Thermal runaway early warning detection system and method of power supply side energy storage unit

Abstract

The invention relates to the technical field of thermal runaway early warning of energy storage units, and discloses a thermal runaway early warning detection system and method for a power supply side energy storage unit, and the method comprises the steps: obtaining the thermal runaway information of various energy storage units, and building an energy storage unit model according to the thermal runaway information of various energy storage units. And obtaining configuration information of the energy storage unit to be detected, substituting the configuration information into the energy storage unit model, and obtaining thermal runaway preset trigger data of the energy storage unit to be detected. And acquiring operation information and environment information of the to-be-detected energy storage unit, and performing thermal runaway evaluation. And determining a risk level according to the thermal runaway assessment, and when the early warning level of the to-be-detected energy storage unit is a medium risk level or a high risk level, determining to send early warning information. According to the method, the information of the energy storage unit is comprehensively analyzed, and multi-dimensional evaluation is performed based on the thermal runaway preset triggering data, so that the thermal runaway risk of the energy storage unit is more accurately judged.

Description

Technical Field

[0001] The present invention relates to the technical field of thermal runaway warning of energy storage units, and in particular to a thermal runaway warning detection system and method for an energy storage unit on a power supply side. Background Art

[0002] With the rapid development of renewable energy, power supply side energy storage units are increasingly used in power systems. Energy storage units can effectively balance power supply and demand and improve the stability and operating efficiency of the power grid. However, with the increase in capacity and complexity of energy storage systems, energy storage units face a variety of safety risks during operation. Thermal runaway is one of the most serious problems, which may cause equipment damage or even fire, explosion and other safety accidents. Therefore, how to timely and accurately warn of thermal runaway of energy storage units has become a technical problem that needs to be solved urgently.

[0003] Existing energy storage units rely on simple temperature, voltage monitoring and other single factors. Although they can provide early warning of thermal runaway, they lack comprehensive analysis of multi-dimensional information. This approach often cannot accurately predict the occurrence of thermal runaway, especially in complex working conditions or harsh environments. Existing early warning systems often cannot detect potential risks in a timely manner. At the same time, existing technologies lack differentiated processing methods for different types of energy storage units (such as lithium batteries, lead-acid batteries, etc.), and cannot perform personalized early warning assessments based on the characteristics of different types of energy storage units.

[0004] Therefore, there is an urgent need to invent a thermal runaway warning technology for energy storage units to solve the problem that the thermal runaway warning technology for energy storage units in the existing technology lacks multi-dimensional comprehensive analysis and differentiated processing, resulting in insufficient warning accuracy under complex working conditions and difficulty in realizing risk assessment of different types of energy storage units. Summary of the invention

[0005] In view of this, the present invention proposes a thermal runaway warning detection system and method for a power supply side energy storage unit, aiming to solve the problem that the existing technology of thermal runaway warning technology of energy storage units lacks multi-dimensional comprehensive analysis and differentiated processing, resulting in insufficient warning accuracy under complex working conditions and difficulty in realizing risk assessment of different types of energy storage units.

[0006] The present invention proposes a thermal runaway early warning detection method for a power supply side energy storage unit, comprising:

[0007] Acquire thermal runaway information of various energy storage units, and establish an energy storage unit model according to the thermal runaway information of various types of energy storage units;

[0008] Acquire configuration information of the energy storage unit to be detected, substitute the configuration information into the energy storage unit model, and acquire thermal runaway preset trigger data of the energy storage unit to be detected;

[0009] Acquiring operation information and environmental information of the energy storage unit to be detected, and performing thermal runaway assessment on the operation information and environmental information according to the preset thermal runaway trigger data;

[0010] Acquire the thermal runaway assessment score, and determine the warning level of the energy storage unit to be detected according to the relationship between the thermal runaway assessment score and the first preset score and the second preset score;

[0011] When the thermal runaway assessment score is lower than the first preset score, determining that the warning level of the energy storage unit to be detected is a low risk level;

[0012] When the thermal runaway assessment score is higher than or equal to the first preset score, and the thermal runaway assessment score is lower than the second preset score, it is determined that the warning level of the energy storage unit to be detected is a medium risk level;

[0013] When the thermal runaway assessment score is higher than or equal to the second preset score, it is determined that the warning level of the energy storage unit to be detected is a high risk level;

[0014] Wherein, the first preset score is lower than the second preset score, and when the warning level of the energy storage unit to be detected is a medium risk level or a high risk level, it is determined to send the warning information.

[0015] Furthermore, when obtaining thermal runaway information of various energy storage units and establishing an energy storage unit model according to the thermal runaway information of various types of energy storage units, it includes:

[0016] Acquire material information of various types of energy storage units, cluster thermal runaway information of various types of energy storage units according to the material information, and acquire thermal runaway trigger data of each material after clustering, wherein the thermal runaway trigger data includes: the number of overcharge energy storage times, internal structural resistances, and ambient temperature of the energy charging unit;

[0017] The energy storage unit model is established according to the thermal runaway trigger data of each of the materials.

[0018] Furthermore, when establishing the energy storage unit model according to the thermal runaway trigger data of each material, it includes:

[0019] Establishing each thermal runaway trigger relational expression of the material according to each thermal runaway trigger data corresponding to the material;

[0020] Obtaining a distance metric between the thermal runaway triggering relational expressions to be clustered;

[0021] constructing a distance matrix according to the distance metric, and recursively merging the thermal runaway trigger relational expressions according to the distance matrix;

[0022] The preset trigger relationship formulas for thermal runaway of the materials after recursive merging are obtained, and the energy storage unit model is established according to the preset trigger relationship formulas for thermal runaway of each material.

