Safety risk prediction and early warning method for solid-state energy storage lithium-ion batteries

Abstract

The present invention belongs to the field of lithium battery risk management and control technology, specifically a solid-state energy storage lithium-ion battery safety risk prediction and early warning method, the steps include obtaining data of N groups of lithium battery groups constituting solid-state energy storage lithium-ion batteries during operation, and classifying them according to the number of the lithium battery groups; analyzing and processing the classified data to determine whether the solid-state energy storage lithium-ion battery is in an abnormal state; issuing a danger alarm when in an abnormal state, and further processing the classified data to analyze the cause of the abnormality; comprehensively analyzing the abnormal cause and the classified data, calculating the abnormal level and thermal runaway time, and adjusting the danger alarm to the corresponding level according to the abnormal level; comparing the abnormal level with the set threshold interval, and selecting and executing the corresponding control strategy according to the comparison result. The present invention can improve the safety performance of solid-state energy storage lithium-ion batteries when in use.

Description

Technical Field

[0001] The present invention belongs to the technical field of lithium battery risk management and control, and specifically provides a safety risk prediction and early warning method for solid-state energy storage lithium-ion batteries. Background Art

[0002] As a new energy storage technology, solid-state energy storage lithium-ion batteries have shown broad application prospects in the fields of electric vehicles and energy storage equipment due to their high energy density, good safety and stability. However, the safety issues of existing lithium-ion batteries have always been the focus of research. At present, the safety risk warning system of lithium-ion batteries mostly adopts a fixed threshold comparison method. By comparing the collected battery data with the preset threshold, it can determine whether the battery is in an abnormal state and trigger the corresponding warning strategy. Although this warning method can reduce the risk of safety accidents caused by thermal runaway to a certain extent, it has obvious limitations in practical applications.

[0003] First, the fixed threshold comparison method cannot adapt to temperature changes in different environments, which can easily lead to false alarms or missed alarms. Secondly, when the battery is abnormal, it is difficult to accurately reflect the degree of danger through an alarm alone, and it is impossible to quickly locate the abnormal point, and it is impossible to provide technicians with sufficient information to solve the abnormal problem in time. In addition, the existing methods do not analyze the causes of the abnormality in depth, and cannot effectively distinguish the impact of different types of abuse (such as mechanical abuse, electrical abuse or thermal abuse) on battery safety, resulting in inaccurate warnings and difficulty in meeting the high requirements for battery safety performance in practical applications. Summary of the invention

[0004] In view of the deficiencies in the prior art, the purpose of the present invention is to provide a solid-state energy storage lithium-ion battery safety risk prediction and early warning method, which can improve the safety performance of the solid-state energy storage lithium-ion battery during use by analyzing and processing each lithium battery pack that constitutes the solid-state energy storage lithium-ion battery.

[0005] To achieve the above objectives, the present invention adopts the following technical solutions:

[0006] The safety risk prediction and early warning method of solid-state energy storage lithium-ion batteries includes the following steps:

[0007] Obtaining operating data of N lithium battery groups constituting solid-state energy storage lithium-ion batteries, and classifying the data according to the numbers of the lithium battery groups;

[0008] Analyze and process the classified data to determine whether the solid-state energy storage lithium-ion battery is in an abnormal state;

[0009] When in an abnormal state, a danger alarm is issued, and the classified data is further processed to analyze the cause of the abnormality;

[0010] Comprehensively analyze the abnormal cause and classified data, calculate the abnormal level and thermal runaway time, and adjust the danger alarm to the corresponding level according to the abnormal level;

[0011] Compare the abnormal level with the set threshold range, and select and execute the corresponding control strategy based on the comparison results.

[0012] Preferably, the data during operation of the solid-state energy storage lithium-ion battery includes voltage data, surface temperature data, hydrogen content data, current data, and carbon monoxide content data of the lithium battery pack.

