Monitoring system for charging safety of energy storage battery

Abstract

The invention discloses a monitoring system for charging safety of an energy storage battery, and relates to the technical field of battery safety monitoring, and the system comprises a detection module which is used for monitoring each single cell during charging, and collecting the capacity trend, real-time internal resistance, current distribution and heat state of all cells when finding voltage fluctuation or temperature abnormity of any cell; the analysis module is used for identifying an energy gathering center and a diffusion path caused by performance difference and disturbance intensity of the energy gathering center and the diffusion path on peripheral battery cells based on acquired data, evaluating the disturbance intensity, and upgrading traditional isolated parameter monitoring into dynamic correlation analysis, so that asymmetric deviation signals at the initial stage of charging can be captured and analyzed; and a new thought is provided for advanced prevention and control of systematic risks.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of battery safety monitoring, and specifically relates to a monitoring system for charging safety of energy storage batteries. BACKGROUND

[0002] An energy storage battery is a device that can convert electrical energy into chemical energy and store it, and convert it back into electrical energy for release when needed, and is widely used in renewable energy, power grid peak shaving, home backup power, electric vehicles and other scenarios.

[0003] The root cause of energy imbalance in an energy storage battery cluster is the nonlinear conduction of cell performance differences. In the charging process, there are inherent differences in performance parameters such as internal resistance and capacity of single cells, and such differences will non-linearly expand with the increase of charging and discharging cycle times. When the internal resistance of a certain cell suddenly changes due to aging, manufacturing errors, etc., it will cause local current concentration and form an energy flow concentration center; and the transmission of energy in series and parallel paths will show nonlinear diffusion characteristics due to the correlation between cells, and traditional linear monitoring models cannot capture such dynamic changes, which is easy to cause heat runaway chain reaction. SUMMARY

[0004] The purpose of the present application is to provide a monitoring system for charging safety of energy storage batteries, which solves the technical problem that asymmetric deviation signals at the initial stage of charging are difficult to be captured and analyzed in the prior art.

[0005] A monitoring system for charging safety of energy storage batteries, comprising: A detection module monitors each single cell during charging, finds any cell voltage fluctuation or temperature anomaly, and collects all cell capacity trends, real-time internal resistance, current distribution and heat state; An analysis module identifies energy concentration centers, diffusion paths and disturbance intensity to surrounding cells caused by performance differences based on collected data, and evaluates the disturbance intensity; A selection module selects a dynamic model that matches the current disturbance intensity according to the location and quantitative intensity of the concentration center; A calculation module calculates the performance difference influence range, diffusion speed and intervention critical point using the selected model; A control module controls the energy storage cluster to perform targeted regulation measures according to the calculation results, gradually adjusts the charging current of the branch where the energy concentration center is located, and enhances heat dissipation in the disturbance affected area to eliminate energy flow imbalance.

[0006] Further, after the control module controls the energy storage cluster to perform targeted regulation, it further comprises: Obtain updated data of cell capacity trends, internal resistance, current distribution and heat state after regulation; Based on the updated data, determine whether the aggregation center is shifted, the diffusion path is changed, and the disturbance intensity is weakened; According to the new results, regulate the branch current of the new aggregation center and the heat dissipation of the new disturbance area until the balance is restored.

[0007] Further, after regulation, the detection module continuously collects cell parameters; when the normal cell voltage fluctuates or the temperature is abnormal, the analysis module repositions the aggregation center and the diffusion direction, and the calculation module calculates the critical state.

[0008] Further, the control module adjusts the amplitude of the charging current and the energy diffusion speed, and adjusts the heat dissipation intensity of the disturbance influence area at the same time, which suppresses the energy imbalance diffusion while maintaining the overall charging efficiency of the energy storage cluster within the preset range.

[0009] Further, when the analysis module identifies the diffusion path, it combines the topological current distribution to mark the high-current density path as a key monitoring object and predicts potential diffusion risks.

[0010] Further, when the aggregation center shifts after regulation / the disturbance is not weakened, and the normal cell suddenly becomes abnormal, including: Analyze the correlation between the new abnormality and the original imbalance area: if the new abnormality characteristics are consistent with the original area conduction, consistent with the circuit / thermal field transmission law, then preferentially deepen the regulation of the original area and cut off the conduction path; If the new abnormality has no conduction correlation with the original area, it is an independent imbalance point, then preferentially intervene in the new area, maintain the original area regulation, and after the new area is stable, integrate the data to optimize the overall strategy.

[0011] Further, when judging the conduction consistency of energy characteristics, it is specifically: Record the characteristics before intervention in the original area: voltage change frequency, temperature gradient direction and its correlation law; Compare the new abnormality characteristics: analyze whether the voltage frequency and temperature gradient are continuously transmitted with the original area and meet the circuit / thermal field transmission attenuation characteristics; Check if the space is in the same transmission channel; if the above conditions are met, determine the correlation.

[0012] Further, when there is indirect conduction between the new abnormality and the original area, the intermediate cells in the conduction chain are monitored synchronously, and the source is preferentially handled while the intermediate cells are subjected to current limiting or heat dissipation prevention.

[0013] Further, when deepening the regulation of the original area to cut off the conduction path, including: If the main path is the circuit, adjust the branch current distribution between the original and new areas to reduce the electrical transmission efficiency; If the main path is thermal diffusion, strengthen the thermal resistance isolation between the original and new areas to weaken the heat transfer; The blocking strength is adjusted according to the conduction decay rate; when the correlation between the new anomaly and the original region continues to weaken, the blocking strength is gradually reduced to reduce the impact on charging.

