Monitoring and maintenance combined storage battery online monitoring and maintenance system and method

Abstract

The invention discloses a monitoring and maintenance combined online monitoring and maintenance system and method for a storage battery, and relates to the technical field of storage batteries, the system does not simply depend on an absolute threshold, but can sensitively capture the tiny trend change in the early stage of thermal runaway by calculating the time gradient of temperature, internal resistance and floating charge current. And on the other hand, historical state parameters such as SOH and cycle times are innovatively combined, differentiated risk assessment of the batteries with different aging degrees is realized, and missing report or false report caused by battery aging is avoided. Moreover, spatial dimension analysis is also introduced into the system, the risk index is corrected by monitoring the temperature change of the adjacent batteries, and the spreading characteristic of thermal runaway is effectively identified. Once the risk is confirmed, the system can immediately execute feedforward intervention measures such as active discharge or voltage reduction, and the thermal runaway positive feedback loop is cut off from the source.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of storage batteries, and particularly relates to a storage battery online monitoring and maintenance system and method combining monitoring and maintenance. BACKGROUND

[0002] Lead-acid storage batteries are widely used in starting, power and industrial fields, among which, industrial emergency backup storage batteries are core components of the energy storage and standby power market, covering lead-acid and gel batteries. In the online monitoring and maintenance of industrial emergency backup power systems and other power systems, the substation DC system relies on storage batteries to provide uninterrupted power supply for control loops, relay protection and emergency lighting. Similarly, in the field of railways and rail transit, from dispatching centers to communication signal rooms, to subway integrated monitoring and shielded door systems, storage battery packs are the only energy supply when AC power is lost, which is crucial to maintaining traffic order and ensuring life safety. In the above application scenarios, the storage battery pack is usually in a floating state for a long time to be ready to respond to sudden power outages at any time to ensure the continuous operation of communication, computing power and control systems. Therefore, ensuring the health and operational reliability of the storage battery pack in these critical infrastructure is an indispensable part of the industrial safety field. Although storage batteries are widely used, existing DC systems have significant limitations in maintenance. On the one hand, the traditional system mainly adopts the whole group charging and discharging mode, which cannot provide individualized balancing maintenance for single batteries, leading to the difficulty of meeting the industry standard for the consistency of the battery pack, and often the performance of the whole group depends on the worst single cell due to the bucket effect. On the other hand, the regular charging method used to recover the capacity of the lagging battery is likely to cause overcharging of the battery in good condition, not only shortening the actual service life of the battery pack, making it far below the designed life, but also long-term overcharging or improper floating is the main cause of thermal runaway. In addition, existing monitoring methods often rely on a single voltage or temperature threshold alarm, lacking the ability to capture early signs of thermal runaway, making it difficult to effectively block the disaster before it happens, posing a major risk to the safe operation of the system. SUMMARY

[0003] In view of the defects in the prior art, the application provides a storage battery online monitoring and maintenance system and method combining monitoring and maintenance to solve the above technical problems.

[0004] On the one hand, a storage battery online monitoring and maintenance system combining monitoring and maintenance is provided, comprising the following contents: A plurality of battery parameter monitoring modules corresponding to single batteries one by one are used to detect the monitoring parameters of each single battery; A battery historical state database is used to store the historical state parameters of each single battery; the historical state parameters include at least one of the following: state of health SOH, cycle number, historical overcharge number, historical overdischarge number; a plurality of battery equalization modules for performing charge-discharge maintenance on each single battery cell; a battery online monitoring and maintenance device, which is communicatively connected to the battery historical state database, the battery equalization modules, and the battery parameter monitoring module.

[0005] Preferably, the battery online monitoring and maintenance device is configured to: calculate a temperature time gradient, an internal resistance time gradient, and a float current time gradient of a target single battery cell based on the monitoring parameters obtained from the battery parameter monitoring module; evaluate an initial thermal runaway risk of the target single battery cell in combination with the temperature time gradient, the internal resistance time gradient, and the float current time gradient, and the historical state parameters of the target single battery cell obtained from the battery historical state database; adjust the initial thermal runaway risk based on temperature parameters of at least one adjacent single battery cell in the physical location of the target single battery cell to obtain a final thermal runaway risk; when the final thermal runaway risk exceeds a warning threshold, control the corresponding battery equalization module to perform charge-discharge maintenance on the target single battery cell.