[0013] Preferably, the step of determining whether the solid-state energy storage lithium-ion battery is in an abnormal state comprises:

[0014] Acquire the surface temperature data of all lithium battery packs, compare the sizes of the acquired surface temperature data, and extract the maximum surface temperature data;

[0015] The maximum surface temperature data is compared with the abnormal temperature threshold Wdyz, and the solid-state energy storage lithium-ion battery is judged to be abnormal by judging whether the lithium battery pack is abnormal;

[0016] If the maximum surface temperature data is greater than or equal to the abnormal temperature threshold Wdyz, it is determined that the lithium battery pack and the solid-state energy storage lithium-ion battery are in an abnormal state; if the maximum surface temperature data is less than the abnormal temperature threshold, it is determined that the lithium battery pack and the solid-state energy storage lithium-ion battery are in a safe state;

[0017] The calculation formula of abnormal temperature threshold Wdyz is as follows:

[0018] ;

[0019] In the formula, is the highest ambient temperature in the area, Bzz is the ambient temperature of the area set The maximum temperature value of the lithium battery pack for safe operation is shown below, Sw is the current ambient temperature, Jbcz is the temperature difference between each temperature level, and Jbxs is the influence coefficient corresponding to the temperature level;

[0020] Extract the surface temperature data of all lithium battery packs that are 3°C below the abnormal state, and determine whether the extracted lithium battery pack is abnormal, until it is determined that the lithium battery pack is in a safe state.

[0021] Preferably, determining whether the solid-state energy storage lithium-ion battery is in an abnormal state further includes comparing the hydrogen content data and the carbon monoxide content data with the set corresponding gas safety concentration thresholds. When the compared hydrogen content data and the carbon monoxide content data exceed the corresponding gas safety concentration thresholds, it is determined that the solid-state energy storage lithium-ion battery is in an abnormal state, and the abnormality level is determined to reach level 10.

[0022] Preferably, the steps of further processing the classified data and analyzing the causes of abnormalities are as follows:

[0023] Adjust the frequency of obtaining lithium battery pack operating data. The adjusted data acquisition frequency is 5 times or more of the original acquisition frequency, and the adjusted data acquisition detection time is less than 3 seconds;

[0024] Obtain the voltage data and temperature data of the lithium battery pack in an abnormal state, and calculate the voltage change rate and temperature change rate. The voltage change rate = (currently collected voltage - last collected voltage) / collection interval time, and the temperature change rate = (currently collected temperature - last collected temperature) / collection interval time;

[0025] Determine the cause of the abnormality based on the voltage change rate and temperature change rate:

[0026] When the temperature change rate is greater than or equal to 1°C / s, the lithium battery pack will experience thermal runaway, and a danger warning will be issued, and the abnormality level will be determined to be level 10;

[0027] When the temperature change rate is less than 1°C / s, the lithium battery pack is not out of control;

[0028] When the system is not out of control, the cause of the abnormality can be analyzed by the voltage change speed;

[0029] When the voltage drops and the voltage change rate is greater than 1V / s, the abnormality of the lithium battery pack is caused by high temperature caused by mechanical abuse;

[0030] When the voltage rises and exceeds the rated voltage, the abnormality of the lithium battery pack is caused by high temperature caused by electrical abuse;

[0031] When the voltage drops at a rate less than 1V / s or the voltage rises but does not reach the rated voltage, the cause of the lithium battery pack abnormality is high temperature caused by thermal abuse.

[0032] Preferably, the abnormality level includes a current abnormality level and a predicted abnormality level;

[0033] The calculation formula for the current abnormal level is:

[0034] ;

[0035] Wherein, Ycdj is the current abnormal level, jcwd is the current detection temperature, wdxs is the level influence coefficient corresponding to the temperature, Ycjb is the initial abnormal level corresponding to the abnormal cause, Wdbh is the temperature change rate, Swxs is the level influence coefficient corresponding to the temperature change, 1≤Ycdj≤10, Ycjb corresponding to mechanical abuse>Ycjb corresponding to electrical abuse>Ycjb corresponding to thermal abuse, and Ycjb corresponding to mechanical abuse is level 5.

[0036] Preferably, the calculation formula for predicting the abnormal level is:

[0037] ;

[0038] In the formula, is the temperature change rate after time t; is the detected temperature after time t; is the abnormal level after time t, ,when When the abnormal level reaches level 10;

[0039] When the abnormal cause is high temperature caused by mechanical abuse;

[0040] ;

[0041] ;

[0042] Where A is a constant and A≥10;

[0043] When the abnormal cause is high temperature caused by electrical abuse;

[0044] ;

[0045] ;

[0046] Wherein, B is a constant, and 220≥B≥180; is the time taken for the temperature to rise by 10°C. It is the multiple of the current charging current and the standard charging current;

[0047] When the abnormal cause is high temperature caused by thermal abuse:

[0048] ;

[0049] ;

[0050] Where C is the influence coefficient of the heating cause on the heating temperature change.

[0051] Preferably, the result of thermal runaway time calculation is The time corresponding to reaching 100+Bzz.

