Cooling liquid flow rate intelligent control method and device

Abstract

The invention discloses a cooling liquid flow rate intelligent control method and device. The method comprises the steps of receiving a plurality of first battery parameter sets sent by a monitoring module; determining at least one battery unit in an abnormal heating state and at least one target cooling liquid flow rate corresponding to the battery unit according to the plurality of first battery parameter sets, a preset first heat mapping relation and a preset first flow rate mapping relation; determining at least one valve opening degree corresponding to the at least one target cooling liquid flow rate; generating at least one control signal according to the at least one valve opening degree; at least one control signal is sent to at least one cooling liquid inlet and outlet valve corresponding to at least one battery unit; and detecting that the absolute value of the difference value between the temperature of any battery unit in the plurality of battery units and the preset temperature value is smaller than a preset threshold value. According to the invention, equalization and optimization of the battery temperature can be realized, the accuracy of temperature control is improved, and the energy storage efficiency is improved.

Description

Technical Field

[0001] The present application relates to the technical field of cooling control of energy storage batteries, and particularly relates to an intelligent control method and device for the flow rate of a coolant. Background Art

[0002] The performance and lifespan of energy storage batteries are closely related to temperature. Within an appropriate temperature range, the batteries can maintain a 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 batteries will change, which may lead to problems such as a decrease in battery capacity, an increase in internal resistance, and a reduction in charge-discharge efficiency.

[0003] Existing methods for controlling the flow rate of the coolant in energy storage systems often use a fixed flow rate or control based on a simple temperature threshold, without considering the actual heat generation of the batteries in different operating states, and cannot accurately adjust the flow rate according to the real-time operating parameters of the batteries, which may result in insufficient heat dissipation or excessive heat dissipation, affecting battery performance and system energy efficiency. In addition, traditional control methods are difficult to adjust the coolant flow rate in real time according to complex operating conditions changes, and cannot achieve the optimal heat dissipation effect and battery temperature control when facing different working scenarios. Summary of the Invention

[0004] The present application provides an intelligent control method and device for the flow rate of a coolant. By obtaining parameters such as the voltage, current, temperature, internal resistance, and battery health status of the batteries, and using the mapping relationship between these parameters and the heat release amount to determine the battery cells in an abnormal heat generation state, and based on the coupling relationship between the parameters and the coolant flow rate, dynamically adjust the coolant flow rate of the battery cells in abnormal heat generation. At the same time, by setting independent coolant flow control valves, different coolant flow rates can be provided for the corresponding battery areas, realizing the balance and optimization of the battery temperature, improving the flexibility and economy of the system, reducing energy loss, and enhancing the thermal management efficiency.

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

[0006] Receiving a plurality of first battery parameter sets sent by the monitoring module, where a single first battery parameter set includes a plurality of battery operating parameters of the corresponding battery cell within a target period;

[0007] Determine at least one battery cell in an abnormal heating state and its corresponding at least one target coolant flow rate among the multiple battery cells according to the multiple 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 represent the corresponding relationship between the heat generation amount of the battery cell in different time periods and the multiple battery operating parameters, and the first flow rate mapping relationship is used to represent the corresponding relationship between the coolant flow rate of the battery cell at different time nodes and the multiple battery operating parameters;

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

[0009] Generate at least one control signal according to the at least one valve opening; and send the at least one control signal to at least one of the coolant inlet and outlet valves corresponding to the at least one battery cell;

[0010] It is detected that the absolute value of the difference between the temperature of any one battery cell among the multiple battery cells and a preset temperature value is less than a preset threshold.

