Multi-row independent flow regulation method and system for cluster-level submerged energy storage system

Abstract

The application relates to the field of energy storage system management, in particular to a multi-row independent flow regulation method and system for a cluster-level immersed energy storage system. The method comprises the following steps: collecting the temperature of the battery cells in each row of the multi-row battery row in real time, and obtaining the oil supply reference temperature of the liquid cooling unit; calculating the temperature difference between the battery cell temperature of each row and the oil supply reference temperature; executing a differentiated flow distribution strategy according to the temperature difference; for the row whose temperature difference exceeds a first preset threshold, increasing the opening degree of the corresponding electric regulating valve; for the row whose temperature difference is lower than a second preset threshold, reducing the opening degree of the corresponding electric regulating valve; adopting a linkage adjustment mechanism: when the temperature difference of the battery row located at the top of the longitudinal direction exceeds a third preset threshold, automatically increasing the flow priority of the top battery row and increasing the flow of the top battery row, and correspondingly reducing the flow distribution of the bottom battery row in proportion to the weight, so that the total circulating flow of the cooling oil is kept as a constant value. The temperature distribution uneven problem caused by the temperature stratification in the longitudinal direction is eliminated.

Description

Technical Field

[0001] This application relates to the field of energy storage system management technology, specifically to a method and system for multi-row independent flow control in a cluster-level submerged energy storage system. Background Technology

[0002] Cluster-level immersion cooling technology is an important development direction in the field of thermal management for energy storage batteries, and it has been initially applied to prismatic battery energy storage systems. This technology completely immerses the battery module in insulating cooling oil, and the heat generated during battery charging and discharging is carried away by the circulating flow of the cooling oil, which has advantages such as high heat dissipation efficiency, good temperature uniformity, and high safety.

[0003] In practical engineering applications, the cooling oil in a submerged energy storage system enters from the bottom of the tank and flows out from the top, continuously absorbing the heat released by each row of batteries during its upward flow. Actual measurement data shows that the temperature of the cooling oil in contact with the top battery row is significantly higher than that at the bottom inlet, with a temperature difference of 5°C to 8°C between the top cells and the cooling oil, while the temperature difference at the bottom is only about 2°C to 3°C, forming a clear vertical temperature stratification phenomenon.

[0004] This uneven vertical temperature distribution presents three technical challenges: First, the top cells operate under high temperatures for extended periods, accelerating capacity decay and chemical aging, leading to uneven aging of the entire battery cluster and shortening the overall lifespan of the energy storage system. Second, the temperature rise at the top is more pronounced during high-rate charging and discharging, easily triggering alarms in the thermal management system and even forcing the system to reduce power, affecting system availability and economic efficiency. Third, the existing unified cooling system cannot differentiate its cooling based on the actual thermal demands of different rows, resulting in either overcooling and energy waste or insufficient cooling leading to localized overheating, lacking precise control measures.

[0005] Therefore, how to eliminate the longitudinal temperature stratification phenomenon in cluster-level immersion energy storage systems and achieve uniform temperature control of each row of cells has become a key technical problem restricting the further promotion and application of this technology. Summary of the Invention

[0006] To address the aforementioned problems, this invention provides a method and system for multi-row independent flow regulation in a cluster-level submerged energy storage system.

[0007] In a first aspect, the present invention provides a multi-row independent flow control method for a cluster-level submerged energy storage system, applicable to an energy storage system including a TANK body, a thermal management controller, and a liquid cooling unit. The TANK body has multiple rows of batteries arranged longitudinally inside, and each row of batteries is equipped with an independent oil supply pipeline and an electric regulating valve. The method is used to eliminate longitudinal temperature stratification caused by the cooling oil circulating and absorbing heat from bottom to top, and includes the following steps: S1. Real-time acquisition of the cell temperature of each row in the multi-row battery pack, and acquisition of the oil supply reference temperature of the liquid cooling unit; S2. Calculate the temperature difference between the cell temperature and the oil supply reference temperature for each row of batteries. S3. Execute a differentiated flow distribution strategy based on the temperature difference. For rows where the temperature difference exceeds a first preset threshold, increase the opening of the corresponding electric regulating valve; for rows where the temperature difference is lower than a second preset threshold, decrease the opening of the corresponding electric regulating valve. In S3, the differentiated flow allocation strategy includes a linkage adjustment mechanism: when the temperature difference of the top battery row in the vertical direction exceeds the third preset threshold, the flow priority of the top battery row is automatically increased and its flow is increased, while the flow allocation of the bottom battery row is reduced accordingly according to the weight ratio, so that the flow increment and decrement of all rows cancel each other out and keep the total circulating flow of cooling oil constant.

[0008] By real-time acquisition of the temperature difference between each row of battery cells and the oil supply reference temperature, and independently controlling the opening of the electric regulating valve based on the temperature difference, flow distribution to battery rows of different heights is achieved. This reduces the longitudinal temperature difference within the system, improving the consistency and safety of the battery pack. The introduced linkage regulation mechanism increases the flow rate to the top high-temperature battery rows while reducing the flow rate to the bottom low-temperature battery rows according to a weighted ratio, so that the increase and decrease in flow rate cancel each other out. This design prioritizes the heat dissipation needs of high-temperature areas while maintaining a constant total circulating flow rate of cooling oil, avoiding the impact of drastic fluctuations in total flow rate on the liquid cooling unit, and ensuring the operational stability and energy efficiency ratio of the thermal management system.