[0006] Preferably, when at least one historical state parameter of the target single battery cell satisfies a corresponding risk judgment condition, a risk value calculated based on the temperature time gradient, the internal resistance time gradient, and the float current time gradient is amplified by weighting to evaluate the initial thermal runaway risk; in the evaluation of the initial thermal runaway risk, it is identified whether the target single battery cell is in a thermal runaway risk feature mode, and the thermal runaway risk feature mode is specifically a mode in which the temperature time gradient is greater than zero, the internal resistance time gradient is less than zero, and the float current time gradient is greater than zero are continuously satisfied within a preset time window. wherein the risk judgment condition is at least one of the following: a state of health (SOH) is lower than a preset SOH reference, a cycle number exceeds a preset cycle threshold, a historical overcharge number exceeds a preset overcharge threshold, and a historical overdischarge number exceeds a preset overdischarge threshold.

[0007] Preferably, in the adjustment of the initial thermal runaway risk by the battery online monitoring and maintenance device, the battery online monitoring and maintenance device is configured to: when the temperature time gradient of the at least one adjacent single battery cell is greater than a preset correlation threshold, increase the initial thermal runaway risk value of the target single battery cell according to a preset exponential function relationship.

[0008] Preferably, the charge-discharge maintenance includes at least one of the following: an instruction to switch the battery equalization module corresponding to the target single battery cell to a discharge mode; reduce the charging voltage of the target monomer battery.

[0009] In another aspect, a battery online monitoring and maintenance method combined with monitoring and maintenance is provided, comprising the following steps: acquiring monitoring parameters of each monomer battery by a battery parameter monitoring module; The battery online monitoring and maintenance device calculates the temperature time gradient, internal resistance time gradient, and floating current time gradient of the target monomer battery based on the monitoring parameters, and obtains historical state parameters of the target monomer battery; the historical state parameters include at least one of the following: state of health SOH, cycle number, historical overcharge number, and historical overdischarge number; The initial thermal runaway risk of the target monomer battery is evaluated in combination with the temperature time gradient, internal resistance time gradient, floating current time gradient, and historical state parameters; The initial thermal runaway risk is adjusted based on the temperature parameters of at least one adjacent monomer battery at the physical location of the target monomer battery to obtain a final thermal runaway risk; When the final thermal runaway risk exceeds a warning threshold, the battery equalization module is controlled to perform charge-discharge maintenance on the target monomer battery based on the final thermal runaway risk.

[0010] As a preferred, when at least one historical state parameter of the target monomer battery meets a corresponding risk judgment condition, the risk value calculated based on the temperature time gradient, internal resistance time gradient, and floating current time gradient is weighted and amplified to evaluate the initial thermal runaway risk; The risk judgment condition is at least one of the following: the state of health SOH is lower than a preset SOH reference, the cycle number exceeds a preset cycle threshold, the historical overcharge number exceeds a preset overcharge threshold, and the historical overdischarge number exceeds a preset overdischarge threshold.

[0011] As a preferred, when evaluating the initial thermal runaway risk, it is identified whether the target monomer battery is in a thermal runaway risk feature mode, and the thermal runaway risk feature mode is specifically: In a preset time window, the temperature time gradient is greater than zero, the internal resistance time gradient is less than zero, and the floating current time gradient is greater than zero.

[0012] As a preferred, the step of adjusting the initial thermal runaway risk is specifically: When the temperature time gradient of the at least one adjacent monomer battery is greater than a preset correlation threshold, the initial thermal runaway risk value of the target monomer battery is increased according to a preset exponential function relationship.

[0013] As a preferred, the charge-discharge maintenance includes at least one of the following: The instruction corresponds to the battery equalization module of the target monomer battery, and the battery equalization module is switched to a discharge mode; The charging voltage of the target monomer battery is reduced.