[0011] In a second aspect, an embodiment of the present application provides a coolant flow rate intelligent control device, which is 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. The energy storage battery pack includes multiple battery cells, and the multiple battery cells are correspondingly connected to the multiple coolant inlet and outlet valves. The controller is respectively connected to the monitoring module and the multiple coolant inlet and outlet valves. The device includes:

[0012] A receiving unit, configured to receive multiple first battery parameter sets sent by the monitoring module, and a single first battery parameter set includes multiple battery operating parameters of the corresponding battery cell in a target time period;

[0013] A first determination unit, configured to determine at least one battery cell in an abnormal heating state and its corresponding at least one target coolant flow rate among the multiple battery cells according to the multiple 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 represent the corresponding relationship between the heat generation amount of the battery cell in different time periods and the multiple battery operating parameters, and the first flow rate mapping relationship is used to represent the corresponding relationship between the coolant flow rate of the battery cell at different time nodes and the multiple battery operating parameters;

[0014] A second determination unit, configured to determine at least one valve opening corresponding to the at least one target coolant flow rate, and the coolant flow rate is associated with the valve opening;

[0015] A sending unit, configured to generate at least one control signal according to the at least one valve opening; and send the at least one control signal to at least one of the coolant inlet and outlet valves corresponding to the at least one battery cell.

[0016] A detecting unit, configured 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] In a third aspect, an embodiment of the present application provides an electronic device, including a processor, a memory, and one or more programs. The one or more programs are stored in the memory and configured to be executed by the processor. The programs include instructions for performing the steps in the first aspect of the embodiments of the present application.

[0018] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program / instructions are stored. The computer program / instructions are executed by a processor to implement the steps of the method described in the first aspect above.

[0019] It can be seen that in the embodiment of the present application, the controller receives a plurality of first battery parameter sets sent by the monitoring module. A single first battery parameter set includes a plurality of battery operating parameters of the corresponding battery cell during the target period; determines at least one battery cell in an abnormal heating state and its corresponding at least one target coolant flow rate among the plurality of battery cells according to the plurality of first battery parameter sets, a preset first heat mapping relationship, and a preset first flow rate mapping relationship; determines at least one valve opening corresponding to the at least one target coolant flow rate, where the coolant flow rate is associated with the valve opening; 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 of the coolant inlet and outlet valves corresponding to the at least one battery cell; detects 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. In this way, compared with the existing coolant flow rate control scheme that uses a fixed flow rate or is based on a simple temperature threshold, the present application can dynamically adjust the coolant flow rate in the corresponding battery area according to different parameter differences of the batteries, improve the temperature uniformity among the batteries, reduce energy consumption at the same time, improve the system economy, and extend the service life and safety of the system. Description of the Drawings

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0021] Figure 1 It is a system architecture diagram of an energy storage system provided by an embodiment of the present application;

[0022] Figure 2 It is a schematic structural diagram of an electronic device provided by an embodiment of the present application;

[0023] Figure 3 It is a structural block diagram of an energy storage system provided by an embodiment of the present application;

[0024] Figure 4 It is an overall flowchart of an intelligent control method for coolant flow rate provided by an embodiment of the present application;

[0025] Figure 5 It is a step flowchart of an intelligent control method for coolant flow rate provided by an embodiment of the present application;

[0026] Figure 6 It is a step flowchart of another intelligent control method for coolant flow rate provided by an embodiment of the present application;

[0027] Figure 7 It is an application scenario diagram of an intelligent control method for coolant flow rate provided by an embodiment of the present application;

[0028] Figure 8 It is a schematic diagram of functional modules of an intelligent control device for coolant flow rate provided by an embodiment of the present application. Detailed implementation manners

[0029] In order to enable those skilled in the art to better understand the solution of 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 in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present application.

[0030] The terms "first", "second", etc. in the specification, claims and above-mentioned drawings of the present application are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products or devices.

[0031] References to "embodiments" in this specification mean that the particular features, structures, or characteristics described in connection with the embodiments can be included in at least one embodiment of the present application. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0032] The "and / or" in the embodiments of the present application describes the association relationship of associated objects and indicates 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 the embodiments of the present application, the symbol " / " can represent an "or" relationship between the associated objects before and after. Additionally, the symbol " / " can also represent a division sign, that is, perform a division operation. For example, A / B can represent A divided by B.