[0009] As a preferred embodiment of the technical solution of the present invention, a fault-tolerant step is also included: When the temperature sensor in a certain row fails, it automatically switches to the temperature reference mode of the adjacent row or takes the average temperature of the remaining normal rows as the reference value for flow control. When an abnormality is detected in the oil supply or return pressure of a certain row, or when a cooling oil leak alarm is detected, the corresponding electric regulating valve of that row is controlled to close or its opening is reduced to a safe maintenance value.

[0010] When a temperature sensor in a row fails, the system can automatically switch to the temperature reference mode of an adjacent row or use the average temperature of the remaining normal rows as the reference value. This redundant control strategy avoids the risk of battery overheating or control failure in that row due to a single-point sensor failure, ensuring the continuous operation of the temperature control system.

[0011] By monitoring the supply and return oil pressure and leakage alarms in real time, the corresponding valves can be shut off or reduced to a safe opening degree immediately upon detection of any abnormality. This effectively prevents the expansion of cooling oil leakage, avoids the risk of battery thermal runaway due to lack of oil, and ensures the physical safety of the energy storage system.

[0012] As a preferred embodiment of the technical solution of the present invention, the step of determining that the temperature sensor has malfunctioned includes: The thermal management controller monitors the signal status and value rationality of each temperature sensor in real time, and determines that the temperature sensor in that row has malfunctioned when any of the following conditions are detected: The sensor signal is interrupted or exceeds the preset physical measurement range; The rate of change of the cell temperature in this line exceeded the normal rate of change threshold within a preset time period. The temperature of this row of cells deviates from the average temperature of other rows of cells by more than a preset deviation threshold.

[0013] By comprehensively judging sensor faults through multi-dimensional judgment logic, the accuracy and timeliness of fault identification are improved. This multi-criteria approach effectively distinguishes between real drastic temperature changes and sensor signal drift / disconnection, avoiding false alarms and missed alarms, and ensuring the reliable triggering of fault-tolerant procedures.

[0014] As a preferred embodiment of the technical solution of the present invention, it further includes a predictive temperature control step in coordination with the battery management system (BMS): Obtain the State of Charge (SOC) and charge / discharge rate sent by the BMS; A longitudinal thermal stratification prediction model is constructed, which predicts the temperature of each row after a preset time based on the SOC, charge / discharge rate and the longitudinal height position of each row in the TANK body. Based on the predicted temperature of each row, the opening of the corresponding row's electric regulating valve is pre-adjusted to the predicted opening value; The actual temperature difference is compared with the predicted temperature difference calculated based on the predicted temperature, and the longitudinal thermal stratification prediction model is corrected according to the comparison results.

[0015] A thermal stratification prediction model is constructed based on SOC, charge / discharge rate, and longitudinal position to predict the temperature distribution at future times. Based on this, valve openings are adjusted in advance, allowing intervention before the temperature actually exceeds limits, significantly reducing temperature overshoot and improving temperature control accuracy. By comparing the actual temperature difference with the predicted temperature difference and correcting the prediction model, the system can adapt to factors such as battery aging and environmental changes, ensuring predictive accuracy and control effectiveness over long-term operation.

[0016] As a preferred embodiment of the technical solution of the present invention, the predictive temperature control step further includes: Obtain the Health Status (SOH) sent by the BMS; Using the SOH as a flow allocation weight, more cooling oil flow is allocated to battery rows with high aging levels to balance battery degradation throughout its life cycle.

[0017] Allocating more cooling oil flow to battery rows with higher aging levels can more effectively suppress the additional heat generated by increased internal resistance, slowing down their further aging rate. This differentiated heat dissipation strategy balances the performance degradation among battery rows with different aging levels, avoiding the bottleneck effect and thus extending the lifespan of the entire energy storage cluster.

[0018] As a preferred embodiment of the technical solution of the present invention, the predictive temperature control step further includes: When a thermal runaway warning signal is received from the BMS, all electric regulating valves are fully opened and the liquid cooling unit is instructed to reduce the oil supply temperature to the limit value.

[0019] A top-level safety protection mechanism has been established. When a thermal runaway warning signal is received from the BMS, the system immediately opens all valves and reduces the oil supply temperature to the limit value to provide emergency cooling to the entire battery cluster with maximum cooling capacity. This minimizes the spread of thermal runaway and buys valuable time for the fire suppression system to intervene, greatly improving the intrinsic safety level of the energy storage system.

[0020] As a preferred embodiment of the technical solution of this invention, a vertical thermal stratification prediction model is constructed to predict the predicted temperature of each row after a preset time period, specifically including: The multiple rows of batteries arranged longitudinally within the TANK body are numbered sequentially from bottom to top as row 1 to row N, where N≥2; Pre-calibrate the longitudinal position weighting coefficients of each row of batteries. And the reference temperature rise function f(SOC, C); Establish the weighting coefficients for predicted temperature, state of charge (SOC), charge / discharge rate (C), and longitudinal position for each row. The functional relationship between them is the vertical thermal stratification prediction model:

[0021] in, For the first Battery life after preset time The predicted temperature afterwards, For the first The current temperature of the battery. The reference temperature rise function for calibration; For the first The vertical position weighting coefficient of the row. Accompanying Number It increases with the increase of, and This characterizes the higher rate of temperature rise in the top battery row due to the cumulative effect of cooling oil temperature rise.

