accuracy and practicality of early warning.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for early warning of thermal runaway in lithium batteries, comprising:

[0007] Several sets of set characteristic data of lithium battery are acquired in real time through a preset acquisition method. The set characteristic data includes the maximum voltage difference of all adjacent cells reflecting the short circuit state inside the cell, the maximum temperature of all cells reflecting the current state inside the cell, and the H2 gas concentration reflecting the chemical reaction state inside the cell.

[0008] Based on the preset alarm threshold and duration threshold corresponding to the set feature data, the abnormality level of each set of set feature data is determined independently. The abnormality level includes normal, low, medium and high.

[0009] According to the preset abnormal level - score mapping rule, convert the abnormal level of each set of set characteristic data into the corresponding score, and combine the preset index weights to calculate the total score through the weighted scoring method;

[0010] Based on the total score and the preset abnormal level - score mapping rule, determine and output the final warning level of lithium - battery thermal runaway, and the final warning level includes normal warning, low - level warning, medium - level warning and high - level warning.

[0011] As an optimal solution of the lithium - battery thermal - runaway warning method, the maximum value of the voltage difference between all adjacent battery cells is Vdiffmax, and the acquisition method is:

[0012] Obtain and update the voltage of each battery cell regularly in sequence through the main board of the battery management unit. After temporarily storing the voltages of all battery cells, calculate the voltage difference between adjacent battery cells connected in series on the circuit, and take the maximum value of all voltage differences as Vdiffmax.

[0013] As an optimal solution of the lithium - battery thermal - runaway warning method, the maximum value of the temperature of all battery cells is TEMPmax, and the acquisition method is:

[0014] Obtain and update the temperature of each battery cell regularly in sequence through the main board of the battery management unit. The temperature sensor is close to the position where each battery cell is prone to heat up. After temporarily storing the temperatures of all battery cells, take the maximum value among them as TEMPmax.

[0015] As an optimal solution of the lithium - battery thermal - runaway warning method, the concentration of H2 gas is CONCh2, and the acquisition method is:

[0016] Collect in real time through the H2 gas sensor, and the H2 gas sensor is placed at the position where the gas released by the detected battery cell is detected, close to the gas source and in the same closed space as the battery cell or the battery PACK.

[0017] As an optimal solution of the lithium - battery thermal - runaway warning method, the method for judging the abnormal level of the maximum value of the voltage difference Vdiffmax between adjacent battery cells is:

[0018] Preset the low - level alarm voltage - difference threshold VthresholdL, the medium - level alarm voltage - difference threshold VthresholdM, the high - level alarm voltage - difference threshold VthresholdH and the duration threshold Tvduration;

[0019] When Vdiffmax≥VthresholdH and the duration reaches Tvduration, it is judged as a high - level warning;

[0020] When VthresholdM≤Vdiffmax<VthresholdH and the duration reaches Tvduration, it is judged as a medium - level warning;

[0021] When VthresholdL ≤ Vdiffmax < VthresholdM and the duration reaches Tvduration, it is determined as a low-level warning.

[0022] As an optimal solution of the lithium battery thermal runaway warning method, the method for judging the abnormal level of the maximum cell temperature TEMPmax is as follows:

[0023] Preset the low-level warning temperature threshold TEMPthresholdL, the medium-level warning temperature threshold TEMPthresholdM, the high-level warning temperature threshold TEMPthresholdH, and the duration threshold Ttempduration;

[0024] When TEMPmax ≥ TEMPthresholdH and the duration reaches Ttempduration, it is determined as a high-level warning;

[0025] When TEMPthresholdM ≤ TEMPmax < TEMPthresholdH and the duration reaches Ttempduration, it is determined as a medium-level warning;

[0026] When TEMPthresholdL ≤ TEMPmax < TEMPthresholdM and the duration reaches Ttempduration, it is determined as a low-level warning.

[0027] As an optimal solution of the lithium battery thermal runaway warning method, the method for judging the abnormal level of the H2 gas concentration CONCh2 is as follows:

[0028] Preset the low-level warning concentration threshold CONCthresholdL, the medium-level warning concentration threshold CONCthresholdM, the high-level warning concentration threshold CONCthresholdH, and the duration threshold Tconcduration;

[0029] When CONCh2 ≥ CONCthresholdH and the duration reaches Tconcduration, it is determined as a high-level warning;

[0030] When CONCthresholdM ≤ CONCh2 < CONCthresholdH and the duration reaches Tconcduration, it is determined as a medium-level warning;

[0031] When CONCthresholdL ≤ CONCh2 < CONCthresholdM and the duration reaches Tconcduration, it is determined as a low-level warning.

[0032] As a preferred scheme for early warning of thermal runaway in lithium batteries, the specific calculation method of the weighted scoring method is as follows:

[0033] Set scores corresponding to the anomaly levels of each feature:

[0034] Cell voltage difference: IND1normal=0 points, low-grade IND1low=1 point, mid-grade IND1mid=2 points, high-grade IND1high=3 points;

[0035] Cell temperature normal IND2normal=0 points, low-grade IND2low=2 points, mid-grade IND2mid=4 points, high-grade IND2high=6 points;

[0036] H2 gas concentration: Normal (IND3) = 0 points, Low (IND3) = 3 points, Mid (IND3) = 6 points, High (IND3) = 9 points;

[0037] Set the weights for each feature:

[0038] Cell pressure difference weight Vdiffwt=0.2, cell temperature weight Tmaxwt=0.3, H2 gas concentration weight Conch2wt=0.5;

[0039] Total score = Cell voltage difference fraction × Vdiffwt + Cell temperature fraction × Tmaxwt + H2 gas concentration fraction × Conch2wt;

[0040] A total score of 0-0.5 corresponds to a normal warning, 0.3-1.7 corresponds to a low-level warning, 1.8-2.9 corresponds to a medium-level warning, and 3.0 and above corresponds to a high-level warning.