[0023] Furthermore, obtaining the operation information and environmental information of the energy storage unit to be detected, and performing thermal runaway assessment on the operation information and environmental information according to the preset thermal runaway trigger data, includes:

[0024] Obtaining the number of overcharge energy storage times of the energy storage unit to be detected in the operation information, as well as the overcharge voltage and excess capacity during each overcharge energy storage;

[0025] Obtaining the preset overcharge voltage limit and the preset excess capacity limit during overcharge energy storage in the thermal runaway preset trigger data;

[0026] According to the relationship between the overcharge voltage and the excess capacity during each overcharge energy storage and the preset overcharge voltage limit and the preset excess capacity limit, the effective overcharge energy storage times during each overcharge energy storage are determined, wherein:

[0027] If the overcharge voltage during the overcharge energy storage is equal to or higher than the preset overcharge voltage limit, and / or the excess capacity during the overcharge energy storage is equal to or higher than the preset excess capacity limit, then determining that the overcharge energy storage is the effective overcharge energy storage number;

[0028] The thermal runaway assessment score is evaluated based on the effective overcharge energy storage times.

[0029] Furthermore, when evaluating the thermal runaway assessment score according to the effective overcharge energy storage times, the following steps are included:

[0030] Pre-configure a preset effective overcharge energy storage number, and obtain the difference between the effective overcharge energy storage number and the preset effective overcharge energy storage number;

[0031] Determining the thermal runaway assessment score according to a relationship between the number difference and a configured first preset number difference and a second preset number difference;

[0032] When the number difference is lower than the first preset number difference, the thermal runaway assessment score is determined to be L1;

[0033] When the number difference is higher than or equal to the first preset number difference, and the number difference is lower than the second preset number difference, the thermal runaway score is determined to be L2;

[0034] When the number difference is greater than or equal to the second preset number difference, the thermal runaway score is determined to be L3;

[0035] The first preset number difference is smaller than the second preset number difference, and L1<L2<L3.

[0036] Further, when the thermal runaway score is determined to be Li, i=1, 2, 3, including:

[0037] Obtaining the real-time operating voltage and real-time internal resistance value inside the energy storage unit in the operating information;

[0038] Obtaining a preset operating voltage and a preset internal resistance value in the preset thermal runaway trigger data, and performing a comparison between the real-time operating voltage and the preset operating voltage, wherein:

[0039] If the real-time operating voltage is lower than the preset operating voltage, a trend curve of the operating voltage within a preset time period in the operating information is obtained;

[0040] Determining a drop amplitude of the operating voltage within the preset period according to the trend curve, and determining whether to adjust the thermal runaway score Li according to a relationship between the drop amplitude and a preset drop amplitude;

[0041] When the decrease range is higher than the preset decrease range, it is determined that the thermal runaway score Li is not adjusted;

[0042] When the decrease is lower than or equal to a preset decrease, it is determined that the thermal runaway score Li is adjusted, and an adjustment coefficient for adjusting the thermal runaway score Li is determined according to a relationship between the real-time internal resistance value and the preset internal resistance value.

[0043] Further, when determining the adjustment coefficient for adjusting the thermal runaway score Li according to the relationship between the real-time internal resistance value and the preset internal resistance value, it includes:

[0044] The internal resistance difference between the real-time internal resistance value and the preset internal resistance value is obtained, and the adjustment coefficient is determined according to the relationship between the internal resistance difference and the configured first preset internal resistance difference and the second preset internal resistance difference:

[0045] When the internal resistance difference is less than or equal to the first preset internal resistance difference, the adjustment coefficient is determined to be M1;

[0046] When the internal resistance difference is greater than the first preset internal resistance difference, and the internal resistance difference is less than or equal to the second preset internal resistance difference, the adjustment coefficient is determined to be M2;

[0047] When the internal resistance difference is greater than the second preset internal resistance difference, the adjustment coefficient is determined to be M3;

[0048] Wherein, the first preset internal resistance difference is smaller than the second preset internal resistance difference, and M1<M2<M3<1.

[0049] Further, when the adjustment coefficient is determined to be Mi, i=1, 2, 3, including:

[0050] Acquire the real-time ambient temperature in the environmental information and the preset ambient temperature in the thermal runaway preset trigger data;

[0051] According to the relationship between the real-time ambient temperature and the preset ambient temperature, determine whether to modify the adjustment coefficient Mi:

[0052] When the real-time ambient temperature is lower than the preset ambient temperature, it is determined that the adjustment coefficient Mi is not to be corrected;

[0053] When the real-time ambient temperature is higher than or equal to the preset ambient temperature, a correction coefficient is determined according to the temperature difference between the real-time ambient temperature and the preset ambient temperature, and the adjustment coefficient Mi is corrected according to the correction coefficient.

[0054] Furthermore, when determining the correction coefficient according to the temperature difference between the real-time ambient temperature and the preset ambient temperature, it includes:

[0055] Determining the correction coefficient according to a relationship between the temperature difference and a configured first preset temperature difference and a second preset temperature difference;

[0056] When the temperature difference is lower than or equal to the first preset temperature difference, the correction coefficient is determined to be N1;

[0057] When the temperature difference is higher than the first preset temperature difference and the temperature difference is lower than or equal to the second preset temperature difference, the correction coefficient is determined to be N2;

[0058] When the temperature difference is higher than the second preset temperature difference, the correction coefficient is determined to be N3;

[0059] The first preset temperature difference is lower than the second preset temperature difference, and N1<N2<N3<1.