[0014] The beneficial effects of the present application are: the system no longer simply relies on the absolute threshold, but can sensitively capture the early trend changes of thermal runaway by calculating the time gradient of temperature, internal resistance and floating current. On the other hand, the present scheme innovatively combines historical state parameters such as SOH and cycle number to realize differentiated risk assessment of batteries with different aging degrees, avoiding false negatives or false positives caused by battery aging. Moreover, the system also introduces spatial dimension analysis, which corrects the risk index by monitoring the temperature changes of adjacent batteries, effectively identifying the spread characteristics of thermal runaway. Once the risk is confirmed, the system can immediately perform proactive discharge or voltage reduction and other feedforward intervention measures to cut off the positive feedback loop of thermal runaway from the root. BRIEF DESCRIPTION OF DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0016] Figure 1 A structural schematic diagram of a monitoring and maintenance combined battery online monitoring and maintenance system provided by the present application; Figure 2 A battery parameter monitoring module wiring schematic diagram of a monitoring and maintenance combined battery online monitoring and maintenance system provided by the present application; Figure 3 A step flowchart of a monitoring and maintenance combined battery online monitoring and maintenance method provided by the present application. DETAILED DESCRIPTION

[0017] In the description of the present application, it should be understood that the terms "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", "axial", "radial", "circumferential" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and therefore cannot be understood as indicating or implying that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application.

[0018] The following disclosure provides many different embodiments, or examples, for implementing different structures of the present application. For the purpose of simplifying the present application, the components and arrangements of the specific examples are described. Of course, they are only examples and are not intended to limit the present application.

[0019] Embodiments of the application will be described in detail with reference to the drawings.

[0020] As shown in Figure 1 , Figure 2 , a battery online monitoring and maintenance system combined with monitoring and maintenance includes the following: A plurality of battery parameter monitoring modules corresponding to single batteries one by one are used to detect monitoring parameters of each single battery; A battery history state database is used to store historical state parameters of each single battery; the historical state parameters include at least one of the following: state of health SOH, cycle number, historical overcharge number, and historical overdischarge number; A plurality of battery equalization modules are used to perform charge and discharge maintenance on each single battery; A battery online monitoring and maintenance device is in communication connection with the battery history state database, the battery equalization module, and the battery parameter monitoring module.

[0021] More specifically, the battery online monitoring and maintenance device is configured to: Based on the monitoring parameters obtained from the battery parameter monitoring module, calculate the temperature time gradient, internal resistance time gradient, and floating charge current time gradient of the target single battery; In combination with the temperature time gradient, internal resistance time gradient, and floating charge current time gradient, and the historical state parameters of the target single battery obtained from the battery history state database, evaluate the initial thermal runaway risk of the target single battery; Based on the temperature parameters of at least one adjacent single battery in the physical location of the target single battery, adjust the initial thermal runaway risk to obtain the final thermal runaway risk; When the final thermal runaway risk exceeds a warning threshold, control the corresponding battery equalization module to perform charge and discharge maintenance on the target single battery.

[0022] The application adopts two-level structure combining decentralization and centralization at the hardware architecture level, flexibly configures different types and quantities of execution level modules according to the battery specifications (2V, 6V, 12V) and the number of the battery pack. The control level is composed of the battery online monitoring and maintenance device, adopts standard 19-inch 2U structure, and realizes system control through the internal cascaded RS485 interface, dry node interface and environmental temperature measurement interface; the execution level includes the battery parameter monitoring module corresponding to the single battery, which adopts a fully decentralized architecture, configures an RJ11 interface and an SBUS communication cascade; the battery equalization module responsible for the individualized charge and discharge maintenance of 4n (n=1, 2, 3) batteries adopts a decentralized and centralized combined architecture, the circuit output end of each battery equalization module is connected to 4n single batteries, wherein n is 1, 2 or 3, a plurality of battery equalization modules are connected through a 4-core phoenix interface, and are configured to cascade communication using the RS485 communication protocol; the voltage and current detection module and the communication conversion device, one battery pack is configured with one voltage and current detection module, the voltage and current detection module is connected to the communication bus through the 4-core phoenix interface, and is configured to communicate using the RS485 communication protocol. The communication conversion device is used to connect the SBUS and RS485 two heterogeneous protocols, realizes transparent data transmission, and the power supply is supplied by the voltage and current detection module. Based on the above hardware platform, the battery online monitoring and maintenance device is configured to execute a thermal runaway early warning strategy with historical traceability and spatial perception capability.