[0041] As a preferred scheme for lithium battery thermal runaway early warning method, VthresholdL, VthresholdM, VthresholdH, Tvduration, TEMPthresholdL, TEMPthresholdM, TEMPthresholdH, Ttempduration, CONCthresholdL, CONCthresholdM, CONCthresholdH, Tconcduration, IND1normal, IND1low, IND1mid, IND1high, IND2normal, IND2low, IND2mid, IND2high, IND3normal, IND3low, IND3mid, IND3high, Vdiffwt, Tmaxwt, Conch2wt, and the total score and the preset anomaly level-score mapping rule are all configured through a communication interface.

[0042] The present invention also provides a lithium battery thermal runaway early warning device, employing the above-mentioned lithium battery thermal runaway early warning method, comprising:

[0043] The data acquisition module is used to acquire several sets of set characteristic data of the lithium battery in real time through a preset acquisition method. The set characteristic data includes the maximum voltage difference of all adjacent cells reflecting the short circuit state inside the cell, the maximum temperature of all cells reflecting the current state inside the cell, and the H2 gas concentration reflecting the chemical reaction state inside the cell.

[0044] An anomaly detection module is used to independently determine the anomaly level of each set of set feature data based on the preset alarm threshold and duration threshold corresponding to the set feature data. The anomaly levels include normal, low, medium and high.

[0045] The total score weighted calculation module is used to convert the anomaly level of each set of set feature data into a corresponding score according to the preset anomaly level-score mapping rule, and calculate the total score by combining the preset index weights and weighted scoring method.

[0046] The result output module is used to determine and output the final warning level of lithium battery thermal runaway based on the total score and the preset abnormal level-score mapping rule. The final warning level includes normal warning, low warning, medium warning and high warning.

[0047] The present invention has the following advantages:

[0048] First, this invention comprehensively characterizes the battery state from multiple dimensions by using the maximum cell voltage difference, the maximum cell temperature, and the H2 gas concentration characteristics to correspond to the internal short circuit, current magnitude, and chemical reaction state of the cell, respectively. Combined with a weighted scoring method to highlight the weight of key features, it significantly improves the accuracy of thermal runaway early warning and reduces the risk of false alarms and missed alarms.

[0049] Second, the warning results are divided into four levels: normal, low, medium and high. The judgment criteria for different risk levels are clarified, which makes it easier for the control system to take differentiated protection actions according to the warning level, provides clear guidance for operation and maintenance work, and improves the pertinence and efficiency of emergency response.

[0050] Third, the specific methods for collecting the three major features are clearly defined, including data sources, sensor installation locations, and data processing procedures, to ensure the standardization and reliability of feature data acquisition and enhance the replicability and stability of the technology in practical applications.

[0051] Fourth, all parameters such as alarm thresholds, duration, level score mapping, indicator weights, and early warning mapping rules can be flexibly set through the communication interface, which can quickly adapt to the personalized needs of different lithium battery application scenarios such as energy storage and various electronic devices, and expand the scope of application of the technology.

[0052] Fifth, through a closed-loop process of standardized data collection, independent anomaly detection, and weighted fusion calculation, real-time monitoring and rapid response to thermal runaway risks are achieved, ensuring the safety and orderliness of lithium battery system operation and reducing losses caused by safety accidents. Attached Figure Description

[0053] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description are merely exemplary, and those skilled in the art can derive other embodiments based on the provided drawings without creative effort.

[0054] The structures, proportions, sizes, etc. illustrated in this specification are only for the purpose of assisting those skilled in the art in understanding and reading the content disclosed herein, and are not intended to limit the conditions under which the present invention can be implemented. Therefore, they have no substantial technical significance. Any modifications to the structure, changes in the proportions, or adjustments to the size, without affecting the effects and objectives that the present invention can produce, should still fall within the scope of the technical content disclosed in the present invention.

[0055] Figure 1 This is a schematic diagram of the lithium battery thermal runaway early warning method provided in the embodiments of the present invention;

[0056] Figure 2 This is a schematic diagram of the framework of the lithium battery thermal runaway early warning method provided in the embodiments of the present invention;

[0057] Figure 3 This is a data acquisition architecture diagram of the lithium battery thermal runaway early warning method provided in this embodiment of the invention;

[0058] Figure 4 This is a schematic diagram of the architecture of a lithium battery thermal runaway early warning device provided in an embodiment of the present invention. Detailed Implementation

[0059] The following specific embodiments illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0060] Example 1

[0061] See Figure 1 and Figure 2 Embodiment 1 of the present invention provides a method for early warning of thermal runaway in lithium batteries, comprising the following steps:

[0062] S1. Several sets of preset characteristic data of the lithium battery are acquired in real time through a preset acquisition method. The preset characteristic data includes the maximum voltage difference of all adjacent cells reflecting the short circuit state of the cell, the maximum temperature of all cells reflecting the current state of the cell, and the H2 gas concentration reflecting the chemical reaction state of the cell. Thermal runaway is the result of multiple factors such as short circuit, abnormal current, and chemical reaction imbalance. A single characteristic data is difficult to fully capture the precursors of thermal runaway. The maximum voltage difference of adjacent cells can directly reflect the short circuit situation inside the cell. When a short circuit occurs inside the cell, its voltage will change drastically, resulting in an increase in the voltage difference with adjacent cells. The maximum cell temperature is a direct manifestation of the current thermal effect. When the current increases abnormally, the cell heats up more intensely, and the maximum temperature can quickly capture this anomaly. H2 gas is a typical product of electrolyte decomposition and electrode reaction imbalance inside the lithium battery. Its concentration change can reflect the degree of abnormality of the chemical reaction inside the cell in advance. Selecting these three sets of core characteristic data can cover the core causes of thermal runaway from three dimensions: short circuit, current, and chemical reaction.