[0014] Compared with the prior art, the present application has the following advantages: First, the present application realizes all-round and real-time monitoring of the charging process of the energy storage battery, can timely find subtle abnormalities of the battery cell, changes the hysteresis of the traditional monitoring, greatly improves the accuracy and timeliness of the monitoring; second, by accurately identifying the energy aggregation center, diffusion path and quantifying the disturbance strength, the energy imbalance problem inside the battery is deeply analyzed, providing a clear basis for subsequent regulation; third, by means of the dynamic model, the influence range, diffusion speed and intervention critical point are accurately predicted, the potential risks are estimated in advance, so that the system can take effective measures before the accident occurs, and the safety of the energy storage battery charging is significantly improved; fourth, the energy storage cluster is controlled to execute targeted regulation measures, which can quickly and effectively eliminate the imbalance of energy flow, ensure the stable operation of the battery system, reduce the battery loss caused by charging failure, and prolong the service life of the battery. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 The figure is a schematic diagram of the method framework structure of the present application.

[0016] Figure 2 The figure is a schematic diagram of the system framework structure of the present application. DETAILED DESCRIPTION

[0017] The technical solutions of the present application will be described below in conjunction with the embodiments, obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor belong to the scope of protection of the present application.

[0018] For this purpose, see Figure 1 The present application provides a monitoring system for the safety of energy storage battery charging, comprising: The detection module monitors each single battery cell during charging, finds any voltage fluctuation or temperature anomaly of the battery cell, i.e. collects the capacity trend, real-time internal resistance, current distribution and heat state of all battery cells; The analysis module identifies the energy aggregation center, diffusion path and disturbance strength to the surrounding battery cells caused by performance difference based on the collected data, and evaluates the disturbance strength; The selection module selects a dynamic model matching the current disturbance strength according to the position of the aggregation center and the quantified strength; The calculation module calculates the performance difference influence range, diffusion speed and intervention critical point by using the selected model; The control module controls the energy storage cluster to perform targeted regulation measures according to the calculation results, and eliminates the imbalance of energy flow by gradually adjusting the charging current of the branch where the energy aggregation center is located and enhancing heat dissipation in the disturbance influence area.

[0019] In this embodiment, the single cell is the basic unit of the energy storage battery pack, usually a lithium ion battery, etc., and its performance parameters include voltage, capacity, internal resistance, etc., which can be monitored by the voltage sensor and temperature sensor provided by the cell, and it is the smallest object of state monitoring during charging.

[0020] The cell capacity trend data is recorded by the coulomb counting method combined with the ampere-hour integration principle, and is used to present the capacity attenuation or abnormal fluctuation of the cell.

[0021] Real-time internal resistance data: The internal resistance of the cell is obtained in real time by AC impedance spectroscopy or DC internal resistance measurement method, which reflects the internal chemical reaction state of the cell.

[0022] Current distribution data: The current of each cell is measured by a Hall current sensor, and the distribution of current in the battery pack is analyzed by combining the circuit topology.

[0023] Thermal state data: Thermocouples or infrared thermal imagers are arranged on the surface and key positions of the cell to monitor the heat generation of the cell in real time.

[0024] Energy aggregation center: The clustering algorithm (such as K-Means) is used for the data of cell capacity trend, real-time internal resistance, current distribution, etc., to find out the cells or cell groups with excessive energy concentration.

[0025] Further, the diffusion path is an energy propagation model based on the circuit and heat conduction model, which models the flow direction and rate of energy between cells, and determines the diffusion path from the aggregation center to the periphery. The disturbance intensity is the difference between the voltage, current and temperature of the energy aggregation center and the surrounding cells, which calculates the interference degree of the surrounding cells. The larger the value, the more serious the interference. Dynamic model: Based on the real-time state of the energy storage battery, the performance of the cell and the energy propagation characteristics, a mathematical model is constructed by using neural network technology, which can predict the performance difference influence range, diffusion speed and intervention critical point after a large amount of historical data training. Influence range: According to the calculation results of the dynamic model, the range of the area affected by the energy aggregation center disturbance and the obvious change of the cell state is determined. Diffusion speed: The rate of energy propagation from the aggregation center to the periphery is obtained by simulating the energy propagation state at different times by the dynamic model, which can be V / s, ℃ / s or A / s. Intervention critical point, when the energy storage battery voltage, temperature, current and other parameters reach the value, such as the area cell temperature reaches 60℃, voltage deviation exceeds ±0.1V, current imbalance degree exceeds 30%, immediate control measures must be taken to avoid accidents.

[0026] Based on the problems raised in the above background art, the present scheme draws on the analysis logic of the interaction between atmospheric circulation and local cyclone in meteorology. It should be understood that in the meteorological system, the formation of local cyclone will change the direction and intensity of the surrounding atmospheric circulation, and the circulation will in turn affect the moving path and diffusion range of the cyclone, forming a dynamically related whole. Similarly, the performance difference of a single cell in the energy storage cluster (such as local energy loss caused by sudden increase of internal resistance) can be regarded as an energy disturbance source (analogous to a local cyclone), while the current flow and heat transfer in the series-parallel path constitute an energy circulation system (analogous to atmospheric circulation).