[0034] The "at least one (item)" or its similar expressions in the embodiments of the present application refer to any combination of these items, including any combination of single items (pieces) or plural items (pieces), which means one or more, and multiple means two or more. For example, at least one (item) of a, b, or c can represent the following seven situations: a, b, c, a and b, a and c, b and c, a, b, and c. Among them, each of a, b, and c can be an element or a set containing one or more elements.

[0035] The "equal to" in the embodiments of the present application can be used in conjunction with "greater than" and is applicable to the technical solutions adopted when it is greater than, or can also be used in conjunction with "less than" and is applicable to the technical solutions adopted when it is less than. When "equal to" is used in conjunction with "greater than", it is not used in conjunction with "less than"; when "equal to" is used in conjunction with "less than", it is not used in conjunction with "greater than".

[0036] Existing intelligent control solutions for coolant flow rate all use fixed flow rate or simple temperature feedback control, and cannot be dynamically adjusted according to the actual working state of the battery, resulting in inaccurate battery temperature control and affecting battery performance and lifespan.

[0037] In view of the above problems, the embodiments of the present application provide an intelligent control method and device for coolant flow rate. The embodiments of the present application will be introduced in detail below with reference to the accompanying drawings.

[0038] Please refer to Figure 1 , Figure 1 is the system architecture diagram of an energy storage system provided by the embodiments of the present application. As Figure 1 shown, the system architecture diagram of the energy storage system includes a controller, a monitoring module, an energy storage battery pack, and multiple coolant inlet and outlet valves.

[0039] Among them, the energy storage battery pack is the core of the entire system, which is composed of multiple battery units (such as battery unit 1, battery unit 2 to battery unit n) and is used to store and release electrical energy. During actual operation, the battery units will generate heat during the charge and discharge process, and their heat generation situation is affected by various factors such as voltage, current, temperature, and internal resistance.

[0040] Among them, the monitoring module is connected to each battery unit in the energy storage battery pack through a circuit, and is used to collect multiple operating parameters of each battery unit during the target period in real time, such as voltage, current, temperature, SOC, SOH, etc.; and, the monitoring module sends the collected battery operating parameters to the controller after simple processing to provide data support for subsequent analysis and control.

[0041] Among them, the coolant inlet and outlet valves include multiple valves, and each battery unit corresponds to a coolant inlet and outlet valve (such as coolant inlet and outlet valve 1, coolant inlet and outlet valve 2 to coolant inlet and outlet valve n). The coolant flows into and out of the coolant pipeline or container connected to the battery unit through these coolant inlet and outlet valves, taking away the heat generated by the battery to achieve the regulation of the battery temperature; and, the coolant inlet and outlet valves are connected to the controller, and the valve opening can be regulated by the controller, thereby regulating the coolant flow rate.

[0042] Among them, the controller is respectively connected to the monitoring module and the coolant inlet and outlet valves. On the one hand, the controller is used to receive multiple sets of battery parameters sent by the monitoring module; on the other hand, based on the received sets of battery parameters, according to the preset first heat mapping relationship and the first flow rate mapping relationship, the controller analyzes and determines the battery units in an abnormal heating state and their corresponding target coolant flow rates, and then determines the opening of the corresponding valves, generates a control signal and sends it to the corresponding coolant inlet and outlet valves to achieve intelligent control of the coolant flow rate.

[0043] It can be seen that in this embodiment, through the connection and information interaction between the various parts of the entire energy storage system, the state of the battery units can be monitored in real time, and for the different parameter differences of the batteries, the coolant flow rate of the corresponding battery area can be adjusted separately, which is beneficial to improving the temperature uniformity between the batteries, ensuring that the energy storage battery pack operates within a suitable temperature range, and is beneficial to improving the performance and lifespan of the energy storage battery.