[0063] S2. Based on the preset alarm threshold and duration threshold corresponding to the set feature data, independently determine the anomaly level of each set of set feature data. The anomaly level includes normal, low, medium, and high. Instantaneous fluctuations of a single feature data may be caused by external interference (such as sudden changes in ambient temperature or measurement errors), and judging solely based on instantaneous values ​​is prone to false alarms. Setting alarm thresholds can clearly define the normal and abnormal boundaries of feature data, while duration thresholds can filter out instantaneous interference. Only when feature data exceeds the threshold and persists for a certain period of time is it determined to be a true anomaly, ensuring the reliability of anomaly judgment. The anomaly levels are divided into normal, low, medium, and high because different degrees of feature anomalies correspond to different levels of urgency of thermal runaway risk. Independently judging the anomaly level of each set of feature data can locate the risk status in each dimension, providing a single-dimensional judgment basis for subsequent weighted fusion.

[0064] S3. According to the preset anomaly level-score mapping rules, the anomaly level of each set of characteristic data is converted into a corresponding score. Combined with preset index weights, the total score is calculated using a weighted scoring method. Different characteristic data contribute differently to thermal runaway early warning. H2 gas concentration is a direct product of abnormal chemical reactions inside the battery cell, and its early warning timeliness and correlation are the strongest. The maximum value of the battery cell temperature is less affected by the external environment and can stably reflect the current anomaly, with a second-highest contribution. The maximum value of the voltage difference between adjacent battery cells is easily affected by individual differences in battery cells and measurement links, and its contribution is relatively low. Through anomaly level-score mapping, qualitative anomaly levels are converted into quantitative scores, which facilitates subsequent calculations. Assigning corresponding weights to different characteristic data highlights the early warning value of key features, avoids early warning bias caused by equal weighting of all features, and allows the total score to more accurately reflect the comprehensive risk of thermal runaway.

[0065] S4. Based on the total score and the preset anomaly level-score mapping rule, determine and output the final warning level for lithium battery thermal runaway. The final warning level includes normal warning, low-level warning, medium-level warning, and high-level warning. The total score is a comprehensive quantitative representation of the anomaly degree of the three sets of feature data. Different score ranges correspond to different thermal runaway risk levels. When the total score is 0~0.5, it indicates that all three sets of feature data are in a normal or very slight abnormal state, the risk of thermal runaway is extremely low, and it is judged as a normal warning; when the total score is 0.3~1.7, only a single feature shows a low-level anomaly or multiple features show slight anomalies, the risk of thermal runaway is low, and it is judged as a low-level warning; when the total score is 1.8~2.9, there is a medium-level anomaly of a feature or multiple features show a superposition of low-to-medium-level anomalies, the risk of thermal runaway is medium, and attention is required; when the total score is above 3.0, there is a high-level anomaly or multiple features show a superposition of medium-to-high-level anomalies, the risk of thermal runaway is extremely high, and emergency handling is required. This mapping rule realizes the hierarchical quantification of comprehensive risk, making the warning results more intuitive and facilitating rapid response of the control system.

[0066] See Figure 3In this embodiment, in step S1, the maximum voltage difference between all adjacent cells is Vdiffmax, and the acquisition method is as follows:

[0067] The battery management unit motherboard sequentially acquires and updates the voltage of each cell, temporarily stores all cell voltages, calculates the voltage difference between adjacent cells connected in series on the circuit, and takes the maximum value among all voltage differences as Vdiffmax.

[0068] Specifically, the Battery Management Unit (BMS) motherboard is the core component of a lithium battery system responsible for monitoring the state of the cells. It can stably and in real-time collect the voltage of each cell, ensuring the accuracy and timeliness of the voltage data. It updates and temporarily stores all cell voltages sequentially to ensure that the voltage data used when calculating the voltage difference between adjacent cells is a value from the same time dimension, avoiding errors in voltage difference calculations caused by differences in data acquisition timing. Adjacent cells connected in series on the circuit are the units with the closest voltage correlation, and their voltage difference changes best reflect the abnormal state of a single cell. The maximum value among all voltage differences is taken because thermal runaway often begins with anomalies in one or a few cells; the maximum value can accurately locate the cell area with the highest risk, avoiding the masking of local anomalies by the average voltage difference.

[0069] The maximum temperature of all battery cells is TEMPmax, and the acquisition method is as follows:

[0070] The battery management unit motherboard sequentially acquires and updates the temperature of each cell. Temperature sensors are placed close to the heat-generating locations of each cell. After temporarily storing all cell temperatures, the maximum value is taken as TEMPmax.

[0071] Specifically, placing the temperature sensor close to areas of the battery cell prone to heat generation, such as the positive and negative terminals or the core heat-generating area in the middle of the cell, shortens the temperature conduction path, reduces the influence of ambient temperature on the measurement results, and ensures that the collected temperature data accurately reflects the internal heating state of the battery cell. The battery management unit motherboard updates the temperature data sequentially at regular intervals, enabling real-time tracking of dynamic changes in battery cell temperature. The maximum value is taken after temporarily storing all cell temperatures because, in the event of thermal runaway, the temperature of the abnormal cell will be much higher than that of other normal cells. The maximum value can quickly pinpoint the core cell with abnormal heating, avoiding warning delays caused by average temperature values.

[0072] The H2 gas concentration is CONCh2, and the collection method is as follows: real-time collection is performed by an H2 gas sensor. The H2 gas sensor is placed at the location where the gas released by the battery cell is detected, close to the gas source and in the same sealed space as the battery cell or battery PACK.

