Abnormal State Detection Method for Liquid-Cooled Energy Storage System

Abstract

The present invention relates to the technical field of abnormal detection of energy storage systems, and specifically discloses an abnormal state detection method for a liquid-cooled energy storage system. The method includes: analyzing the environment where the liquid-cooled energy storage system is located to obtain the environmental characteristic values; analyzing the usage status of the cooling system of the liquid-cooled energy storage system to determine whether there is an abnormality in the cooling system and determine the cooling threshold of the liquid-cooled energy storage system; analyzing the actual operating status of the liquid-cooled energy storage system to determine whether there is an operating abnormality in the liquid-cooled energy storage system and performing abnormal detection on the battery unit of the liquid-cooled energy storage system to determine the abnormal detection level of overheating of the battery unit. The present invention solves the problem that the abnormal detection of traditional liquid-cooled systems relies on fixed rules or preset thresholds and lacks intelligent data processing and adaptive adjustment capabilities, improves the intelligent level of system operation, and further enhances the stability and safety of the system.

Description

Technical Field

[0001] The present invention relates to the technical field of abnormality detection of energy storage systems, and in particular to an abnormal state detection method for a liquid-cooled energy storage system. Background Art

[0002] Modern society is increasingly dependent on renewable energy sources, such as solar and wind energy. However, due to the intermittent nature of these energy sources, it is difficult to achieve stable power supply. In this context, energy storage systems play a role in balancing loads, storing excess energy, and releasing energy during peak demand periods, becoming an important part of the renewable energy industry. Large-scale battery energy storage systems generate a lot of heat during the charging and discharging process. If the heat is not dissipated in time, the battery performance will decline, and may even lead to dangers such as thermal runaway. Liquid cooling technology has become one of the mainstream technologies for thermal management of energy storage systems due to its efficient heat dissipation capacity and uniform cooling effect, especially for high-power and high-density battery packs. Compared with traditional air cooling, liquid cooling technology can conduct heat more effectively. The coolant directly contacts the cooling components and can quickly take away the heat from the battery module or other heat-generating components. Especially in high-power intensive energy storage systems, liquid cooling technology can provide more accurate and efficient temperature control. The operation of the liquid cooling system involves multiple complex factors, such as the flow rate, pressure, and temperature control of the coolant. If the liquid cooling system fails and cannot effectively control the heat, it may cause overheating of the battery pack and even cause safety problems. Therefore, abnormal state detection of the liquid cooling system is crucial.

[0003] Nowadays, there are still some deficiencies in the research on abnormal state detection of liquid-cooled energy storage systems. Specifically, traditional liquid cooling system abnormality detection relies on fixed rules or preset thresholds, lacks intelligent data processing and adaptive adjustment capabilities, and cooling system performance degradation, battery aging and other problems have an impact on system operation. Fixed detection methods cannot adapt to these changes. Traditional detection systems cannot automatically adjust parameters according to real-time working conditions or environmental conditions, resulting in the inability to respond effectively in time. Most of the detection methods for liquid cooling systems do not fully consider the impact of changes in external environmental conditions on the system, lack dynamic adjustment capabilities, and cannot detect and handle system abnormalities in a timely manner. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a method for detecting an abnormal state of a liquid-cooled energy storage system, which can effectively solve the problems involved in the above-mentioned background technology.

[0005] To achieve the above object, the present invention is realized through the following technical solutions: An abnormal state detection method for a liquid-cooled energy storage system, comprising the following steps: analyzing the environment where the liquid-cooled energy storage system is located to obtain the environmental characteristic values; analyzing the usage status of the cooling system of the liquid-cooled energy storage system to determine whether there is an abnormality in the cooling system: if there is an abnormality in the cooling system, an alarm for the abnormality of the cooling system is issued; if there is no abnormality in the cooling system, combining the environmental characteristic values to determine the cooling threshold of the liquid-cooled energy storage system; analyzing the actual operating status of the liquid-cooled energy storage system to determine whether there is an operating abnormality in the liquid-cooled energy storage system and obtaining the detection data sets of each battery unit, and combining the cooling threshold of the liquid-cooled energy storage system to determine the abnormal level of overheating detection of the battery unit.

[0006] As a further method, analyzing the environment where the liquid-cooled energy storage system is located to obtain the environmental characteristic values, the specific analysis process is: obtaining the environmental data set where the liquid-cooled energy storage system is located, and the environmental data set where the liquid-cooled energy storage system is located specifically includes the ambient temperature, the ambient wind speed, and the outlet temperature of the cooling system; based on the obtained environmental data set where the liquid-cooled energy storage system is located, comprehensively analyzing to obtain the environmental characteristic values, and the environmental characteristic values are used as the analysis basis for determining the cooling threshold of the liquid-cooled energy storage system.

[0007] As a further method, determining whether there is an abnormality in the cooling system, the specific analysis process is: obtaining the usage status data set of the cooling system, and based on the obtained usage status data set of the cooling system, comprehensively analyzing to obtain the usage status evaluation value of the cooling system, and the usage status evaluation value of the cooling system is used as the analysis basis for determining whether there is an abnormality in the cooling system; comparing the usage status evaluation value of the cooling system with the usage status threshold of the cooling system stored in the database; if the usage status evaluation value of the cooling system is lower than the usage status threshold of the cooling system, the cooling system corresponding to the usage status evaluation value has an abnormality, and an alarm for the abnormality of the cooling system is issued; if the usage status evaluation value of the cooling system is not lower than the usage status threshold of the cooling system, the cooling system corresponding to the usage status evaluation value has no abnormality.

[0008] As a further method, the usage status data set of the cooling system specifically includes the absolute value of the difference between the coolant flow rate and the reference coolant flow rate, the absolute value of the difference between the coolant pressure and the reference coolant pressure, and the absolute value of the difference between the coolant liquid level and the reference coolant liquid level.

[0009] As a further method, the specific analysis process of the usage status evaluation value of the cooling system is:

[0010]

[0011] Wherein, β is the evaluation value of the cooling system usage status, ls is the absolute value of the difference between the coolant flow rate and the reference coolant flow rate, yl is the absolute value of the difference between the coolant pressure and the reference coolant pressure, yw is the absolute value of the difference between the coolant level and the reference coolant level, τ1 is the compensation factor of the set ls, τ2 is the compensation factor of the set yl, τ3 is the compensation factor of the set yw, and e is the natural constant.