[0060] Compared with the prior art, the beneficial effect of the present invention is that: by obtaining the thermal runaway information of various types of energy storage units, models of different types of energy storage units are established accordingly. Thereby improving the applicability and prediction accuracy of different types of energy storage units. Secondly, by substituting the configuration information of the energy storage unit to be detected into the energy storage unit model, the key parameters that trigger thermal runaway of the energy storage unit to be detected are obtained. These preset trigger data contain the risk points that may occur during the operation of the energy storage unit. Combined with the modeled analysis, the key factors that may cause thermal runaway can be locked in advance. Further, by obtaining the operating information and environmental information of the energy storage unit to be detected, and performing a comprehensive thermal runaway assessment on it according to the key parameters that trigger thermal runaway. Thereby identifying the thermal runaway risk more comprehensively, thereby significantly reducing the possibility of misjudgment or omission. Finally, the risk level of the energy storage unit is carefully divided according to the thermal runaway assessment score. And when the assessment score reaches the medium risk or high risk level, an early warning message will be sent to notify the operator to intervene in time. Not only the possibility of sudden accidents is reduced. At the same time, unnecessary alarms are avoided, and the interference of excessive early warnings on system stability is reduced.

[0061] On the other hand, the present application also provides a thermal runaway early warning detection system for a power supply side energy storage unit, comprising:

[0062] A model generation module, used to obtain thermal runaway information of various energy storage units, and establish an energy storage unit model according to the thermal runaway information of various types of energy storage units;

[0063] A data acquisition module, used to acquire configuration information of the energy storage unit to be detected, as well as operation information and environmental information of the energy storage unit to be detected;

[0064] An evaluation module, respectively connected to the model generation module and the data acquisition module, the evaluation module is used to substitute the configuration information into the energy storage unit model, and obtain the thermal runaway preset trigger data of the energy storage unit to be detected; the evaluation module is also used to perform thermal runaway evaluation on the operation information and environmental information according to the thermal runaway preset trigger data;

[0065] an early warning module, electrically connected to the evaluation module, and configured to obtain the thermal runaway evaluation score, and determine the early warning level of the energy storage unit to be detected according to the relationship between the thermal runaway evaluation score and the first preset score and the second preset score, wherein:

[0066] When the warning level of the energy storage unit to be detected is a medium risk level or a high risk level, it is determined to send a warning message.

[0067] It can be understood that the thermal runaway early warning detection system and method of a power-side energy storage unit in the above-mentioned embodiments of the present invention have the same beneficial effects and will not be described in detail. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0069] Figure 1 A flowchart of a thermal runaway early warning detection method for a power supply side energy storage unit provided by an embodiment of the present invention;

[0070] Figure 2 A functional block diagram of a thermal runaway early warning detection system for a power supply side energy storage unit provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0071] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features described in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0072] like Figure 1 As shown, in some embodiments of the present application, this embodiment provides a thermal runaway early warning detection method for a power supply side energy storage unit, comprising:

[0073] Step S100: Acquire thermal runaway information of various types of energy storage units, and establish an energy storage unit model according to the thermal runaway information of various types of energy storage units.

[0074] Specifically, when obtaining thermal runaway information of various energy storage units and establishing an energy storage unit model based on the thermal runaway information of various types of energy storage units, it includes: obtaining material information of various types of energy storage units, clustering the thermal runaway information of various types of energy storage units based on the material information, and obtaining thermal runaway trigger data of each material after clustering, and the thermal runaway trigger data includes: the number of overcharge energy storage, the internal structural resistance and the ambient temperature of the charging unit. According to the thermal runaway trigger data of each material, the energy storage unit model is established.

[0075] Specifically, when establishing an energy storage unit model based on the thermal runaway trigger data of each material, it includes: establishing each thermal runaway trigger relationship of the material according to the thermal runaway trigger data corresponding to the material. Obtaining the distance measurement between each thermal runaway trigger relationship to be clustered. Constructing a distance matrix based on the distance measurement, and recursively merging each thermal runaway trigger relationship according to the distance matrix. Obtaining the thermal runaway preset trigger relationship of the recursively merged material, and establishing the energy storage unit model according to the thermal runaway preset trigger relationship of each material.

[0076] It can be seen that by obtaining the material information of different energy storage units and combining the thermal runaway trigger data corresponding to each material (such as the number of overcharge energy storage, the resistance of each internal structure, and the ambient temperature of the energy storage unit and other key parameters), the energy storage units are classified. These trigger data represent the key factors that may cause thermal runaway of the energy storage unit under different working conditions. Collecting these data can help reveal the operating risks of the energy storage unit in practical applications. By clustering these data, different energy storage units can be targeted according to the thermal runaway information of each material. In the clustering process, thermal runaway trigger relationships are established by using the thermal runaway trigger data of different materials. These relationships reflect the intrinsic connection between materials and thermal runaway risks. For example, a certain material is more likely to have thermal runaway under specific temperatures or overcharge conditions. Then, the similarity between different trigger relationships is measured by distance measurement. The smaller the distance, the closer the trigger characteristics of the two relationships are. Through this distance measurement method, a distance matrix is ​​constructed to comprehensively analyze the feature differences of energy storage units. Based on the distance matrix, each thermal runaway trigger relationship is recursively merged. This process is similar to layer-by-layer clustering, gradually combining similar relationships together to form a more representative classification result. The recursively merged material thermal runaway preset trigger relationship can clearly reflect the key differences in thermal runaway risks of different materials. These relationships not only help to establish the energy storage unit model, but also further optimize the system's early warning mechanism, so that it can more accurately predict the thermal runaway risk of the energy storage unit under different conditions. Finally, based on the thermal runaway preset trigger relationship generated by cluster analysis and recursive merging, the corresponding energy storage unit model was established. This model is not only a simple risk prediction tool, but also a multidimensional analysis system that integrates the material characteristics, environmental factors and operating conditions of the energy storage unit. It can provide accurate thermal runaway warnings based on specific materials and trigger conditions, and improve the safety and reliability of the energy storage unit by real-time comparison with actual operating data.