[0023] In an embodiment, for the scenario of thermal stability decline caused by battery aging, the device collects the voltage, internal resistance and temperature data of the single battery through the SBUS bus at a millisecond level frequency, and calculates the time gradient of each parameter using a sliding time window algorithm. At the same time, the device accesses the built-in battery historical state database to retrieve the SOH (state of health) and the number of historical overcharges of the target battery. If the SOH of the target battery is lower than 80% and the number of historical overcharges exceeds 5 times, the device will automatically increase the weight coefficient of the time gradient based on the preset weighting algorithm, so that even if the temperature gradient has not reached the traditional high temperature alarm threshold, the initial thermal runaway risk value calculated can still quickly break through the early warning line. At this time, the device instructs the corresponding battery equalization module to switch to the micro-discharge mode through the RS485 bus, actively reduces the state of charge of the aging battery, and prevents thermal accumulation from running out of control.

[0024] Furthermore, for thermal propagation scenarios, after calculating the initial risk of the target battery, the device further iterates through the real-time temperature data of adjacent batteries at its physical location. If a sharp temperature rise greater than 1.0℃ / s is detected in an adjacent battery, the device uses an exponential function to spatially correct the risk value of the target battery, causing its eventual thermal runaway risk to increase exponentially. This ensures that even if the target battery's own parameters are normal, feedforward protection can be triggered due to environmental deterioration, and the device then controls the equalization module to perform coordinated voltage reduction maintenance on the battery pack in that area.

[0025] Compared to existing technologies, this invention firstly solves the technical problem of missed alarms for old batteries and false alarms for new batteries caused by traditional BMS relying solely on real-time thresholds by introducing SOH and historical overcharge parameters as risk correction factors, thus achieving adaptive safety management throughout the entire life cycle. Secondly, by combining a spatial correlation correction mechanism based on physical location, it effectively blocks the chain reaction of thermal runaway within the battery pack, improving the system's disaster prevention capabilities. Simultaneously, the hardware adopts a hybrid networking of SBUS and RS485 and a modular equalization design, which not only ensures high-frequency acquisition of individual parameters but also enables targeted charging and discharging maintenance for specific faulty batteries, significantly extending the overall service life of the battery pack.

[0026] To capture the instantaneous changing trends of battery parameters and filter out measurement noise, this scheme employs a sliding time window algorithm to calculate the temporal gradient of each monitored parameter. The sampling time interval is set to , and the sliding window length is . The specific formulas for calculating the time gradient of the target single-cell battery at time are as follows: Temperature gradient formula:

[0027] Internal resistance gradient formula:

[0028] Current gradient formula:

[0029] in, For the current moment Push forward Historical temperature values ​​during each sampling period; Since temperature, internal resistance, and current have different physical units, they cannot be directly weighted. Therefore, a preset safety benchmark value is introduced as the denominator to convert the dimensional gradient values ​​into dimensionless normalized exponents.

[0030]

[0031] in, This is the preset temperature gradient safety limit value; This is the preset limit value for the change in internal resistance gradient; This is the preset safety limit value for the float charge current gradient; For temperature normalization gradient, For the internal resistance normalization gradient, This is the normalized gradient of the current.

[0032] More specifically, when at least one historical state parameter of the target single cell meets the corresponding risk judgment condition, the risk value calculated based on the temperature time gradient, internal resistance time gradient, and float charge current time gradient is weighted and amplified to assess the initial thermal runaway risk; when assessing the initial thermal runaway risk, it is identified whether the target single cell is in a thermal runaway risk characteristic mode, which specifically means that within a preset time window, the temperature time gradient is greater than zero, the internal resistance time gradient is less than zero, and the float charge current time gradient is greater than zero. The risk determination condition is at least one of the following: the state of health (SOH) is lower than the preset SOH benchmark, the number of cycles exceeds the preset cycle threshold, the number of historical overcharges exceeds the preset overcharge threshold, and the number of historical over-discharges exceeds the preset over-discharge threshold.