[0012] As a further method, determine the cooling threshold of the liquid-cooled energy storage system. The specific analysis process is as follows: Obtain the evaluation value of the cooling system usage status and the characteristic value of the environment where it is located, store the evaluation value of the cooling system usage status and the characteristic value of the environment where it is located as a specified tag, and compare the specified tag with the cooling thresholds of the liquid-cooled energy storage systems corresponding to each specified tag stored in the database to obtain the cooling threshold of the liquid-cooled energy storage system corresponding to the specified tag.

[0013] As a further method, determine whether there is an abnormal operation in the liquid-cooled energy storage system. The specific analysis process is as follows: Obtain the actual operation status data set of the liquid-cooled energy storage system, and based on the obtained actual operation status data set of the liquid-cooled energy storage system, comprehensively analyze to obtain the actual operation status evaluation value. The actual operation status evaluation value is used as the analysis basis for determining whether there is an abnormal operation in the liquid-cooled energy storage system; compare the actual operation status evaluation value with the actual operation status threshold stored in the database; if the actual operation status evaluation value is lower than the actual operation status threshold, there is an abnormal operation in the liquid-cooled energy storage system corresponding to the actual operation status evaluation value, and an alarm for abnormal operation of the liquid-cooled energy storage system is issued; if the actual operation status evaluation value is not lower than the actual operation status threshold, there is no abnormal operation in the liquid-cooled energy storage system corresponding to the actual operation status evaluation value.

[0014] As a further method, the actual operation status data set of the liquid-cooled energy storage system specifically includes the absolute value of the difference between the system power output and the reference power output, the absolute value of the difference between the system load rate and the reference load rate, and the absolute value of the difference between the system voltage and the reference voltage.

[0015] As a further method, the detection data set of each battery unit specifically includes the average temperature of the battery unit, the maximum internal temperature difference of the battery unit, and the difference between the coolant outlet temperature and the inlet temperature of the battery unit.

[0016] As a further method, in combination with the cooling threshold of the liquid-cooled energy storage system, the overheat detection abnormal level of the battery unit is determined. The specific analysis process is as follows: Based on the obtained detection data sets of each battery unit, the detection evaluation values of each battery unit are comprehensively analyzed. The detection evaluation values of each battery unit serve as the analysis basis for determining the overheat detection abnormal level of the battery unit; the detection evaluation values of each battery unit are compared with the cooling threshold of the liquid-cooled energy storage system stored in the database; the difference between the detection evaluation value of each battery unit and the cooling threshold of the liquid-cooled energy storage system is recorded as the detection deviation value of each battery unit; the detection deviation value of each battery unit is compared with the first threshold of the battery unit detection deviation stored in the database; if the number of battery unit detection deviation values higher than the first threshold of the battery unit detection deviation is greater than the amount of the first threshold of the battery unit detection deviation, the overheat detection abnormal level of the battery unit is marked as the fourth level; if the number of battery unit detection deviation values higher than the first threshold of the battery unit detection deviation is not greater than the amount of the first threshold of the battery unit detection deviation but greater than the amount of the second threshold of the battery unit detection deviation, the overheat detection abnormal level of the battery unit is marked as the third level; if the number of battery unit detection deviation values higher than the first threshold of the battery unit detection deviation is not greater than the amount of the second threshold of the battery unit detection deviation but is not zero, the overheat detection abnormal level of the battery unit is marked as the second level; if the number of battery unit detection deviation values higher than the first threshold of the battery unit detection deviation is zero, the overheat detection abnormal level of the battery unit is marked as the first level.

[0017] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0018] (1) By providing an abnormal state detection method for the liquid-cooled energy storage system, analyzing the environmental characteristic values and monitoring the state of the cooling system, the stable operation of the energy storage system is maintained. The early warning of the cooling system abnormality helps to prevent overheating and potential thermal runaway of the battery pack, thereby reducing the downtime and damage risk. Through a multi-level abnormal detection mechanism, it is timely to judge whether the system operation and cooling state are abnormal, which helps to detect potential faults as early as possible. In particular, the abnormal detection and overheat detection of the battery unit can effectively prevent the occurrence of battery thermal runaway events. Through environmental analysis and real-time data monitoring, the system can automatically adjust the cooling threshold, improving the intelligent level of the system operation. It can also reduce false alarms or missed alarms through a precise monitoring method, further improving the stability and safety of the system.

[0019] (2) When the cooling system is normal, the present invention determines the cooling threshold of the liquid-cooled energy storage system by combining the environmental characteristic values. The environmental characteristic values directly affect the heat dissipation effect of the cooling system, and the cooling threshold can be dynamically adjusted. By dynamically adjusting the cooling threshold in combination with the environmental characteristic values, the energy storage system can achieve better stability in complex environments. Static cooling threshold settings often cannot adapt to changes in environmental conditions, easily causing false alarms or misjudgments. In the case of high environmental temperatures, the static threshold of the cooling system may lead to frequent temperature over-limit alarms, even though the system is actually still within the safe operating range. By dynamically setting the cooling threshold in combination with the environmental characteristic values, false alarms or misjudgments can be effectively reduced, and the detection accuracy of the system can be improved. Incorporating the environmental characteristic values into the dynamic adjustment process of the cooling threshold enables the system to have intelligent and adaptive capabilities.

[0020] (3) The present invention determines the overheat detection abnormal level of the battery unit by obtaining the detection data sets of each battery unit and combining the cooling threshold of the liquid-cooled energy storage system. By combining the detection data of the battery unit and the threshold of the cooling system, it is possible to accurately detect whether the battery is in an overheated state. The overheating of the battery is one of the main risk factors of thermal runaway in the energy storage system. By carefully detecting and classifying the temperature of each battery unit in combination with the cooling threshold, it is possible to identify early overheating trends and prevent the battery temperature from continuously rising to an out-of-control state. The hierarchical management method enables the system to react in a timely manner and avoid serious safety accidents such as battery explosion or fire. Combining the environmental characteristics and the threshold of the cooling system helps to reduce false alarms or misjudgments, and the system can dynamically adjust the overheat detection threshold to reduce false alarms caused by changes in the external environmental temperature. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The present invention will be further described with reference to the accompanying drawings. However, the embodiments in the drawings do not constitute any limitation to the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to the following drawings.

[0022] Figure 1 It is a schematic flowchart of the method of the present invention.

[0023] Figure 2 It is a flowchart of the steps for judging whether there is an abnormal operation in the liquid-cooled energy storage system. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0024] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0025] Reference Figure 1 As shown, the present invention provides a method for detecting abnormal states of a liquid-cooled energy storage system, including: analyzing the environment where the liquid-cooled energy storage system is located to obtain environmental characteristic values.

