Intelligent control method and device for flow rate of cooling liquid

Abstract

The application discloses a kind of cooling liquid flow rate intelligent control method and device, comprising: receiving multiple first battery parameter sets sent by monitoring module;According to multiple first battery parameter sets, the first heat mapping relationship of pre-set and the first flow rate mapping relationship of pre-set determine at least one battery unit in abnormal heating state and at least one target cooling liquid flow rate corresponding thereto;Determine at least one target cooling liquid flow rate corresponding at least one valve opening;According to at least one valve opening, at least one control signal is generated;And, at least one control signal is sent to at least one cooling liquid inlet and outlet valve corresponding to at least one battery unit;The absolute value of the difference between the temperature of any one of the multiple battery units and the pre-set temperature value is less than the pre-set threshold value.The application can realize the balance and optimization of battery temperature, improve the accuracy of temperature control, and improve the energy storage efficiency.

Description

Technical Field

[0001] This application relates to the field of cooling control technology for energy storage batteries, and in particular to a method and device for intelligent control of coolant flow rate. Background Technology

[0002] The performance and lifespan of energy storage batteries are closely related to temperature. Within a suitable temperature range, batteries can maintain high charge-discharge efficiency, good cycle stability, and a long service life. When the temperature is too high or too low, the chemical reaction rate of the battery will change, which may lead to problems such as decreased battery capacity, increased internal resistance, and reduced charge-discharge efficiency.

[0003] Existing methods for controlling coolant flow rate in energy storage systems often employ fixed flow rates or rely on simple temperature thresholds, failing to consider the actual heat generation of the battery under different operating conditions. This makes precise flow rate adjustment based on real-time battery operating parameters impossible, potentially leading to insufficient or excessive heat dissipation, impacting battery performance and system efficiency. Furthermore, traditional control methods struggle to adjust coolant flow rate in real-time to adapt to complex operating conditions, failing to achieve optimal heat dissipation and battery temperature control in diverse scenarios. Summary of the Invention

[0004] This application provides a method and apparatus for intelligent control of coolant flow rate. By acquiring parameters such as battery voltage, current, temperature, internal resistance, and battery health status, and utilizing the mapping relationship between these parameters and heat dissipation, battery cells in an abnormal heating state are identified. Based on the coupling relationship between these parameters and coolant flow rate, the coolant flow rate of the abnormally heating battery cells is dynamically adjusted. Simultaneously, by setting independent coolant flow control valves, different coolant flow rates can be applied to corresponding battery areas, achieving temperature balance and optimization of the battery, improving system flexibility and economy, reducing energy loss, and enhancing thermal management efficiency.

[0005] In a first aspect, this application provides a method for intelligent control of coolant flow rate, applied to a controller of an energy storage system. The energy storage system further includes a monitoring module, an energy storage battery pack, and multiple coolant inlet and outlet valves. The monitoring module is connected to the energy storage battery pack, which includes multiple battery cells. The multiple battery cells are correspondingly connected to the multiple coolant inlet and outlet valves. The controller is connected to the monitoring module and the multiple coolant inlet and outlet valves respectively. The method includes:

[0006] The system receives multiple sets of first battery parameters sent by the monitoring module. Each set of first battery parameters includes multiple battery operating parameters of the corresponding battery cell within the target time period.

[0007] Based on the plurality of first battery parameter sets, the preset first heat mapping relationship and the preset first flow rate mapping relationship, at least one battery cell in the plurality of battery cells that is in an abnormal heating state and its corresponding at least one target coolant flow rate are determined. The first heat mapping relationship is used to characterize the correspondence between the heat generated by the battery cell in different time periods and the plurality of battery operating parameters. The first flow rate mapping relationship is used to characterize the correspondence between the coolant flow rate of the battery cell at different time points and the plurality of battery operating parameters.

[0008] Determine at least one valve opening corresponding to the at least one target coolant flow rate, wherein the coolant flow rate is associated with the valve opening;

[0009] At least one control signal is generated based on the opening degree of the at least one valve; and the at least one control signal is sent to at least one of the coolant inlet and outlet valves corresponding to the at least one battery cell;

[0010] The absolute value of the difference between the temperature of any one of the plurality of battery cells and a preset temperature value is less than a preset threshold.

[0011] Secondly, embodiments of this application provide a coolant flow rate intelligent control device applied to a controller of an energy storage system. The energy storage system further includes a monitoring module, an energy storage battery pack, and multiple coolant inlet and outlet valves. The monitoring module is connected to the energy storage battery pack, which includes multiple battery cells. The multiple battery cells are correspondingly connected to the multiple coolant inlet and outlet valves. The controller is connected to the monitoring module and the multiple coolant inlet and outlet valves respectively. The device includes:

[0012] The receiving unit is used to receive multiple first battery parameter sets sent by the monitoring module. Each first battery parameter set includes multiple battery operating parameters of the corresponding battery cell within the target time period.

[0013] The first determining unit is configured to determine at least one battery cell in the plurality of battery cells that is in an abnormal heating state and its corresponding at least one target coolant flow rate based on the plurality of first battery parameter sets, a preset first heat mapping relationship and a preset first flow rate mapping relationship. The first heat mapping relationship is used to characterize the correspondence between the heat generated by the battery cell in different time periods and the plurality of battery operating parameters. The first flow rate mapping relationship is used to characterize the correspondence between the coolant flow rate of the battery cell at different time points and the plurality of battery operating parameters.

[0014] The second determining unit is used to determine at least one valve opening corresponding to the at least one target coolant flow rate, wherein the coolant flow rate is associated with the valve opening.

[0015] A transmitting unit is configured to generate at least one control signal based on the opening degree of the at least one valve; and to transmit the at least one control signal to at least one coolant inlet / outlet valve corresponding to the at least one battery cell;

[0016] The detection unit is used to detect that the absolute value of the difference between the temperature of any one of the plurality of battery cells and a preset temperature value is less than a preset threshold.

[0017] Thirdly, embodiments of this application provide an electronic device including a processor, a memory, and one or more programs, the one or more programs being stored in the memory and configured to be executed by the processor, the programs including instructions for performing the steps in the first aspect of embodiments of this application.

[0018] Fourthly, embodiments of this application provide a computer-readable storage medium having a computer program / instructions stored thereon, which is executed by a processor to implement the steps of the method described in the first aspect above.

[0019] As can be seen, in this embodiment, the controller receives multiple first battery parameter sets sent by the monitoring module. Each first battery parameter set includes multiple battery operating parameters of the corresponding battery cell within a target time period. Based on the multiple first battery parameter sets, a preset first heat mapping relationship, and a preset first flow rate mapping relationship, the controller determines at least one battery cell in an abnormal heating state and its corresponding at least one target coolant flow rate. It determines at least one valve opening corresponding to the at least one target coolant flow rate, with the coolant flow rate associated with the valve opening. It generates at least one control signal based on the at least one valve opening. It also sends at least one control signal to at least one coolant inlet / outlet valve corresponding to the at least one battery cell. The controller detects that the absolute value of the difference between the temperature of any one battery cell and a preset temperature value is less than a preset threshold. Thus, compared to existing coolant flow rate control schemes that use a fixed flow rate or are based on a simple temperature threshold, this application can dynamically adjust the coolant flow rate of the corresponding battery region according to the differences in different battery parameters, improving temperature uniformity between batteries, reducing energy loss, improving system economy, and extending system lifespan and safety. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the 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.

[0021] Figure 1 This is a system architecture diagram of an energy storage system provided in an embodiment of this application;

[0022] Figure 2 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application;

[0023] Figure 3 This is a structural block diagram of an energy storage system provided in an embodiment of this application;

[0024] Figure 4 This is an overall flowchart of a method for intelligent control of coolant flow rate provided in an embodiment of this application;

[0025] Figure 5 This is a flowchart illustrating the steps of an intelligent coolant flow rate control method provided in an embodiment of this application.