[0044] Please refer to Figure 2 , Figure 2 which is the structural block diagram of an electronic device provided by an embodiment of the present application and is used to execute the Figure 1 energy storage system in Figure 2As shown in the figure, 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 on the memory 23 and are configured to be executed by the processor 21. The one or more programs 231 include instructions for performing any step in the following method embodiments. In a specific implementation, the processor 21 is used to execute any step in the following method embodiments, and when performing data transmission such as sending, the communication interface 22 can be selectively called to complete the corresponding operation. Among them, the electronic device 20 may be a mobile phone terminal, a tablet computer, a laptop computer, and a wearable intelligent device.

[0045] It can be understood that the electronic device 20 may include more or fewer structural elements than those in the above structural block diagram. For example, it includes a power module, physical buttons, a Wi-Fi module, a speaker, a Bluetooth module, a sensor, etc., which are not limited herein.

[0046] Please refer to Figure 3 , Figure 3 is a structural block diagram of an energy storage system provided by an embodiment of the present application. As Figure 3 shown, the energy storage system 300 includes a monitoring module 310, an energy storage battery pack 320, a coolant inlet and outlet valve 330, and a controller 340.

[0047] Among them, 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 have differences in aspects such as energy density, charge and discharge efficiency, and cycle life.

[0048] Among them, the monitoring module 310 includes a sensor 311, a processing module 312, and a communication module 313. Among them, the sensor 311 is used to obtain the battery operation parameters of the battery cells 321 in the energy storage battery pack 320. Specifically, the temperature sensor is used to accurately measure the real-time temperature of the battery cells 321; the voltage and current sensors monitor the electrical parameters during the charge and discharge process of the battery in real time. Among them, the processing module 312 is used to perform pre-processing on a large amount of raw data transmitted by the sensor 311. For example, digital signal processing technology is used to remove noise and interference in the data, improving the accuracy and reliability of the data. At the same time, advanced algorithms are used to extract and analyze the data features. For example, the Kalman filter algorithm is used to process the voltage and current data of the battery, which can more accurately estimate the SOC of the battery. Among them, the communication module 313 is used to perform data transmission 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] Among them, the coolant inlet and outlet valve 330 includes a coolant inlet valve 331 and a coolant outlet valve 332, which jointly control the circulation of the coolant. The coolant plays a key role in heat dissipation in the energy storage system 300, and water-based or oil-based coolants are usually used. The coolant inlet valve 331 controls the inflow of low-temperature coolant into the cooling channels or containers closely connected to the battery unit 321, and the coolant outlet valve 332 controls the outflow of the high-temperature coolant after absorbing heat. The control methods of the valves include electric control and hydraulic control, etc. The electric valve adjusts the opening degree through the electrical signal sent by the controller 340 to achieve precise heat dissipation of the battery unit 321.

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

[0051] It can be seen that in this embodiment, the controller 340 determines the battery unit with abnormal heat generation and its corresponding valve opening degree based on the preset heat mapping relationship and flow rate mapping relationship through multiple parameters such as voltage, current, SOC, SOH, temperature, internal resistance, and number of cycles of the battery units 321 obtained, and then realizes dynamic control of the coolant flow rate of the energy storage battery pack 320 by controlling the valve opening degree, thereby improving the accuracy of battery temperature control.

[0052] Please refer to Figure 4 , Figure 4 which is the overall flowchart of an intelligent control method for coolant flow rate provided by an embodiment of the present application, and is applied to the Figure 1 controller in, as Figure 4 shown, the method includes the following steps:

[0053] Step S401: Receive multiple first battery parameter sets sent by the monitoring module, and a single first battery parameter set includes multiple battery operation parameters of the corresponding battery unit within the target time period.