[0022] By introducing a longitudinal position weighting coefficient with increasing row numbers, the physical characteristics of the top battery row exhibiting a higher temperature rise rate due to the cumulative effect of cooling oil temperature rise are accurately characterized. Combined with a reference temperature rise function, this model can accurately predict the temperature changes of each row under different operating conditions, providing a solid theoretical foundation for predictive temperature control and ensuring the scientific validity of the pre-adjustment strategy.

[0023] As a preferred embodiment of the technical solution of the present invention, SOH is used as the flow distribution weight to allocate more cooling oil flow to batteries with high aging levels, specifically including: Get the health status of each battery row sent by BMS; Based on the health status of each battery row, and in conjunction with the preset aging compensation coefficient, the aging weight coefficient for that row is calculated: In the differentiated flow allocation strategy, the aging weight coefficient is multiplied by the basic flow adjustment amount calculated based on the temperature difference for that row, as the initial flow adjustment amount; The initial flow rate adjustment for each row is normalized and corrected to maintain a constant total cooling oil circulation flow rate. The corrected initial flow rate adjustment is then used as the final flow rate adjustment. Based on the flow-opening characteristic curves of each row of electric control valves, the final flow regulation is converted into the corresponding electric control valve opening regulation, and the opening regulation is executed in S3.

[0024] First, the base flow rate adjustment is calculated, then multiplied by the aging weighting coefficient to obtain the target flow rate. Finally, it is converted into valve opening using the flow-opening characteristic curve. This hierarchical calculation method makes the control logic clear and adaptable to the nonlinear characteristics of different valves. The introduction of a normalization correction step ensures that while distributing flow according to the state of equilibrium (SOH), the total circulating flow rate of the cooling oil remains constant or controllable.

[0025] Secondly, the present invention provides a multi-row independent flow control system for a cluster-level submerged energy storage system, including a TANK body, a thermal management controller, a liquid cooling unit for providing cooling oil and controlling the oil supply reference temperature, and multiple rows of independent oil supply pipelines and multiple rows of independent oil return pipelines controlled by the thermal management controller. The TANK body has multiple rows of batteries arranged longitudinally inside, each row of batteries being completely submerged in cooling oil. The side wall of the TANK body has oil inlets and oil outlets corresponding to the multiple rows of batteries. Multiple independent oil supply pipelines are connected to the oil inlets, and each independent oil supply pipeline is equipped with an electric regulating valve. Multiple independent oil return pipelines are connected to the oil return outlets, which are used to return the cooling oil to the liquid cooling unit. Multiple temperature sensors are respectively arranged in each row of batteries within the TANK body to collect the cell temperature of the corresponding row of batteries; The thermal management controller is communicatively connected to each temperature sensor, each electric regulating valve, and the liquid cooling unit, and is configured to perform the method described in the first aspect.

[0026] The system has a compact structure and can implement independent flow control for each row of batteries, effectively solving the long-standing problem of vertical thermal stratification in submerged energy storage systems.

[0027] As a preferred embodiment of the technical solution of the present invention, the thermal management controller includes: The temperature difference calculation module is used to calculate the temperature difference between the cell temperature of each row of batteries and the oil supply reference temperature of the liquid cooling unit. The differentiated flow distribution module is used to execute a differentiated flow distribution strategy based on the temperature difference. For rows where the temperature difference exceeds a first preset threshold, it generates an instruction to increase the opening of the corresponding electric regulating valve. For rows where the temperature difference is lower than a second preset threshold, it generates an instruction to decrease the opening of the corresponding electric regulating valve. The linkage adjustment module is used to automatically increase the flow priority of the top battery row and generate an instruction to increase its flow when the temperature difference of the top battery row exceeds the third preset threshold. At the same time, it generates an instruction to reduce the flow of the bottom battery row according to the weight ratio, so that the flow increase and decrease of all rows cancel each other out and keep the total circulation flow of cooling oil constant. The fault-tolerant module is used to switch to the adjacent row temperature reference mode or the average temperature reference mode for flow control when the temperature sensor fails, and to control the corresponding electric regulating valve to close or reduce the opening to a safe maintenance value when the pressure is abnormal or a leakage alarm is triggered. The predictive temperature control module is used to obtain the SOC and charge / discharge rate sent by the BMS, build a longitudinal thermal stratification prediction model to predict the predicted temperature of each row, pre-adjust the opening of the electric regulating valve before performing differentiated flow distribution, and correct the prediction model based on the comparison between the actual temperature difference and the predicted temperature difference after performing differentiated flow distribution. The SOH weighting module is used to obtain the SOH sent by the BMS, use the SOH as the flow allocation weight to calculate the aging weight coefficient, allocate more cooling oil flow to the battery row with high aging degree, and perform normalization correction to keep the total circulation flow constant. Then, it is converted into the electric regulating valve opening adjustment amount according to the flow-opening characteristic curve. The thermal runaway protection module is used to generate a control command to fully open all electric regulating valves and instruct the liquid cooling unit to reduce the oil supply temperature to the limit value when a thermal runaway early warning signal is received from the BMS.