[0026] The specific analysis process is as follows: Obtain the environmental data set where the liquid-cooled energy storage system is located. The environmental data set where the liquid-cooled energy storage system is located specifically includes the ambient temperature, the ambient wind speed, and the outlet temperature of the cooling system. Based on the obtained environmental data set where the liquid-cooled energy storage system is located, comprehensively analyze to obtain environmental characteristic values, and the environmental characteristic values are used as the analysis basis for determining the cooling threshold of the liquid-cooled energy storage system.

[0027] In a specific embodiment, the ambient temperature refers to the air temperature of the external environment or the indoor environment where the energy storage system is located. Temperature sensors (such as thermistors, thermocouples, RTDs, etc.) are used to measure the ambient temperature. The ambient wind speed refers to the speed of air flow around the energy storage system. The wind speed has a direct impact on the heat dissipation performance of the cooling system. Wind speed sensors (such as ultrasonic anemometers, thermal anemometers, mechanical anemometers, etc.) are used to measure the wind speed in the environment. The outlet temperature of the cooling system refers to the temperature when the coolant discharges from the system after absorbing heat inside the energy storage system. Temperature sensors (such as thermocouples, PT100, NTC thermistors) are used to monitor the outlet temperature of the coolant.

[0028] It should be explained that the above ambient temperature directly affects the heat dissipation efficiency of the cooling system. The higher the ambient temperature, the weaker the heat dissipation ability of the coolant in the radiator because it is more difficult for heat to transfer from the coolant to the external environment. The lower the ambient temperature, the better the heat dissipation effect, and the coolant can dissipate heat faster. The wind speed directly affects the heat dissipation ability of the cooling system (such as the radiator). The higher the ambient wind speed, the faster the heat exchange between the coolant and the air when the coolant passes through the radiator, and the heat can be quickly carried away by the wind, resulting in a decrease in the outlet temperature of the cooling system and an improvement in the heat dissipation effect. The ambient temperature and the wind speed jointly affect the cooling effect. In the case of high ambient temperature and low wind speed, the heat dissipation effect is the worst, the outlet temperature of the cooling system is the highest, the cooling load increases, and there may be a risk of overheating of the battery. In the case of low ambient temperature and high wind speed, the heat dissipation effect is the best, the outlet temperature of the cooling system is the lowest, and the coolant can efficiently carry away the heat generated by the battery.

[0029] It should be noted that external factors such as the above-mentioned ambient temperature and wind speed directly affect the working effect of the cooling system. The ambient characteristic values obtained by comprehensively analyzing the ambient data can reflect the heat dissipation conditions of the current system, which helps to reasonably adjust the cooling threshold. When the threshold of the cooling system can dynamically adapt to the environment, unnecessary cooling operations can be avoided, thus saving energy. When the ambient temperature is low, the cooling system does not need to work intensively. A reasonable cooling threshold can reduce the flow rate of the coolant or the working frequency of the cooling equipment, thereby reducing energy consumption. A higher ambient wind speed also helps with natural heat dissipation and reduces the dependence on the liquid cooling system, which further reduces the energy consumption of the system. Setting the cooling threshold based on the ambient characteristic values can ensure that the system is always in a stable operating environment. Different environmental conditions have different requirements for battery thermal management. By dynamically adjusting the cooling threshold, the cooling system can better adapt to complex environmental changes. Analyzing the ambient data and flexibly adjusting the cooling threshold can effectively avoid this situation and ensure that the cooling intensity always meets the actual requirements.

[0030] It should be noted that the above-mentioned ambient characteristic values, the specific analysis process is as follows:

[0031]

[0032] In the formula, α is the ambient characteristic value, hw is the ambient temperature, hf is the ambient wind speed, ck is the outlet temperature of the cooling system, σ1 is the compensation factor for the set hw, σ2 is the compensation factor for the set hf, and σ3 is the compensation factor for the set ck.

[0033] It should be noted that the above-mentioned ambient characteristic values are calculated from the ambient temperature, ambient wind speed, and outlet temperature of the cooling system. After normalizing hw, hf, and ck, the ambient characteristic value combines external factors such as ambient temperature and wind speed with the outlet temperature of the cooling system, which can more accurately reflect the impact of the external environment on the performance of the cooling system. The higher the ambient temperature, the greater the cooling difficulty. When the wind speed is relatively high, it helps to improve the heat dissipation effect. The system can better understand the impact of external conditions on the cooling effect and make adjustments in a timely manner. The ambient characteristic value provides real-time feedback on the current environment for the system, enabling the abnormal judgment of the cooling system to be dynamically adjusted according to different environmental conditions. The ambient characteristic value can dynamically reflect the pressure brought by the environment to the cooling system. If the ambient temperature is too high and the wind speed is low, the cooling effect may weaken. The system can predict the overheating risk in advance based on the ambient characteristic value and take measures to prevent the battery unit from overheating. This prevention mechanism helps to prevent safety hazards such as thermal runaway caused by insufficient heat dissipation and ensures the safe operation of the system.

[0034] It should be explained that the compensation factors of hw, hf, and ck set above are obtained from the database. A mapping set of the ambient temperature, ambient wind speed, outlet temperature of the cooling system, and the compensation factors of hw, hf, and ck for historical measurements is established based on historical data, and the compensation factors of hw, hf, and ck corresponding to the current hw, hf, and ck are obtained.

[0035] It should be noted that τ1, τ2, τ3, ε1, ε2, ε3, μ1, μ2, and μ3 in the following text are also obtained through the mapping set of historical data and compensation factors established in the database, that is, the corresponding compensation factors are obtained according to the current data.

[0036] In a specific embodiment, the ambient temperature at this time is 35 °C, the ambient wind speed is 2 m / s, the outlet temperature of the cooling system is 50 °C, the compensation factor of hw is 1.2, the compensation factor of hf is 0.8, and the compensation factor of ck is 1.1. The ambient characteristic value α is calculated to be 19.82, indicating that the current ambient temperature is relatively high and the wind speed is relatively low, and the cooling effect is relatively poor.

[0037] Analyze the usage status of the cooling system of the liquid-cooled energy storage system to determine whether there is an abnormality in the cooling system: If there is an abnormality in the cooling system, an alarm for the abnormality of the cooling system is issued; if there is no abnormality in the cooling system, the cooling threshold of the liquid-cooled energy storage system is determined in combination with the ambient characteristic value.