[0026] Figure 6 This is a flowchart of another intelligent coolant flow rate control method provided in the embodiments of this application;

[0027] Figure 7 This is an application scenario diagram of an intelligent coolant flow rate control method provided in an embodiment of this application;

[0028] Figure 8 This is a schematic diagram of the functional modules of a coolant flow rate intelligent control device provided in an embodiment of this application. Detailed Implementation

[0029] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0030] The terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0031] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0032] In the embodiments of this application, "and / or" describes the relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent the following three situations: A exists alone; A and B exist simultaneously; B exists alone. Among them, A and B can be singular or plural.

[0033] In this embodiment, the symbol " / " can indicate that the preceding and following objects are in an "or" relationship. Alternatively, the symbol " / " can also represent a division sign, i.e., performing a division operation. For example, A / B can mean A divided by B.

[0034] In the embodiments of this application, "at least one item" or its similar expression refers to any combination of these items, including any combination of a single item or a plurality of items. "One or more" means one or more, while "multiple" means two or more. For example, "at least one item" of a, b, or c can represent the following seven cases: a, b, c; a and b; a and c; b and c; a, b, and c. Each of a, b, and c can be an element or a set containing one or more elements.

[0035] In the embodiments of this application, "equal to" can be used with "greater than" and is applicable to technical solutions used when "greater than" is used; it can also be used with "less than" and is applicable to technical solutions used when "less than" is used. When "equal to" is used with "greater than", it is not used with "less than"; when "equal to" is used with "less than", it is not used with "greater than".

[0036] Existing intelligent coolant flow rate control solutions all rely on fixed flow rates or simple temperature feedback control, which cannot dynamically adjust according to the actual operating state of the battery. This results in inaccurate battery temperature control, affecting battery performance and lifespan.

[0037] To address the aforementioned issues, this application provides a method and apparatus for intelligent control of coolant flow rate. The embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0038] Please see Figure 1 , Figure 1 This is a system architecture diagram of an energy storage system provided in an embodiment of this application, such as... Figure 1 As shown in the diagram, the system architecture of this energy storage system includes a controller, a monitoring module, an energy storage battery pack, and multiple coolant inlet and outlet valves.

[0039] The energy storage battery pack is the core of the entire system, consisting of multiple battery cells (such as battery cell 1, battery cell 2 to battery cell n) used to store and release electrical energy. In actual operation, the battery cells generate heat during charging and discharging, and the heat generation is affected by various factors such as voltage, current, temperature, and internal resistance.

[0040] The monitoring module is connected to each battery cell in the energy storage battery pack via a line to collect multiple operating parameters of each battery cell in real time during the target period, such as voltage, current, temperature, SOC, SOH, etc. The monitoring module also processes the collected battery operating parameters and sends them to the controller to provide data support for subsequent analysis and control.

[0041] The coolant inlet and outlet valves include multiple valves, with each battery cell corresponding to one coolant inlet and outlet valve (e.g., coolant inlet and outlet valve 1, coolant inlet and outlet valve 2 to coolant inlet and outlet valve n). Coolant flows into and out of the coolant pipes or containers connected to the battery cell through these valves, carrying away the heat generated by the battery and regulating its temperature. Furthermore, the coolant inlet and outlet valves are connected to a controller, and their opening degree can be adjusted by the controller to regulate the coolant flow rate.

[0042] The controller is connected to both the monitoring module and the coolant inlet and outlet valves. On one hand, the controller receives multiple battery parameter sets from the monitoring module. On the other hand, based on the received battery parameter sets and a preset first heat mapping relationship and first flow rate mapping relationship, the controller analyzes and determines the battery cells in an abnormal heating state and their corresponding target coolant flow rates. It then determines the opening degree of the corresponding valves, generates control signals, and sends them to the corresponding coolant inlet and outlet valves, thus achieving intelligent control of the coolant flow rate.

[0043] As can be seen, in this embodiment, the entire energy storage system can monitor the status of battery cells in real time through the connection and information exchange between its various parts. Furthermore, it can adjust the coolant flow rate of the corresponding battery area individually to address the differences in different battery parameters. This helps to improve the temperature uniformity between batteries, ensure that the energy storage battery pack operates within a suitable temperature range, and improve the performance and lifespan of the energy storage battery.

[0044] Please see Figure 2 , Figure 2 This is a structural block diagram of an electronic device provided in an embodiment of this application, used for performing... Figure 1 Energy storage systems, such as Figure 2As shown, the electronic device 20 may include one or more of the following components: a memory 23, a processor 21, a communication bus 30, a communication interface 22, and one or more programs 231. The one or more programs 231 are stored in the memory 23 and configured to be executed by the processor 21. The one or more programs 231 include instructions for performing any step in any of the methods described in the following embodiments. Specifically, the processor 21 is used to perform any step in the methods described below, and when performing data transmission such as sending, it may selectively invoke the communication interface 22 to complete the corresponding operation. The electronic device 20 may be a mobile terminal, a tablet computer, a laptop computer, or a wearable smart device.

[0045] It is understood that the electronic device 20 may include more or fewer structural elements than those shown in the above block diagram, such as a power module, physical buttons, a Wi-Fi module, a speaker, a Bluetooth module, sensors, etc., without limitation.

[0046] Please see Figure 3 , Figure 3 This is a structural block diagram of an energy storage system provided in an embodiment of this application, such as... Figure 3 As shown, the energy storage system 300 includes a monitoring module 310, an energy storage battery pack 320, coolant inlet and outlet valves 330, and a controller 340.

[0047] The energy storage battery pack 320 includes battery cells 321, which are the core energy storage components of the energy storage system. Different types of battery cells vary in terms of energy density, charge / discharge efficiency, and cycle life.

[0048] The monitoring module 310 includes a sensor 311, a processing module 312, and a communication module 313. The sensor 311 acquires the battery operating parameters of the battery cells 321 in the energy storage battery pack 320. Specifically, the temperature sensor accurately measures the real-time temperature of the battery cells 321; the voltage and current sensors monitor the electrical parameters during the battery charging and discharging process in real time. The processing module 312 performs pre-processing on the large amount of raw data from the sensor 311, for example, using digital signal processing technology to remove noise and interference from the data, improving the accuracy and reliability of the data. Simultaneously, advanced algorithms are used for feature extraction and analysis of the data, such as using Kalman filtering to process the battery voltage and current data, enabling a more accurate estimation of the battery's SOC. The communication module 313 transmits data with the controller 340. Common communication methods include wired communication (such as CAN bus, RS-485, etc.) and wireless communication (such as Bluetooth, Wi-Fi, etc.).

[0049] The coolant inlet and outlet valves 330 include a coolant inlet valve 331 and a coolant outlet valve 332, which together control the circulation of coolant. Coolant plays a crucial role in heat dissipation in the energy storage system 300, and is typically water-based or oil-based. The coolant inlet valve 331 controls the flow of low-temperature coolant into the cooling channel or container closely connected to the battery unit 321, while the coolant outlet valve 332 controls the flow of high-temperature coolant after heat absorption. Valve control methods include electric control and hydraulic control. Electric valves adjust their opening degree through electrical signals sent by the controller 340, achieving precise heat dissipation for the battery unit 321.

[0050] The controller 340 is used to receive battery operating parameters from the monitoring module 310, and to determine the battery cell 321 in an abnormal heating state based on the battery operating parameters and the preset first heat mapping relationship and first flow rate mapping relationship, and to calculate the corresponding target coolant flow rate; and to generate a control signal and send it to the coolant inlet and outlet valves 330 based on the correlation between coolant flow rate and valve opening, so as to realize intelligent adjustment of coolant flow rate, ensure that the temperature of battery cell 321 is maintained within a reasonable range, and ensure the safe and efficient operation of energy storage system 300.