[0054] Among them, the multiple battery operating parameters at least include voltage, current, temperature, internal resistance, number of charge and discharge cycles, state of charge (SOC), and state of health (SOH). Among them, the voltage, current, and temperature parameters are directly monitored by corresponding multiple types of sensors, and the internal resistance, state of charge (SOC), and state of health (SOH) need to be calculated based on the multiple battery operating parameters and battery configuration parameters. Specifically, the internal resistance can be calculated by the direct current internal resistance method or the alternating current internal resistance method; the state of charge (SOC) can be calculated by the Coulomb counting method, the voltage method, the Kalman filter method, or estimated by an electrochemical model, neural network fixation, etc.; the state of health (SOH) can be estimated by measuring the actual available capacity of the battery and comparing it with the initial capacity, by monitoring the change in internal resistance and combining with the empirical relationship with SOH or the established mathematical model, or by using machine learning algorithms such as support vector machines and random forests, inputting various parameters of the battery (such as voltage, current, temperature, number of cycles, etc.), and training the model to predict SOH and other methods. It should be clear that the embodiments of the present application do not limit the acquisition of multiple battery operating parameters only through the foregoing methods.

[0055] Specifically, within each battery parameter set, the multiple battery operating parameters can exist in the form of parameter curves. For example, the battery parameter set includes a voltage parameter curve, a current parameter curve, a temperature parameter curve, a state of charge (SOC) parameter curve, a state of health (SOH) parameter curve, etc. Among them, each parameter curve is used to characterize the change of the corresponding parameter over time within the target time period. It should be noted that this embodiment only gives one form of existence of the battery operating parameters, and the battery operating parameters can also exist in the form of a parameter-time comparison table, etc., as long as it can represent the change of the parameter within the target time period.

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

[0057] Receiving multiple reference battery parameter sets sent by the monitoring module, where a single reference battery parameter set includes multiple battery operating parameters of the corresponding battery unit within the historical time period;

[0058] Establishing the first heat mapping relationship according to the multiple reference battery sets, and the first heat mapping relationship is represented by the following formula (1):

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

[0060] Wherein, 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 and 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 operation period of the battery cell, and f is the functional relationship.

[0061] Wherein, the first heat mapping relationship is used to characterize the corresponding relationship between the heat generation of the battery cell in different periods and multiple battery operation parameters.

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

[0063] Receiving multiple sets of reference battery parameters sent by the monitoring module, where a single set of reference battery parameters includes multiple battery operation parameters of the corresponding battery cell in the historical period;

[0064] Establishing a heat inference model according to the multiple reference battery sets;

[0065] Determining the first heat mapping relationship according to the heat inference model.

[0066] Wherein, the first heat mapping relationship is a core component of the heat inference model. The main function of the heat inference model is to analyze the heat generation situation based on the changes in battery operation parameters. The heat inference model not only performs simple calculations using the first heat mapping relationship, but also expands it. For example, according to the actual application scenario, the weights of different parameters may be adjusted, or other non-electrical parameters (such as environmental humidity, etc.) may be combined to further optimize the inference of the heat generation.

[0067] In a possible embodiment, establishing a heat inference model includes theoretical modeling and data-driven modeling. Among them, theoretical modeling is used to establish a theoretical model of battery heat generation based on the electrochemical reaction principle and heat transfer principle of the battery. For example, the heat generated by the electrochemical reaction inside the battery can be calculated according to the enthalpy change of the reaction, and the heat generated through the internal resistance of the battery follows Joule's law; data-driven modeling is used to use a large amount of experimental data and adopt machine learning algorithms (such as multiple linear regression, neural network, decision tree, etc.) to establish the functional relationship between the heat generation Q and parameters such as voltage V, current I, temperature T, internal resistance R, number of cycles C, state of charge SOC, state of health SOH, etc. When training the model, the historical data is divided into a training set and a test set, and the model parameters are adjusted through an optimization algorithm (such as gradient descent method) to minimize the prediction error of the model on the test set.