[0028] As can be seen from the above technical solution, this application has the following advantages: By using a differentiated flow distribution strategy with independent oil supply pipelines and electric regulating valves for each row, combined with a linkage regulation mechanism, the temperature difference between the cell temperature and the oil supply reference temperature of each row is strictly controlled within a preset threshold range. When the temperature difference of the top battery row exceeds the standard, its flow priority is automatically increased and the flow rate is increased, while the flow rate of the bottom battery row is reduced according to the weight ratio, thus eliminating the problem of uneven temperature distribution caused by vertical temperature stratification.

[0029] By using the State of Health (SOH) sent by the BMS as the flow allocation weight, more cooling oil flow is allocated to battery rows with higher aging levels, effectively slowing down the degradation rate of aged battery rows. Simultaneously, the top-priority cooling strategy reduces the operating temperature of the top cells, mitigating the negative impact of high temperatures on cell chemical stability, achieving balanced aging of the entire battery cluster, and extending the service life of the energy storage system.

[0030] A longitudinal thermal stratification prediction model was constructed to predict the temperature rise trend of each row based on SOC and charge / discharge rate. The opening of the electric regulating valve was pre-adjusted before implementing differentiated flow allocation, achieving a leap from passive response to active intervention. By comparing the actual temperature difference with the predicted temperature difference and correcting the model, the thermal management system gained adaptive capabilities, improving the system's operational reliability and intelligence. Attached Figure Description

[0031] To more clearly illustrate the technical solution of this application, the accompanying drawings used in the description will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0032] Figure 1 This is a flowchart illustrating the method provided in an embodiment of the present invention.

[0033] Figure 2 A block diagram of a system provided in an embodiment of the present invention. Detailed Implementation

[0034] To make the purpose, features, and advantages of this application more apparent and understandable, specific embodiments and accompanying drawings will be used to clearly and completely describe the technical solution protected by this application. Obviously, the embodiments described below are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0035] Unless otherwise defined, all technical and scientific terms used in this application have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used in this application and in the specification of this invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.

[0036] This invention provides a multi-row independent flow control method for a cluster-level submerged energy storage system, applied to an energy storage system including a tank body, a thermal management controller, and a liquid cooling unit. The tank body has multiple rows of batteries arranged longitudinally, and each row is equipped with an independent oil supply pipeline and an electric regulating valve. The method is used to eliminate longitudinal temperature stratification caused by the cooling oil circulating and absorbing heat from bottom to top. Figure 1 As shown, it includes the following steps: S1. Real-time acquisition of the cell temperature of each row in the multi-row battery pack, and acquisition of the oil supply reference temperature of the liquid cooling unit; S2. Calculate the temperature difference between the cell temperature and the oil supply reference temperature for each row of batteries. S3. Execute a differentiated flow distribution strategy based on the temperature difference. For rows where the temperature difference exceeds a first preset threshold, increase the opening of the corresponding electric regulating valve; for rows where the temperature difference is lower than a second preset threshold, decrease the opening of the corresponding electric regulating valve. In S3, the differentiated flow allocation strategy includes a linkage adjustment mechanism: when the temperature difference of the top battery row in the vertical direction exceeds the third preset threshold, the flow priority of the top battery row is automatically increased and its flow is increased, while the flow allocation of the bottom battery row is reduced accordingly according to the weight ratio, so that the flow increase and decrease of all rows cancel each other out, thereby keeping the total circulating flow of cooling oil constant.

[0037] In some embodiments, fault-tolerant steps are also included: When the temperature sensor in a certain row fails, it automatically switches to the temperature reference mode of the adjacent row or takes the average temperature of the remaining normal rows as the reference value for flow control. When a pressure sensor on a certain oil supply or return line detects an abnormal pressure or receives a leak alarm signal from a leak detection device, the corresponding electric regulating valve in that line is controlled to close or its opening is reduced to a safe maintenance value.

[0038] In some embodiments, the step of determining that the temperature sensor has malfunctioned includes: The thermal management controller monitors the signal status and value rationality of each temperature sensor in real time, and determines that the temperature sensor in that row has malfunctioned when any of the following conditions are detected: The sensor signal is interrupted or exceeds the preset physical measurement range; The rate of change of the cell temperature in this line exceeded the normal rate of change threshold within a preset time period. The temperature of this row of cells deviates from the average temperature of other rows of cells by more than a preset deviation threshold.

[0039] In some embodiments, a predictive temperature control step in conjunction with the battery management system (BMS) is also included: Obtain the State of Charge (SOC) and charge / discharge rate sent by the BMS; construct a longitudinal thermal stratification prediction model, and predict the temperature of each row after a preset time period based on the SOC, charge / discharge rate, and the longitudinal height position of each row within the tank; adjust the opening of the corresponding row's electric regulating valve to the predicted opening value according to the obtained predicted temperature of each row; the predicted opening value is a preset target opening value, the purpose of which is to avoid temperature fluctuations. Compare the actual temperature difference with the predicted temperature difference calculated based on the predicted temperature, and correct the longitudinal thermal stratification prediction model according to the comparison results.