[0033] In this scheme, the battery's historical health status is introduced as a correction factor for risk assessment. For batteries that are severely aged or have a history of damage, the system will automatically amplify their risk index to achieve differentiated supervision.

[0034]

[0035] Among them, aging factors As shown in the following formula:

[0036] In the formula, For target single cell battery The initial risk value of thermal runaway; These are the weight coefficients of the real-time gradient, and ; The absolute value of the normalized internal resistance gradient; SOH represents the current battery health state, with a value of (0,1). This represents the current loop count; The maximum cycle life designed for the battery; This refers to the cumulative number of overcharges in history. The preset overcharge tolerance threshold; The influence weights of each historical parameter; In practice, the device first performs dimensionless processing on the collected real-time monitoring data, dividing the time gradients of temperature, internal resistance, and float current by preset safety benchmark values ​​to obtain normalized gradient exponents. Subsequently, the device executes weighted amplification logic, which is not a simple linear superposition but rather constructs a multiplier effect by calculating aging factors.

[0037] The system detected that the health status of a single battery cell had dropped to 70% (below the preset 80% baseline). At this point, the SOH weight term in the algorithm significantly increased, leading to a higher aging factor and a final amplification factor of 1.5. This means that when the aged battery experiences a slight temperature rise gradient of only 0.2℃ / s, its calculated initial risk value will be equivalent to the risk level of a new battery with a temperature rise of 0.3℃ / s. This triggers an early warning and controls the equalization module to perform micro-discharge maintenance, effectively avoiding sudden thermal runaway caused by the decrease in heat capacity due to electrolyte drying in the aged battery. For batteries with a history of multiple overcharges, the system retrieves its historical overcharge count from the database (e.g., 12 times, exceeding the preset threshold of 10 times). In this case, the overcharge weight term in the algorithm dominates, pushing up the aging factor. Even if the battery's current SOH is acceptable, the system will increase its sensitivity to float charge current fluctuations due to its past abuse history. Once abnormal fluctuations in the current gradient are detected, the risk value is immediately amplified and a reduction in charging voltage is ordered.

[0038] In the specific implementation of the initial thermal runaway risk assessment process, the device allocates a configurable sliding time window in memory to cache normalized temperature time gradient, internal resistance time gradient, and float charge current time gradient data in real time. The device performs a logical AND operation in each sampling cycle, and only marks the target cell as having an activated thermal runaway characteristic mode when all sampling points within the time window continuously satisfy the three-dimensional vector condition that temperature time gradient > 0, internal resistance time gradient < 0, and float charge current time gradient > 0.

[0039] In the first embodiment, addressing the thermal runaway scenario of a valve-regulated sealed lead-acid battery under long-term float charging, when the oxygen cycle reaction within a single cell intensifies, the increased temperature leads to enhanced electrolyte activity, causing a decrease in the equivalent internal resistance. Under constant-voltage float charging conditions, this decrease in internal resistance directly results in a nonlinear increase in the float charging current, and the Joule heat generated by the increased current further pushes up the temperature. If the system detects that this typical vicious cycle pattern persists for more than 60 seconds, it immediately determines that the battery is in the early stages of thermal runaway and superimposes a high-weighted mode penalty factor on the basic risk value, forcibly triggering the current-limiting protection of the equalization module.

[0040] In the second embodiment, regarding the heating scenario caused by loose connecting strips, although the temperature gradient is greater than zero, poor contact will lead to a significant increase in contact internal resistance, manifested as an internal resistance gradient greater than zero or fluctuating, which does not meet the characteristic condition. Based on this, the algorithm removes such anomalies from the risk of thermal runaway, accurately identifying them as connection failures rather than chemical thermal runaway, thus avoiding erroneous charging and discharging interventions.