[0027] Through this conversion in thinking, the present scheme upgrades the traditional isolated parameter monitoring to dynamic correlation analysis, identifies the energy flow concentration center (analogous to the cyclone center), diffusion path (analogous to the direction of air flow movement), and disturbance intensity (analogous to the cyclone influence range) caused by performance difference, and establishes an analysis model that can reflect the imbalance trend of the overall energy flow, thereby facilitating the capture and analysis of the asymmetric deviation signal at the initial stage of charging, and providing a new way of thinking for the early prevention and control of systematic risks.

[0028] The working principle of the present application can be divided into the following key steps: During the charging process, the voltage and temperature of each single cell are monitored in real time using high-precision sensors. When the voltage fluctuation of any cell exceeds the normal range or the temperature abnormally rises, the comprehensive data acquisition process is immediately started, and multi-dimensional data such as the capacity trend, real-time internal resistance, current distribution, and heat state of all cells are obtained.

[0029] Based on the collected data, data mining and analysis algorithms are used to identify the energy concentration center caused by the performance difference of the cells, determine the path of energy diffusion from the concentration center to the surrounding cells, and calculate the disturbance intensity to the surrounding cells. According to the position information of the energy concentration center and the quantified disturbance intensity, a dynamic model that best matches the current working condition is selected from the pre-constructed model library. This model is trained based on the physical characteristics, electrochemical principles, and a large amount of historical operation data of the energy storage battery, and can accurately reflect the behavior characteristics of the battery system under different conditions.

[0030] Using the selected dynamic model, the current key parameters (such as the position of the energy concentration center, the disturbance intensity, etc.) are input, and the influence range of the performance difference on the energy storage battery system, the energy diffusion speed, and the impending intervention critical point are calculated.

[0031] The control energy storage cluster receives the calculation results and performs targeted control measures according to the results. For the branch where the energy aggregation center is located, the controllable resistance in the charging circuit or the power converter is adjusted to gradually reduce or adjust the charging current to reduce energy input; for the disturbance influence area, additional heat dissipation fans, cooling water pumps and other heat dissipation equipment are started to enhance the heat dissipation effect, so as to eliminate the imbalance of energy flow and restore the energy storage battery system to a safe and stable operating state.

[0032] As a preferred embodiment, the application for the energy storage battery charging safety monitoring system is implemented as follows: For example, in a 1000 lithium iron phosphate battery pack, each battery is equipped with a high-precision voltage sensor (measurement accuracy ±0.001V) and a thermistor (measurement accuracy ±0.1℃) for real-time monitoring of battery voltage and temperature. When the charging is carried out for 30 minutes, the monitoring system detects that the voltage of the No. 350 battery suddenly rises by 0.1V, which exceeds the normal fluctuation range, and the temperature rises to 45℃, which is 5℃ higher than the normal working temperature. The system immediately triggers comprehensive data collection, obtains the capacity trend of all batteries through coulomb counting method and ampere-hour integral principle, measures the real-time internal resistance by AC impedance spectroscopy technology, collects current distribution data by Hall current sensor, and obtains heat state data by thermocouple arranged on the surface of the battery.

[0033] The collected data is analyzed by using K-Means clustering algorithm, and the energy aggregation center with battery 350 as the core is identified, and 50 batteries around the center form an energy aggregation area. Through the established energy propagation model, it is determined that the energy mainly spreads from the aggregation center to the adjacent batteries along the series circuit direction. According to the voltage difference, current difference, temperature difference and other factors, the specific calculation method is as follows: first, calculate the ratio of voltage difference, current difference and temperature difference to the corresponding threshold value respectively (i.e. normalization, so that each ratio is in the range of 0~1), then weighted sum according to the weight of voltage difference ratio accounting for 40%, current difference ratio accounting for 30% and temperature difference ratio accounting for 30%, to get the disturbance intensity (value range 0~1), the larger the value, the more serious the interference; Wherein, the voltage difference is the absolute difference of the real-time voltage of the energy accumulation center and a certain cell in the periphery, and its corresponding threshold is the maximum voltage difference allowed in the normal charging process of the type of cell (such as 0.5V, which can be preset according to the cell specification); the current difference is the absolute difference of the real-time current of the branch where the energy accumulation center is located and the branch where the peripheral cell is located, and its corresponding threshold is the maximum current difference allowed in the normal charging process of the type of battery pack (such as 5A, which can be preset according to the circuit design); the temperature difference is the absolute difference of the real-time temperature of the energy accumulation center and a certain cell in the periphery, and its corresponding threshold is the maximum temperature difference allowed in the normal charging process of the type of cell (such as 20℃, which can be preset according to the safety standard).

[0034] According to the position of the energy accumulation center and the disturbance intensity, a dynamic model based on long short-term memory network (LSTM) is selected from the model library. The model is trained by a large amount of charging and discharging data of the same type of energy storage battery, and can accurately predict the state of the battery under different working conditions. After inputting the current parameters, the model calculates that the influence range of performance difference will expand to the surrounding 200 cells within the next 10 minutes, and the energy diffusion speed is 0.05V / s (voltage change), 0.2℃ / s (temperature change), and it is expected that the intervention critical point will be reached after 15 minutes (at this time, the average temperature of the cells in the region will reach 60℃, and the voltage deviation will exceed ±0.1V).