[0051] As can be seen, in this embodiment, the controller 340 obtains multiple parameters such as voltage, current, SOC, SOH, temperature, internal resistance, and number of cycles of multiple battery cells 321, and determines the battery cells with abnormal heating and their corresponding valve openings based on preset heat mapping and flow rate mapping relationships. Then, by controlling the valve openings, the controller dynamically controls the coolant flow rate of the energy storage battery pack 320, thereby improving the accuracy of battery temperature control.

[0052] Please see Figure 4 , Figure 4 This is an overall flowchart of a smart coolant flow rate control method provided in an embodiment of this application, which is applied to... Figure 1 The controller in, such as Figure 4 As shown, the method includes the following steps:

[0053] Step S401: Receive multiple sets of first battery parameters sent by the monitoring module. Each set of first battery parameters includes multiple battery operating parameters of the corresponding battery cell within the target time period.

[0054] The battery operating parameters include at least voltage, current, temperature, internal resistance, charge / discharge cycle count, state of charge (SOC), and state of health (SOH). Voltage, current, and temperature are directly monitored by various types of sensors. Internal resistance, SOC, and SOH are calculated based on multiple battery operating parameters and battery configuration parameters. Specifically, internal resistance can be calculated using DC or AC internal resistance methods; SOC can be calculated using methods such as Coulomb counting, voltage method, Kalman filter method, electrochemical model estimation, or neural network fixation; SOH can be estimated by measuring the battery's actual usable capacity and comparing it with the initial capacity, by monitoring changes in internal resistance and combining it with empirical relationships with SOH or establishing mathematical models, or by using machine learning algorithms such as support vector machines or random forests, inputting multiple battery parameters (such as voltage, current, temperature, and cycle count), and training the model to predict SOH. It should be noted that the embodiments of this application do not limit the acquisition of multiple battery operating parameters to the methods described above.

[0055] Specifically, within each battery parameter set, multiple battery operating parameters can exist as parameter curves. For example, a battery parameter set may include voltage parameter curves, current parameter curves, temperature parameter curves, state of charge (SOC) parameter curves, and state of health (SOH) parameter curves. Each parameter curve characterizes the change of the corresponding parameter over time within a target period. It should be noted that this embodiment only provides one form of battery operating parameters; battery operating parameters can also exist in the form of parameter-time lookup tables, etc., as long as they can characterize the changes of the parameters within the target period.

[0056] In one possible embodiment, before receiving the plurality of first battery parameter sets sent by the monitoring module, the method further includes:

[0057] The system receives multiple reference battery parameter sets sent by the monitoring module. Each reference battery parameter set includes multiple battery operating parameters of the corresponding battery cell within a historical time period.

[0058] The first heat mapping relationship is established based on the plurality of reference battery sets, and the first heat mapping relationship is expressed by the following formula (1):

[0059] Q = f(V,I,T,R,C,SOC,SOH,t);

[0060] Where Q is the heat generated by the battery cell, V is the voltage of the battery cell, I is the current of the battery cell, T is the temperature of the battery cell, R is the internal resistance of the battery cell, C is the number of charge-discharge cycles of the battery cell, SOC is the state of charge of the battery cell, SOH is the state of health of the battery cell, t is the operating period of the battery cell, and f is the functional relationship.

[0061] The first heat mapping relationship is used to characterize the correspondence between the heat generated by the battery cell in different time periods and multiple battery operating parameters.

[0062] In one possible embodiment, the method further includes:

[0063] The system receives multiple reference battery parameter sets sent by the monitoring module. Each reference battery parameter set includes multiple battery operating parameters of the corresponding battery cell within a historical time period.

[0064] A thermal inference model is established based on the multiple reference battery sets;

[0065] The first heat mapping relationship is determined based on the heat inference model.

[0066] The first heat mapping relationship is the core component of the heat inference model. The main function of the heat inference model is to analyze heat generation based on changes in battery operating parameters. The model goes beyond simple calculations using the first heat mapping relationship; it extends the model further. For example, it may adjust the weights of different parameters according to the actual application scenario, or combine other non-electrical parameters (such as ambient humidity) to further optimize the inference of heat generation.

[0067] In one possible embodiment, a heat inference model is established, including theoretical modeling and data-driven modeling. Theoretical modeling is used to establish a theoretical model of the battery's heat generation based on the electrochemical reaction and heat transfer principles of the battery. For example, the heat generated by the electrochemical reaction inside the battery can be calculated based on the enthalpy change of the reaction, while the heat generated through the battery's internal resistance follows Joule's law. Data-driven modeling utilizes a large amount of experimental data and employs machine learning algorithms (such as multiple linear regression, neural networks, decision trees, etc.) to establish the functional relationship between the heat generation Q and parameters such as voltage V, current I, temperature T, internal resistance R, cycle number C, state of charge (SOC), and state of health (SOH). During model training, historical data is divided into training and testing sets, and model parameters are adjusted using optimization algorithms (such as gradient descent) to minimize the prediction error of the model on the testing set.

[0068] In one possible embodiment, the method further includes:

[0069] A reference flow rate mapping relationship is established based on the first heat mapping relationship. The reference flow rate mapping relationship is used to characterize the correspondence between the coolant flow rate and the heat generation and current instantaneous state of the battery cell.

[0070] The reference flow rate mapping relationship is coupled based on the multiple battery operating parameters to obtain the first flow rate mapping relationship, which is expressed by the following formula:

[0071] q=K1V+K2I+K3T+K4R+K5C+K6SOC+K7SOH+q b ;

[0072] Where q is the coolant flow rate of the battery cell, K1-K7 are the weighting coefficients of the multiple battery operating parameters, and q b is a constant term, representing the system's base coolant flow rate.

[0073] The first flow rate mapping relationship is used to characterize the correspondence between the coolant flow rate of the battery cell at different time points and multiple battery operating parameters.

[0074] The reference velocity mapping relationship is expressed by the following formula:

[0075] q = f(Q, α);

[0076] Where q is the coolant flow rate of the battery cell, Q is the heat generated by the battery cell, α is the instantaneous state of the battery cell, and f is the functional relationship.

[0077] Understandably, the reference flow rate mapping relationship is used to initially determine the correlation between coolant flow rate and battery heat generation and current instantaneous state, providing a basic framework for subsequent accurate calculation of coolant flow rate. The instantaneous state of the battery cell can refer to the operating state of the battery cell at the end time node of the target time period during its operation. Furthermore, by introducing and coupling multiple battery operating parameters corresponding to the instantaneous state, a first flow rate mapping relationship can be obtained. The weighting coefficients K1 to K7 in the calculation formula corresponding to the first flow rate mapping relationship can be dynamically adjusted based on the actual operating conditions of the battery cell.

[0078] As can be seen, in this embodiment, the controller pre-calculates the first heat mapping relationship, which can accurately predict heat generation with the help of battery operating parameters, analyze the factors affecting heat generation and provide early warning of anomalies; and, by pre-calculating the first flow rate mapping relationship, it can intelligently adjust the coolant flow rate by integrating multiple parameters, improve the efficiency of the thermal management system, and ensure battery performance and lifespan.

[0079] Step S402: Based on the plurality of first battery parameter sets, the preset first heat mapping relationship, and the preset first flow rate mapping relationship, determine at least one battery cell in the plurality of battery cells that is in an abnormal heating state and its corresponding at least one target coolant flow rate. The first heat mapping relationship is used to characterize the correspondence between the heat generated by the battery cell in different time periods and the plurality of battery operating parameters. The first flow rate mapping relationship is used to characterize the correspondence between the coolant flow rate of the battery cell at different time points and the plurality of battery operating parameters.