[0038] The specific analysis process is as follows: Obtain the dataset of the usage status of the cooling system. Based on the obtained dataset of the usage status of the cooling system, comprehensively analyze to obtain the evaluation value of the usage status of the cooling system. The evaluation value of the usage status of the cooling system is used as the analysis basis for determining whether there is an abnormality in the cooling system; compare the evaluation value of the usage status of the cooling system with the threshold of the usage status of the cooling system stored in the database; if the evaluation value of the usage status of the cooling system is lower than the threshold of the usage status of the cooling system, there is an abnormality in the cooling system corresponding to the evaluation value of the usage status of the cooling system, and an alarm for the abnormality of the cooling system is issued; if the evaluation value of the usage status of the cooling system is not lower than the threshold of the usage status of the cooling system, there is no abnormality in the cooling system corresponding to the evaluation value of the usage status of the cooling system.

[0039] It should be noted that by obtaining the actual usage status data of the cooling system and conducting comprehensive analysis, the obtained evaluation value of the cooling system usage status can accurately reflect the operating status of the system. Comparing it with the threshold stored in the database can effectively determine whether there is an abnormality in the system. If the usage status evaluation value is lower than the threshold, the system can immediately identify the abnormality and issue an alarm to help take measures quickly. This accurate abnormality identification reduces the possibility of misjudgment, timely discovers and alarms the abnormal conditions in the cooling system, and can avoid potential risks brought by the failure or overwork of the cooling system. For example, the failure of the cooling system may cause the battery pack of the energy storage system to overheat, and ultimately may trigger safety accidents such as battery thermal runaway and fire. Through the automatic detection and alarm mechanism, the system can issue a warning when the problem first appears, prevent the occurrence of serious accidents, and ensure the safety of the energy storage system. Through the dynamic analysis and evaluation of the usage status data, the system can identify abnormal operating states of the cooling system, such as problems like insufficient coolant flow rate, too high coolant pressure, or too low liquid level, and can achieve intelligent adjustment, enabling the cooling system to have higher adaptability.

[0040] Furthermore, the cooling system usage status data set specifically includes the absolute value of the difference between the coolant flow rate and the reference coolant flow rate, the absolute value of the difference between the coolant pressure and the reference coolant pressure, and the absolute value of the difference between the coolant liquid level and the reference coolant liquid level.

[0041] In a specific embodiment, the absolute value of the difference between the coolant flow rate and the reference coolant flow rate is the absolute value of the difference between the actual coolant flow rate and the reference flow rate, which reflects the degree of deviation of the actual flow rate from the ideal flow rate. The larger the difference, the greater the degree of deviation of the coolant flow rate from the design value, which may mean a decrease in pump efficiency, pipeline blockage, or a malfunction in the cooling system. Flow meters (such as electromagnetic flow meters, ultrasonic flow meters, turbine flow meters) are used to measure the actual coolant flow rate. The absolute value of the difference between the coolant pressure and the reference coolant pressure reflects the pressure deviation of the cooling system. When the difference is large, it may indicate problems such as a decrease in pump performance, pipeline blockage, or leakage. Pressure sensors or pressure transmitters are installed in the coolant pipeline to measure the actual coolant pressure. The absolute value of the difference between the coolant liquid level and the reference coolant liquid level is the absolute value of the difference between the actual coolant liquid level and the reference liquid level. The larger the difference, it may indicate that the coolant has leaked, evaporated, or is insufficiently replenished. A low liquid level may cause the cooling system to malfunction, while an excessively high liquid level may indicate overfilling or overflow in the system. Level sensors (such as float level gauges, ultrasonic level gauges, capacitive level gauges) are installed in the coolant storage tank to monitor the liquid level height in real time.

[0042] It should be noted that the abnormal coolant flow rate (such as too low) may cause changes in the coolant pressure because the resistance of liquid flow affects the pressure. When the flow rate is too low, the coolant may stagnate in the pipeline, resulting in a local pressure drop or increase. When the flow rate is too high, it may cause an increase in the coolant pressure. The change in the flow rate may also be related to the change in the liquid level. If the liquid level is low, the flow rate may also be low. There is a direct relationship between pressure and flow rate. Based on Bernoulli's principle, flow rate and pressure are often inversely proportional. If the pressure is too low, the flow rate may decrease because the pump cannot generate enough driving force. If the pressure is too high, the flow rate may increase. Pressure abnormality may also be related to the liquid level. When the coolant liquid level is too low, the pump may not be able to generate enough pressure, resulting in a decrease in the pressure and flow rate of the entire system. When the liquid level is too low, the coolant circulation will be restricted, resulting in a decrease in the flow rate and possibly a decrease in the pressure. When the liquid level is too high, it may increase the circulation resistance of the liquid, resulting in an increase in the working load of the pump, an increase in the pressure, and even possibly affecting the flow rate.

[0043] Specifically, for the evaluation value of the cooling system usage status, the specific analysis process is as follows:

[0044]

[0045] In the formula, β is the evaluation value of the cooling system usage status, ls is the absolute value of the difference between the coolant flow rate and the reference coolant flow rate, yl is the absolute value of the difference between the coolant pressure and the reference coolant pressure, yw is the absolute value of the difference between the coolant liquid level and the reference coolant liquid level, τ1 is the compensation factor set for ls, τ2 is the compensation factor set for yl, τ3 is the compensation factor set for yw, and e is the natural constant.

[0046] It should be noted that the above evaluation value of the cooling system usage state is calculated through the absolute value of the difference between the coolant flow rate and the reference coolant flow rate, the absolute value of the difference between the coolant pressure and the reference coolant pressure, and the absolute value of the difference between the coolant level and the reference coolant level. After normalizing ls, yl, and yw, and comprehensively analyzing the deviations of the coolant flow rate, pressure, and level, the system can comprehensively evaluate the overall operating state of the cooling system, which can help the system more accurately determine whether the cooling system is in a normal working state, whether there are problems such as insufficient cooling, overcooling, or equipment failures. A single flow rate, pressure, or level parameter may not be able to accurately judge the operating state of the cooling system. However, by combining the differences of these parameters, the evaluation value of the cooling system usage state can detect abnormalities in the cooling system more comprehensively and accurately, reduce false alarms and missed alarms, and ensure that the alarm is triggered only when there is a real problem in the system. The balance of the coolant flow rate, pressure, and level is crucial for maintaining the normal operation of the cooling system. Any abnormality in a parameter will affect the cooling efficiency. By monitoring these parameters in multiple dimensions and calculating the differences, the system can quickly identify and solve potential problems, ensure that the cooling system is always in the best operating state, and thus maintain the overall operating stability of the energy storage system.