[0052] Preferably, the set threshold intervals include an abnormality handling threshold interval (0, 5], a danger handling threshold interval (5, 8], and a fire handling threshold interval (8, 10];

[0053] According to the comparison results, the corresponding control strategy is selected as follows:

[0054] The current abnormality level is within the abnormality handling threshold range, and the heat dissipation device on the solid-state energy storage lithium-ion battery is started at full power to cool down;

[0055] If the current abnormality level is within the danger handling threshold range, the heat dissipation device on the solid-state energy storage lithium-ion battery is fully activated to cool it down, the line of the abnormal lithium battery pack is cut off, and the corresponding number of backup lithium battery packs are connected;

[0056] The current abnormality level is within the fire protection threshold range. The heat dissipation equipment and fire protection equipment on the solid-state energy storage lithium-ion battery are started, the circuit of the abnormal lithium battery pack is cut off, and the solid-state energy storage lithium-ion battery is shut down.

[0057] Preferably, the safe working time of the lithium battery pack is predicted when it is in a safe state. The safe working time is the time to maintain the current use conditions until an abnormal state occurs. The specific calculation formula is as follows:

[0058] ;

[0059] Where Taq is the predicted safe working time. When the calculated Taq is less than 600 seconds, a safety warning is issued.

[0060] The present invention has the following beneficial effects:

[0061] The present invention can analyze and process each lithium battery pack constituting a solid-state energy storage lithium ion battery, and can greatly improve the safety performance of the solid-state energy storage lithium ion battery when in use; a step-by-step judgment method is adopted, and temperature is used as the first layer to judge whether the lithium battery pack is abnormal, and the temperature values ​​are first compared, and then the maximum surface temperature data is used for comparison and judgment, so that the amount of data processed in the process of judging whether the lithium battery pack is abnormal is greatly reduced, thereby greatly reducing the time for abnormal warning, and the solid-state energy storage lithium ion battery is dynamically adjusted according to the temperature of the use site, further improving the accuracy of abnormal state recognition, and then abnormal analysis is performed to further determine the level of the abnormality, and a corresponding strategy is formulated according to the abnormality level, so that rapid warning can be achieved, and a comprehensive analysis of the solid-state energy storage lithium ion battery can be realized.

[0062] The present invention can analyze specific causes in the event of an abnormality and evaluate the losses caused by the abnormality. In addition, different methods are used to calculate the abnormality levels of thermal runaway caused by different reasons during the evaluation, so that the abnormality analysis is more accurate, and the problem of inaccurate early warning caused by the simple comparison method used in existing predictions, incomplete comparison data, and the use of the same standard for measurement is effectively solved. In addition, the present invention can also make predictions for the future according to the current situation during normal use, helping users understand the battery operation status, facilitating corresponding adjustments to solid-state energy storage lithium-ion batteries, and achieving better management and control effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 Flow chart of the method of the present invention. DETAILED DESCRIPTION

[0064] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0065] The hardware part of the solid-state energy storage lithium-ion battery safety risk prediction and early warning method of this embodiment is based on the existing sensor components for collecting lithium battery pack working data, and there is no need to add new sensors. If the accuracy is to be further improved, an industrial camera can be added to further detect the deformation of the lithium battery pack, and whether it is abnormal can be determined by whether deformation occurs, and the abnormality level can be further optimized by the degree of deformation. However, due to the large amount of data processed by the image, it is easy to affect the overall efficiency. If you want to increase the speed, you must use computer equipment with high computing speed, so the cost is relatively high. Under normal circumstances, this kind of accuracy is not required.

[0066] The solid-state energy storage lithium-ion battery safety risk prediction and early warning method of this embodiment is based on the existing battery management system and includes the following steps:

[0067] Obtaining operating data of N lithium battery groups constituting solid-state energy storage lithium-ion batteries, and classifying the data according to the numbers of the lithium battery groups;

[0068] A solid-state energy storage lithium-ion battery is usually composed of N groups of lithium battery packs connected in series and in parallel, and each lithium battery pack is composed of a number of lithium batteries connected in series. Since the lithium battery packs are all composed of calibrated lithium batteries and there are too many lithium batteries, it is impossible to collect the working data of all lithium batteries. Therefore, this embodiment starts from the lithium battery pack and collects the working data of the lithium battery pack. The state of the lithium battery pack more accurately reflects the state of the entire solid-state energy storage lithium-ion battery.