[0040] In some embodiments, the predictive temperature control step further includes: Obtain the Health Status (SOH) sent by the BMS; use the SOH as a flow allocation weight to allocate more cooling oil flow to battery rows with high aging levels in order to balance battery degradation throughout the entire life cycle.

[0041] In some embodiments, the predictive temperature control step further includes: When a thermal runaway warning signal is received from the BMS, all electric regulating valves are fully opened and the liquid cooling unit is instructed to reduce the oil supply temperature to the limit value.

[0042] In some embodiments, a vertical thermal stratification prediction model is constructed to predict the predicted temperature of each row after a preset time period, specifically including: The multiple rows of batteries arranged longitudinally within the TANK body are numbered sequentially from bottom to top as row 1 to row N, where N≥2; Pre-calibrate the longitudinal position weighting coefficients of each row of batteries. And the reference temperature rise function f(SOC, C); Establish the weighting coefficients for predicted temperature, state of charge (SOC), charge / discharge rate (C), and longitudinal position for each row. The functional relationship between them is the vertical thermal stratification prediction model:

[0043] in, For the first Battery life after preset time The predicted temperature afterwards For the first The current temperature of the battery. This is the baseline temperature rise function, whose value is positively correlated with the current SOC and charge / discharge rate C; For the first The vertical position weighting coefficient of the row. Accompanying Number It increases with the increase of, and This characterizes the higher rate of temperature rise in the top battery row due to the cumulative effect of cooling oil temperature rise.

[0044] The reference temperature rise function Pre-calibrate using the following methods: During the commissioning phase of the energy storage system, charge and discharge tests were conducted with different SOC values ​​and different charge and discharge rates C, and the steady-state temperature rise rate of each row was recorded. Establish a mapping table or fitting formula between SOC and charge / discharge rate C and reference temperature rise rate by curve fitting or interpolation methods; The mapping table or fitting formula is stored in the thermal management controller for use during real-time prediction.

[0045] The vertical position weighting coefficient Determined in the following ways: Temperature sensors are placed at each row of batteries within the tank to collect the steady-state temperature rise rate of each row under standard charge and discharge conditions; using the temperature rise rate of the bottom row as a reference value, the temperature rise rate of the first row is calculated. The ratio of the temperature rise rate of row 1 to the temperature rise rate of row 2 is used as the ratio of the temperature rise rate of row 3 to row 4. Vertical position weighting coefficient of the row ; in, The value is greater than 1, and the top row's The maximum value is taken to reflect the cumulative temperature rise effect caused by the cooling oil absorbing heat from bottom to top.

[0046] In some embodiments, based on the predicted temperature of each row, the opening degree of the corresponding row's electric regulating valve is pre-adjusted to the predicted opening value, specifically including: Set target temperature difference range [ , ],in The lower limit threshold of temperature difference. This is the upper limit threshold for temperature difference; Calculate and predict temperature difference ,in The reference temperature for oil supply to the liquid cooling unit; Get the Current opening of the electric regulating valve ; Based on predicted temperature difference The relationship with the target temperature difference range determines the first Predicted opening value of electric control valve : like > If this is the case, it is determined that the bank will face overheating risks in the future, and a setting is made. = + ,in This is the preset opening increment; like < If this is the case, it is determined that the bank will face a risk of overheating in the future, and a setting is made. = - ,in Reduce the preset opening size; like ≤ ≤ If so, the temperature in that row is expected to be within the normal range and should be maintained. = ; Before executing S3, the opening degree of the electric regulating valves in each row is pre-adjusted to the predicted opening degree value. .

[0047] After executing S3, the actual temperature difference is compared with the predicted temperature difference, and the longitudinal thermal stratification prediction model is corrected based on the comparison results, specifically including: After S3 is completed and the system reaches steady state, the actual cell temperature of each battery row is collected. Calculate the actual temperature difference ; Obtain the predicted temperature difference before performing step S3. ; Calculate the first Temperature difference prediction error ; when When the error exceeds the preset error threshold, model correction is triggered.

[0048] In some embodiments, the model correction includes at least one of the following: Method 1: Adjusting the weighting coefficient of vertical position , will the The ratio of the actual temperature rise rate to the predicted temperature rise rate is used as a correction factor to update the data. = × (Actual temperature rise rate / Predicted temperature rise rate); Method 2: Modify the reference temperature rise function The SOC and charge / discharge rate C under this operating condition are used as new sample points to refit or interpolate and update the mapping table. Method 3: Use the recursive least squares algorithm to update the parameters of the prediction model online, so that the predicted temperature difference gradually approaches the actual temperature difference.

[0049] In some embodiments, an adaptive adjustment step for predictive temperature control is also included: Set a frequency threshold for model correction, allowing for a maximum of L corrections within a single charge / discharge cycle; After multiple consecutive corrections If the error threshold is still exceeded, it is determined that the current prediction model does not match the actual aging state of the battery, and a SOH recalibration request is triggered. In response to the SOH recalibration request, the updated SOH value from the BMS is obtained, and the longitudinal position weighting coefficient is reset based on the updated SOH value. .