[0073] Specifically, in the early stage of lithium battery thermal runaway, the amount of H2 gas released by the battery cell is small and it is easy to diffuse. Placing the H2 gas sensor at the position where the battery cell releases gas, such as near the exhaust port of the battery PACK, in the gap between battery cells, and close to the gas source, can improve the capture efficiency of the sensor for H2 gas and shorten the response time; being in the same closed space as the battery cell or the battery PACK can avoid the concentration attenuation caused by the diffusion of H2 gas and ensure that the collected H2 gas concentration data can truly reflect the abnormal degree of the chemical reaction inside the battery cell, realizing early warning of thermal runaway.

[0074] In this embodiment, in step S2, the method for judging the abnormal level of the maximum differential pressure Vdiffmax between adjacent battery cells is as follows: preset a low-level alarm differential pressure threshold VthresholdL, a medium-level alarm differential pressure threshold VthresholdM, a high-level alarm differential pressure threshold VthresholdH, and a duration threshold Tvduration; when Vdiffmax ≥ VthresholdH and the duration reaches Tvduration, it is determined as a high-level warning; when VthresholdM ≤ Vdiffmax < VthresholdH and the duration reaches Tvduration, it is determined as a medium-level warning; when VthresholdL ≤ Vdiffmax < VthresholdM and the duration reaches Tvduration, it is determined as a low-level warning.

[0075] Specifically, VthresholdL, VthresholdM, and VthresholdH are critical values determined based on a large amount of lithium battery thermal runaway test data. VthresholdL corresponds to the differential pressure range of slight short circuit or poor contact inside the battery cell, and the thermal runaway risk is relatively low at this time; VthresholdM corresponds to the differential pressure range of local short circuit inside the battery cell, and the thermal runaway risk is medium; VthresholdH corresponds to the differential pressure range of serious short circuit inside the battery cell, and the thermal runaway risk is extremely high. Set the duration threshold Tvduration to exclude misjudgment caused by instantaneous voltage fluctuations of the battery cell. Only when the differential pressure continuously exceeds the corresponding threshold is it considered an abnormality of this level, ensuring the accuracy and stability of the abnormal level judgment.

[0076] In this embodiment, in step S2, the method for judging the abnormal level of the maximum cell temperature TEMPmax is as follows: preset a low-level warning temperature threshold TEMPthresholdL, a medium-level warning temperature threshold TEMPthresholdM, a high-level warning temperature threshold TEMPthresholdH, and a duration threshold Ttempduration; when TEMPmax≥TEMPthresholdH and the duration reaches Ttempduration, it is determined as a high-level warning; when TEMPthresholdM≤TEMPmax<TEMPthresholdH and the duration reaches Ttempduration, it is determined as a medium-level warning; when TEMPthresholdL≤TEMPmax<TEMPthresholdM and the duration reaches Ttempduration, it is determined as a low-level warning.

[0077] Specifically, the change of the cell temperature follows the thermal runaway evolution law of normal, slow temperature rise, and rapid temperature rise. TEMPthresholdL, TEMPthresholdM, and TEMPthresholdH respectively correspond to the key temperature nodes in this evolution process. TEMPthresholdL corresponds to the upper limit of the normal operating temperature of the cell, and exceeding it indicates a slight heating abnormality; TEMPthresholdM corresponds to the critical temperature at which the heating rate of the cell accelerates, and at this time, the internal current may have become abnormal; TEMPthresholdH corresponds to the critical temperature at which the cell is about to enter the stage of rapid temperature rise during thermal runaway, with extremely high risk. The setting of the duration threshold Ttempduration can filter out sudden changes in the ambient temperature, such as instantaneous temperature rises caused by external factors such as exposure to sunlight or being close to a heat source. Only when the temperature continuously exceeds the threshold is it determined as abnormal, ensuring the pertinence of the temperature abnormality judgment.

[0078] In this embodiment, in step S2, the method for judging the abnormal level of the H2 gas concentration CONCh2 is as follows: preset a low-level warning concentration threshold CONCthresholdL, a medium-level warning concentration threshold CONCthresholdM, a high-level warning concentration threshold CONCthresholdH, and a duration threshold Tconcduration; when CONCh2≥CONCthresholdH and the duration reaches Tconcduration, it is determined as a high-level warning; when CONCthresholdM≤CONCh2<CONCthresholdH and the duration reaches Tconcduration, it is determined as a medium-level warning; when CONCthresholdL≤CONCh2<CONCthresholdM and the duration reaches Tconcduration, it is determined as a low-level warning.

[0079] Specifically, the H2 gas concentration is positively correlated with the intensity of the internal chemical reaction of the battery cell. In the early stages of thermal runaway, the internal reaction of the battery cell is slightly unbalanced, and the amount of H2 gas released is small, with the concentration in the range of CONCthresholdL to CONCthresholdM. As the reaction intensifies, the amount of H2 gas released increases, and the concentration enters the range of CONCthresholdM to CONCthresholdH. When approaching the critical state of thermal runaway, the H2 gas concentration will rise sharply to above CONCthresholdH. CONCthresholdL, CONCthresholdM, and CONCthresholdH are calibrated based on thermal runaway test data of different types of lithium batteries and can match the gas concentration anomaly judgment requirements in different scenarios. The duration threshold Tconcduration can exclude situations such as sensor false triggering and small amounts of H2 interference in the environment, ensuring that only when the battery cell continuously releases H2 gas is it judged as an anomaly, thus improving the reliability of gas concentration anomaly judgment.