[0069] The data collected when the solid-state energy storage lithium-ion battery is in operation include the voltage data of the lithium battery pack (the existing battery management system is equipped with a corresponding voltage sensor or voltage data acquisition circuit), surface temperature data (most battery management systems use the MF5C series, NTC temperature sensor model SD14028), hydrogen content data (mostly using a hydrogen sensor model TGS2615-E00), current data (the existing battery management system is equipped with a corresponding current sensor or current data acquisition circuit) and carbon monoxide content data (mostly using a carbon monoxide sensor model TGS5141). Regarding the hydrogen content data and carbon monoxide content data, only one of them or both can be collected.

[0070] This embodiment is based on the existing data acquisition device and does not need to set up various equipment acquisition devices separately. Therefore, overall, the cost is relatively low.

[0071] After all the data are collected, the collected data must be analyzed to determine the state of the solid-state energy storage lithium-ion battery based on the data, so as to determine whether the solid-state energy storage lithium-ion battery is in an abnormal state.

[0072] Analyze and process the classified data to determine whether the solid-state energy storage lithium-ion battery is in an abnormal state;

[0073] The steps of determining whether the solid-state energy storage lithium-ion battery is in an abnormal state include:

[0074] Obtain the surface temperature data of all lithium battery packs, compare the sizes of the obtained surface temperature data, and extract the maximum surface temperature data (because as long as there is a group of lithium battery packs with abnormal temperature, the entire solid-state energy storage lithium-ion battery is in an abnormal state. In order to reduce the amount of related data calculation, the highest temperature data is directly used for calculation to determine whether the lithium battery pack is in an abnormal state);

[0075] The maximum surface temperature data is compared with the abnormal temperature threshold Wdyz, and the solid-state energy storage lithium-ion battery is judged to be abnormal by judging whether the lithium battery pack is abnormal;

[0076] If the maximum surface temperature data is greater than or equal to the abnormal temperature threshold Wdyz, it is determined that the lithium battery pack and the solid-state energy storage lithium-ion battery are in an abnormal state; if the maximum surface temperature data is less than the abnormal temperature threshold, it is determined that the lithium battery pack and the solid-state energy storage lithium-ion battery are in a safe state;

[0077] The calculation formula of abnormal temperature threshold Wdyz is as follows:

[0078] ;

[0079] In the formula, is the highest ambient temperature in the area, Bzz is the ambient temperature of the area set The maximum temperature value of the lithium battery pack for safe operation is shown below, Sw is the current ambient temperature, Jbcz is the temperature difference between each temperature level, and Jbxs is the influence coefficient corresponding to the temperature level;

[0080] For example, if the Bzz is set to 60°C, is 42°C, the current ambient temperature Sw is 30°C, Jbcz is 3°C, and Jbxs is 1.5%, then the abnormal temperature threshold Wdyz=60×(1-12 / 3×1.5%)=56.4°C.

[0081] Existing research usually uses a fixed threshold method for comparison and judgment, which is prone to false alarms at noon in summer and misses the best warning time in winter. Therefore, improvements are needed to set up more flexible and accurate alarm plans.

[0082] Extract the surface temperature data of all lithium battery packs that are 3°C below the abnormal state, and determine whether the extracted lithium battery pack is abnormal, until it is determined that the lithium battery pack is in a safe state.

[0083] This step is mainly for the subsequent processing of abnormal lithium battery packs. Through this step, it can be determined whether all lithium battery packs are abnormal or only a single lithium battery pack is abnormal.

[0084] The setting of this step can effectively avoid processing the data of all lithium battery packs, which can greatly reduce the amount of data processing, thereby increasing the speed of warning and the speed of subsequent abnormal calculation, so that subsequent personnel have a longer reaction time.

[0085] Determining whether the solid-state energy storage lithium-ion battery is in an abnormal state also includes comparing the hydrogen content data and the carbon monoxide content data with the set corresponding gas safety concentration thresholds. When the compared hydrogen content data and the carbon monoxide content data exceed the corresponding gas safety concentration thresholds (because when gas appears outside, it means that the internal pressure of the lithium battery is too high, and the corresponding explosion-proof valve opens to release pressure, which will cause gas leakage. Gas leakage plus high temperature conditions have a very high probability of danger), the solid-state energy storage lithium-ion battery is determined to be in an abnormal state, and the abnormality level is determined to reach level 10.