[0080] In one possible embodiment, determining at least one battery cell in an abnormally heated state and its corresponding at least one target coolant flow rate among the plurality of battery cells based on the plurality of first battery parameter sets, a preset first heat mapping relationship, and a preset first flow rate mapping relationship includes:

[0081] Perform the following operations for each of the plurality of battery cells to determine at least one battery cell in an abnormally heated state and its corresponding at least one target coolant flow rate:

[0082] The reference heat generation of the battery cell in the target time period is determined based on the first battery parameter set corresponding to the currently processed battery cell and the first heat mapping relationship.

[0083] If it is determined that the reference heat generation is outside the preset heat generation range, then the battery cell is determined to be in the abnormal heat generation state.

[0084] Obtain multiple target battery operating parameters corresponding to the battery unit at the end time node of the target time period;

[0085] The target coolant flow rate corresponding to the battery cell is determined based on the multiple target battery operating parameters and the first flow rate mapping relationship.

[0086] In one possible embodiment, the abnormal heating state includes an excessive heating state and an insufficient heating state; the step of determining that the battery cell is in the abnormal heating state if it is determined that the reference heat generation is outside the preset heat generation range includes:

[0087] If it is determined that the reference heat generation is less than the minimum heat generation corresponding to the heat generation range, then the battery cell is determined to be in the state of insufficient heat generation; and,

[0088] If it is determined that the reference heat generation is greater than the maximum heat generation corresponding to the heat generation range, then the battery cell is determined to be in the state of excessive heat generation.

[0089] In one possible embodiment, if it is determined that the reference heat generation is outside a preset heat generation range, then the battery cell is determined to be in the abnormal heating state. The method further includes:

[0090] If it is determined that the reference heat generation is within the heat generation range, then the battery cell is determined to be in a normal heating state.

[0091] Continue to acquire multiple battery parameter sets corresponding to the multiple battery cells according to a preset cycle;

[0092] Based on the newly acquired sets of multiple battery parameters, the system repeatedly determines at least one battery cell in an abnormal heating state and its corresponding at least one target coolant flow rate according to the multiple sets of first battery parameters, a preset first heat mapping relationship, and a preset first flow rate mapping relationship; and determines at least one valve opening corresponding to the at least one target coolant flow rate, wherein the coolant flow rate is associated with the valve opening; and generates at least one control signal according to the at least one valve opening; and sends the at least one control signal to at least one coolant inlet / outlet valve corresponding to the at least one battery cell.

[0093] For example, taking battery cell 3 as an example, the monitoring module sends its first set of battery parameters for the target time period (assuming it's 30 minutes from 10:00 to 10:30), which includes multiple operating parameters such as voltage, current, and temperature. The controller, based on the first heat mapping relationship, substitutes these parameters of battery cell 3 for the target time period to calculate the reference heat output of the battery cell during these 30 minutes, assuming the calculation result is 800J. A normal heat output range is pre-set based on the battery type, specifications, and historical operating data, for example, the normal heat output range for the target time period is 300J-600J. Since the calculated reference heat output of battery cell 3, 800J, is greater than 600J and exceeds the normal heat output range, it can be determined that battery cell 3 is in an abnormal heating state.

[0094] Furthermore, continuing with battery cell 3 as an example, the controller acquires multiple target battery operating parameters corresponding to its end time node of the target period (i.e., 10:30), such as a voltage of 3.8V, a current of 70A, and a temperature of 40℃. Based on the first flow rate mapping relationship, the controller substitutes the target battery operating parameters of battery cell 3 acquired earlier at 10:30. Assuming that the calculation shows the target coolant flow rate for battery cell 3 at this time is 12L / min, it means that in order to restore the temperature of battery cell 3 to normal, its corresponding coolant flow rate needs to be adjusted to 12L / min.

[0095] Step S403: Determine at least one valve opening corresponding to the at least one target coolant flow rate, wherein the coolant flow rate is associated with the valve opening.

[0096] The relationship between coolant flow rate and valve opening can be expressed by the following formula:

[0097] D = f(q);

[0098] Where D represents the valve opening degree of the coolant inlet and outlet, q represents the coolant flow rate of the battery cell, and f is a functional relationship.

[0099] For example, the valve opening / closing degree is linearly related to the coolant flow rate. In practical applications, the function f(q) can be a linear function derived experimentally or theoretically, such as D = kq + b (where k and b are constants). The values ​​of k and b are determined based on the specific system characteristics. If the function f(q) in this system is determined experimentally to be D = 0.1q, substituting the target coolant flow rate q = 12 L / min for battery unit 3, the opening / closing degree of the solenoid valve can be obtained as D = 0.1 × 12 = 1.2. Here, "1.2" is a relative value obtained according to the set calculation method, representing a certain degree of opening / closing.

[0100] The controller also features algorithm optimization capabilities, which utilize genetic algorithms to analyze the opening degree of solenoid valves in the energy storage system and the temperature of the implementation effect, optimize parameters, improve temperature control accuracy, and balance battery temperature and energy consumption.

[0101] Step S404: Generate at least one control signal based on the opening degree of the at least one valve; and send the at least one control signal to at least one coolant inlet / outlet valve corresponding to the at least one battery cell.

[0102] Step S405: It is detected that the absolute value of the difference between the temperature of any one of the plurality of battery cells and the preset temperature value is less than the preset threshold.

[0103] In one possible embodiment, the method further includes, where the absolute value of the difference between the temperature of any one of the plurality of battery cells and a preset temperature value is less than a preset threshold, the method further includes:

[0104] At the first time point, it is detected that the absolute value of the difference between the temperature of at least one of the plurality of battery cells and the preset temperature value is greater than the preset threshold.

[0105] Determine whether the time interval between the first time node and the end time node of the target time period is greater than a first preset value, and obtain a first determination result;

[0106] Based on the first judgment result, different coolant flow rate control operations are performed to achieve the goal of detecting at the second time node that the absolute value of the difference between the temperature of any one of the multiple battery cells and the preset temperature value is less than the preset threshold, and the second time node is later than the first time node.

[0107] In one possible embodiment, the step of performing different coolant flow rate control operations based on the first determination result includes:

[0108] Based on the first judgment result, it is determined that the time interval between the first time node and the end time node of the target time period is greater than the first preset value;

[0109] Send first information to the monitoring module, the first information being used to instruct the monitoring module to send multiple second battery parameter sets to the controller, each second battery parameter set including multiple battery operating parameters of the corresponding battery cell in a second time period, the second time period being earlier than the first time node;

[0110] Based on the received multiple sets of second battery parameters, the first heat mapping relationship, and the first flow rate mapping relationship, determine the second battery cell in the abnormal heating state during the second time period and its corresponding second coolant flow rate; and determine the second valve opening corresponding to the second coolant flow rate; and...

[0111] A second control signal is generated based on the opening degree of the second valve; and the second control signal is sent to the coolant inlet and outlet valves corresponding to the second battery unit.

[0112] At the second time node, it is detected that the absolute value of the difference between the temperature of any one of the plurality of battery cells and the preset temperature value is less than the preset threshold.

[0113] In one possible embodiment, the method further includes:

[0114] Based on the first judgment result, the time interval between the first time node and the end time node of the target time period is determined to be less than or equal to the first preset value.

[0115] At the first time node, the system repeatedly determines, based on the plurality of first battery parameter sets, a preset first heat mapping relationship, and a preset first flow rate mapping relationship, at least one battery cell in the plurality of battery cells that is in an abnormal heating state and its corresponding at least one target coolant flow rate; and determines at least one valve opening corresponding to the at least one target coolant flow rate, wherein the coolant flow rate is associated with the valve opening; and generates at least one control signal based on the at least one valve opening; and sends the at least one control signal to at least one coolant inlet / outlet valve corresponding to the at least one battery cell.

[0116] At the second time node, it is detected that the absolute value of the difference between the temperature of any one of the plurality of battery cells and the preset temperature value is less than the preset threshold.