[0041] More specifically, when the battery online monitoring and maintenance device adjusts the initial thermal runaway risk, it is configured as follows: When the temperature time gradient of at least one adjacent single cell is greater than a preset correlation threshold, the initial thermal runaway risk value of the target single cell is increased according to a preset exponential function relationship.

[0042] In this scheme, a spatial correlation mechanism is introduced to address the contagious nature of thermal runaway. When surrounding batteries experience abnormal temperature increases, the risk level of the target battery will rise exponentially.

[0043]

[0044] in, This represents the final risk value for thermal runaway. This is the spatial sensitivity coefficient, used to adjust the system's sensitivity to adjacent heat sources; It represents the maximum normalized temperature gradient among all physically adjacent cells of the target cell.

[0045] The device establishes an adjacency matrix table in memory based on the actual installation arrangement of the battery pack, such as a matrix or shelf arrangement, to map the index relationship between each individual battery cell and its physical neighbors in real time. After calculating the initial risk value of the target individual battery cell, the device retrieves the normalized temperature gradient of all its neighboring batteries in parallel. If the heating rate of any neighboring battery exceeds a preset correlation threshold, such as >0.5, the risk value is nonlinearly amplified. The exponential term ensures that the risk assessment responds explosively to environmental degradation, rather than accumulating nonlinearly.

[0046] In one embodiment, within a tightly packed rack-mounted battery pack, target battery A operates normally, with an initial risk of 0.2. However, its adjacent battery B experiences a rapid temperature rise due to an internal short circuit, resulting in a normalized temperature gradient of 2.0. The device detects this anomaly and calculates using a spatial sensitivity coefficient λ=2.0, with an adjustment factor of 54.6. The final risk value of target battery A instantly spikes to 10.92, far exceeding the warning threshold. The device then determines that the risk of regional heat spread is extremely high and instructs the equalization module to simultaneously perform emergency discharge on battery A and surrounding batteries, actively cutting off the heat transfer path.

[0047] For scenarios where the overall ambient temperature rises, the temperature rise gradient of all adjacent batteries is relatively consistent and slow, generally less than 0.1, with an exponential term of 1.22, thus having a limited amplification effect on the risk value. This allows the system to effectively distinguish between thermal radiation caused by a single point of failure and the ambient temperature rise, avoiding erroneous site-wide shutdowns due to air conditioning malfunctions.

[0048] More specifically, the charge / discharge maintenance includes at least one of the following: The instruction is given to switch the battery balancing module corresponding to the target single battery cell to discharge mode. Reduce the charging voltage of the target single cell.

[0049] Based on the final risk value calculated earlier, the device sends control commands to the battery balancing module corresponding to the target battery via the RS485 bus to execute differentiated maintenance actions. The exponential function relationship here is not only used for alarm determination but also serves as a quantitative basis for maintenance intensity: an exponential increase in the risk value corresponds to a non-linear increase in intervention priority.

[0050] During implementation, when the risk value of the target battery exceeds the warning threshold due to exponential amplification caused by thermal radiation from adjacent batteries, the system determines that the battery has a passive thermal runaway risk. The device immediately instructs the equalization module to switch to constant current discharge mode, using the module's built-in energy-consuming load or bidirectional DC / DC converter to forcibly reduce the target battery's state of charge to below 90% with a preset current. This action actively reduces the heat generation capacity of the battery by lowering the concentration of electrochemical active materials inside the battery, preventing external heat sources from inducing internal exothermic reactions. When the system identifies the target battery in an early thermal runaway characteristic mode of constant voltage and surge in current, the device instructs the equalization module to execute a voltage reduction clamping strategy. The equalization module adjusts the PWM duty cycle of the power circuit to linearly reduce the float charge voltage applied to the target battery from 2.25V to 2.18V or even lower. The slight reduction in voltage will cause a significant decrease in the float charge current, thereby directly blocking the Joule heat generation circuit, allowing the battery's internal temperature to gradually return to equilibrium, achieving a cold treatment of thermal runaway.