[0086] When in an abnormal state, a danger alarm is issued, and the classified data is further processed to analyze the cause of the abnormality;

[0087] The steps for further processing the classified data and analyzing the causes of abnormalities are as follows:

[0088] Adjust the frequency of obtaining lithium battery pack operating data. The adjusted data acquisition frequency is 5 times or more of the original acquisition frequency, and the adjusted data acquisition detection time is less than 3 seconds;

[0089] The normal data acquisition time is between 10 seconds and 30 seconds. When an abnormality occurs, if the detection frequency is still used, it may cause a major accident. Therefore, the detection frequency needs to be adjusted. After detection, when the abnormality level is lower than level 5, the best detection time is 2 seconds each time. When the abnormality level is higher than level 5, the best detection time is 1 second each time. The shorter the interval, the more frequently the data is processed.

[0090] Obtain the voltage data and temperature data of the lithium battery pack in an abnormal state, and calculate the voltage change rate and temperature change rate. The voltage change rate = (currently collected voltage - last collected voltage) / collection interval time, and the temperature change rate = (currently collected temperature - last collected temperature) / collection interval time;

[0091] Determine the cause of the abnormality based on the voltage change rate and temperature change rate:

[0092] When the temperature change rate is greater than or equal to 1°C / s, the lithium battery pack will experience thermal runaway, and a danger warning will be issued, and the abnormality level will be determined to be level 10;

[0093] For example, when an abnormality occurs, the detection time is adjusted to 2 seconds each time. The temperature is 60°C during the first detection and 66°C during the second detection. Then the voltage change rate = (66-60) / 2 = 3°C / s. Thermal runaway has occurred at this time. During the thermal runaway stage, the temperature changes dramatically and danger may occur at any time. At this time, the abnormality level is directly determined to be level 10.

[0094] When the temperature change rate is less than 1°C / s, the lithium battery pack is not out of control;

[0095] When the system is not out of control, the cause of the abnormality can be analyzed by the voltage change speed;

[0096] When the voltage drops and the voltage change rate is greater than 1V / s, the abnormality of the lithium battery pack is caused by high temperature caused by mechanical abuse;

[0097] Due to mechanical abuse, the voltage of one or more lithium batteries may drop to 0 instantly.

[0098] The lithium batteries in the lithium battery pack are connected in series. At this time, the damaged lithium battery is equivalent to an increase in internal resistance, and the voltage of the entire lithium battery pack will change significantly. The most direct manifestation is that the voltage change rate is greater than 1V / s.

[0099] The lithium battery pack does not experience instantaneous voltage changes during normal operation. Therefore, the status of the lithium battery pack can be determined by the sudden change in voltage.

[0100] When the voltage rises and exceeds the rated voltage, the abnormality of the lithium battery pack is caused by high temperature caused by electrical abuse;

[0101] This situation is normally caused by overcharging of the battery, and the voltage may drop beyond the rated voltage. As existing batteries have protection measures, over-discharge usually does not occur.

[0102] When the voltage drops at a rate less than 1V / s or the voltage rises but does not reach the rated voltage, the cause of the lithium battery pack abnormality is high temperature caused by thermal abuse.

[0103] This situation mainly occurs when lithium battery packs are used at high power. The heat dissipation speed of lithium battery packs is limited. When the heat generation speed is higher than the heat dissipation speed, heat accumulation will occur.

[0104] Comprehensively analyze the abnormal cause and classified data, calculate the abnormal level and thermal runaway time, and adjust the danger alarm to the corresponding level according to the abnormal level;

[0105] After understanding the cause of the abnormality, you need to analyze the specific cause, determine the abnormality level, and formulate corresponding adjustment strategies based on the abnormality level.

[0106] The anomaly level includes the current anomaly level (obtained based on current detection data) and the predicted anomaly level (predicted future detected data, obtained based on predicted data);

[0107] The calculation formula for the current abnormal level is:

[0108] ;

[0109] Wherein, Ycdj is the current abnormal level, jcwd is the current detected temperature, wdxs is the level influence coefficient corresponding to the temperature, Ycjb is the initial abnormal level corresponding to the abnormal cause, Wdbh is the temperature change rate, Swxs is the level influence coefficient corresponding to the temperature change, 1≤Ycdj≤10, Ycjb corresponding to mechanical abuse>Ycjb corresponding to electrical abuse>Ycjb corresponding to thermal abuse, Ycjb corresponding to mechanical abuse is level 5, Ycjb corresponding to electrical abuse is level 3, and Ycjb corresponding to thermal abuse is level 2.