[0077] Step S200: obtaining configuration information of the energy storage unit to be detected, substituting the configuration information into the energy storage unit model, and obtaining thermal runaway preset trigger data of the energy storage unit to be detected.

[0078] Step S300: Acquire the operation information and environmental information of the energy storage unit to be detected, and perform thermal runaway assessment on the operation information and environmental information according to preset thermal runaway trigger data.

[0079] Specifically, when the operation information and environmental information of the energy storage unit to be detected are obtained and the thermal runaway assessment is performed on the operation information and environmental information according to the preset trigger data of thermal runaway, it includes: obtaining the number of overcharge energy storage of the energy storage unit to be detected in the operation information, as well as the overcharge voltage and excess capacity at each overcharge energy storage. Obtain the preset overcharge voltage limit and the preset excess capacity limit at overcharge energy storage in the preset trigger data of thermal runaway. According to the relationship between the overcharge voltage and excess capacity at each overcharge energy storage and the preset overcharge voltage limit and the preset excess capacity limit, determine the effective number of overcharge energy storage at each overcharge energy storage, wherein: if the overcharge voltage at the time of overcharge energy storage is equal to or higher than the preset overcharge voltage limit, and / or the excess capacity at the time of overcharge energy storage is equal to or higher than the preset excess capacity limit, then determine that the overcharge energy storage is the effective number of overcharge energy storage. According to the effective number of overcharge energy storage, evaluate the thermal runaway assessment score.

[0080] Specifically, when evaluating the thermal runaway assessment score according to the effective overcharge energy storage times, it includes: pre-configuring a preset effective overcharge energy storage times, and obtaining the difference between the effective overcharge energy storage times and the preset effective overcharge energy storage times. Determine the thermal runaway assessment score based on the relationship between the difference in times and the configured first preset difference in times and the second preset difference in times. When the difference in times is lower than the first preset difference in times, the thermal runaway assessment score is determined to be L1. When the difference in times is higher than or equal to the first preset difference in times, and the difference in times is lower than the second preset difference in times, the thermal runaway score is determined to be L2. When the difference in times is higher than or equal to the second preset difference in times, the thermal runaway score is determined to be L3. Among them, the first preset difference in times is less than the second preset difference in times, and L1<L2<L3.

[0081] It can be seen that by obtaining the operating information of the energy storage unit to be detected, especially the number of overcharge energy storage, overcharge voltage, and excess capacity data, it is compared with the preset thermal runaway trigger data (such as overcharge voltage limit and excess capacity limit). According to the comparison result, it is determined whether a certain overcharge energy storage behavior reaches or exceeds the preset safety limit. If the overcharge voltage or excess capacity reaches the preset limit, the overcharge is regarded as a valid overcharge energy storage number. Next, by calculating the difference between the effective overcharge energy storage number and the preset safety number, the thermal runaway risk level of the energy storage unit is judged according to the size of the difference. In technical principle, by configuring different preset number differences (first preset number difference, second preset number difference) as the dividing line, when the difference is small (lower than the first preset number difference), the risk is low and is evaluated as L1; when the difference is moderate (between the first and second preset number differences), the risk increases and is evaluated as L2; ​​when the difference is large (higher than the second preset number difference), the risk is the greatest and is evaluated as L3. This process evaluates the thermal runaway risk of the energy storage unit based on the relationship between the real-time data of overcharging behavior and the preset trigger data, and generates a corresponding thermal runaway score.

[0082] It is understandable that by introducing the concept of "effective overcharge energy storage times", it is clearly stipulated that when the overcharge voltage or excess capacity reaches or exceeds the preset limit, the overcharge behavior will be counted as an effective overcharge energy storage. The introduction of this process greatly improves the accuracy of the assessment, because not all overcharge behaviors will have a significant impact on the energy storage unit, and only those overcharge behaviors that reach or exceed the preset limit will increase the risk of thermal runaway. Therefore, by filtering out unimportant overcharge behaviors, it is possible to focus more on key factors that may cause thermal runaway. Secondly, by further comparing the effective overcharge energy storage times with the preset safety times, the thermal runaway risk level of the energy storage unit is determined. By setting different preset times difference, the level assessment of thermal runaway risk can be flexibly adjusted according to the size of the difference. When the difference between the effective overcharge energy storage times and the preset safety times is small, the risk of the energy storage unit is low and is assessed as L1; when the difference is in the medium range, the risk is medium and is assessed as L2; ​​when the difference is large, the risk is the highest and is assessed as L3. This hierarchical assessment mechanism helps to timely discover potential risks of energy storage units and provide data support for the next decision. The impact of the difference on the assessment score can dynamically reflect the risk changes of energy storage units, helping operation and maintenance personnel to take timely action when there is a greater risk in the energy storage unit.