[0051] like Figure 3 As shown, an online monitoring and maintenance method for batteries that combines monitoring and maintenance includes the following steps; The monitoring parameters of each individual battery cell are collected through the battery parameter monitoring module; Based on the monitoring parameters, the battery online monitoring and maintenance device calculates the temperature time gradient, internal resistance time gradient, and float charge current time gradient of the target single cell, and simultaneously acquires the historical state parameters of the target single cell; the historical state parameters include at least one of the following: state of health (SOH), number of cycles, number of historical overcharges, and number of historical over-discharges. By combining the temperature time gradient, internal resistance time gradient, float charge current time gradient and the historical state parameters, the initial thermal runaway risk of the target single cell is assessed. Based on the temperature parameters of at least one adjacent cell at the physical location of the target cell, the initial thermal runaway risk is adjusted to obtain the final thermal runaway risk. When the risk of ultimate thermal runaway exceeds the warning threshold, the battery balancing module is controlled to perform charge and discharge maintenance on the target single cell based on the risk of ultimate thermal runaway.

[0052] More specifically, when at least one historical state parameter of the target single cell meets the corresponding risk judgment condition, the risk value calculated based on the temperature time gradient, internal resistance time gradient and float charge current time gradient is weighted and amplified to assess the initial thermal runaway risk. The risk determination condition is at least one of the following: the state of health (SOH) is lower than the preset SOH benchmark, the number of cycles exceeds the preset cycle threshold, the number of historical overcharges exceeds the preset overcharge threshold, and the number of historical over-discharges exceeds the preset over-discharge threshold.

[0053] More specifically, when assessing the initial thermal runaway risk, it is determined whether the target single-cell battery is in a thermal runaway risk characteristic mode, wherein the thermal runaway risk characteristic mode is specifically: Within a preset time window, the system continuously satisfies the following conditions: temperature time gradient is greater than zero, internal resistance time gradient is less than zero, and float charge current time gradient is greater than zero.

[0054] More specifically, the steps for adjusting the initial thermal runaway risk are as follows: When the temperature time gradient of at least one adjacent single cell is greater than a preset correlation threshold, the initial thermal runaway risk value of the target single cell is increased according to a preset exponential function relationship.

[0055] More specifically, the charge / discharge maintenance includes at least one of the following: The instruction is given to switch the battery balancing module corresponding to the target single battery cell to discharge mode. Reduce the charging voltage of the target single cell.

[0056] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A battery online monitoring and maintenance system combining monitoring and maintenance, characterized in that, Includes the following: Multiple battery parameter monitoring modules, each corresponding to a single battery cell, are used to detect the monitoring parameters of each battery cell. A battery history status database is used to store the historical status parameters of each individual battery cell; the historical status parameters include at least one of the following: State of Health (SOH), number of cycles, number of historical overcharges, and number of historical over-discharges. Multiple battery balancing modules are used for charging and discharging maintenance of each individual battery cell; The battery online monitoring and maintenance device is communicatively connected to the battery historical status database, the battery balancing module, and the battery parameter monitoring module.

2. The online monitoring and maintenance system for batteries combining monitoring and maintenance according to claim 1, characterized in that, The battery online monitoring and maintenance device is configured as follows: Based on the monitoring parameters obtained from the battery parameter monitoring module, the temperature time gradient, internal resistance time gradient, and float charge current time gradient of the target single cell are calculated. By combining the temperature time gradient, internal resistance time gradient, and float charge current time gradient, as well as the historical state parameters of the target cell obtained from the battery historical state database, the initial thermal runaway risk of the target cell is assessed. Based on the temperature parameters of at least one adjacent cell at the physical location of the target cell, the initial thermal runaway risk is adjusted to obtain the final thermal runaway risk. When the risk of ultimate thermal runaway exceeds the warning threshold, the corresponding battery balancing module is controlled to perform charge and discharge maintenance on the target single cell.