[0117] For example, the target time period is set to 9:00-9:30, and the first preset value is 10 minutes. At 9:55 (the first time node), if the absolute value of the temperature difference of battery cell 5 is detected to be greater than the preset threshold, and the time interval between 9:55 and 9:30 is calculated to be 25 minutes, which is greater than the first preset value of 10 minutes, the controller sends the first information to the monitoring module, instructing the monitoring module to send the operating parameters of multiple battery cells from 9:20 to 9:50 (the second time period). Furthermore, assuming that analysis reveals that battery cell 5 is in an abnormally hot state from 9:20 to 9:50, the second coolant flow rate is calculated to be 15 L / min, corresponding to a second valve opening of 0.8 (an assumed relative value). Based on the second valve opening of 0.8, second control information is generated and sent to the coolant inlet and outlet valves corresponding to the second battery cell (i.e., battery cell 5). Finally, at the second time node later than 9:55, such as 10:00, if the absolute value of the temperature difference between all battery cells and the preset temperature value is again detected to be less than the preset threshold,...

[0118] For example, if the absolute value of the temperature difference of battery cell 5 is detected to be greater than a preset threshold at 9:40 (the first time node), the time interval between 9:40 and 9:30 is calculated to be 10 minutes, which is equal to the first preset value of 10 minutes. Since the time interval is too small, the changes in the operating parameters of the energy storage battery are minimal, and there is no need to re-acquire the battery parameter set. Therefore, the operation of determining the battery cell in an abnormal heating state based on multiple first battery parameter sets, a preset first heat mapping relationship, and a preset first flow rate mapping relationship, and determining the corresponding coolant flow rate and valve opening and sending control signals, is repeated. For example, the current operating parameters of each battery cell are recalculated, and it is determined that battery cell 5 is still in an abnormal heating state. A suitable coolant flow rate and valve opening are re-determined, and control signals are sent to adjust the coolant inlet and outlet valves. Finally, at the second time node, such as 9:45, the absolute value of the temperature difference between all battery cells and the preset temperature value is detected to be less than the preset threshold.

[0119] As can be seen, in this embodiment, the controller obtains the battery's operating status, including charging / discharging status, power output, and battery health status, based on battery operating parameters by real-time monitoring of the battery's voltage and current. It then dynamically adjusts the coolant flow rate by utilizing the coupling relationship between these parameters and the coolant flow rate. Simultaneously, by setting independent coolant flow control valves, different coolant flow rates can be applied to corresponding battery areas, achieving balanced and optimized battery temperature, improving system flexibility and economy, reducing energy loss, and enhancing the efficiency of the energy storage system.

[0120] Please see Figure 5 , Figure 5 This is a flowchart illustrating the steps of an intelligent coolant flow rate control method provided in an embodiment of this application, as follows: Figure 5 As shown, the method includes the following steps:

[0121] Step S501: Periodically receive battery parameter sets sent by the monitoring module.

[0122] In one possible embodiment, before periodically receiving the battery parameter set sent by the monitoring module, the method further includes: receiving multiple reference battery parameter sets sent by the monitoring module, each reference battery parameter set including multiple battery operating parameters of the corresponding battery cell in a historical period; establishing a first heat mapping relationship based on the multiple reference battery sets, the first heat mapping relationship being expressed by the following formula (1): Q = f(V, I, T, R, C, SOC, SOH, t); where Q is the heat generation of the battery cell, V is the voltage of the battery cell, I is the current of the battery cell, T is the temperature of the battery cell, R is the internal resistance of the battery cell, C is the number of charge-discharge cycles of the battery cell, SOC is the state of charge of the battery cell, SOH is the health state of the battery cell, t is the operating period of the battery cell, and f is a function relationship.

[0123] In one possible embodiment, before periodically receiving the battery parameter set sent by the monitoring module, the method further includes: establishing a reference flow rate mapping relationship based on the first heat mapping relationship, the reference flow rate mapping relationship being used to characterize the correspondence between the coolant flow rate and the heat generation and current instantaneous state of the battery cell; coupling the reference flow rate mapping relationship based on the plurality of battery operating parameters to obtain the first flow rate mapping relationship, the first flow rate mapping relationship being expressed by the following formula: q=K1V+K2I+K3T+K4R+K5C+K6SOC+K7SOH+q b Where q is the coolant flow rate of the battery cell, K1-K7 are the weighting coefficients of the multiple battery operating parameters, and q b is a constant term, representing the system's base coolant flow rate.

[0124] The first heat mapping relationship is used to characterize the correspondence between the heat generated by the battery cell at different time periods and the multiple battery operating parameters, and the first flow rate mapping relationship is used to characterize the correspondence between the coolant flow rate of the battery cell at different time points and the multiple battery operating parameters.

[0125] Step S502: After receiving the battery parameter set each time, determine the battery cell with abnormal heating and its corresponding target coolant flow rate based on the battery parameter set, the first heat mapping relationship and the first flow rate mapping relationship.

[0126] In one possible embodiment, determining the abnormally heated battery cell and its corresponding target coolant flow rate based on the battery parameter set, the first heat mapping relationship, and the first flow rate mapping relationship includes: performing the following operations for each of the plurality of battery cells to determine at least one battery cell in an abnormally heated state and its corresponding at least one target coolant flow rate: determining the reference heat generation of the battery cell in the target time period based on the first battery parameter set and the first heat mapping relationship corresponding to the currently processed battery cell; if it is determined that the reference heat generation is outside a preset heat generation range, then determining that the battery cell is in the abnormally heated state; obtaining a plurality of target battery operating parameters corresponding to the battery cell at the end time node of the target time period; and determining the target coolant flow rate corresponding to the battery cell based on the plurality of target battery operating parameters and the first flow rate mapping relationship.

[0127] Step S503: Determine the valve opening corresponding to the target coolant flow rate, and generate a control signal based on the valve opening and send the control signal to the coolant inlet and outlet valves corresponding to the battery cell.

[0128] The relationship between coolant flow rate and valve opening can be expressed by the following formula: D = f(q); where D represents the valve opening at the coolant inlet and outlet, q represents the coolant flow rate of the battery cell, and f is a function.

[0129] Step S504: Detect whether the temperature of multiple battery cells is uniform.

[0130] Specifically, if yes, then step S501 is executed, and if no, then step S505 is executed.

[0131] Step S505: Re-determine the battery cell with abnormal heating and its corresponding valve opening, and send a control signal to the battery cell based on the newly determined valve opening.

[0132] Furthermore, after step S505 is completed, step S504 is executed to continuously detect whether the temperature of multiple battery cells is balanced.

[0133] In one possible embodiment, the step of re-determining the abnormally heated battery cell and its corresponding valve opening, and sending a control signal to the battery cell based on the newly determined valve opening, includes: detecting at a first time node that the absolute value of the difference between the temperature of at least one of the plurality of battery cells and the preset temperature value is greater than the preset threshold; determining whether the time interval between the first time node and the end time node of the target time period is greater than a first preset value, and obtaining a first determination result; and performing different coolant flow rate control operations according to the first determination result, so as to achieve the detection at a second time node that the absolute value of the difference between the temperature of any one of the plurality of battery cells and the preset temperature value is less than the preset threshold, wherein the second time node is later than the first time node.

[0134] Understandably, when a battery cell with excessively high or low temperature is detected at a certain time point, it is necessary to re-detect the abnormal heating of the battery cell. However, due to various factors, such as battery cell performance and electrical connection relationships, the time point at which the temperature imbalance is detected may be too large or too small compared to the target time corresponding to the battery parameter set collected in this detection. Therefore, it is necessary to use different methods based on the size of the time interval to redetermine the abnormally heating battery cell and its corresponding valve opening and adjust the coolant flow rate to differentiate the temperature imbalance under different conditions, thereby enabling more intelligent and efficient adjustment of the coolant flow rate of the energy storage system.

[0135] Please see Figure 6 , Figure 6 This is a flowchart illustrating the steps of another intelligent coolant flow rate control method provided in this application embodiment, as follows: Figure 6 As shown, this method is for Figure 5 The sub-step performed in step S505 of the method includes the following steps:

[0136] Step S601: Multiple battery cells are found to have uneven temperatures, and the time interval between the current time node and the end time node of the target time period is determined.