[0047] In a specific embodiment, at this time, the absolute value of the difference between the coolant flow rate and the reference coolant flow rate is 0.5 m / s, the absolute value of the difference between the coolant pressure and the reference coolant pressure is 0.2 bar, the absolute value of the difference between the coolant level and the reference coolant level is 0.1 m, the compensation factor of ls is 0.5, the compensation factor of yl is 0.3, and the compensation factor of yw is 1.1. The calculated evaluation value of the cooling system usage state is 1.7009, and the threshold value of the cooling system usage state is 1.5. Since 1.7009 is less than 1.5, it indicates that the overall state of the cooling system is good and there are no abnormalities.

[0048] Furthermore, to determine the cooling threshold of the liquid-cooled energy storage system, the specific analysis process is as follows: Obtain the evaluation value of the cooling system usage state and the characteristic value of the environment where it is located, store the evaluation value of the cooling system usage state and the characteristic value of the environment where it is located as a specified label, and compare this specified label with the cooling thresholds of the liquid-cooled energy storage systems corresponding to each specified label stored in the database to obtain the cooling threshold of the liquid-cooled energy storage system corresponding to this specified label.

[0049] In a specific embodiment, when the usage status evaluation value of the cooling system is 1.7009 and the environmental characteristic value is 19.82, the specified label is recorded as (1.7009, 19.82). The cooling threshold of the liquid-cooled energy storage system is matched to be 6, and the matching rule is as follows: the usage status evaluation value of the cooling system is 1.7009, which is rounded to 2 after rounding; the environmental characteristic value is 19.82, which is rounded to 20 after rounding. The updated specified label is recorded as (2, 20). 2 is recorded as value 1, and 20 is recorded as value 2. The value 1 and value 2 in the specified label are imported into the matching model, and the matching model is: the cooling threshold of the liquid-cooled energy storage system = {[(value 1 + value 2) / 2] + 1} / 2. The cooling threshold of the liquid-cooled energy storage system is matched to be 6.

[0050] In a specific embodiment, different environmental characteristic values and usage status evaluation values of the cooling system reflect the requirements of the system under different operating conditions. By storing these data as specified labels, the system can select the most suitable cooling threshold from historical data according to the actual situation, realizing dynamic adjustment, which helps to judge whether the cooling of the battery unit meets the standard. This dynamic adjustment mechanism enables the system to maintain the best cooling effect and operating efficiency under complex and changing working conditions. By comparing the specified labels of the cooling system usage status and environmental characteristic values with the corresponding labels in the database, the most suitable cooling threshold for the current state can be found, realizing the intelligent management of the cooling system. The system can autonomously select the appropriate cooling threshold, reducing manual intervention, improving the intelligent level of the system, enabling it to automatically adapt to changes in the environment and usage status according to real-time data, enhancing the adaptive ability of the system. Based on the threshold setting of historical data and environmental characteristic value labels, false alarms caused by fluctuations in a single parameter can be reduced. When the environmental temperature suddenly rises, the system can automatically select the appropriate cooling threshold by comparing historical labels, avoiding overly frequent false alarms.

[0051] Analyze the actual operating status of the liquid-cooled energy storage system to determine whether there is an operating abnormality in the liquid-cooled energy storage system: If there is no operating abnormality in the liquid-cooled energy storage system, perform abnormality detection on the battery unit of the liquid-cooled energy storage system; If there is an operating abnormality in the liquid-cooled energy storage system, issue an alarm for the operating abnormality of the liquid-cooled energy storage system and perform abnormality detection on the battery unit of the liquid-cooled energy storage system.

[0052] The specific analysis process is as follows: Obtain the actual operation status data set of the liquid-cooled energy storage system. Based on the obtained actual operation status data set of the liquid-cooled energy storage system, comprehensively analyze to obtain the actual operation status evaluation value. The actual operation status evaluation value is used as the analysis basis for judging whether there is an abnormal operation in the liquid-cooled energy storage system; compare the actual operation status evaluation value with the actual operation status threshold stored in the database; if the actual operation status evaluation value is lower than the actual operation status threshold, the liquid-cooled energy storage system corresponding to the actual operation status evaluation value has an abnormal operation, and an alarm for the abnormal operation of the liquid-cooled energy storage system is issued; if the actual operation status evaluation value is not lower than the actual operation status threshold, the liquid-cooled energy storage system corresponding to the actual operation status evaluation value does not have an abnormal operation.

[0053] It should be explained that by continuously obtaining the actual operation status data of the liquid-cooled energy storage system, the system can achieve real-time monitoring, enabling the system to quickly detect any signs of abnormality during operation, ensuring that problems can be discovered and handled at an early stage, thus avoiding system failures or accidents. The actual operation status evaluation value is obtained based on comprehensive data analysis, reflecting the current health status of the system. By comparing it with the historical threshold stored in the database, it can accurately judge whether there is an abnormal situation, which is more comprehensive and accurate than simple single-parameter analysis, reducing the risk of misjudgment or missed reports. Once the evaluation value is lower than the actual operation status threshold, the system can promptly issue an abnormal alarm, and the instant feedback mechanism allows operators to take prompt actions to prevent small problems from evolving into serious failures, which is crucial for ensuring the stability and safety of the liquid-cooled energy storage system.

[0054] Furthermore, the actual operation status data set of the liquid-cooled energy storage system specifically includes the absolute value of the difference between the system power output and the reference power output, the absolute value of the difference between the system load rate and the reference load rate, and the absolute value of the difference between the system voltage and the reference voltage.

[0055] In a specific embodiment, the absolute value of the difference between the system power output and the reference power output is the absolute value of the difference between the actual system power output and the reference power output, which can reflect whether the system provides sufficient power as expected or operates overloaded. A larger absolute value of the difference may indicate that the system output deviates from the expectation, such as insufficient output power or overloaded operation. A power meter (such as an intelligent electricity meter) is used to monitor the actual output power of the system in real time. The absolute value of the difference between the system load rate and the reference load rate refers to the absolute value of the difference between the actual load rate and the reference load rate. The load rate difference can help determine whether the system is within a reasonable operating range. An excessive difference indicates that the system load deviates from the expected state, which may be overloaded or underloaded, affecting the system efficiency. Based on the intelligent electricity meter or load monitoring device, the absolute value of the difference between the system voltage and the reference voltage refers to the absolute value of the difference between the actual system voltage and the reference voltage. This difference can reflect whether the system voltage is stable or deviates from the normal range. An excessive difference will cause the system to operate unstably or equipment damage. A voltmeter or an intelligent electricity meter is used to monitor the actual voltage of the system in real time.