[0083] Specifically, when the thermal runaway score is determined to be Li, i=1,2,3, including: obtaining the real-time operating voltage and real-time internal resistance value inside the energy storage unit in the operating information. Obtaining the preset operating voltage and preset internal resistance value in the preset trigger data of thermal runaway, and comparing the real-time operating voltage with the preset operating voltage, wherein: if the real-time operating voltage is lower than the preset operating voltage, then obtaining the trend curve of the operating voltage in the preset time period in the operating information. Determine the drop in the operating voltage in the preset time period according to the trend curve, and determine whether to adjust the thermal runaway score Li according to the relationship between the drop and the preset drop. When the drop is higher than the preset drop, it is determined not to adjust the thermal runaway score Li. When the drop is lower than or equal to the preset drop, it is determined to adjust the thermal runaway score Li, and determine the adjustment coefficient for adjusting the thermal runaway score Li according to the relationship between the real-time internal resistance and the preset internal resistance.

[0084] Specifically, when determining the adjustment coefficient for adjusting the thermal runaway score Li according to the relationship between the real-time internal resistance value and the preset internal resistance value, it includes: obtaining the internal resistance difference between the real-time internal resistance value and the preset internal resistance value, and determining the adjustment coefficient according to the relationship between the internal resistance difference and the configured first preset internal resistance difference and the second preset internal resistance difference: when the internal resistance difference is less than or equal to the first preset internal resistance difference, the adjustment coefficient is determined to be M1. When the internal resistance difference is greater than the first preset internal resistance difference, and the internal resistance difference is less than or equal to the second preset internal resistance difference, the adjustment coefficient is determined to be M2. When the internal resistance difference is greater than the second preset internal resistance difference, the adjustment coefficient is determined to be M3. Among them, the first preset internal resistance difference is less than the second preset internal resistance difference, and M1<M2<M3<1.

[0085] It can be seen that when the real-time operating voltage is lower than the preset operating voltage, the voltage trend curve within the preset time period is obtained to analyze the voltage drop. If the drop is higher than the preset safety range, it means that the risk of thermal runaway is low and there is no need to adjust the score; if the drop is lower than or equal to the preset range, it is necessary to further analyze the internal resistance difference to determine whether to adjust the thermal runaway score Li. Then, by comparing the difference between the real-time internal resistance value and the preset internal resistance value, the internal resistance difference is calculated, and according to the size of the difference, different adjustment coefficients M1, M2 or M3 are selected to adjust the thermal runaway score Li. This process can dynamically evaluate the risk of thermal runaway according to the changes in voltage and internal resistance, and ensure the accuracy and timeliness of the score through a comprehensive evaluation of multi-dimensional parameters, thereby improving the safety of the energy storage system.

[0086] It is understandable that when it is detected that the real-time operating voltage of the energy storage unit is lower than the preset operating voltage, the voltage trend curve of the energy storage unit in a specific period of time will be further obtained. By analyzing the trend of voltage drop, the amplitude of voltage change can be determined. If the voltage drop exceeds the preset safety range, it means that the current energy storage unit may be in a relatively safe state, and there is no need to adjust the thermal runaway score Li at this time; but if the voltage drop is small, or the voltage fails to meet the preset safety standard, it is considered that the energy storage unit may have a higher risk of thermal runaway, so the score Li needs to be adjusted. This analysis method based on voltage trend can more comprehensively reflect the health status of the energy storage unit. In many cases, the voltage data at a single time point is not enough to accurately assess the safety of the energy storage unit, and the voltage change trend provides a more comprehensive perspective. For example, the voltage may be lower than the preset voltage at a certain measurement, but if the voltage decline trend is slow or stable, it may not indicate a serious risk. If the rapid decline trend of the voltage exceeds the preset amplitude, it means that the voltage decays too fast and there may be a risk of thermal runaway. Therefore, through trend analysis, problems can be discovered earlier, so that early warning can be given before the problem worsens. Furthermore, when evaluating the risk of thermal runaway, a comprehensive analysis is performed in combination with the internal resistance value of the energy storage unit. When the voltage trend shows a potential risk, the difference between the real-time internal resistance value and the preset internal resistance value, that is, the internal resistance difference, is calculated. The internal resistance usually reflects changes in the internal health of the energy storage unit. As the use time of the energy storage unit increases, the internal resistance may also gradually increase. By analyzing the internal resistance difference, the degree of degradation of the current energy storage unit can be judged, and according to the size of the internal resistance difference, an appropriate adjustment coefficient is selected to adjust the thermal runaway score Li. Specifically, two internal resistance difference thresholds are set: a first preset internal resistance difference and a second preset internal resistance difference. When the internal resistance difference is small (less than or equal to the first preset internal resistance difference), it is determined that the internal resistance of the energy storage unit has not changed much and the risk is low. At this time, the adjustment coefficient M1 is selected for score adjustment; when the internal resistance difference is in the middle range (greater than the first preset internal resistance difference and less than or equal to the second preset internal resistance difference), it indicates that the internal resistance has increased and there may be a moderate risk. At this time, the adjustment coefficient M2 is selected; if the internal resistance difference is large (greater than the second preset internal resistance difference), it indicates that the change in internal resistance has exceeded the safe range, and the energy storage unit may have a greater safety hazard. At this time, the highest adjustment coefficient M3 is selected for adjustment. This hierarchical regulation of the internal resistance difference further makes the score adjustment more targeted and accurate. At the same time, by designing the order relationship of the adjustment coefficient, that is, M1<M2<M3<1, this means that the larger the adjustment coefficient, the higher the risk of thermal runaway, and the larger the adjustment range. This design ensures that when the internal resistance difference is larger, the adjustment of the score Li is more sensitive, further improving the early warning capability of the potential thermal runaway risk of the energy storage unit.