[0080] In this embodiment, in step S3, the specific calculation method of the weighted scoring method is as follows: The scores corresponding to each abnormality level are set as follows: Normal cell voltage difference IND1normal=0 points, low level IND1low=1 point, medium level IND1mid=2 points, high level IND1high=3 points; Normal cell temperature IND2normal=0 points, low level IND2low=2 points, medium level IND2mid=4 points, high level IND2high=6 points; Normal H2 gas concentration IND3normal=0 points, low level IND3low=3 points, medium level IND3mid=6 points, high level IND3high=9 points; The weights of each feature are set as follows: Cell voltage difference weight Vdiffwt=0.2, Cell temperature weight Tmaxwt=0.3, H2 gas concentration weight Conch2wt=0.5.

[0081] Specifically, the anomaly level-score mapping rule is designed based on the correlation strength between the characteristic anomaly level and the risk of thermal runaway. The higher the level, the higher the corresponding score, and the score difference gradually increases with the level. For example, the difference between a high-level H2 gas concentration anomaly (9 points) and a medium-level anomaly (6 points), and the difference between a medium-level anomaly and a low-level anomaly (3 points) are both 3 points, highlighting the risk weight of high-level anomalies. H2 gas concentration is one of the earliest precursors to thermal runaway and has the strongest warning timeliness, so it is assigned the highest weight of 0.5. The maximum cell temperature can stably reflect current anomalies and is less affected by external interference, so it is assigned a weight of 0.3. The maximum cell voltage difference is easily affected by individual cell differences and measurement links, so its warning priority is relatively low, and it is assigned a weight of 0.2. By adjusting the weights, the total score is made to better reflect the actual risk level of thermal runaway.

[0082] In this embodiment, in step S3, the total score = cell voltage difference score × Vdiffwt + cell temperature score × Tmaxwt + H2 gas concentration score × Conch2wt; a total score of 0~0.5 corresponds to a normal warning, 0.3~1.7 corresponds to a low-level warning, 1.8~2.9 corresponds to a medium-level warning, and 3.0 and above corresponds to a high-level warning.

[0083] Specifically, the formula for calculating the total score is a weighted fusion of the abnormality levels of the three sets of features. By amplifying the impact of key features (such as H2 gas concentration) through weighting, the total score can comprehensively reflect multi-dimensional risks. The scoring range is based on statistical analysis of a large amount of experimental data: a total score of 0-0.5 indicates that all features are in a normal or very slight abnormal state, the risk of thermal runaway is negligible, and it is judged as a normal warning; a total score of 0.3-1.7 usually indicates a single feature with low-level abnormality (e.g., low-level abnormality of H2 gas concentration: 3 points × 0.5 = 1.5 points) or multiple features with slight abnormalities superimposed, with low risk, and it is judged as a low-level warning; a total score of 1.8-2.9 may indicate a single feature with medium-level abnormality (e.g., medium-level abnormality of cell temperature: 4 points × 0.3 = 1.2 points) superimposed with another feature with low-level abnormality (e.g., low-level abnormality of H2 gas concentration: 3 points × 0.5 = 1.5 points) (total score 2.7 points), with medium risk, and it is judged as a medium-level warning; a total score of 3.0 or above may indicate a single feature with high-level abnormality (e.g., high-level abnormality of H2 gas concentration: 9 points × 0.5 = 4.5 points) or multiple features with medium-to-high-level abnormalities superimposed, with extremely high risk, and it is judged as a high-level warning. This classification rule can achieve precise quantification of risk level.

[0084] In one possible embodiment, VthresholdL, VthresholdM, VthresholdH, Tvduration, TEMPthresholdL, TEMPthresholdM, TEMPthresholdH, Ttempduration, CONCthresholdL, CONCthresholdM, CONCthresholdH, Tconcduration, IND1normal, IND1low, IND1mid, IND1high, IND2normal, IND2low, IND2mid, IND2high, IND3normal, IND3low, IND3mid, IND3high, Vdiffwt, Tmaxwt, Conch2wt, and the total score along with the preset anomaly level-score mapping rule are all configured via a communication interface.

[0085] Specifically, different types of lithium batteries (such as lithium iron phosphate batteries and ternary lithium batteries) have different thermal runaway characteristics and operating environments (such as energy storage power stations and portable electronic devices), resulting in different requirements for warning parameters. For example, lithium battery packs in energy storage power stations are large and have special heat dissipation conditions, requiring temperature thresholds to be adapted to their heat dissipation capabilities. Lithium batteries in portable electronic devices have small capacities and release less H2 gas, necessitating adjustments to their concentration thresholds. By allowing users to flexibly configure various parameters through a communication interface, this warning method can quickly adapt to the personalized needs of different lithium battery types and application scenarios without modifying the hardware structure, significantly improving the method's versatility and practicality, and reducing the cost of technology implementation.

[0086] The application scenarios of this invention are as follows:

[0087] In the field of energy storage systems, this invention is applicable to centralized energy storage power stations and distributed energy storage cabinets (such as residential and commercial energy storage). In these scenarios, lithium battery packs have large capacities and numerous cells, leading to rapid thermal runaway risk propagation. This invention utilizes multi-dimensional monitoring and tiered early warning systems based on cell pressure differential, temperature, and H2 gas concentration to identify localized cell anomalies in advance. This provides precise data for initiating differentiated protection actions such as cooling and power outages in the energy storage system, preventing the escalation of accidents.

[0088] In the field of new energy vehicles: it can be applied to power battery systems for pure electric vehicles and hybrid electric vehicles. During vehicle operation, power batteries are susceptible to factors such as bumps, high temperatures, and fast charging. This invention can detect early signs such as cell short circuits, abnormal currents, and chemical reaction imbalances in real time, and assist the vehicle control system in taking measures such as power limiting, alarm prompts, and emergency power cut-off through graded early warning to ensure driving safety.