[0035] After the energy storage cluster receives the calculation result, it immediately adjusts the charging current of the branch where the energy accumulation center is located. By controlling the power converter in the charging circuit, the charging current of the branch is gradually reduced from 50A to 30A, reducing the energy input. At the same time, the cooling fans and cooling water pipelines arranged in the disturbance affected area are started to enhance the cooling effect. After 10 minutes of regulation and control, the voltage and temperature of the cells in the region gradually return to normal, the voltage fluctuation is controlled within ±0.03V, and the temperature is stabilized at about 40℃, successfully eliminating the energy flow imbalance and ensuring the safe charging of the energy storage battery.

[0036] The beneficial effects of the present application mainly reflect in the following aspects: first, the full range and real-time monitoring of the charging process of the energy storage battery is realized, which can timely find the subtle abnormalities of the cells, changes the hysteresis of traditional monitoring, greatly improves the accuracy and timeliness of monitoring; second, through accurate identification of the energy accumulation center, diffusion path and quantification of disturbance intensity, the energy imbalance problem inside the battery is deeply analyzed, providing clear basis for subsequent regulation and control; third, with the help of dynamic model, the influence range, diffusion speed and intervention critical point are accurately predicted, the potential risks are estimated in advance, so that the system can take effective measures before the accident occurs, significantly improving the safety of the energy storage battery charging; fourth, the energy storage cluster controls the implementation of targeted regulation and control measures, which can quickly and effectively eliminate the energy flow imbalance, ensure the stable operation of the battery system, reduce the battery loss caused by charging failure, and prolong the service life of the battery.

[0037] In another embodiment of the present application, after the control of the energy storage cluster performs targeted adjustment, further comprising: obtaining updated data of the capacity trend, internal resistance, current distribution and thermal state of the regulated battery cells; based on the updated data, determining whether the aggregation center is shifted, the diffusion path is changed, and the disturbance intensity is weakened; according to the new results, regulating the branch current of the new aggregation center and the heat dissipation of the new disturbance area until the balance is restored.

[0038] The present embodiment adds the acquisition and analysis of various data after the control of the energy storage cluster performs targeted adjustment. Because only one targeted adjustment may not completely solve the imbalance problem of the energy storage cluster, the problem may shift or change. By introducing the acquisition of updated data, the system can comprehensively understand the effect after regulation, so as to judge the dynamic change of the problem.

[0039] Furthermore, by determining the changes of the aggregation center, the diffusion path and the disturbance intensity, the system can timely grasp the new situation of the problem, and ensure that the subsequent regulation measures are more targeted. Only by regulating the new aggregation center and the new disturbance area according to the new determination results, can the energy storage cluster gradually restore balance. This mechanism combining the monitoring of data after regulation and dynamic determination makes the regulation of the energy storage cluster more accurate and effective. The updated data is used to reflect the regulation effect and the problem change, and the determination of the aggregation center is used as a key basis to ensure that the regulation strategy can be adjusted in time when the problem dynamically changes. This is helpful to solve the limitations of one-time regulation, avoid the failure of regulation due to the change of the problem, and improve the stability and reliability of the operation of the energy storage cluster. A specific embodiment of the present embodiment is as follows: assuming that there is a problem of local battery overheating in an energy storage cluster, after the initial targeted adjustment, the updated data of the capacity trend, internal resistance, current distribution and thermal state of each battery cell after regulation is obtained. By analyzing these data, it is determined that the original overheated aggregation center has shifted to another area, the diffusion path has changed from horizontal spread to vertical spread, and the disturbance intensity has been weakened but still not reached a balanced state. Therefore, according to this new result, the branch current of the new aggregation center is limited, which is helpful to reduce the current load of the area, and at the same time, the power of the heat dissipation fan in the new disturbance area is increased to increase the heat dissipation. After a period of continuous regulation, the data monitoring is performed again, and it is found that the aggregation center disappears, the diffusion path is terminated, the disturbance intensity is reduced to the normal range, and the energy storage cluster restores the balanced state, at which time the regulation is stopped. If the aggregation center shifts again or the diffusion path changes again during the regulation process, the above process is repeated until the balance is restored.

[0040] In another embodiment of the present application: after the regulation, the detection module continuously collects the parameters of the battery cells; when the normal battery cells have voltage fluctuations or temperature abnormalities, the analysis module repositions the aggregation center and the diffusion direction, and the calculation module redefines the critical state.

[0041] It should be understood that the critical state refers to the critical threshold state of the battery cell about to have a serious failure (such as thermal runaway, short circuit, etc.), which can be determined based on a model trained on a large amount of battery cell failure data or a preset safety threshold range.

[0042] The present embodiment, based on the continuous collection of battery cell parameters after the regulation, increases the steps of repositioning the aggregation center and the diffusion direction and redefining the critical state in response to voltage fluctuations or temperature abnormalities of normal battery cells. The reason for doing so is that the state of the battery cell after the regulation may change dynamically during use, and it is difficult to early warn potential serious failures by only continuously collecting parameters. It is precisely because the aggregation center and the diffusion direction of the abnormal battery cell are introduced that the system can accurately locate the core area of the abnormality and the trend of the spread, thereby providing a targeted basis for the subsequent redefinition of the critical state.