[0050] In some embodiments, SOH is used as a flow allocation weight to allocate more cooling oil flow to battery rows with higher aging levels, specifically including: Get the health status of each battery row sent by BMS. ,in For the first The ratio of the current capacity to the factory rated capacity of each battery row; based on the battery row... The aging weight coefficient for this row is calculated by combining the preset aging compensation coefficient. ,in, The preset aging compensation coefficient ranges from 0.2 to 1.0. The larger the value, the greater the compensation for aging batteries; In the differentiated traffic allocation strategy, the aging weight coefficient is... Multiply by the baseline flow rate adjustment calculated based on the temperature difference in this row to obtain the initial flow rate adjustment. ,in, The first one determined based on temperature difference The initial flow rate adjustment for each row is determined; the initial flow rate adjustment for each row is then normalized to maintain a constant total cooling oil circulation flow rate, and the corrected initial flow rate adjustment is used as the final flow rate adjustment. ; Normalize the initial flow adjustment amounts for each row, including: after using SOH for flow weighting, calculate the total weighted flow adjustment amount for all rows. ; like If the value is not equal to zero, then the flow rate adjustment for each row is normalized to maintain a constant total circulation flow rate.

[0051] Where N is the total number of battery rows. For the corrected first The final flow adjustment amount.

[0052] Based on the flow-opening characteristic curve of each row of electric regulating valves, the final flow regulation amount is converted into the corresponding electric regulating valve opening regulation amount, and in S3, based on the preset predicted opening value, the opening regulation amount is executed, that is, the final opening = predicted opening value ± opening regulation amount.

[0053] The flow-opening characteristic curve is pre-calibrated in the following manner: During the commissioning phase of the energy storage system, calibration tests are performed on the electric regulating valves of each row. The opening degree of the electric regulating valve is changed by a preset step size, and the corresponding cooling oil flow rate is measured and the opening degree-flow rate data pairs are recorded. The recorded data is subjected to curve fitting or interpolation to generate the flow rate-opening degree characteristic curve or lookup table of the electric regulating valve. The characteristic curve or lookup table obtained from the calibration is stored in the thermal management controller for use during real-time conversion.

[0054] The preset aging compensation coefficient Dynamic adjustments will be made according to the following rules: When the minimum SOH value of all rows is lower than the first threshold, increase Values ​​are used to increase the aging compensation effect; When the minimum SOH value of all rows is higher than the second threshold, decrease This reduces the need for aging compensation.

[0055] In some embodiments, a closed-loop feedback step for SOH balancing effect is also included: Regularly obtain battery data from each line. Update value; Calculate each row Standard deviation It is used to characterize the uneven aging degree of the entire battery cluster; When the standard deviation exceeds a preset imbalance threshold, the current aging compensation strategy is deemed insufficient, triggering at least one of the following operations: Increase the aging compensation coefficient ; Extend the execution time window of the SOH weighted strategy; Send a leveling aging alarm signal to the BMS or operation and maintenance system.

[0056] like Figure 2 As shown, this embodiment of the invention also provides a multi-row independent flow control system for a cluster-level submerged energy storage system, including a TANK body, a thermal management controller, a liquid-cooled unit for providing cooling oil and controlling the oil supply reference temperature, and multiple rows of independent oil supply pipelines and multiple rows of independent oil return pipelines controlled by the thermal management controller. The TANK body has multiple rows of batteries arranged longitudinally inside, each row of batteries being completely submerged in cooling oil. The side wall of the TANK body has oil inlets and oil outlets corresponding to the multiple rows of batteries. Multiple independent oil supply pipelines are connected to the oil inlets, and each independent oil supply pipeline is equipped with an electric regulating valve. Multiple independent oil return pipelines are connected to the oil return outlets, which are used to return the cooling oil to the liquid cooling unit. Multiple temperature sensors are respectively arranged in each row of batteries within the TANK body to collect the cell temperature of the corresponding row of batteries; The thermal management controller is communicatively connected to each temperature sensor, each electric regulating valve, and the liquid cooling unit, and is configured to perform the methods described in the above embodiments.