3. The online monitoring and maintenance system for batteries combining monitoring and maintenance according to claim 2, characterized in that, When at least one historical state parameter of the target single cell meets the corresponding risk judgment condition, the risk value calculated based on the temperature time gradient, internal resistance time gradient, and float charge current time gradient is weighted and amplified to assess the initial thermal runaway risk; when assessing the initial thermal runaway risk, it is identified whether the target single cell is in a thermal runaway risk characteristic mode, which specifically means that within a preset time window, the temperature time gradient is greater than zero, the internal resistance time gradient is less than zero, and the float charge current time gradient is greater than zero. The risk determination condition is at least one of the following: the state of health (SOH) is lower than the preset SOH benchmark, the number of cycles exceeds the preset cycle threshold, the number of historical overcharges exceeds the preset overcharge threshold, and the number of historical over-discharges exceeds the preset over-discharge threshold.

4. The online monitoring and maintenance system for batteries combining monitoring and maintenance according to claim 1, characterized in that, When the battery online monitoring and maintenance device adjusts the initial thermal runaway risk, it is configured as follows: When the temperature time gradient of at least one adjacent single cell is greater than a preset correlation threshold, the initial thermal runaway risk value of the target single cell is increased according to a preset exponential function relationship.

5. The online monitoring and maintenance system for batteries combining monitoring and maintenance according to claim 1, characterized in that, The charge / discharge maintenance includes at least one of the following: The instruction is given to switch the battery balancing module corresponding to the target single battery cell to discharge mode. Reduce the charging voltage of the target single cell.

6. A method for online monitoring and maintenance of a storage battery that combines monitoring and maintenance, characterized in that, Includes the following steps: The monitoring parameters of each individual battery cell are collected through the battery parameter monitoring module; Based on the monitoring parameters, the battery online monitoring and maintenance device calculates the temperature time gradient, internal resistance time gradient, and float charge current time gradient of the target single cell, and simultaneously acquires the historical state parameters of the target single cell; the historical state parameters include at least one of the following: state of health (SOH), number of cycles, number of historical overcharges, and number of historical over-discharges. By combining the temperature time gradient, internal resistance time gradient, float charge current time gradient and the historical state parameters, the initial thermal runaway risk of the target single cell is assessed. Based on the temperature parameters of at least one adjacent cell at the physical location of the target cell, the initial thermal runaway risk is adjusted to obtain the final thermal runaway risk. When the risk of ultimate thermal runaway exceeds the warning threshold, the battery balancing module is controlled to perform charge and discharge maintenance on the target single cell based on the risk of ultimate thermal runaway.

7. The online monitoring and maintenance method for batteries combining monitoring and maintenance according to claim 6, characterized in that, When at least one historical state parameter of the target single cell meets the corresponding risk assessment condition, the risk value calculated based on the temperature time gradient, internal resistance time gradient and float charge current time gradient is weighted and amplified to assess the initial thermal runaway risk. The risk determination condition is at least one of the following: the state of health (SOH) is lower than the preset SOH benchmark, the number of cycles exceeds the preset cycle threshold, the number of historical overcharges exceeds the preset overcharge threshold, and the number of historical over-discharges exceeds the preset over-discharge threshold.

8. The online monitoring and maintenance method for batteries combining monitoring and maintenance according to claim 6, characterized in that, When assessing the initial thermal runaway risk, it is determined whether the target single-cell battery is in a thermal runaway risk characteristic mode, wherein the thermal runaway risk characteristic mode is specifically: Within a preset time window, the system continuously satisfies the following conditions: temperature time gradient is greater than zero, internal resistance time gradient is less than zero, and float charge current time gradient is greater than zero.

9. The online monitoring and maintenance method for batteries combining monitoring and maintenance according to claim 6, characterized in that, The specific steps for adjusting the initial thermal runaway risk are as follows: When the temperature time gradient of at least one adjacent single cell is greater than a preset correlation threshold, the initial thermal runaway risk value of the target single cell is increased according to a preset exponential function relationship.

10. The online monitoring and maintenance method for batteries combining monitoring and maintenance according to claim 6, characterized in that, The charge / discharge maintenance includes at least one of the following: The instruction is given to switch the battery balancing module corresponding to the target single battery cell to discharge mode. Reduce the charging voltage of the target single cell.

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