[0087] Specifically, when the adjustment coefficient is determined to be Mi, i=1,2,3, including: obtaining the real-time ambient temperature in the environmental information and the preset ambient temperature in the preset trigger data of thermal runaway. According to the relationship between the real-time ambient temperature and the preset ambient temperature, determine whether to correct the adjustment coefficient Mi: when the real-time ambient temperature is lower than the preset ambient temperature, it is determined not to correct the adjustment coefficient Mi. When the real-time ambient temperature is higher than or equal to the preset ambient temperature, the correction coefficient is determined according to the temperature difference between the real-time ambient temperature and the preset ambient temperature, and the adjustment coefficient Mi is corrected according to the correction coefficient.

[0088] Specifically, when determining the correction coefficient according to the temperature difference between the real-time ambient temperature and the preset ambient temperature, it includes: determining the correction coefficient according to the relationship between the temperature difference and the configured first preset temperature difference and the second preset temperature difference. When the temperature difference is lower than or equal to the first preset temperature difference, the correction coefficient is determined to be N1. When the temperature difference is higher than the first preset temperature difference, and the temperature difference is lower than or equal to the second preset temperature difference, the correction coefficient is determined to be N2. When the temperature difference is higher than the second preset temperature difference, the correction coefficient is determined to be N3. Among them, the first preset temperature difference is lower than the second preset temperature difference, and N1<N2<N3<1.

[0089] It can be seen that the thermal runaway risk adjustment coefficient Mi of the energy storage unit is dynamically corrected by the temperature difference between the real-time ambient temperature and the preset ambient temperature to more accurately reflect the impact of the ambient temperature on the safety of the energy storage unit. Specifically, by comparing the real-time ambient temperature with the preset ambient temperature, when the real-time ambient temperature is lower than the preset temperature, it is considered that the impact of the ambient temperature on thermal runaway is small, so there is no need to correct the adjustment coefficient. However, when the real-time ambient temperature is higher than or equal to the preset temperature, the system will determine the correction coefficient based on the temperature difference between the two, thereby correcting the adjustment coefficient. During the correction process, the temperature difference is compared with the two-level preset temperature difference and divided into three levels: when the temperature difference is small (lower than or equal to the first preset temperature difference), the correction coefficient is N1, and it is believed that the temperature difference has little impact on the safety of thermal runaway; when the temperature difference is in the middle range (higher than the first preset temperature difference and lower than or equal to the second preset temperature difference), the correction coefficient is N2, indicating that the ambient temperature has a greater impact on thermal runaway; and when the temperature difference exceeds the second preset temperature difference, the correction coefficient is N3, indicating that the ambient temperature has the greatest impact on thermal runaway and requires the greatest degree of correction. This dynamic correction method based on ambient temperature can enable the energy storage unit to more sensitively predict the risk of thermal runaway in a high temperature environment, thereby further improving the safety of the energy storage unit.

[0090] Step S400: Obtain a thermal runaway assessment score, and determine a warning level of the energy storage unit to be detected according to a relationship between the thermal runaway assessment score and a first preset score and a second preset score.

[0091] Specifically, when determining the warning level of the energy storage unit to be detected based on the relationship between the thermal runaway assessment score and the first preset score and the second preset score, it includes: when the thermal runaway assessment score is lower than the first preset score, the warning level of the energy storage unit to be detected is determined to be a low risk level. When the thermal runaway assessment score is higher than or equal to the first preset score, and the thermal runaway assessment score is lower than the second preset score, the warning level of the energy storage unit to be detected is determined to be a medium risk level. When the thermal runaway assessment score is higher than or equal to the second preset score, the warning level of the energy storage unit to be detected is determined to be a high risk level. Among them, the first preset score is lower than the second preset score, and when the warning level of the energy storage unit to be detected is a medium risk level or a high risk level, it is determined to send a warning message.

[0092] In the above embodiment, the thermal runaway information of various types of energy storage units is obtained, and models of different types of energy storage units are established accordingly. Thereby improving the applicability and prediction accuracy of different types of energy storage units. Secondly, by substituting the configuration information of the energy storage unit to be detected into the energy storage unit model, the key parameters that trigger thermal runaway of the energy storage unit to be detected are obtained. These preset trigger data contain the risk points that may occur during the operation of the energy storage unit. Combined with the modeled analysis, the key factors that may cause thermal runaway can be locked in advance. Further, by obtaining the operating information and environmental information of the energy storage unit to be detected, and performing a comprehensive thermal runaway assessment on it according to the key parameters that trigger thermal runaway. Thereby identifying the thermal runaway risk more comprehensively, thereby significantly reducing the possibility of misjudgment or omission. Finally, the risk level of the energy storage unit is carefully divided according to the thermal runaway assessment score. And when the assessment score reaches the medium risk or high risk level, an early warning message will be sent to notify the operator to intervene in time. Not only the possibility of sudden accidents is reduced. At the same time, unnecessary alarms are avoided, and the interference of excessive early warnings on system stability is reduced.