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

[0069] Establish a reference flow rate mapping relationship according to the first heat mapping relationship, where the reference flow rate mapping relationship is used to characterize the corresponding relationship between the coolant flow rate, the heat generation of the battery cell, and the current instantaneous state;

[0070] Couple the reference flow rate mapping relationship according to the multiple battery operating parameters to obtain the first flow rate mapping relationship, and the first flow rate mapping relationship is expressed by the following formula:

[0071] q = K 1 V + K 2 I + K 3 T + K 4 R + K 5 C + K 6 SOC + K 7 SOH + q b ;

[0072] where q is the coolant flow rate of the battery cell, and K 1 -K 7 are the weight coefficients of the multiple battery operating parameters respectively, and q b is a constant term representing the system base coolant flow rate.

[0073] Among them, the first flow rate mapping relationship is used to characterize the corresponding relationship between the coolant flow rate of the battery cell at different time nodes and multiple battery operating parameters.

[0074] Among them, the reference flow rate 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 generation of the battery cell, α is the instantaneous state of the battery cell, and f is a functional relationship.

[0077] It can be understood that the reference flow rate mapping relationship is used to preliminarily determine the association between the coolant flow rate, the battery heat generation, and the current instantaneous state, providing a basic framework for the subsequent accurate calculation of the coolant flow rate. Among them, the instantaneous state of the battery cell may refer to the operating state of the battery cell at the end time node of the target time period when the battery cell is operating within the target time period. Further, by introducing multiple battery operating parameters corresponding to the instantaneous state and performing coupling, the first flow rate mapping relationship can be obtained. Among them, the weight coefficients K 1 to K 7 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] It can be seen that in this embodiment, the controller pre-calculates the first heat mapping relationship, can accurately predict the heat generation with the help of battery operating parameters, analyze the factors affecting the heat generation and warn of abnormalities; and, pre-calculates the first flow rate mapping relationship, can intelligently adjust the coolant flow rate based on multiple parameters, improve the efficiency of the thermal management system, and ensure battery performance and life.

[0079] Step S402, determining at least one battery cell in the multiple battery cells that is in an abnormally hot state and its corresponding at least one target coolant flow rate based on the multiple first battery parameter sets, the preset first heat mapping relationship and the preset first flow rate mapping relationship, 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 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 nodes and the multiple battery operating parameters.

[0080] In a possible embodiment, determining 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 according to the plurality of first battery parameter sets, the preset first heat mapping relationship, and the preset first flow rate mapping relationship includes:

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

[0082] Determine a reference heating value of the battery cell within the target time period according to a 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 heating value is outside the preset heating value range, it is determined that the battery unit is in the abnormal heating state;

[0084] Acquire a plurality of 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 unit is determined according to the plurality of target battery operating parameters and the first flow rate mapping relationship.

[0086] In a possible embodiment, the abnormal heating state includes an overheating state and an underheating state; if it is determined that the reference heating value is outside a preset heating value range, determining that the battery unit is in the abnormal heating state includes:

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

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

[0089] In a possible embodiment, if it is determined that the reference calorific value is outside the preset calorific value range, it is determined that the battery cell is in the state of abnormal heat generation, and the method further includes:

[0090] If it is determined that the reference calorific value is within the calorific value range, it is determined that the battery cell is in the state of normal heat generation;

[0091] Continue to obtain multiple sets of battery parameters corresponding to the multiple battery cells according to a preset period;

[0092] Based on the latest obtained multiple sets of battery parameters, repeatedly determine at least one battery cell in the state of abnormal heat generation and its corresponding at least one target coolant flow rate among the multiple battery cells according to the multiple sets of first battery parameters, a preset first heat mapping relationship, and a preset first flow rate mapping relationship; and determine at least one valve opening corresponding to the at least one target coolant flow rate, where the coolant flow rate is associated with the valve opening; and generate at least one control signal according to the at least one valve opening; and send the at least one control signal to at least one coolant inlet and outlet valve corresponding to the at least one battery cell.