[0056] It should be noted that the above power output is the electricity provided by the system to the load or the power grid, which directly affects the load rate of the system. The load rate is the ratio of the current power output of the system to its maximum design power, usually expressed as a percentage. The higher the load rate, the closer the power output of the system is to its maximum design power. If the power output increases, the load rate will also increase accordingly. When the power output difference (the difference between the actual and reference power outputs) increases, the system may enter a high-load operation state, and at this time, the load rate will also increase, and the absolute value of the difference rises. The voltage is positively correlated with the power output. When the voltage increases, the power output increases; when the voltage decreases, the power output decreases. The larger the absolute value of the voltage difference, the greater the possibility that the power output deviates from the normal range. There is an inverse correlation between the system load rate and the voltage. An increase in the load rate may cause the voltage to drop. When the load rate decreases, the voltage may be more stable. The fluctuation of the load rate will also affect the voltage stability, thereby affecting the power output of the system operation.

[0057] It should be noted that the above actual operating state evaluation value, the specific analysis process is as follows:

[0058]

[0059] In the formula, γ is the actual operating state evaluation value, gl is the absolute value of the difference between the system power output and the reference power output, fz is the absolute value of the difference between the system load rate and the reference load rate, dy is the absolute value of the difference between the system voltage and the reference voltage, ε1 is the compensation factor set for gl, ε2 is the compensation factor set for fz, and ε3 is the compensation factor set for dy.

[0060] It should be explained that the above-mentioned actual operating status evaluation value is calculated by the absolute value of the difference between the system power output and the reference power output, the absolute value of the difference between the system load rate and the reference load rate, and the absolute value of the difference between the system voltage and the reference voltage. gl, fz, and dy are normalized. Combined with the power output difference, load rate difference, and voltage difference, the actual operating status evaluation value can comprehensively reflect the overall operating health status of the system. This multi-dimensional analysis provides a more complete perspective and can identify potential problems that cannot be revealed by a single parameter. Through the linkage analysis of power output, load rate, and voltage, the system can judge abnormalities more accurately. The multi-dimensional analysis method helps to detect potential faults earlier. Even if the power output seems normal, voltage fluctuations or abnormal load rates may be early signals of system instability. By combining these differences into an evaluation value, the system can issue an early warning before the problem worsens, thereby providing sufficient response time for timely repairs and preventive maintenance and reducing the possibility of major failures.

[0061] In a specific embodiment, at this time, the absolute value of the difference between the system power output and the reference power output is 10 kilowatts, the absolute value of the difference between the system load rate and the reference load rate is 0.15, the absolute value of the difference between the system voltage and the reference voltage is 5 volts, the compensation factor of gl is 0.8, the compensation factor of fz is 1.2, and the compensation factor of dy is 1.0. The actual operating status evaluation value is calculated to be 0.5011, which is greater than the actual operating status threshold of 0.5 stored in the database, and there is no operating abnormality in the liquid-cooled energy storage system.

[0062] Obtain the detection data set of each battery cell, and determine the abnormal level of battery cell overheat detection in combination with the cooling threshold of the liquid-cooled energy storage system.

[0063] Specifically, the battery cell detection data set includes the average temperature of the battery cell, the maximum temperature difference inside the battery cell, and the difference between the outlet temperature and the inlet temperature of the battery cell coolant.

[0064] It should be noted that the above-mentioned average temperature of the battery cell refers to the average value of the temperature sensor readings in various regions within the entire battery cell, which reflects the overall thermal state of the battery cell under the current operating conditions. Multiple temperature sensors (such as NTC thermistors, thermocouples, RTD sensors) are installed at different positions inside the battery cell to measure the temperatures of various regions. The maximum temperature difference inside the battery cell refers to the difference between the highest temperature and the lowest temperature among different regions inside the battery cell, which is used to evaluate the heat dissipation uniformity of each part inside the battery cell. If the temperature difference is too large, it indicates uneven heat dissipation inside the battery cell, which may lead to local overheating, thereby accelerating the aging of some batteries and even triggering safety issues (such as thermal runaway). Multiple temperature sensors distributed at different positions in the battery cell are used to monitor the local temperatures. The system calculates the difference between the highest temperature and the lowest temperature based on the readings of these sensors to obtain the maximum temperature difference. The difference between the coolant outlet temperature and the inlet temperature of the battery cell refers to the difference between the temperature of the coolant before entering the battery cell and the temperature after flowing out of the battery cell, which reflects the heat carried away by the coolant in the battery cell. Two temperature sensors are installed at the inlet and outlet positions of the coolant to monitor the temperatures of the coolant when it enters and flows out of the battery cell respectively. By collecting the temperature data of these two sensors, the temperature difference of the coolant can be calculated.

[0065] It should be noted that the above-mentioned average temperature of the battery cell reflects the overall thermal state of the battery cell, while the maximum temperature difference inside the battery cell reflects whether the temperature distribution in different regions inside the battery is uniform. Although the average temperature of the battery is within the safe range, if the maximum temperature difference inside is large, it indicates that there may be hot spots in local areas and the heat dissipation is uneven. The difference between the coolant outlet and inlet temperatures represents the heat carried away by the coolant in the battery cell. The difference between the coolant outlet and inlet temperatures directly affects the temperature distribution inside the battery cell. If the coolant can effectively carry away heat, the temperature distribution inside the battery cell will be more uniform and the maximum temperature difference inside will be smaller.