[0137] Step S602: Whether the time interval is greater than the first preset value.

[0138] Specifically, if not, then step S603 is executed, and if yes, then step S604 is executed.

[0139] Step S603: Again, based on the first battery parameter set, determine the battery cell with abnormal heating and its corresponding valve opening, and generate a control signal according to the valve opening and send the control signal to the battery cell.

[0140] For example, the target time period is set to 9:00-9:30, and the first preset value is 10 minutes. At 9:40 (the first time node), if the absolute value of the temperature difference of battery cell 5 is detected to be greater than a preset threshold, the time interval between 9:40 and 9:30 is calculated to be 10 minutes, which is equal to the first preset value of 10 minutes. Then, the operation of determining the battery cell in an abnormal heating state based on multiple first battery parameter sets, a preset first heat mapping relationship, and a preset first flow rate mapping relationship, and determining the corresponding coolant flow rate and valve opening and sending control signals is repeated. For example, the current operating parameters of each battery cell are recalculated, it is determined that battery cell 5 is still in an abnormal heating state, the appropriate coolant flow rate and valve opening are re-determined, and control signals are sent to adjust the coolant inlet and outlet valves.

[0141] Step S604: Send the first information to the monitoring module.

[0142] The first information is used to instruct the monitoring module to send multiple second battery parameter sets to the controller. Each second battery parameter set includes multiple battery operating parameters of the corresponding battery cell in a second time period, which is earlier than the first time node.

[0143] Step S605: Receive the second battery parameter set sent by the monitoring module.

[0144] Step S606: Determine the second battery cell with abnormal heating and its corresponding second coolant flow rate based on the second battery parameter set, the first heat mapping relationship, and the first flow rate mapping relationship.

[0145] In one possible embodiment, determining the second battery cell with abnormal heating and its corresponding second coolant flow rate based on the second battery parameter set, the first heat mapping relationship, and the first flow rate mapping relationship includes: performing the following operations for each of the plurality of battery cells to determine the second battery cell with abnormal heating and its corresponding second coolant flow rate: determining the reference heat generation of the battery cell in the target time period based on the second battery parameter set corresponding to the currently processed battery cell and the first heat mapping relationship; if it is determined that the reference heat generation is outside a preset heat generation range, then determining the battery cell as the second battery cell; obtaining a plurality of target battery operating parameters corresponding to the second battery cell at the end time node of the target time period; and determining the second coolant flow rate corresponding to the second battery cell based on the plurality of target battery operating parameters and the first flow rate mapping relationship.

[0146] Step S607: Determine the second valve opening degree corresponding to the second coolant flow rate, and generate a second control signal based on the second valve opening degree and send the second control signal to the coolant inlet and outlet valves corresponding to the second battery unit.

[0147] For example, the target time period is set to 9:00-9:30, and the first preset value is 10 minutes. At 9:55 (the first time node), if the absolute value of the temperature difference of battery cell 5 is detected to be greater than the preset threshold, and the time interval between 9:55 and 9:30 is calculated to be 25 minutes, which is greater than the first preset value of 10 minutes, the controller sends the first information to the monitoring module, instructing the monitoring module to send the operating parameters of multiple battery cells from 9:20 to 9:50 (the second time period); and, assuming that the analysis finds that battery cell 5 is in an abnormal heating state from 9:20 to 9:50, the second coolant flow rate is calculated to be 15 L / min, and the corresponding second valve opening is 0.8 (an assumed relative value). Then, based on the second valve opening of 0.8, the controller generates the second control information and sends it to the coolant inlet and outlet valves corresponding to the second battery cell (i.e., battery cell 5).

[0148] As can be seen, in this embodiment, different schemes are used to redetermine the abnormally heated battery cells and adjust the coolant flow rate based on different time intervals. This can adapt to different battery operating conditions. For example, in energy storage systems with stringent requirements for battery temperature stability, when the first adjustment is found to be ineffective, a second adjustment can be quickly performed based on the same target time period data, which can quickly respond and stabilize the battery temperature. Similarly, in electric vehicle energy storage systems, the operating conditions of the vehicle change continuously during driving, and the working state of the battery also changes accordingly. When a second coolant flow rate adjustment is required, using new target time period data can better adapt to the changes, which is beneficial to improving the accuracy and effectiveness of coolant flow rate adjustment.

[0149] Please see Figure 7 , Figure 7 This is an application scenario diagram of an intelligent coolant flow rate control method provided in an embodiment of this application, such as... Figure 7 As shown, this application scenario diagram is a real-world application scenario diagram of the energy storage system, which includes a controller 710, a monitoring module 720, a battery unit 730, a cooling module 740, and a coolant storage tank 750.

[0150] The energy storage system includes multiple battery cells 730 and multiple cooling modules 740. Each cooling module 740 is attached to the lower end face of the battery cell 730 and is used to cool the battery cell. Each cooling module 740 includes a pipe 741, a coolant inlet valve 742, and a coolant outlet valve 743. The pipe 741 is connected to a coolant storage tank 750 via the coolant inlet valve 742 and the coolant outlet valve 743. The coolant outlet valve 743 introduces cold water from the coolant storage tank 750 into the pipe 741 of the cooling module to cool the battery cell 730, and the coolant outlet valve 743 returns the cold water from the pipe 741 of the cooling module to its original position, thus achieving water circulation.

[0151] The monitoring module 720 is connected to multiple battery units 730. The monitoring module 720 is used to acquire multiple battery operating parameters of the battery units 730 during a target time period, and perform preliminary processing to form a battery parameter set; and to send multiple battery parameter sets to the controller 710.

[0152] The controller 710 is connected to the monitoring module 720, the coolant inlet valve 742, and the coolant outlet valve 743. The controller 710 interacts with the monitoring module 720, receiving a set of battery parameters corresponding to the battery unit 730 from the monitoring module 720. Based on the received battery parameter set and a preset first heat mapping relationship and first flow rate mapping relationship, the controller analyzes and determines the battery unit in an abnormal heating state and its corresponding target coolant flow rate, thereby determining the opening degree of the corresponding coolant inlet valve 742 and / or coolant outlet valve 743, generating a control signal and sending it to the corresponding valve to achieve intelligent control of the coolant flow rate.

[0153] As can be seen, in this embodiment, the entire energy storage system can monitor the status of battery cells in real time through the connection and information exchange between its various parts. Furthermore, it can adjust the coolant flow rate of the corresponding battery area individually to address the differences in different battery parameters. This helps to improve the temperature uniformity between batteries, ensure that the energy storage battery pack operates within a suitable temperature range, and improve the performance and lifespan of the energy storage battery.

[0154] Please see Figure 8 , Figure 8A functional module diagram of a coolant flow rate intelligent control device 8 provided in this application embodiment is shown below. Figure 8 As shown, the intelligent coolant flow rate control device 8 includes the following units:

[0155] The receiving unit 801 is used to receive multiple first battery parameter sets sent by the monitoring module. Each first battery parameter set includes multiple battery operating parameters of the corresponding battery cell within the target time period.

[0156] The first determining unit 802 is used to determine at least one battery cell in the plurality of battery cells that is in an abnormal heating state and its corresponding at least one target coolant flow rate based on the plurality of first battery parameter sets, a preset first heat mapping relationship and a preset first flow rate mapping relationship. The first heat mapping relationship is used to characterize the correspondence between the heat generated by the battery cell in different time periods and the plurality of battery operating parameters. The first flow rate mapping relationship is used to characterize the correspondence between the coolant flow rate of the battery cell at different time points and the plurality of battery operating parameters.

[0157] The second determining unit 803 is used to determine at least one valve opening corresponding to the at least one target coolant flow rate, wherein the coolant flow rate is associated with the valve opening.