[0089] In the field of portable electronic devices: lithium battery modules adapted for smartphones, laptops, tablets, and other terminals. These devices have high cell integration and limited heat dissipation space, making them susceptible to thermal runaway even with minor anomalies. The refined monitoring and graded early warning system of this invention can quickly respond to risks and trigger protective mechanisms such as device shutdown and heat dissipation to prevent device damage or user burns.

[0090] In the field of industrial equipment: This invention is applicable to industrial and special equipment that relies on lithium batteries for power, such as drones, robots, and medical devices (e.g., portable ventilators). These devices often operate under complex conditions (e.g., high altitude, high temperature, high humidity environments), requiring extremely high battery safety. This invention can adapt to the battery characteristics of different devices through flexible parameter configuration, enabling customized early warning and ensuring continuous and stable operation of the equipment.

[0091] Other lithium battery application scenarios include electric bicycles, power tools (such as electric drills and chainsaws), and emergency power supplies. These products are used in diverse scenarios and under various operating conditions. The standardized feature acquisition method and flexible parameter configuration capabilities of this invention can quickly adapt to the early warning needs of different types of lithium batteries, improving product safety performance and market competitiveness.

[0092] It should be noted that the method of this embodiment can also be applied to a distributed scenario, where multiple devices cooperate to complete the task. In such a distributed scenario, one of these devices may execute only one or more steps of the method in this embodiment, and the multiple devices will interact with each other to complete the method described.

[0093] It should be noted that the above description describes some embodiments of this disclosure. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in a different order than that shown in the above embodiments and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0094] Example 2

[0095] See Figure 4 Embodiment 2 of the present invention also provides a lithium battery thermal runaway early warning device, which adopts the lithium battery thermal runaway early warning method of the above embodiments, including:

[0096] The data acquisition module 100 is used to acquire several sets of set characteristic data of the lithium battery in real time through a preset acquisition method. The set characteristic data includes the maximum voltage difference of all adjacent cells reflecting the short circuit state inside the cell, the maximum temperature of all cells reflecting the current state inside the cell, and the H2 gas concentration reflecting the chemical reaction state inside the cell.

[0097] The anomaly judgment module 200 is used to independently judge the anomaly level of each set of set feature data based on the preset alarm threshold and duration threshold corresponding to the set feature data. The anomaly level includes normal, low level, medium level and high level.

[0098] The total score weighted calculation module 300 is used to convert the anomaly level of each set of set feature data into a corresponding score according to the preset anomaly level-score mapping rule, and calculate the total score by combining the preset index weights and using a weighted scoring method.

[0099] A result output module 400 is configured to determine and output a final warning level for thermal runaway of a lithium battery according to the total score and a preset abnormal level - score mapping rule. The final warning levels include normal warning, low - level warning, medium - level warning, and high - level warning.

[0100] In this embodiment, in the data acquisition module 100, the maximum value of the voltage difference between all adjacent battery cells is Vdiffmax, and the acquisition method is as follows:

[0101] The voltage of each battery cell is obtained and updated sequentially at regular intervals through the main board of the battery management unit. After temporarily storing the voltages of all battery cells, the voltage difference between adjacent battery cells connected in series in the circuit is calculated, and the maximum value among all voltage differences is taken as Vdiffmax.

[0102] The maximum value of the temperatures of all battery cells is TEMPmax, and the acquisition method is as follows:

[0103] The temperature of each battery cell is obtained and updated sequentially at regular intervals through the main board of the battery management unit. The temperature sensor is placed close to the position where each battery cell is prone to heat up. After temporarily storing the temperatures of all battery cells, the maximum value among them is taken as TEMPmax.

[0104] In this embodiment, in the data acquisition module 100, the concentration of H2 gas is CONCh2, and the acquisition method is as follows:

[0105] It is collected in real - time through an H2 gas sensor. The H2 gas sensor is placed at the position for detecting the gas released by the battery cell, close to the gas source and in the same enclosed space as the battery cell or the battery PACK.

[0106] In this embodiment, in the abnormal judgment module 200, the method for judging the abnormal level of the maximum value of the voltage difference Vdiffmax between adjacent battery cells is as follows:

[0107] A preset low - level warning voltage - difference threshold VthresholdL, a medium - level warning voltage - difference threshold VthresholdM, a high - level warning voltage - difference threshold VthresholdH, and a duration threshold Tvduration are set;

[0108] When Vdiffmax≥VthresholdH and the duration reaches Tvduration, it is determined as a high - level warning;

[0109] When VthresholdM≤Vdiffmax<VthresholdH and the duration reaches Tvduration, it is determined as a medium - level warning;

[0110] When VthresholdL≤Vdiffmax<VthresholdM and the duration reaches Tvduration, it is determined as a low - level warning.

[0111] In this embodiment, in the abnormal judgment module 200, the method for judging the abnormal level of the maximum cell temperature TEMPmax is as follows:

[0112] Preset a low-level warning temperature threshold TEMPthresholdL, a medium-level warning temperature threshold TEMPthresholdM, a high-level warning temperature threshold TEMPthresholdH, and a duration threshold Ttempduration;

[0113] When TEMPmax ≥ TEMPthresholdH and the duration reaches Ttempduration, it is determined as a high-level warning;

[0114] When TEMPthresholdM ≤ TEMPmax < TEMPthresholdH and the duration reaches Ttempduration, it is determined as a medium-level warning;

[0115] When TEMPthresholdL ≤ TEMPmax < TEMPthresholdM and the duration reaches Ttempduration, it is determined as a low-level warning.[[ID=1*]]

[0116] In this embodiment, in the abnormal judgment module 200, the method for judging the abnormal level of the H2 gas concentration CONCh2 is as follows:

[0117] Preset a low-level warning concentration threshold CONCthresholdL, a medium-level warning concentration threshold CONCthresholdM, a high-level warning concentration threshold CONCthresholdH, and a duration threshold Tconcduration;

[0118] When CONCh2 ≥ CONCthresholdH and the duration reaches Tconcduration, it is determined as a high-level warning;

[0119] When CONCthresholdM ≤ CONChz < CONCthresholdH and the duration reaches Tconcduration, it is determined as a medium-level warning;

[0120] When CONCthresholdL ≤ CONCh2 < CONCthresholdM and the duration reaches Tconcduration, it is determined as a low-level warning.