[0110] For example, the current detected temperature jcwd is 80℃, Wdyz is 60℃, and the level influence coefficient wdxs corresponding to the temperature is 0.05, which is judged as mechanical abuse, that is, Ycjb is level 5, the temperature change rate is 0.8℃ / s, and the level influence coefficient Swxs corresponding to the temperature change is 0.08. Then the calculated current abnormal level Ycdj=(80-60)×0.05+5+0.8×0.05=6.64.

[0111] For example, the current detected temperature jcwd is 70℃, Wdyz is 60℃, the level influence coefficient wdxs corresponding to the temperature is 0.05, and it is judged as electrical abuse, that is, Ycjb is level 3, the temperature change rate is 0.6℃ / s, and the level influence coefficient Swxs corresponding to the temperature change is 0.08. Then the calculated current abnormal level Ycdj=(70-60)×0.05+3+0.8×0.05=4.98.

[0112] For example, the current detected temperature jcwd is 70℃, Wdyz is 60℃, and the level influence coefficient wdxs corresponding to the temperature is 0.05, which is judged as thermal abuse, that is, Ycjb is level 3, the temperature change rate is 0.5℃ / s, and the level influence coefficient Swxs corresponding to the temperature change is 0.08. Then the calculated current abnormal level Ycdj=(70-60)×0.05+3+0.8×0.05=4.9.

[0113] ;

[0114] In the formula, is the temperature change rate after time t; is the detected temperature after time t; is the abnormal level after time t, ,when When the abnormal level reaches level 10;

[0115] For example, 100+Bzz is 160℃, that is, when the temperature reaches 160℃, there is no need to perform any calculations and it can be considered very dangerous.

[0116] When the abnormal cause is high temperature caused by mechanical abuse;

[0117] ;

[0118] ;

[0119] Where A is a constant and A≥10;

[0120] This situation lasts very short, about 20 seconds from the beginning to the highest danger level, because mechanical abuse is usually needle puncture, under normal circumstances the voltage drops to 0 when the needle penetrates the battery, or 2-3 seconds, the lithium battery has thermal runaway, the battery temperature rises sharply, normally within 10 seconds the temperature exceeds the set 100+Bzz, that is, reaches the highest level.

[0121] Once this state is determined, the normal alarm is adjusted to the second-level danger alarm, and then switched to the third-level danger alarm after one or two seconds (the three levels of alarms correspond to three threshold intervals, different sounds can be set, and different alarm frequencies can be set for different abnormal levels in the same threshold interval).

[0122] When the abnormal cause is high temperature caused by electrical abuse;

[0123] ;

[0124] ;

[0125] Wherein, B is a constant, and 220≥B≥180; is the time taken for the temperature to rise by 10°C. It is a multiple of the current charging current and the standard charging current (due to the high temperature, the temperature dissipated by charging is high, and the high temperature will cause thermal abuse, so the overcharge current is exponentially large compared to the small overcharge current).

[0126] In the early stage of lithium battery overcharging, the diaphragm and SEI film will decompose due to high temperature, and it takes a long time for the internal materials of the battery to decompose, which also causes the process of thermal runaway caused by battery abuse to be relatively slow. In this process, the internal materials of the battery first absorb heat, and then release heat to the temperature at which the SEI film begins to decompose. Due to the decomposition of the SEI film, the negative electrode of the battery contacts and reacts with the electrolyte. The battery temperature continues to rise slowly until the positive electrode reacts with the electrolyte. When the battery temperature rises to the thermal runaway trigger threshold, the temperature of the lithium battery will rise explosively. In the early stage, the image of its temperature change is close to a broken line, and in the later stage it is exponential.

[0127] When the abnormal cause is high temperature caused by thermal abuse:

[0128] ;

[0129] ;

[0130] Where C is the influence coefficient of the heating cause on the heating temperature change.

[0131] The high temperature caused by thermal abuse is similar to the first half of the high temperature caused by electrical abuse, but in most cases the temperature rises more slowly. In this case, the temperature usually reaches the set 100+Bzz first, and then the temperature changes exponentially. Therefore, there is no need to calculate the second half, and you can directly calculate the abnormal level reaching the 100+Bzz temperature.

[0132] The result of thermal runaway time calculation is: The time corresponding to reaching 100+Bzz.

[0133] Compare the abnormal level with the set threshold range, and select and execute the corresponding control strategy based on the comparison results.