[0158] The transmitting unit 804 is configured to generate at least one control signal based on the opening degree of the at least one valve; and to transmit the at least one control signal to at least one coolant inlet / outlet valve corresponding to the at least one battery cell;

[0159] The detection unit 805 is used to detect that the absolute value of the difference between the temperature of any one of the plurality of battery cells and a preset temperature value is less than a preset threshold.

[0160] In one embodiment, determining at least one battery cell in an abnormal heating state and its corresponding at least one target coolant flow rate based on the plurality of first battery parameter sets, a preset first heat mapping relationship, and a preset first flow rate mapping relationship includes: performing the following operations for each of the plurality of battery cells to determine the at least one battery cell in an abnormal heating state and its corresponding at least one target coolant flow rate: determining the reference heat generation of the battery cell in the target time period based on the first battery parameter set corresponding to the currently processed battery cell and the first heat mapping relationship; if it is determined that the reference heat generation is outside the preset heat generation range, then determining that the battery cell is in the abnormal heating state; obtaining a plurality of target battery operating parameters corresponding to the battery cell at the end time node of the target time period; and determining the target coolant flow rate corresponding to the battery cell based on the plurality of target battery operating parameters and the first flow rate mapping relationship.

[0161] In one embodiment, the method further includes: detecting at least one battery cell among the plurality of battery cells whose absolute difference between its temperature and a preset temperature value is less than a preset threshold at a first time node; determining whether the time interval between the first time node and the end time node of the target time period is greater than a first preset value to obtain a first determination result; and performing different coolant flow rate control operations according to the first determination result to achieve the detection at a second time node where the absolute difference between the temperature of any one battery cell among the plurality of battery cells and the preset temperature value is less than the preset threshold, wherein the second time node is later than the first time node.

[0162] In one embodiment, performing different coolant flow rate control operations based on the first determination result includes: determining, based on the first determination result, that the time interval between the first time node and the end time node of the target time period is greater than the first preset value; sending first information to the monitoring module, the first information being used to instruct the monitoring module to send multiple second battery parameter sets to the controller, each second battery parameter set including multiple battery operating parameters of the corresponding battery cell in a second time period, the second time period being earlier than the first time node; determining, based on the received multiple second battery parameter sets, the first heat mapping relationship, and the first flow rate mapping relationship, the second battery cell in the abnormal heating state and its corresponding second coolant flow rate in the second time period; and determining the second valve opening degree corresponding to the second coolant flow rate; and generating a second control signal based on the second valve opening degree; and sending the second control signal to the coolant inlet and outlet valves corresponding to the second battery cell; and detecting, at the second time node, that the absolute value of the difference between the temperature of any one of the multiple battery cells and a preset temperature value is less than the preset threshold.

[0163] In one embodiment, the method further includes: determining, based on the first judgment result, that the time interval between the first time node and the end time node of the target time period is less than or equal to the first preset value; at the first time node, repeatedly determining, based on the plurality of first battery parameter sets, a preset first heat mapping relationship, and a preset first flow rate mapping relationship, at least one battery cell in the plurality of battery cells that is in an abnormal heating state and its corresponding at least one target coolant flow rate; and determining, at least one valve opening degree corresponding to the at least one target coolant flow rate, wherein the coolant flow rate is associated with the valve opening degree; and generating at least one control signal based on the at least one valve opening degree; and sending the at least one control signal to at least one coolant inlet / outlet valve corresponding to the at least one battery cell; and detecting, at the second time node, that the absolute value of the difference between the temperature of any one of the plurality of battery cells and a preset temperature value is less than the preset threshold.

[0164] In one embodiment, the plurality of battery operating parameters include at least voltage, current, temperature, internal resistance, charge-discharge cycle count, state of charge (SOC), and state of health (SOH). Before receiving the plurality of first battery parameter sets sent by the monitoring module, the method further includes: receiving the plurality of reference battery parameter sets sent by the monitoring module, wherein a single reference battery parameter set includes the plurality of battery operating parameters of the corresponding battery cell in a historical period; establishing a first heat mapping relationship based on the plurality of reference battery sets, wherein the first heat mapping relationship is expressed by the following formula (1): Q = f(V, I, T, R, C, SOC, SOH, t); where Q is the heat generated by the battery cell, V is the voltage of the battery cell, I is the current of the battery cell, T is the temperature of the battery cell, R is the internal resistance of the battery cell, C is the charge-discharge cycle count of the battery cell, SOC is the state of charge of the battery cell, SOH is the state of health of the battery cell, t is the operating period of the battery cell, and f is a function relationship.

[0165] In one embodiment, the method further includes: establishing a reference flow rate mapping relationship based on the first heat mapping relationship, the reference flow rate mapping relationship being used to characterize the correspondence between the coolant flow rate and the heat generation and current instantaneous state of the battery cell; coupling the reference flow rate mapping relationship based on the plurality of battery operating parameters to obtain the first flow rate mapping relationship, the first flow rate mapping relationship being expressed by the following formula: q=K1V+K2I+K3T+K4R+K5C+K6SOC+K7SOH+q b Where q is the coolant flow rate of the battery cell, K1-K7 are the weighting coefficients of the multiple battery operating parameters, and q b is a constant term, representing the system's base coolant flow rate.

[0166] It is understood that since the method embodiments and the device embodiments are different presentations of the same technical concept, the content of the method embodiment section in this application should be adapted to the device embodiment section in a synchronous manner, and will not be repeated here.

[0167] As can be seen, the controller of this device acquires parameters such as battery voltage, current, temperature, internal resistance, and battery health status. It then uses the mapping relationship between these parameters and heat dissipation to identify battery cells in an abnormally overheating state. Based on the coupling relationship between these parameters and coolant flow rate, it dynamically adjusts the coolant flow rate of the abnormally overheating battery cells. Simultaneously, by setting independent coolant flow control valves, different coolant flow rates can be applied to corresponding battery areas, achieving battery temperature balance and optimization, improving system flexibility and economy, reducing energy loss, and enhancing thermal management efficiency.

[0168] Furthermore, this application embodiment also provides a computer storage medium that stores a computer program capable of being loaded by a processor and executed as described above for the intelligent control method of coolant flow rate. The computer-readable storage medium includes, for example, various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0169] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0170] In the several embodiments provided in this application, it should be understood that the disclosed methods, apparatuses, and systems can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for example, the division of units is merely a logical functional division, and other division methods may exist in actual implementation; 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, and the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0171] 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.

[0172] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can be physically comprised separately, or two or more units can be integrated into one unit. The integrated unit described above can be implemented in hardware or in the form of hardware plus software functional units.

[0173] The integrated units implemented as software functional units described above can be stored in a computer-readable storage medium. These software functional units, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute some steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes: a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, volatile memory, or non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (SLDRAM), and direct rambus RAM (DRRAM), etc., which are various media that can store program code.

[0174] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0175] The embodiments of this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

[0176] While this application discloses the above information, it is not limited thereto. Any person skilled in the art can easily conceive of variations or substitutions without departing from the spirit and scope of this application, and can make various alterations and modifications, including combinations of the different functions and implementation steps described above, as well as software and hardware implementation methods, all of which are within the protection scope of this application.