[0121] In this embodiment, in the total score weighted calculation module 300, the specific calculation method of the weighted scoring method is as follows:

[0122] Set scores corresponding to the anomaly levels of each feature:

[0123] Cell voltage difference: IND1normal=0 points, low-grade IND1low=1 point, mid-grade IND1mid=2 points, high-grade IND1high=3 points;

[0124] Cell temperature normal IND2normal=0 points, low-grade IND2low=2 points, mid-grade IND2mid=4 points, high-grade IND2high=6 points;

[0125] H2 gas concentration: Normal (IND3) = 0 points, Low (IND3) = 3 points, Mid (IND3) = 6 points, High (IND3) = 9 points;

[0126] Set the weights for each feature:

[0127] Cell pressure difference weight Vdiffwt=0.2, cell temperature weight Tmaxwt=0.3, H2 gas concentration weight Conch2wt=0.5;

[0128] Total score = Cell voltage difference fraction × Vdiffwt + Cell temperature fraction × Tmaxwt + H2 gas concentration fraction × Conch2wt;

[0129] A total score of 0-0.5 corresponds to a normal warning, 0.3-1.7 corresponds to a low-level warning, 1.8-2.9 corresponds to a medium-level warning, and 3.0 and above corresponds to a high-level warning.

[0130] It should be noted that the information interaction and execution process between the modules of the above-mentioned device are based on the same concept as the method embodiment in Embodiment 1 of this application, and the resulting technical effects are the same as those in the method embodiment of this application. For details, please refer to the description in the method embodiment shown above in this application, and it will not be repeated here.

[0131] Example 3

[0132] Embodiment 3 of the present invention provides a non-transitory computer-readable storage medium storing program code for a lithium battery thermal runaway early warning method. The program code includes instructions for executing the lithium battery thermal runaway early warning method of Embodiment 1 or any possible implementation thereof.

[0133] Computer-readable storage media can be any available medium that a computer can access, or a data storage device such as a server or data center that integrates one or more available media. The available medium can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state drives (SSDs)).

[0134] Example 4

[0135] Embodiment 4 of the present invention provides an electronic device, including: a memory and a processor;

[0136] The processor and the memory communicate with each other via a bus; the memory stores program instructions that can be executed by the processor, and the processor can execute the lithium battery thermal runaway early warning method of Embodiment 1 or any possible implementation thereof by calling the program instructions.

[0137] Specifically, a processor can be implemented in hardware or software. When implemented in hardware, the processor can be a logic circuit, an integrated circuit, etc. When implemented in software, the processor can be a general-purpose processor that reads software code stored in memory. This memory can be integrated into the processor or located outside the processor and exist independently.

[0138] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable system. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means.

[0139] It is obvious to those skilled in the art that the modules or steps of the present invention described above can be implemented using general-purpose computing systems. They can be centralized on a single computing system or distributed across a network of multiple computing systems. Optionally, they can be implemented using program code executable by a computing system, thereby storing them in a storage system for execution by the computing system. In some cases, the steps shown or described can be performed in a different order than those presented herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0140] Although the present invention has been described in detail above with general descriptions and specific embodiments, modifications or improvements can be made to it, which will be obvious to those skilled in the art. Therefore, all such modifications or improvements made without departing from the spirit of the present invention fall within the scope of protection claimed by the present invention.

Claims

1. A method for early warning of thermal runaway in lithium batteries, characterized in that, Including: Obtain several groups of set characteristic data of the lithium battery in real time through a preset acquisition method. The set characteristic data includes the maximum value of the voltage difference between all adjacent battery cells reflecting the internal short - circuit state of the battery cell, the maximum value of the temperature of all battery cells reflecting the internal current magnitude state of the battery cell, and the concentration of H2 gas reflecting the internal chemical reaction state of the battery cell; Based on the preset alarm threshold and duration threshold corresponding to the set characteristic data, independently judge the abnormal level of each group of set characteristic data. The abnormal levels include normal, low - level, medium - level, and high - level; According to the preset abnormal - level - score mapping rule, convert the abnormal level of each group of set characteristic data into the corresponding score, and combine the preset index weights to calculate the total score through the weighted scoring method; Based on the total score and the preset abnormal - level - score mapping rule, determine and output the final warning level of the lithium - battery thermal runaway. The final warning levels include normal warning, low - level warning, medium - level warning, and high - level warning.

2. The lithium battery thermal runaway early warning method according to claim 1, characterized in that, The maximum value of the voltage difference between all adjacent battery cells is Vdiffmax, and the acquisition method is as follows: Obtain and update the voltage of each battery cell sequentially at regular intervals through the main board of the battery management unit. After temporarily storing the voltages of all battery cells, calculate the voltage difference between adjacent battery cells connected in series on the circuit, and take the maximum value of all voltage differences as Vdiffmax.

3. The lithium battery thermal runaway early warning method according to claim 3, characterized in that, The maximum value of the temperature of all battery cells is TEMPmax, and the acquisition method is as follows: Obtain and update the temperature of each battery cell sequentially at regular intervals through the main board of the battery management unit. The temperature sensor is close to the position where each battery cell is prone to heat up. After temporarily storing the temperatures of all battery cells, take the maximum value as TEMPmax.