[0134] The set threshold intervals include the abnormality handling threshold interval (0, 5], the danger handling threshold interval (5, 8] and the fire fighting threshold interval (8, 10];

[0135] According to the comparison results, the corresponding control strategy is selected as follows:

[0136] The current abnormality level is within the abnormality handling threshold range, and the heat dissipation device on the solid-state energy storage lithium-ion battery is started at full power to cool down;

[0137] The heat dissipation equipment on solid-state energy storage lithium-ion batteries usually combines air cooling and water cooling, and this form of regulation is used to check whether abnormal conditions are under control.

[0138] If the current abnormality level is within the danger handling threshold range, the heat dissipation device on the solid-state energy storage lithium-ion battery is fully activated to cool it down, the line of the abnormal lithium battery pack is cut off, and the corresponding number of backup lithium battery packs are connected;

[0139] Disconnecting the circuit of the abnormal lithium battery pack, cutting off its power consumption and alleviating its self-heating phenomenon is a further regulation.

[0140] The current abnormality level is within the fire protection threshold range. The heat dissipation equipment and fire protection equipment on the solid-state energy storage lithium-ion battery are started, the circuit of the abnormal lithium battery pack is cut off, and the solid-state energy storage lithium-ion battery is shut down.

[0141] This situation is usually dangerous and difficult to control, and this method can effectively reduce the losses caused by the abnormality.

[0142] The safe working time of the lithium battery pack is predicted when it is in a safe state. The safe working time is the time it takes to maintain the current use conditions until an abnormal state occurs. The specific calculation formula is as follows:

[0143] ;

[0144] Where Taq is the predicted safe working time. When the calculated Taq is less than 600 seconds, a safety warning is issued.

[0145] This safety warning can help staff adjust strategies reasonably, appropriately reduce the working intensity of lithium batteries, and significantly extend the service life of lithium battery packs.

[0146] The above formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formula are set by technicians in this field according to actual conditions. The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product.

Claims

1. A method for predicting and warning safety risks of solid-state energy storage lithium-ion batteries, characterized in that: The following steps are involved: Obtaining operating data of N groups of lithium battery packs constituting solid-state energy storage lithium-ion batteries, including voltage data, surface temperature data, hydrogen content data, current data, and carbon monoxide content data of the lithium battery packs, and classifying the data according to the numbers of the lithium battery packs; The classified data is analyzed and processed to determine whether the solid-state energy storage lithium-ion battery is in an abnormal state. The steps include: Acquire the surface temperature data of all lithium battery packs, compare the sizes of the acquired surface temperature data, and extract the maximum surface temperature data; The maximum surface temperature data is compared with the abnormal temperature threshold Wdyz, and the solid-state energy storage lithium-ion battery is judged to be abnormal by judging whether the lithium battery pack is abnormal; If the maximum surface temperature data is greater than or equal to the abnormal temperature threshold Wdyz, it is determined that the lithium battery pack and the solid-state energy storage lithium-ion battery are in an abnormal state; if the maximum surface temperature data is less than the abnormal temperature threshold, it is determined that the lithium battery pack and the solid-state energy storage lithium-ion battery are in a safe state; The calculation formula of abnormal temperature threshold Wdyz is as follows: ； In the formula, is the highest ambient temperature in the area, Bzz is the ambient temperature of the area set The maximum temperature value of the lithium battery pack for safe operation is shown below, Sw is the current ambient temperature, Jbcz is the temperature difference between each temperature level, and Jbxs is the influence coefficient corresponding to the temperature level; Extract the surface temperature data of all lithium battery packs that are 3°C below the abnormal state, and determine whether the extracted lithium battery pack is abnormal, until it is determined that the lithium battery pack is in a safe state; When in an abnormal state, a danger alarm is issued, and the classified data is further processed to analyze the cause of the abnormality; Comprehensively analyze the abnormal cause and classified data, calculate the abnormal level and thermal runaway time, and adjust the danger alarm to the corresponding level according to the abnormal level; Compare the abnormal level with the set threshold range, and select and execute the corresponding control strategy based on the comparison results.

2. The method for predicting and warning safety risks of solid-state energy storage lithium-ion batteries according to claim 1, characterized in that: Determining whether the solid-state energy storage lithium-ion battery is in an abnormal state also includes comparing the hydrogen content data and the carbon monoxide content data with the set corresponding gas safety concentration thresholds. When the compared hydrogen content data and the carbon monoxide content data exceed the corresponding gas safety concentration thresholds, it is determined that the solid-state energy storage lithium-ion battery is in an abnormal state, and the abnormality level is determined to reach level 10.