Claims

1. A method for intelligent control of coolant flow rate, characterized in that, A controller is applied to an energy storage system, the energy storage system further including a monitoring module, an energy storage battery pack, and multiple coolant inlet and outlet valves. The monitoring module is connected to the energy storage battery pack, the energy storage battery pack including multiple battery cells, the multiple battery cells being connected to the multiple coolant inlet and outlet valves respectively, and the controller being connected to the monitoring module and the multiple coolant inlet and outlet valves respectively. The method includes: The system receives multiple sets of first battery parameters sent by the monitoring module. Each set of first battery parameters includes multiple battery operating parameters of the corresponding battery cell within the target time period. The multiple battery operating parameters include at least voltage, current, temperature, internal resistance, charge / discharge cycle count, state of charge (SOC), and state of health (SOH). For each of the plurality of battery cells, the following operations are performed to determine at least one battery cell in an abnormally hot state and its corresponding at least one target coolant flow rate: The reference heat generation of the battery cell in the target time period is determined based on the first battery parameter set and the first heat mapping relationship corresponding to the battery cell currently being processed. The first heat mapping relationship is used to characterize the correspondence between the heat generation of the battery cell in different time periods and the multiple battery operating parameters. If it is determined that the reference heat generation is outside the preset heat generation range, then the battery cell is determined to be in the abnormal heat generation state. Obtain multiple target battery operating parameters corresponding to the battery unit at the end time node of the target time period; The target coolant flow rate of the battery cell is determined based on the plurality of target battery operating parameters and the first flow rate mapping relationship. The first flow rate mapping relationship is used to characterize the correspondence between the coolant flow rate of the battery cell at different time points and the plurality of battery operating parameters. Determine at least one valve opening corresponding to the at least one target coolant flow rate, wherein the coolant flow rate is associated with the valve opening; At least one control signal is generated based on the opening degree of the at least one valve; and the at least one control signal is sent to at least one of the coolant inlet and outlet valves corresponding to the at least one battery cell; The absolute value of the difference between the temperature of any one of the plurality of battery cells and a preset temperature value is less than a preset threshold.

2. The method according to claim 1, characterized in that, The method further includes detecting that the absolute value of the difference between the temperature of any one of the plurality of battery cells and a preset temperature value is less than a preset threshold. At the first time point, it is detected that the absolute value of the difference between the temperature of at least one of the plurality of battery cells and the preset temperature value is greater than the preset threshold. Determine whether the time interval between the first time node and the end time node of the target time period is greater than a first preset value, and obtain a first determination result; Based on the first judgment result, different coolant flow rate control operations are performed to achieve the goal of detecting at the second time node that the absolute value of the difference between the temperature of any one of the multiple battery cells and the preset temperature value is less than the preset threshold, and the second time node is later than the first time node.

3. The method according to claim 2, characterized in that, The step of performing different coolant flow rate control operations based on the first determination result includes: Based on the first judgment result, it is determined that the time interval between the first time node and the end time node of the target time period is greater than the first preset value; Send first information to the monitoring module, the first information being used to instruct the monitoring module to send multiple second battery parameter sets to the controller, each second battery parameter set including multiple battery operating parameters of the corresponding battery cell in a second time period, the second time period being earlier than the first time node; Based on the received multiple sets of second battery parameters, the first heat mapping relationship, and the first flow rate mapping relationship, determine the second battery cell in the abnormal heating state during the second time period and its corresponding second coolant flow rate; and determine the second valve opening corresponding to the second coolant flow rate; and... A second control signal is generated based on the opening degree of the second valve; and the second control signal is sent to the coolant inlet and outlet valves corresponding to the second battery unit. At the second time node, it is detected that the absolute value of the difference between the temperature of any one of the plurality of battery cells and the preset temperature value is less than the preset threshold.

4. The method according to claim 3, characterized in that, The method further includes: Based on the first judgment result, the time interval between the first time node and the end time node of the target time period is determined to be less than or equal to the first preset value. At the first time node, the system repeatedly determines, based on the plurality of first battery parameter sets, a preset first heat mapping relationship, and a preset first flow rate mapping relationship, at least one battery cell in the plurality of battery cells that is in an abnormal heating state and its corresponding at least one target coolant flow rate; and determines at least one valve opening corresponding to the at least one target coolant flow rate, wherein the coolant flow rate is associated with the valve opening; and generates at least one control signal based on the at least one valve opening; and sends the at least one control signal to at least one coolant inlet / outlet valve corresponding to the at least one battery cell. At the second time node, it is detected that the absolute value of the difference between the temperature of any one of the plurality of battery cells and the preset temperature value is less than the preset threshold.

5. The method according to any one of claims 2-4, characterized in that, Before receiving the multiple sets of first battery parameters sent by the monitoring module, the method further includes: The system receives multiple reference battery parameter sets sent by the monitoring module. Each reference battery parameter set includes multiple battery operating parameters of the corresponding battery cell within a historical time period. The first heat mapping relationship is established based on the multiple reference battery parameter sets, and the first heat mapping relationship is expressed by the following formula (1): Q=f(V,I,T,R,C,SOC,SOH,t); Where Q is the heat generated by the battery cell, V is the voltage of the battery cell, I is the current of the battery cell, T is the temperature of the battery cell, R is the internal resistance of the battery cell, C is the number of charge-discharge cycles of the battery cell, SOC is the state of charge of the battery cell, SOH is the state of health of the battery cell, t is the operating period of the battery cell, and f is the functional relationship.

6. The method according to claim 5, characterized in that, The method further includes: A reference flow rate mapping relationship is established based on the first heat mapping relationship. The reference flow rate mapping relationship is used to characterize the correspondence between the coolant flow rate and the heat generation and current instantaneous state of the battery cell. The reference flow rate mapping relationship is coupled based on the multiple battery operating parameters to obtain the first flow rate mapping relationship, which is expressed by the following formula: q= ； Where q is the coolant flow rate of the battery cell, - The weighting coefficients of the multiple battery operating parameters are respectively. is a constant term, representing the system's base coolant flow rate.

7. A smart control device for coolant flow rate, characterized in that, A controller for an energy storage system, the energy storage system further comprising a monitoring module, an energy storage battery pack, and multiple coolant inlet and outlet valves, the monitoring module being connected to the energy storage battery pack, the energy storage battery pack comprising multiple battery cells, the multiple battery cells being correspondingly connected to the multiple coolant inlet and outlet valves, the controller being connected to the monitoring module and the multiple coolant inlet and outlet valves respectively, the device comprising: The receiving unit is used to receive multiple sets of first battery parameters sent by the monitoring module. Each set of first battery parameters includes multiple battery operating parameters of the corresponding battery cell within a target time period. The multiple battery operating parameters include at least voltage, current, temperature, internal resistance, charge-discharge cycle count, state of charge (SOC), and state of health (SOH). A first determining unit is configured to perform the following operations for each of the plurality of battery cells to determine at least one battery cell in an abnormal heating state and its corresponding at least one target coolant flow rate: determining a reference heat generation of the battery cell in the target time period based on a first battery parameter set and a first heat mapping relationship corresponding to the currently processed battery cell, wherein the first heat mapping relationship is used to characterize the correspondence between the heat generation of the battery cell in different time periods and the plurality of battery operating parameters; if it is determined that the reference heat generation is outside a preset heat generation range, then the battery cell is determined to be in the abnormal heating state; acquiring the plurality of target battery operating parameters corresponding to the battery cell at the end time node of the target time period; determining the target coolant flow rate corresponding to the battery cell based on the plurality of target battery operating parameters and the first flow rate mapping relationship, wherein the first flow rate mapping relationship is used to characterize the correspondence between the coolant flow rate of the battery cell at different time nodes and the plurality of battery operating parameters; The second determining unit is used to determine at least one valve opening corresponding to the at least one target coolant flow rate, wherein the coolant flow rate is associated with the valve opening. A transmitting unit is configured to generate at least one control signal based on the opening degree of the at least one valve; and to transmit the at least one control signal to at least one coolant inlet / outlet valve corresponding to the at least one battery cell; The detection unit is used to detect that the absolute value of the difference between the temperature of any one of the plurality of battery cells and a preset temperature value is less than a preset threshold.

8. An electronic device, characterized in that, The method includes a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, the programs including instructions for performing the steps of the method of any one of claims 1-6.

9. A computer-readable storage medium having a computer program / instructions stored thereon, characterized in that, The computer program / instructions are executed by the processor to implement the steps of the method according to any one of claims 1-6.

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