[0043] Furthermore, by redefining the critical state through the calculation module, the safety threshold can be updated according to the real-time abnormal development, avoiding the problems of early warning lag or false early warning caused by using a fixed critical value, and ensuring that a warning can be issued in time when the state of the battery cell is close to the danger edge.

[0044] This mechanism that combines continuous collection of battery cell parameters, analysis of abnormal aggregation and diffusion, and dynamic redefinition of the critical state makes the monitoring and early warning of the battery cell state more accurate and timely. The continuous collection of battery cell parameters provides basic data for abnormal detection, while the analysis of the aggregation center and the diffusion direction clarifies the scope and development trend of the abnormality, and the redefinition of the critical state provides a dynamically adjusted threshold standard for accurate early warning. This effectively solves the problem of insufficient response to dynamic abnormalities of the battery cell in the fixed monitoring mode, and improves the safety during use of the battery cell.

[0045] In some embodiments of the present application, the adjustment range of the control module for the charging current is positively correlated with the energy diffusion speed, and the heat dissipation intensity of the corresponding adjustment disturbance influence area is adjusted, so as to suppress the diffusion of energy imbalance while maintaining the overall charging efficiency of the energy storage cluster within a preset range.

[0046] It should be noted that the energy diffusion speed refers to the speed of the spread of the abnormal state of the battery cell to the surrounding, which can be calculated by the time difference of the parameter change of the adjacent battery cells; the disturbance influence area is the range of the battery cells affected by the abnormal state, which is determined by the analysis module according to the parameter abnormality range.

[0047] When the control module adjusts the charging current, the amplitude increases with the increase of the energy diffusion speed, and at the same time, the heat dissipation intensity of the corresponding disturbance influence area is enhanced. In this way, the energy imbalance diffusion can be quickly suppressed, and by reasonable adjustment, the charging can be avoided to be excessively limited, so that the overall charging efficiency of the energy storage cluster can be maintained within the preset range, and the charging effect can take into account the safety and charging efficiency. More importantly, this kind of dynamic correlation adjustment method is beneficial to avoid the chain type abnormal amplification problem caused by the lag of single parameter adjustment, that is, when the energy diffusion speed increases suddenly, the simultaneously increased current adjustment amplitude and heat dissipation intensity can form a synergistic regulation, which can cut off the energy support of abnormal diffusion from two dimensions of energy input and heat dissipation, which is a synergistic prevention and control effect that cannot be achieved by adjusting the current or heat dissipation respectively.

[0048] For example, when a certain energy storage cluster is charging, the energy diffusion speed increases, and the control module increases the charging current adjustment amplitude at the same time, and enhances the heat dissipation of the disturbance area. Finally, the energy imbalance diffusion is suppressed, and the overall charging efficiency is also maintained within the preset range.

[0049] In another embodiment of the present application, when the analysis module identifies the diffusion path, the high current density path is marked as the key monitoring object in combination with the topological current distribution, and the potential diffusion risk is predicted.

[0050] In this embodiment, the topological current distribution refers to the current flow network layout formed by each battery cell and the connecting line in the energy storage cluster, which can be presented by combining the circuit topology diagram with real-time current monitoring data; the high current density path is a flow path with large current in unit cross-sectional area, which is determined by current monitoring data calculation.

[0051] It should be understood that when the analysis module identifies the diffusion path, the possible diffusion direction can be more accurately located in combination with the topological current distribution. The high current density path is marked as the key monitoring object because such path is more likely to become a channel for the spread of abnormal state, which is convenient for predicting the potential diffusion risk in advance and providing targeted basis for subsequent prevention and control. It is worth noting that this consideration of combining topology and current density breaks through the limitation of judging diffusion direction only according to physical position, which is helpful to capture the cross-regional jumping diffusion problem caused by circuit connection relationship.

[0052] For example, when a local battery cell in a certain energy storage cluster is abnormal, the analysis module identifies the diffusion path in combination with the topological current distribution of the abnormal battery cell, finds that several high current density paths may be related to the abnormal area, and marks these paths as key monitoring objects. Through continuous monitoring, it is predicted in advance that there is a risk that the abnormality will spread along these paths, which saves time for taking prevention and control measures in time.

[0053] Further, in another embodiment of the present application, when the control center after regulation and control is transferred / perturbed and has not been weakened, and a normal battery cell suddenly becomes abnormal, including: Analyze the association between the new anomaly and the original unbalanced region: if the new anomaly characteristics are consistent with the original region conduction and comply with the circuit / thermal field transmission rules, then prioritize deepening the regulation of the original region and cutting off the conduction path; If the new anomaly has no conduction association with the original region and is an independent imbalance point, then prioritize intervening in the new region, maintaining the original region regulation, and after the new region stabilizes, integrate the data to optimize the overall strategy.

[0054] In this embodiment, the new anomaly characteristics refer to the parameter change characteristics presented when a normal battery cell suddenly becomes abnormal, such as voltage drop amplitude, temperature rise rate, internal resistance fluctuation law, etc., which can be extracted from real-time data collected by the detection module. The original region conduction consistency means that the characteristics of the new anomaly are consistent with the original unbalanced region in terms of parameter change trend and transmission timing, for example, the original region caused by overheating leads to voltage drop, and the new abnormal battery cell also presents the same "temperature rise first and then voltage drop" rule. The circuit / thermal field transmission rule refers to the physical law of energy transmission in the circuit through current conduction and in the thermal field through heat radiation / conduction / convection, for example, high resistance regions in the circuit will conduct current to low resistance regions, and high temperature objects in the thermal field will transfer heat to low temperature objects. An independent imbalance point refers to a new imbalance region that has no physical conduction association with the original imbalance region (such as no direct circuit connection, no heat exchange channel) and has completely independent abnormal characteristics.