[0057] In some embodiments, the thermal management controller includes: The temperature difference calculation module is used to calculate the temperature difference between the cell temperature of each row of batteries and the oil supply reference temperature of the liquid cooling unit. The differentiated flow distribution module is used to execute a differentiated flow distribution strategy based on the temperature difference. For rows where the temperature difference exceeds a first preset threshold, it generates an instruction to increase the opening of the corresponding electric regulating valve. For rows where the temperature difference is lower than a second preset threshold, it generates an instruction to decrease the opening of the corresponding electric regulating valve. The linkage adjustment module is used to automatically increase the flow priority of the top battery row and generate an instruction to increase its flow when the temperature difference of the top battery row exceeds the third preset threshold. At the same time, it generates an instruction to reduce the flow of the bottom battery row according to the weight ratio, so that the flow increase and decrease of all rows cancel each other out and keep the total circulation flow of cooling oil constant. The fault-tolerant module is used to switch to the adjacent row temperature reference mode or the average temperature reference mode for flow control when the temperature sensor fails, and to control the corresponding electric regulating valve to close or reduce the opening to a safe maintenance value when the pressure is abnormal or a leakage alarm is triggered. The predictive temperature control module is used to obtain the SOC and charge / discharge rate sent by the BMS, build a longitudinal thermal stratification prediction model to predict the predicted temperature of each row, pre-adjust the opening of the electric regulating valve before performing differentiated flow distribution, and correct the prediction model based on the comparison between the actual temperature difference and the predicted temperature difference after performing differentiated flow distribution. The SOH weighting module is used to obtain the SOH sent by the BMS, use the SOH as the flow allocation weight to calculate the aging weight coefficient, allocate more cooling oil flow to the battery row with high aging degree, and perform normalization correction to keep the total circulation flow constant. Then, it is converted into the electric regulating valve opening adjustment amount according to the flow-opening characteristic curve. The thermal runaway protection module is used to generate a control command to fully open all electric regulating valves and instruct the liquid cooling unit to reduce the oil supply temperature to the limit value when a thermal runaway early warning signal is received from the BMS.

[0058] Those skilled in the art will clearly understand that the techniques in the embodiments of the present invention can be implemented using software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solutions in the embodiments of the present invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium such as a USB flash drive, mobile hard drive, read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk, or other media capable of storing program code. It includes several instructions to cause a computer terminal (which may be a personal computer, server, or a second terminal, network terminal, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention.

[0059] In the embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0060] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0061] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0062] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for multi-row independent flow control in a cluster-level submerged energy storage system, characterized in that, This method is applied to an energy storage system comprising a tank body, a thermal management controller, and a liquid cooling unit. The tank body has multiple rows of batteries arranged longitudinally inside, and each row is equipped with an independent oil supply line and an electric regulating valve. The method aims to eliminate longitudinal temperature stratification caused by the cooling oil absorbing heat from bottom to top, and includes the following steps: S1. Real-time acquisition of cell temperature in each row of multiple battery rows, and acquisition of oil supply reference temperature of liquid cooling unit; S2. Calculate the temperature difference between the cell temperature and the oil supply reference temperature for each row of batteries. S3. Execute a differentiated flow distribution strategy based on the temperature difference. For rows where the temperature difference exceeds a first preset threshold, increase the opening of the corresponding electric regulating valve; for rows where the temperature difference is lower than a second preset threshold, decrease the opening of the corresponding electric regulating valve. In S3, the differentiated flow allocation strategy includes a linkage adjustment mechanism: when the temperature difference of the top battery row in the vertical direction exceeds the third preset threshold, the flow priority of the top battery row is automatically increased and its flow is increased, while the flow allocation of the bottom battery row is reduced accordingly according to the weight ratio, so that the flow increase and decrease of all rows cancel each other out and keep the total circulating flow of cooling oil constant.

2. The multi-row independent flow control method for a cluster-level submerged energy storage system according to claim 1, characterized in that, It also includes fault-tolerant steps: When the temperature sensor in a certain row fails, it automatically switches to the temperature reference mode of the adjacent row or takes the average temperature of the remaining normal rows as the reference value for flow control. When an abnormality is detected in the oil supply or return pressure of a certain row, or when a cooling oil leak alarm is detected, the corresponding electric regulating valve of that row is controlled to close or its opening is reduced to a safe maintenance value.

3. The multi-row independent flow control method for a cluster-level submerged energy storage system according to claim 2, characterized in that, The steps to determine if a temperature sensor is malfunctioning include: The thermal management controller monitors the signal status and value rationality of each temperature sensor in real time, and determines that the temperature sensor in that row has malfunctioned when any of the following conditions are detected: The sensor signal is interrupted or exceeds the preset physical measurement range; The rate of change of the cell temperature in this line exceeded the normal rate of change threshold within a preset time period. The temperature of this row of cells deviates from the average temperature of other rows of cells by more than a preset deviation threshold.

4. The multi-row independent flow control method for a cluster-level submerged energy storage system according to claim 1, characterized in that, It also includes predictive temperature control steps that work in conjunction with the battery management system (BMS): Obtain the State of Charge (SOC) and charge / discharge rate sent by the BMS; A longitudinal thermal stratification prediction model is constructed, which predicts the temperature of each row after a preset time based on the SOC, charge / discharge rate and the longitudinal height position of each row in the TANK body. Based on the predicted temperature of each row, the opening of the corresponding row's electric regulating valve is pre-adjusted to the predicted opening value; The actual temperature difference is compared with the predicted temperature difference calculated based on the predicted temperature, and the longitudinal thermal stratification prediction model is corrected according to the comparison results.

5. The multi-row independent flow control method for a cluster-level submerged energy storage system according to claim 4, characterized in that, The predictive temperature control step further includes: Obtain the Health Status (SOH) sent by the BMS; Using the SOH as a flow allocation weight, more cooling oil flow is allocated to battery rows with high aging levels to balance battery degradation throughout its life cycle.

6. The multi-row independent flow control method for a cluster-level submerged energy storage system according to claim 4, characterized in that, The predictive temperature control step further includes: When a thermal runaway warning signal is received from the BMS, all electric regulating valves are fully opened and the liquid cooling unit is instructed to reduce the oil supply temperature to the limit value.