3. The method for predicting and warning safety risks of solid-state energy storage lithium-ion batteries according to claim 2, characterized in that: The steps for further processing the classified data and analyzing the causes of abnormalities are as follows: Adjust the frequency of obtaining lithium battery pack operating data. The adjusted data acquisition frequency is 5 times or more of the original acquisition frequency, and the adjusted data acquisition detection time is less than 3 seconds; Obtain the voltage data and temperature data of the lithium battery pack in an abnormal state, and calculate the voltage change rate and temperature change rate. The voltage change rate = (currently collected voltage - last collected voltage) / collection interval time, and the temperature change rate = (currently collected temperature - last collected temperature) / collection interval time; Determine the cause of the abnormality based on the voltage change rate and temperature change rate: When the temperature change rate is greater than or equal to 1°C / s, the lithium battery pack will experience thermal runaway, and a danger warning will be issued, and the abnormality level will be determined to be level 10; When the temperature change rate is less than 1°C / s, the lithium battery pack is not out of control; When the system is not out of control, the cause of the abnormality can be analyzed by the voltage change speed; When the voltage drops and the voltage change rate is greater than 1V / s, the abnormality of the lithium battery pack is caused by high temperature caused by mechanical abuse; When the voltage rises and exceeds the rated voltage, the abnormality of the lithium battery pack is caused by high temperature caused by electrical abuse; When the voltage drops at a rate less than 1V / s or the voltage rises but does not reach the rated voltage, the cause of the lithium battery pack abnormality is high temperature caused by thermal abuse.

4. The method for predicting and warning safety risks of solid-state energy storage lithium-ion batteries according to claim 3 is characterized in that: The abnormality level includes a current abnormality level and a predicted abnormality level; The calculation formula for the current abnormal level is: ； Wherein, Ycdj is the current abnormal level, jcwd is the current detection temperature, wdxs is the level influence coefficient corresponding to the temperature, Ycjb is the initial abnormal level corresponding to the abnormal cause, Wdbh is the temperature change rate, Swxs is the level influence coefficient corresponding to the temperature change, 1≤Ycdj≤10, Ycjb corresponding to mechanical abuse>Ycjb corresponding to electrical abuse>Ycjb corresponding to thermal abuse, and Ycjb corresponding to mechanical abuse is level 5.

5. The method for predicting and warning safety risks of solid-state energy storage lithium-ion batteries according to claim 4 is characterized in that: The calculation formula for predicting the abnormal level is: ； In the formula, is the temperature change rate after time t; is the detected temperature after time t; is the abnormal level after time t, ,when When the abnormal level reaches level 10; When the abnormal cause is high temperature caused by mechanical abuse; ； ； Where A is a constant and A≥10; When the abnormal cause is high temperature caused by electrical abuse; ； ； Wherein, B is a constant, and 220≥B≥180; is the time taken for the temperature to rise by 10°C. It is the multiple of the current charging current and the standard charging current; When the abnormal cause is high temperature caused by thermal abuse: ； ； Where C is the influence coefficient of the heating cause on the heating temperature change.

6. The method for predicting and warning safety risks of solid-state energy storage lithium-ion batteries according to claim 5, characterized in that: The result of thermal runaway time calculation is: The time corresponding to reaching 100+Bzz.

7. The method for predicting and warning safety risks of solid-state energy storage lithium-ion batteries according to claim 6, characterized in that: The set threshold intervals include the abnormality handling threshold interval (0, 5], the danger handling threshold interval (5, 8] and the fire fighting threshold interval (8, 10]; According to the comparison results, the corresponding control strategy is selected as follows: The current abnormality level is within the abnormality handling threshold range, and the heat dissipation device on the solid-state energy storage lithium-ion battery is started at full power to cool down; If the current abnormality level is within the danger handling threshold range, the heat dissipation device on the solid-state energy storage lithium-ion battery is fully activated to cool it down, the line of the abnormal lithium battery pack is cut off, and the corresponding number of backup lithium battery packs are connected; The current abnormality level is within the fire protection threshold range. The heat dissipation equipment and fire protection equipment on the solid-state energy storage lithium-ion battery are started, the circuit of the abnormal lithium battery pack is cut off, and the solid-state energy storage lithium-ion battery is shut down.

8. The method for predicting and warning safety risks of solid-state energy storage lithium-ion batteries according to claim 7, characterized in that: The safe working time of the lithium battery pack is predicted when it is in a safe state. The safe working time is the time to maintain the current use conditions until an abnormal state occurs. The specific calculation formula is as follows: ； Where Taq is the predicted safe working time. When the calculated Taq is less than 600 seconds, a safety warning is issued.

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