[0055] This embodiment realizes separate processing of complex imbalance scenarios by analyzing the association between the new anomaly and the original unbalanced region when the gathering center transfer / disturbance has not weakened after regulation and normal battery cells suddenly become abnormal. Further, because when the system is faced with the situation of original problems not being solved and new problems appearing at the same time, blind simultaneous regulation may lead to resource allocation confusion and even trigger new chain reactions. By introducing association analysis, the nature of the new anomaly can be determined, whether it is an extension of the original problem or an independent new problem, thereby avoiding inefficient adjustment that cannot be synchronized.

[0056] Further, when it is determined that the new anomaly is consistent with the original region conduction and complies with the transmission rules, the original region is prioritized for deepening regulation and cutting off the conduction path, because at this time the new anomaly is essentially a derivative problem of the original imbalance, and if it is not solved from the source, only processing the new region will lead to repeated problems. When the new anomaly is an independent imbalance point, the new region is prioritized for intervention and the original region regulation is maintained, which can prevent the expansion of new problems and ensure the continuity of the original regulation. After the new region stabilizes, the data is integrated to optimize the overall strategy, which can avoid the interference of different region regulation measures.

[0057] This way of first correlation judgment and then separate treatment can break through the limitations of traditional regulation, thereby identifying the primary and secondary relationship of imbalance problems and maximizing the regulation efficiency under limited resources. For example, when the thermal runaway of the original area causes new cell abnormalities through heat conduction, cutting off the heat dissipation channel of the original area (deepening regulation) is more efficient than cooling the new cell alone; when the new abnormality is an independent internal short circuit of the battery, preferentially processing the new area can avoid the short-circuit current affecting the regulation effect of the original area. This dynamic priority adjustment based on correlation can significantly reduce the regulation cost (such as energy consumption and equipment wear) in complex scenarios, while shortening the time for the system to recover to balance.

[0058] One specific implementation of the embodiment is as follows: Assuming that after regulation, the disturbance of the original imbalance area of a certain energy storage cluster has not weakened, and a piece of normal cell suddenly has a temperature anomaly. The system first analyzes the new abnormality characteristics: the temperature of the new cell rises at a rate of 5°C per minute, and the voltage linearly decreases, which is completely consistent with the characteristics of the original imbalance area (caused by internal short circuit, resulting in "fast temperature rise, voltage drop"). At the same time, it is found through the circuit topology diagram that the new cell and the original area are connected through the same series branch (consistent with the circuit transmission law), and the thermal field simulation shows that the distance between the two is only 3 cm (consistent with the heat conduction law). Therefore, the system determines that the new abnormality is caused by the original area, and preferentially deepens the regulation of the original area: increases the heat dissipation power of the original area (from 200W to 300W), and at the same time cuts off the current of the series branch (reduces the branch current from 5A to 0A). After 10 minutes, the temperature of the original area decreases, and the temperature and voltage of the new cell also return to normal.

[0059] Another case: If the new abnormal cell has no circuit connection with the original area (belongs to different parallel groups), and the abnormality characteristics are "voltage sudden rise and then sudden drop" (which is completely different from the "continuous voltage drop" characteristics of the original area), the system determines it as an independent imbalance point. At this time, preferentially take measures on the new area (such as starting the standby cooling device), while keeping the regulation parameters of the original area (such as maintaining the heat dissipation power of 200W). After the new area stabilizes (temperature and voltage return to the normal range), the system integrates the abnormal data of the two areas, finds that the regulation parameters of the original area may cause the voltage fluctuation to be too large, and then optimizes the overall strategy (increases the current regulation accuracy of the original area from ±0.5A to ±0.2A).

[0060] In another embodiment of the present application, when judging the consistency of the conduction of energy characteristics, it is specifically: recording the characteristics of the original area before intervention: voltage variation frequency, temperature gradient direction and its correlation law; comparing the new abnormality characteristics: analyzing whether its voltage frequency and temperature gradient are continuously transmitted with the original area and meet the attenuation characteristics of circuit / thermal field transmission; checking whether the space is in the same transmission channel; if the above conditions are met, it is determined to be related.

[0061] It should be understood that in judging the consistency of the new anomaly with the energy feature transmission of the original unbalanced region, the specific operation is as follows: First, record the original region characteristics before intervention, including the voltage change frequency of the battery cell in the region, the temperature gradient direction, and the correlation between the two. The voltage change frequency refers to the number of times the voltage of the battery cell fluctuates in a unit of time, which can be obtained by continuously collecting voltage data and calculating the period; the temperature gradient direction refers to the direction of the change of temperature in space, for example, from the high temperature region to the low temperature region, which can be determined by comparing the data of temperature sensors arranged at different positions; and the correlation refers to the internal relationship between the voltage change frequency and the temperature gradient direction, for example, when the temperature gradient direction points to a certain direction, the voltage change frequency shows a specific change trend.