[0066] Further, in combination with the cooling threshold of the liquid-cooled energy storage system, determine the overheat detection abnormal level of the battery unit. The specific analysis process is as follows: Based on the obtained detection data sets of each battery unit, comprehensively analyze to obtain the detection evaluation values of each battery unit. The detection evaluation values of each battery unit are used as the analysis basis for determining the overheat detection abnormal level of the battery unit; compare the detection evaluation values of each battery unit with the cooling threshold of the liquid-cooled energy storage system stored in the database; record the difference between the detection evaluation value of each battery unit and the cooling threshold of the liquid-cooled energy storage system as the detection deviation value of each battery unit; compare the detection deviation value of each battery unit with the first threshold of the battery unit detection deviation stored in the database; if the number of battery unit detection deviation values higher than the first threshold of the battery unit detection deviation is greater than the first threshold quantity of the battery unit detection deviation, mark the overheat detection abnormal level of the battery unit as the fourth level; if the number of battery unit detection deviation values higher than the first threshold of the battery unit detection deviation is not greater than the first threshold quantity of the battery unit detection deviation, but greater than the second threshold quantity of the battery unit detection deviation, mark the overheat detection abnormal level of the battery unit as the third level; if the number of battery unit detection deviation values higher than the first threshold of the battery unit detection deviation is not greater than the second threshold quantity of the battery unit detection deviation, but is not zero, mark the overheat detection abnormal level of the battery unit as the second level; if the number of battery unit detection deviation values higher than the first threshold of the battery unit detection deviation is zero, mark the overheat detection abnormal level of the battery unit as the first level.

[0067] In a specific embodiment, the detection evaluation value of the battery unit, the specific analysis process is as follows:

[0068]

[0069] Where ω is the detection evaluation value of the battery unit, jw is the average temperature of the battery unit, wc is the maximum temperature difference inside the battery unit, cr is the difference between the coolant outlet temperature and the inlet temperature of the battery unit, cr0 is the reference difference between the coolant outlet temperature and the inlet temperature of the battery unit, μ1 is the compensation factor of the set jw, μ2 is the compensation factor of the set wc, and μ3 is the compensation factor of the set cr.

[0070] It should be noted that the above battery cell detection and evaluation value is calculated through the average temperature of the battery cell, the maximum internal temperature difference of the battery cell, and the difference between the coolant outlet temperature and the inlet temperature of the battery cell. After normalizing jw, wc, and cr, by combining the average temperature, the maximum internal temperature difference, and the coolant temperature difference of the battery cell, the system can comprehensively evaluate the thermal management of the battery cell. A single parameter may not be able to fully reflect the actual state of the battery cell, while multi-dimensional evaluation can comprehensively consider the overall temperature situation, heat dissipation effect, and whether the temperature distribution of the battery is uniform, thus more accurately reflecting the health status of the battery cell. The battery cell detection and evaluation value calculated by multiple parameters helps to improve the accuracy of overheat detection. Relying solely on the average temperature cannot identify local overheating phenomena, while combining the maximum internal temperature difference can detect uneven heat dissipation inside the battery cell and prevent risks caused by excessively high local temperatures in certain areas. The difference between the coolant outlet and inlet temperatures reflects the cooling efficiency and can help determine whether the cooling system is working effectively, thus preventing overheating caused by insufficient cooling. The combination of multi-dimensional parameters helps to reduce misjudgments of the system, and through comprehensive calculation and evaluation of multiple indicators, the system can more comprehensively judge the true state of the battery cell.

[0071] For example:

[0072]

[0073]

[0074] In a specific embodiment, the compensation factor of jw is 1.0, the compensation factor of wc is 1.0, the compensation factor of cr is 1.0, the reference difference between the coolant outlet temperature and the inlet temperature of the battery cell is 30, there are ten battery cells, and the calculated battery cell detection and evaluation values are 11.5356, 8.4772, 15.0000, 9.0000, 4.9494, 24.8745, 13.3741, 31.4316, 4.6457, 4.0495 respectively. When the evaluation value of the cooling system usage status is 1.7009 and the environmental characteristic value α is 19.82, the cooling threshold of the liquid-cooled energy storage system is matched to be 6, the first threshold of the battery cell detection deviation is 6, the first threshold quantity of the battery cell detection deviation is 6, and the second threshold quantity of the battery cell detection deviation is 3. At this time, there are 4 battery cells whose battery cell detection deviation values are higher than the first threshold of the battery cell detection deviation. Based on the scheme for determining the overheat detection abnormal level of the battery cell, since the number of battery cell detection deviation values higher than the first threshold of the battery cell detection deviation is not greater than the first threshold quantity of the battery cell detection deviation but not lower than the second threshold quantity of the battery cell detection deviation, the overheat detection abnormal level of the battery cell is marked as the third level.

[0075] It should be explained that the above classification of battery cell overheating anomalies into four levels can make detailed graded judgments based on different detection deviation values. Through multiple thresholds and different detection conditions, the system can accurately identify the severity of battery cell overheating and avoid overly simple abnormal judgments. This helps to more accurately assess overheating risks, thereby distinguishing between minor and severe overheating conditions, taking appropriate measures in a targeted manner, and comprehensively analyzing the detection evaluation values ​​of the battery cells and comparing them with different thresholds. This method can reduce false alarms caused by minor temperature fluctuations. A high-level alarm will only be triggered when the detection deviation values ​​of multiple battery cells exceed the set threshold. This helps to reduce system misjudgments, improve the accuracy of alarms, and avoid unnecessary system interference. When the battery cells are at different abnormal levels, the system can adjust the workload of the energy storage system according to the situation. When the overheating detection abnormality level reaches level three or four, the system can reduce the workload of the battery cells to avoid further overheating due to continuous high load. The system can strengthen cooling measures to reduce the thermal load of the battery cells. The dynamic adjustment mechanism can improve the stability and reliability of the system. The analysis process is based on real-time data acquisition and intelligent threshold comparison, which can realize the automatic management of the system. The detection evaluation value of each battery cell is comprehensively analyzed and compared with the cooling threshold in the database. The system can automatically determine the abnormality level and issue an alarm. The automated management method reduces the need for manual monitoring and improves the overall intelligence level of the system.