7. The multi-row independent flow control method for a cluster-level submerged energy storage system according to claim 4, characterized in that, Construct a vertical thermal stratification prediction model to predict the temperature of each row after a preset time period, specifically including: The multiple rows of batteries arranged longitudinally within the TANK body are numbered sequentially from bottom to top as row 1 to row N, where N≥2; Pre-calibrate the longitudinal position weighting coefficients of each row of batteries. And the reference temperature rise function f(SOC, C); Establish the weighting coefficients for predicted temperature, state of charge (SOC), charge / discharge rate (C), and longitudinal position for each row. The functional relationship between them is the vertical thermal stratification prediction model: in, For the first Battery life after preset time The predicted temperature afterwards For the first The current temperature of the battery. The reference temperature rise function for calibration; For the first The vertical position weighting coefficient of the row. Accompanying Number It increases with the increase of, and This characterizes the higher rate of temperature rise in the top battery row due to the cumulative effect of cooling oil temperature rise.

8. The multi-row independent flow control method for a cluster-level submerged energy storage system according to claim 5, characterized in that, Using SOH as the flow allocation weight, more cooling oil flow is allocated to battery rows with higher aging levels, specifically including: Get the health status of each battery row sent by BMS; Based on the health status of each battery row, and in conjunction with the preset aging compensation coefficient, the aging weight coefficient for that row is calculated: In the differentiated flow allocation strategy, the aging weight coefficient is multiplied by the basic flow adjustment amount calculated based on the temperature difference for that row, as the initial flow adjustment amount; The initial flow rate adjustment for each row is normalized and corrected to maintain a constant total cooling oil circulation flow rate. The corrected initial flow rate adjustment is then used as the final flow rate adjustment. Based on the flow-opening characteristic curves of each row of electric control valves, the final flow regulation is converted into the corresponding electric control valve opening regulation, and the opening regulation of this adjustment is executed in S3.

9. A multi-row independent flow control system for a cluster-level submerged energy storage system, characterized in that, It includes a TANK body, a thermal management controller, a liquid cooling unit for supplying cooling oil and controlling the oil supply reference temperature, and multiple independent oil supply lines and multiple independent oil return lines regulated by the thermal management controller; The TANK body has multiple rows of batteries arranged longitudinally inside, each row of batteries being completely submerged in cooling oil. The side wall of the TANK body has oil inlets and oil outlets corresponding to the multiple rows of batteries. Multiple independent oil supply pipelines are connected to the oil inlets, and each independent oil supply pipeline is equipped with an electric regulating valve. Multiple independent oil return pipelines are connected to the oil return outlets, which are used to return the cooling oil to the liquid cooling unit. Multiple temperature sensors are respectively arranged in each row of batteries within the TANK body to collect the cell temperature of the corresponding row of batteries; The thermal management controller is communicatively connected to each temperature sensor, each electric regulating valve and the liquid cooling unit, and is configured to perform the method of any one of claims 1 to 8.

10. The multi-row independent flow control system for a cluster-level submerged energy storage system according to claim 9, characterized in that, The thermal management controller includes: The temperature difference calculation module is used to calculate the temperature difference between the cell temperature of each row of batteries and the oil supply reference temperature of the liquid cooling unit. The differentiated flow distribution module is used to execute a differentiated flow distribution strategy based on the temperature difference. For rows where the temperature difference exceeds a first preset threshold, it generates an instruction to increase the opening of the corresponding electric regulating valve. For rows where the temperature difference is lower than a second preset threshold, it generates an instruction to decrease the opening of the corresponding electric regulating valve. The linkage adjustment module is used to automatically increase the flow priority of the top battery row and generate an instruction to increase its flow when the temperature difference of the top battery row exceeds the third preset threshold. At the same time, it generates an instruction to reduce the flow of the bottom battery row according to the weight ratio, so that the flow increase and decrease of all rows cancel each other out and keep the total circulation flow of cooling oil constant. The fault-tolerant module is used to switch to the adjacent row temperature reference mode or the average temperature reference mode for flow control when the temperature sensor fails, and to control the corresponding electric regulating valve to close or reduce the opening to a safe maintenance value when the pressure is abnormal or a leakage alarm is triggered. The predictive temperature control module is used to obtain the SOC and charge / discharge rate sent by the BMS, build a longitudinal thermal stratification prediction model to predict the predicted temperature of each row, pre-adjust the opening of the electric regulating valve before performing differentiated flow distribution, and correct the prediction model based on the comparison between the actual temperature difference and the predicted temperature difference after performing differentiated flow distribution. The SOH weighting module is used to obtain the SOH sent by the BMS, use the SOH as the flow allocation weight to calculate the aging weight coefficient, allocate more cooling oil flow to the battery row with high aging degree, and perform normalization correction to keep the total circulation flow constant. Then, it is converted into the electric regulating valve opening adjustment amount according to the flow-opening characteristic curve. The thermal runaway protection module is used to generate a control command to fully open all electric regulating valves and instruct the liquid cooling unit to reduce the oil supply temperature to the limit value when a thermal runaway early warning signal is received from the BMS.

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