[0062] Second, compare the new abnormal characteristics. Analyze the voltage frequency and temperature gradient of the battery cell in the new abnormal region to see if it presents a continuous transmission state with the characteristics of the original region, and conforms to the attenuation characteristics of circuit / thermal field transmission. The attenuation characteristics of circuit transmission refers to the gradual weakening of current or voltage during transmission, for example, in a series circuit, the voltage at a position far from the power source will be lower; the attenuation characteristics of thermal field transmission refers to the gradual decrease of temperature during transmission, for example, the temperature at a position far from the heat source will be lower than that at a position close to the heat source. If the voltage frequency of the new abnormal region gradually changes according to the circuit transmission law based on the voltage change frequency of the original region, and the temperature gradient gradually changes according to the thermal field transmission law in the direction of the temperature gradient of the original region, it means that the two have continuity in characteristics.

[0063] Finally, check whether the space is in the same transmission channel. Transmission channel refers to the path of energy (including electrical energy and thermal energy) transmission in the energy storage cluster, which can be determined according to the circuit connection structure and heat dissipation channel layout of the energy storage cluster. For example, in the circuit, the same series or parallel branch can be regarded as a circuit transmission channel; in the thermal field, adjacent regions with thermal conduction medium (such as metal connecting piece, air, etc.) can be regarded as the same thermal field transmission channel. If the new abnormal region and the original unbalanced region are in the same transmission channel in space, it further supports the possibility of the existence of conduction correlation between the two.

[0064] When the voltage frequency, temperature gradient of the new abnormality and the original region continuously transmit and conform to the attenuation characteristics, and are in the same transmission channel in space, it can be determined that the new abnormality is related to the original unbalanced region.

[0065] For example, before the original unbalanced area intervention, the voltage change frequency is 5 times per second, the temperature gradient direction is from left to right, and the voltage change frequency decreases slightly along the extension of the temperature gradient direction. After the appearance of the new abnormal area, its voltage frequency is 4.8 times per second, the temperature gradient direction is also from left to right, consistent with the temperature gradient direction of the original area, and the voltage frequency and temperature change amplitude are attenuated compared to the original area according to the circuit and heat field transmission law, and the new abnormal area is in the same series branch and heat conduction channel as the original area. At this time, it can be determined that the new abnormality is related to the original unbalanced area.

[0066] In another embodiment of the present application, when the new abnormality is indirectly conducted with the original area, the intermediate cells in the conduction chain are monitored synchronously, and the source is preferentially processed while the intermediate cells are implemented with current limiting or heat dissipation prevention.

[0067] The working principle of the present application is that when the new abnormality is indirectly conducted with the original area, the intermediate cells in the conduction chain need to be monitored synchronously. The intermediate cells in the conduction chain refer to the cells located between the new abnormal area and the original area, which participate in the indirect energy transmission.

[0068] At this time, while preferentially processing the imbalance source (such as the original area), preventive measures such as current limiting (reducing the current load) or heat dissipation (enhancing the heat dissipation intensity) are implemented on the intermediate cells, which can stop the energy from continuing to conduct through the intermediate link and avoid the expansion of the new abnormality, thereby ensuring the stability of the energy storage cluster.

[0069] For example, the new abnormality is indirectly conducted with the original area through 3 intermediate cells, and when the system processes the original area, the 3 cells are monitored synchronously, and current limiting and heat dissipation are enhanced, effectively blocking the conduction path.

[0070] In another embodiment of the present application, when the original area is deepened to cut off the conduction path, including: if the main path is the circuit, adjusting the branch current distribution between the original and new areas to reduce the electrical transmission efficiency; if the main path is heat diffusion, strengthening the thermal isolation between the original and new areas to weaken the heat transfer; the blocking strength is adjusted according to the conduction decay rate; when the correlation between the new abnormality and the original area continues to weaken, gradually reduce the blocking strength to reduce the impact on charging.

[0071] When the original area is deepened to cut off the conduction path, the specific operation is as follows: If the main path is the circuit, that is, the correlation between the new abnormality and the original unbalanced area is mainly realized through the circuit transmission, at this time, the branch current distribution between the original area and the new abnormal area needs to be adjusted. By adjusting the current control device (such as current limiting resistor, switching element, etc.) of the branch, the proportion of current flowing in the branch is changed, the current flowing from the original area to the new abnormal area is reduced, and thus the electrical transmission efficiency between the two is reduced, and the energy conduction through the circuit is weakened.

[0072] If the main path is thermal diffusion, that is, the correlation mainly depends on heat transfer, the thermal resistance isolation between the original area and the new abnormal area needs to be strengthened. The thermal resistance between the two areas can be increased by starting the thermal insulation device (such as the retractable thermal insulation plate) of the area, increasing the thickness of the thermal insulation material, or optimizing the direction of the heat dissipation airflow to reduce heat exchange, thereby reducing the heat transfer from the original area to the new abnormal area.

[0073] The blocking strength needs to be adjusted according to the conduction decay rate. The conduction decay rate refers to the speed at which energy weakens during conduction, which can be calculated by the amount of energy transferred per unit time. When the conduction decay rate is slow, that is, the speed at which energy transfer weakens is slow, it indicates that the current blocking effect is not good, and the blocking strength needs to be increased, such as further reducing the branch current of the circuit or strengthening the thermal resistance isolation. When the conduction decay rate is fast, the blocking strength can be appropriately reduced to avoid unnecessary impact on the normal operation of the energy storage cluster due to excessive regulation.