4. The lithium battery thermal runaway early warning method according to claim 3, characterized in that, The concentration of H2 gas is CONCh2, and the acquisition method is as follows: Collect in real time through an H2 gas sensor. The H2 gas sensor is placed at the position where the gas released by the detected battery cell is detected, close to the gas source and in the same closed space as the battery cell or the battery PACK.

5. The lithium battery thermal runaway early warning method according to claim 4, characterized in that, The method for judging the abnormal level of the maximum value of the voltage difference Vdiffmax between adjacent battery cells is as follows: Preset a low - level alarm voltage - difference threshold VthresholdL, a medium - level alarm voltage - difference threshold VthresholdM, a high - level alarm voltage - difference threshold VthresholdH, and a duration threshold Tvduration; When Vdiffmax≥VthresholdH and the duration reaches Tvduration, it is judged as a high - level warning; When VthresholdM≤Vdiffmax<VthresholdH and the duration reaches Tvduration, it is judged as a medium - level warning; When VthresholdL≤Vdiffmax<VthresholdM and the duration reaches Tvduration, it is judged as a low - level warning.

6. The lithium battery thermal runaway early warning method according to claim 5, characterized in that, The method for judging the abnormal level of the maximum value of the battery - cell temperature TEMPmax is as follows: Preset a low - level alarm temperature threshold TEMPthresholdL, a medium - level alarm temperature threshold TEMPthresholdM, a high - level alarm temperature threshold TEMPthresholdH, and a duration threshold Ttempduration; When TEMPmax ≥ TEMPthresholdH and the duration reaches Ttempduration, it is determined as a high-level warning; When TEMPthresholdM ≤ TEMPmax < TEMPthresholdH and the duration reaches Ttempduration, it is determined as a medium-level warning; When TEMPthresholdL ≤ TEMPmax < TEMPthresholdM and the duration reaches Ttempduration, it is determined as a low-level warning.

7. The lithium battery thermal runaway early warning method according to claim 6, characterized in that, The method for judging the abnormal level of the H2 gas concentration of CONCh2 is as follows: Preset the low-level alarm concentration threshold CONCthresholdL, medium-level alarm concentration threshold CONCthresholdM, high-level alarm concentration threshold CONCthresholdH, and duration threshold Tconcduration; When CONCh2 ≥ CONCthresholdH and the duration reaches Tconcduration, it is determined as a high-level warning; When CONCthresholdM ≤ CONCh2 < CONCthresholdH and the duration reaches Tconcduration, it is determined as a medium-level warning; When CONCthresholdL ≤ CONCh2 < CONCthresholdM and the duration reaches Tconcduration, it is determined as a low-level warning.

8. The lithium battery thermal runaway early warning method according to claim 7, characterized in that, The specific calculation method of the weighted scoring method is as follows: Set the scores corresponding to the abnormal levels of each feature: The normal difference of the cell voltage IND1normal = 0 points, low level IND1low = 1 point, medium level IND1mid = 2 points, high level IND1high = 3 points; The normal temperature of the cell IND2normal = 0 points, low level IND2low = 2 points, medium level IND2mid = 4 points, high level IND2high = 6 points; The normal H2 gas concentration IND3normal = 0 points, low level IND3low = 3 points, medium level IND3mid = 6 points, high level IND3high = 9 points; Set the weights of each feature: The weight of the cell voltage difference Vdiffwt = 0.2, the weight of the cell temperature Tmaxwt = 0.3, the weight of the H2 gas concentration Conch2wt = 0.5; The total score = the score of the cell voltage difference × Vdiffwt + the score of the cell temperature × Tmaxwt + the score of the H2 gas concentration × Conch2wt; The total score of 0 to 0.5 corresponds to a normal warning, 0.3 to 1.7 corresponds to a low-level warning, 1.8 to 2.9 corresponds to a medium-level warning, and above 3.0 corresponds to a high-level warning.

9. The lithium battery thermal runaway early warning method according to claim 8, characterized in that, The values ​​of VthresholdL, VthresholdM, VthresholdH, Tvduration, TEMPthresholdL, TEMPthresholdM, TEMPthresholdH, Ttempduration, CONCthresholdL, CONCthresholdM, CONCthresholdH, Tconcduration, IND1normal, IND1low, IND1mid, IND1high, IND2normal, IND2low, IND2mid, IND2high, IND3normal, IND3low, IND3mid, IND3high, Vdiffwt, Tmaxwt, Conch2wt, and the total score along with the preset anomaly level-score mapping rules are all configured through a communication interface.

10. A lithium battery thermal runaway early warning device, employing the lithium battery thermal runaway early warning method according to any one of claims 1 to 10, characterized in that, include: The data acquisition module is used to acquire several sets of set characteristic data of the lithium battery in real time through a preset acquisition method. The set characteristic data includes the maximum voltage difference of all adjacent cells reflecting the short circuit state inside the cell, the maximum temperature of all cells reflecting the current state inside the cell, and the H2 gas concentration reflecting the chemical reaction state inside the cell. An anomaly detection module is used to independently determine the anomaly level of each set of set feature data based on the preset alarm threshold and duration threshold corresponding to the set feature data. The anomaly levels include normal, low, medium and high. The total score weighted calculation module is used to convert the anomaly level of each set of set feature data into a corresponding score according to the preset anomaly level-score mapping rule, and calculate the total score by combining the preset index weights and weighted scoring method. The result output module is used to determine and output the final warning level of lithium battery thermal runaway based on the total score and the preset abnormal level-score mapping rule. The final warning level includes normal warning, low warning, medium warning and high warning.

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