[0093] In another preferred embodiment based on the above embodiment, Figure 2As shown, this embodiment provides a thermal runaway early warning detection system for a power supply side energy storage unit, including: a model generation module, a data acquisition module, an evaluation module and an early warning module. The model generation module is used to obtain thermal runaway information of various energy storage units, and establish an energy storage unit model according to the thermal runaway information of various types of energy storage units. The data acquisition module is used to obtain the configuration information of the energy storage unit to be detected, as well as the operation information and environmental information of the energy storage unit to be detected. The evaluation module is respectively connected to the model generation module and the data acquisition module, and the evaluation module is used to substitute the configuration information into the energy storage unit model and obtain the thermal runaway preset trigger data of the energy storage unit to be detected. The evaluation module is also used to perform thermal runaway evaluation on the operation information and environmental information according to the thermal runaway preset trigger data. The early warning module is electrically connected to the evaluation module, and the early warning module is used to obtain the thermal runaway evaluation score, and determine the early warning level of the energy storage unit to be detected according to the relationship between the thermal runaway evaluation score and the first preset score and the second preset score, wherein: when the early warning level of the energy storage unit to be detected is a medium risk level or a high risk level, it is determined to send the early warning information.

[0094] It can be understood that the thermal runaway early warning detection system and method of a power-side energy storage unit in the above-mentioned embodiments of the present invention have the same beneficial effects and will not be described in detail.

[0095] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0096] The present application is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0097] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0098] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0099] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A thermal runaway early warning detection method for a power supply side energy storage unit, characterized in that: include: Acquire thermal runaway information of various energy storage units, and establish an energy storage unit model according to the thermal runaway information of various types of energy storage units; Acquire configuration information of the energy storage unit to be detected, substitute the configuration information into the energy storage unit model, and acquire thermal runaway preset trigger data of the energy storage unit to be detected; Acquiring operation information and environmental information of the energy storage unit to be detected, and performing thermal runaway assessment on the operation information and environmental information according to the preset thermal runaway trigger data; Acquire the thermal runaway assessment score, and determine the warning level of the energy storage unit to be detected according to the relationship between the thermal runaway assessment score and the first preset score and the second preset score; When the thermal runaway assessment score is lower than the first preset score, determining that the warning level of the energy storage unit to be detected is a low risk level; When the thermal runaway assessment score is higher than or equal to the first preset score, and the thermal runaway assessment score is lower than the second preset score, it is determined that the warning level of the energy storage unit to be detected is a medium risk level; When the thermal runaway assessment score is higher than or equal to the second preset score, it is determined that the warning level of the energy storage unit to be detected is a high risk level; Wherein, the first preset score is lower than the second preset score, and when the warning level of the energy storage unit to be detected is a medium risk level or a high risk level, it is determined to send the warning information.

2. The thermal runaway early warning detection method for the power supply side energy storage unit according to claim 1, characterized in that: Acquiring thermal runaway information of various energy storage units and establishing an energy storage unit model according to the thermal runaway information of various energy storage units includes: Acquire material information of various types of energy storage units, cluster thermal runaway information of various types of energy storage units according to the material information, and acquire thermal runaway trigger data of each material after clustering, wherein the thermal runaway trigger data includes: the number of overcharge energy storage times, internal structural resistances, and ambient temperature of the energy charging unit; The energy storage unit model is established according to the thermal runaway trigger data of each of the materials.

3. The thermal runaway early warning detection method for the power supply side energy storage unit according to claim 2, characterized in that: When establishing the energy storage unit model according to the thermal runaway trigger data of each material, it includes: Establishing each thermal runaway trigger relational expression of the material according to each thermal runaway trigger data corresponding to the material; Obtaining a distance metric between the thermal runaway triggering relational expressions to be clustered; constructing a distance matrix according to the distance metric, and recursively merging the thermal runaway trigger relational expressions according to the distance matrix; The preset trigger relationship formulas for thermal runaway of the materials after recursive merging are obtained, and the energy storage unit model is established according to the preset trigger relationship formulas for thermal runaway of each material.

4. The thermal runaway early warning detection method for the power supply side energy storage unit according to claim 3, characterized in that: Acquiring the operation information and environmental information of the energy storage unit to be detected, and performing thermal runaway assessment on the operation information and environmental information according to the preset thermal runaway trigger data, including: Obtaining the number of overcharge energy storage times of the energy storage unit to be detected in the operation information, as well as the overcharge voltage and excess capacity during each overcharge energy storage; Obtaining the preset overcharge voltage limit and the preset excess capacity limit during overcharge energy storage in the thermal runaway preset trigger data; According to the relationship between the overcharge voltage and the excess capacity during each overcharge energy storage and the preset overcharge voltage limit and the preset excess capacity limit, the effective overcharge energy storage times during each overcharge energy storage are determined, wherein: If the overcharge voltage during the overcharge energy storage is equal to or higher than the preset overcharge voltage limit, and / or the excess capacity during the overcharge energy storage is equal to or higher than the preset excess capacity limit, then determining that the overcharge energy storage is the effective overcharge energy storage number; The thermal runaway assessment score is evaluated based on the effective overcharge energy storage times.