[0074] When it is monitored that the correlation between the new abnormality and the original area continues to weaken, for example, the voltage, temperature, and other characteristics of the new abnormal area gradually increase the difference from the original area, and meet the characteristics of no correlation, the blocking strength should be gradually reduced. This can reduce the impact on the overall charging process of the energy storage cluster, ensure the blocking effect, and maintain a high charging efficiency as much as possible to achieve the balance between prevention and efficiency.

[0075] For example, if it is determined that the main path between the new abnormality and the original area is the circuit, and the branch current between them is large at the beginning, the conduction decay rate is slow. At this time, the system adjusts the current limiting element of the branch to reduce the branch current distribution and increase the blocking strength. As the adjustment proceeds, it is monitored that the conduction decay rate is accelerated, and the correlation between the new abnormality and the original area continues to weaken. The system gradually reduces the current limiting strength and the blocking strength until the new abnormal area is stable, and finally restores the normal current distribution of the branch to reduce the impact on the overall charging. If the main path is thermal diffusion, the heat transfer between the two areas is obvious at the beginning, and the conduction decay rate is slow. The system starts the thermal insulation plate and increases the thickness to strengthen the thermal resistance isolation and increase the blocking strength. When the heat transfer is weakened, the conduction decay rate is accelerated, and the correlation continues to weaken, the thermal insulation plate is gradually withdrawn, the blocking strength is reduced, and the impact on the overall operation of the heat dissipation system is reduced.

[0076] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A monitoring system for energy storage battery charging safety, characterized by, Comprise: A detection module monitors each single battery cell during charging, finds any cell voltage fluctuation or temperature anomaly, and collects all cell capacity trends, real-time internal resistance, current distribution, and heat state; An analysis module identifies energy accumulation centers, diffusion paths, and their disturbance intensity based on the collected data, and evaluates the disturbance intensity; A selection module selects a dynamic model that matches the current disturbance intensity based on the location and intensity of the accumulation center; A calculation module calculates the performance difference impact range, diffusion speed, and intervention critical point using the selected model; A control module controls the energy storage cluster to execute targeted regulation measures based on the calculation results, gradually adjusts the charging current of the branch where the energy accumulation center is located, and enhances heat dissipation in the disturbed area to eliminate energy flow imbalance.

2. A monitoring system for energy storage battery charging safety according to claim 1, characterized in that, After the control module executes targeted regulation, it also includes: Obtain updated data on cell capacity trends, internal resistance, current distribution, and heat state after regulation; Based on the updated data, determine whether the accumulation center has shifted, the diffusion path has changed, and the disturbance intensity has weakened; Based on the new results, regulate the branch current of the new accumulation center and the heat dissipation of the new disturbed area until balance is restored.

3. A monitoring system for energy storage battery charging safety as claimed in claim 1 wherein, After regulation, the detection module continuously collects cell parameters; when normal cells experience voltage fluctuations or temperature anomalies, the analysis module repositions the accumulation center and diffusion direction, and the calculation module recalculates the critical state.

4. A monitoring system for energy storage battery charging safety according to claim 1, characterized in that, The control module adjusts the charging current in proportion to the energy diffusion speed, and adjusts the heat dissipation intensity of the disturbed area accordingly, suppressing energy imbalance diffusion while maintaining the overall charging efficiency of the energy storage cluster within a preset range.

5. A monitoring system for energy storage battery charging safety as claimed in claim 1, wherein, When identifying diffusion paths, the analysis module combines topological current distribution to mark high-current density paths as key monitoring objects and predict potential diffusion risks.

6. A monitoring system for energy storage battery charging safety according to claim 3, wherein, When the accumulation center shifts after regulation and the disturbance does not weaken, and normal cells experience sudden anomalies, include: Analyze the correlation between the new anomaly and the original imbalance area: if the new anomaly characteristics are consistent with the original area transmission and meet the circuit / thermal field transmission rules, prioritize deepening regulation of the original area and cutting off the transmission path; If the new anomaly is not related to the original area and is an independent imbalance point, prioritize intervention in the new area and maintain regulation of the original area. After the new area stabilizes, integrate data to optimize the overall strategy.

7. A monitoring system for energy storage battery charging safety according to claim 6, wherein, When determining the consistency of energy characteristics, specifically: Record the characteristics before intervention in the original area: voltage change frequency, temperature gradient direction, and their correlation rules; Compare the new anomaly characteristics: analyze whether the voltage frequency and temperature gradient are continuously transmitted from the original area and meet the circuit / thermal field transmission decay characteristics; Check if the space is in the same transmission channel; if the above conditions are met, determine the correlation.

8. A monitoring system for energy storage battery charging safety according to claim 6, wherein, When there is indirect transmission between the new anomaly and the original area, monitor the intermediate cells in the transmission chain and prioritize handling the source while implementing current limiting or heat dissipation prevention for the intermediate cells.

9. A monitoring system for energy storage battery charging safety according to claim 6, wherein, When deepening regulation of the original area to cut off the transmission path, include: If the main path is the circuit, adjust the branch current distribution between the original and new areas to reduce electrical transmission efficiency; If the main path is thermal diffusion, strengthen thermal isolation between the original and new areas to reduce heat transmission. The blocking strength is adjusted according to the conduction decay rate; when the new anomaly and the original region relevance continues to weaken, gradually reduce the blocking strength to reduce the impact on charging.

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