[0076] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. An abnormal state detection method for a liquid-cooled energy storage system, characterized in that, It includes the following steps: Analyze the environment where the liquid-cooled energy storage system is located to obtain the environmental characteristic values; Analyze the environment where the liquid-cooled energy storage system is located to obtain the environmental characteristic values. The specific analysis process is as follows: Obtain the environmental data set where the liquid-cooled energy storage system is located. The environmental data set where the liquid-cooled energy storage system is located specifically includes the environmental temperature, the environmental wind speed, and the outlet temperature of the cooling system; Based on the obtained environmental data set where the liquid-cooled energy storage system is located, comprehensively analyze to obtain the environmental characteristic values, and the environmental characteristic values are used as the analysis basis for determining the cooling threshold of the liquid-cooled energy storage system; The environmental characteristic values. The specific analysis process is as follows: ； Wherein, is the environmental characteristic value of the location, is the environmental temperature of the location, is the environmental wind speed of the location, is the outlet temperature of the cooling system, is the set compensation factor, is the set compensation factor, is the set compensation factor; Analyze the usage status of the cooling system of the liquid-cooled energy storage system to determine whether there is an abnormality in the cooling system: If there is an abnormality in the cooling system, an alarm for the abnormality of the cooling system is issued; If there is no abnormality in the cooling system, combine the environmental characteristic values to determine the cooling threshold of the liquid-cooled energy storage system; Determine the cooling threshold of the liquid-cooled energy storage system. The specific analysis process is as follows: Obtain the evaluation value of the usage status of the cooling system and the environmental characteristic values, store the evaluation value of the usage status of the cooling system and the environmental characteristic values as a specified label, and compare the specified label with the cooling thresholds of the liquid-cooled energy storage system corresponding to each specified label stored in the database to obtain the cooling threshold of the liquid-cooled energy storage system corresponding to the specified label; Analyze the actual operating status of the liquid-cooled energy storage system to determine whether there is an operating abnormality in the liquid-cooled energy storage system and obtain the detection data sets of each battery unit, and combine the cooling threshold of the liquid-cooled energy storage system to determine the overheat detection abnormality level of the battery unit; Determine whether there is an operating abnormality in the liquid-cooled energy storage system. The specific analysis process is as follows: Obtain the actual operating status data set of the liquid-cooled energy storage system. Based on the obtained actual operating status data set of the liquid-cooled energy storage system, comprehensively analyze to obtain the actual operating status evaluation value, and the actual operating status evaluation value is used as the analysis basis for determining whether there is an operating abnormality in the liquid-cooled energy storage system; The actual operating status evaluation value. The specific analysis process is as follows: ； Wherein, is the actual operation status evaluation value, is the absolute value of the difference between the system power output and the reference power output, is the absolute value of the difference between the system load factor and the reference load factor, is the absolute value of the difference between the system voltage and the reference voltage, is the set compensation factor, is the set compensation factor, is the set compensation factor; Compare the actual operating status evaluation value with the actual operating status threshold stored in the database; If the actual operating status evaluation value is lower than the actual operating status threshold, the liquid-cooled energy storage system corresponding to the actual operating status evaluation value has an operating abnormality, and an alarm for the operating abnormality of the liquid-cooled energy storage system is issued; If the actual operating status evaluation value is not lower than the actual operating status threshold, the liquid-cooled energy storage system corresponding to the actual operating status evaluation value has no operating abnormality; The actual operating status data set of the liquid-cooled energy storage system specifically includes the absolute value of the difference between the system power output and the reference power output, the absolute value of the difference between the system load rate and the reference load rate, and the absolute value of the difference between the system voltage and the reference voltage; The detection data sets of each battery unit specifically include the average temperature of the battery unit, the maximum internal temperature difference of the battery unit, and the difference between the outlet temperature and the inlet temperature of the coolant of the battery unit; Based on the obtained detection data sets of each battery unit, comprehensively analyze to obtain the detection evaluation values of each battery unit, and the detection evaluation values of each battery unit are used as the analysis basis for determining the overheat detection abnormality level of the battery unit; The detection and evaluation value of the battery cell, and the specific analysis process is as follows: ； Wherein, is the detection and evaluation value of the battery cell, is the average temperature of the battery cell, is the maximum temperature difference inside the battery cell, is the difference between the coolant outlet temperature and the inlet temperature of the battery cell, is the reference difference between the coolant outlet temperature and the inlet temperature of the battery cell, is the set compensation factor, is the set compensation factor, is the set compensation factor; Compare the detection and evaluation values of each battery cell with the cooling threshold of the liquid-cooled energy storage system stored in the database; Record the difference between the detection and evaluation value of each battery cell and the cooling threshold of the liquid-cooled energy storage system as the detection deviation value of each battery cell; Compare the detection deviation values of each battery cell with the first detection deviation threshold of the battery cell stored in the database; If the number of battery cell detection deviation values higher than the first battery cell detection deviation threshold is greater than the first battery cell detection deviation threshold amount, mark the overheat detection abnormal level of the battery cell as the fourth level; If the number of battery cell detection deviation values higher than the first battery cell detection deviation threshold is not greater than the first battery cell detection deviation threshold amount, but greater than the second battery cell detection deviation threshold amount, mark the overheat detection abnormal level of the battery cell as the third level; If the number of battery cell detection deviation values higher than the first battery cell detection deviation threshold is not greater than the second battery cell detection deviation threshold amount, but is not zero, mark the overheat detection abnormal level of the battery cell as the second level; If the number of battery cell detection deviation values higher than the first battery cell detection deviation threshold is zero, mark the overheat detection abnormal level of the battery cell as the first level.

2. The abnormal state detection method of the liquid-cooled energy storage system according to claim 1, characterized in that: The specific analysis process for judging whether there is an abnormality in the cooling system is as follows: Obtain the cooling system usage status data set. Based on the obtained cooling system usage status data set, comprehensively analyze to obtain the cooling system usage status evaluation value, and the cooling system usage status evaluation value is used as the analysis basis for judging whether there is an abnormality in the cooling system; Compare the cooling system usage status evaluation value with the cooling system usage status threshold stored in the database; If the cooling system usage status evaluation value is lower than the cooling system usage status threshold, the cooling system corresponding to the cooling system usage status evaluation value has an abnormality, and an alarm for the cooling system abnormality is issued; If the cooling system usage status evaluation value is not lower than the cooling system usage status threshold, the cooling system corresponding to the cooling system usage status evaluation value has no abnormality.

3. The abnormal state detection method of the liquid-cooled energy storage system according to claim 2, characterized in that: The cooling system usage status data set specifically includes the absolute value of the difference between the coolant flow rate and the reference coolant flow rate, the absolute value of the difference between the coolant pressure and the reference coolant pressure, and the absolute value of the difference between the coolant liquid level and the reference coolant liquid level.

4. The abnormal state detection method of the liquid-cooled energy storage system according to claim 2, wherein: The specific analysis process for the cooling system usage status evaluation value is as follows: ； In the formula, is the evaluation value of the cooling system usage status, is the absolute value of the difference between the coolant flow rate and the reference coolant flow rate, is the absolute value of the difference between the coolant pressure and the reference coolant pressure, is the absolute value of the difference between the coolant level and the reference coolant level, is the set compensation factor, is the set compensation factor, is the set compensation factor, where e is the natural constant.

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