5. The thermal runaway early warning detection method for the power supply side energy storage unit according to claim 4, characterized in that: When evaluating the thermal runaway assessment score based on the effective overcharge energy storage times, the following are included: Pre-configure a preset effective overcharge energy storage number, and obtain the difference between the effective overcharge energy storage number and the preset effective overcharge energy storage number; Determining the thermal runaway assessment score according to a relationship between the number difference and a configured first preset number difference and a second preset number difference; When the number difference is lower than the first preset number difference, the thermal runaway assessment score is determined to be L1; When the number difference is higher than or equal to the first preset number difference, and the number difference is lower than the second preset number difference, the thermal runaway score is determined to be L2; When the number difference is greater than or equal to the second preset number difference, the thermal runaway score is determined to be L3; The first preset number difference is smaller than the second preset number difference, and L1<L2<L3.

6. The thermal runaway early warning detection method for the power supply side energy storage unit according to claim 5, characterized in that: When the thermal runaway score is determined to be Li, i=1, 2, 3, including: Obtaining the real-time operating voltage and real-time internal resistance value inside the energy storage unit in the operating information; Obtaining a preset operating voltage and a preset internal resistance value in the preset thermal runaway trigger data, and performing a comparison between the real-time operating voltage and the preset operating voltage, wherein: If the real-time operating voltage is lower than the preset operating voltage, a trend curve of the operating voltage within a preset time period in the operating information is obtained; Determining a drop amplitude of the operating voltage within the preset period according to the trend curve, and determining whether to adjust the thermal runaway score Li according to a relationship between the drop amplitude and a preset drop amplitude; When the decrease range is higher than the preset decrease range, it is determined that the thermal runaway score Li is not adjusted; When the decrease is lower than or equal to a preset decrease, it is determined that the thermal runaway score Li is adjusted, and an adjustment coefficient for adjusting the thermal runaway score Li is determined according to a relationship between the real-time internal resistance value and the preset internal resistance value.

7. The thermal runaway early warning detection method for the power supply side energy storage unit according to claim 6, characterized in that: When determining the adjustment coefficient for adjusting the thermal runaway score Li according to the relationship between the real-time internal resistance value and the preset internal resistance value, it includes: The internal resistance difference between the real-time internal resistance value and the preset internal resistance value is obtained, and the adjustment coefficient is determined according to the relationship between the internal resistance difference and the configured first preset internal resistance difference and the second preset internal resistance difference: When the internal resistance difference is less than or equal to the first preset internal resistance difference, the adjustment coefficient is determined to be M1; When the internal resistance difference is greater than the first preset internal resistance difference, and the internal resistance difference is less than or equal to the second preset internal resistance difference, the adjustment coefficient is determined to be M2; When the internal resistance difference is greater than the second preset internal resistance difference, the adjustment coefficient is determined to be M3; Wherein, the first preset internal resistance difference is smaller than the second preset internal resistance difference, and M1<M2<M3<1.

8. The thermal runaway early warning detection method for the power supply side energy storage unit according to claim 7, characterized in that: When the adjustment coefficient is determined to be Mi, i=1, 2, 3, including: Acquire the real-time ambient temperature in the environmental information and the preset ambient temperature in the thermal runaway preset trigger data; According to the relationship between the real-time ambient temperature and the preset ambient temperature, determine whether to modify the adjustment coefficient Mi: When the real-time ambient temperature is lower than the preset ambient temperature, it is determined that the adjustment coefficient Mi is not to be corrected; When the real-time ambient temperature is higher than or equal to the preset ambient temperature, a correction coefficient is determined according to the temperature difference between the real-time ambient temperature and the preset ambient temperature, and the adjustment coefficient Mi is corrected according to the correction coefficient.

9. The thermal runaway early warning detection method for the power supply side energy storage unit according to claim 8, characterized in that: When determining the correction coefficient according to the temperature difference between the real-time ambient temperature and the preset ambient temperature, it includes: Determining the correction coefficient according to a relationship between the temperature difference and a configured first preset temperature difference and a second preset temperature difference; When the temperature difference is lower than or equal to the first preset temperature difference, the correction coefficient is determined to be N1; When the temperature difference is higher than the first preset temperature difference and the temperature difference is lower than or equal to the second preset temperature difference, the correction coefficient is determined to be N2; When the temperature difference is higher than the second preset temperature difference, the correction coefficient is determined to be N3; The first preset temperature difference is lower than the second preset temperature difference, and N1<N2<N3<1.

10. A thermal runaway early warning detection system for a power supply side energy storage unit, applicable to a thermal runaway early warning detection method for a power supply side energy storage unit as claimed in any one of claims 1 to 9, characterized in that: include: A model generation module, used to obtain thermal runaway information of various energy storage units, and establish an energy storage unit model according to the thermal runaway information of various types of energy storage units; A data acquisition module, used to acquire configuration information of the energy storage unit to be detected, as well as operation information and environmental information of the energy storage unit to be detected; An evaluation module, respectively connected to the model generation module and the data acquisition module, the evaluation module is used to substitute the configuration information into the energy storage unit model, and obtain the thermal runaway preset trigger data of the energy storage unit to be detected; the evaluation module is also used to perform thermal runaway evaluation on the operation information and environmental information according to the thermal runaway preset trigger data; an early warning module, electrically connected to the evaluation module, and configured to obtain the thermal runaway evaluation score, and determine the early warning level of the energy storage unit to be detected according to the relationship between the thermal runaway evaluation score and the first preset score and the second preset score, wherein: When the warning level of the energy storage unit to be detected is a medium risk level or a high risk level, it is determined to send a warning message.

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