[0093] Exemplarily, taking battery cell 3 as an example, the monitoring module sends a set of first battery parameters during a target period (assumed to be 30 minutes from 10:00 to 10:30), which includes multiple operating parameters such as voltage, current, and temperature. The controller substitutes these parameters of battery cell 3 during the target period into the first heat mapping relationship to calculate the reference calorific value of this battery cell within these 30 minutes. Suppose the calculation result is 800 J. A normal calorific value range is preset according to the type, specifications, and historical operating data of the battery, etc. For example, the normal calorific value range during this target period is 300 J - 600 J. Since the calculated reference calorific value of battery cell 3, 800 J, is greater than 600 J and exceeds the normal calorific value range, it can be determined that battery cell 3 is in the state of abnormal heat generation.

[0094] Further, continuing with the battery cell 3 as an example, the controller obtains multiple target battery operating parameters corresponding to the termination time node (i.e., 10:30) of the target period. For example, the voltage at this time is 3.8V, the current is 70A, the temperature is 40°C, etc. The controller substitutes the target battery operating parameters of the battery cell 3 at 10:30 just obtained according to the first flow rate mapping relationship. Assuming that through calculation, it is obtained that the target coolant flow rate corresponding to the battery cell 3 at this time is 12L / min, it means that in order to restore the temperature of the battery cell 3 to normal, the 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, where the coolant flow rate is associated with the valve opening.

[0096] Among them, the association relationship between the coolant flow rate and the valve opening can be expressed by the following formula:

[0097] D = f(q);

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

[0099] Exemplarily, the degree of valve opening and closing is linearly related to the coolant flow rate. In practical applications, the function f(q) can be a linear function obtained through experiments or theoretical derivations. For example, D = kq + b (k and b are constants), and the values of k and b are determined according to the specific system characteristics. If it is determined through experiments that the function f(q) in this system is D = 0.1q, substituting the target coolant flow rate q = 12L / min of the battery cell 3, the opening and closing degree D of the solenoid valve can be obtained as D = 0.1×12 = 1.2. Among them, the "1.2" here is a relative value obtained according to the set calculation method, representing a certain degree of opening and closing.

[0100] Among them, the controller also has an algorithm optimization function, which can use the genetic algorithm to analyze the situation of the solenoid valve opening degree and the implementation effect temperature in the energy storage system, perform parameter optimization, improve the temperature control accuracy, and balance the battery temperature and energy consumption at the same time.

[0101] Step S404, generate at least one control signal according to the at least one valve opening; and send the at least one control signal to at least one of the coolant inlet and outlet valves corresponding to the at least one battery cell.

[0102] Step S405, detect 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.

[0103] In a possible embodiment, when 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 a preset threshold, the method further includes:

[0104] At a first time node, it is detected that the absolute value of the difference between the temperature of at least one of the multiple 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 period is greater than a first preset value, to obtain a first judgment result;

[0106] Perform different coolant flow rate regulation operations according to the first judgment result, so as to detect at a 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, where the second time node is later than the first time node.

[0107] In a possible embodiment, the performing different coolant flow rate regulation operations according to the first judgment result includes:

[0108] Determine according to the first judgment result that the time interval between the first time node and the end time node of the target period is greater than the first preset value;

[0109] Send a first message to the monitoring module, where the first message is used to instruct the monitoring module to send multiple second battery parameter sets to the controller, and a single second battery parameter set includes multiple battery operation parameters of the corresponding battery cell during a second period, and the second period is earlier than the first time node;

[0110] Determine the second battery cells in the abnormal heating state and their corresponding second coolant flow rates during the second period according to the received multiple second battery parameter sets, the first heat mapping relationship, and the first flow rate mapping relationship; and determine the second valve opening corresponding to the second coolant flow rate; and,

[0111] Generate a second control signal according to the second valve opening; and send the second control signal to the coolant inlet and outlet valve corresponding to the second battery cell;

[0112] At the second time node, it is detected 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.

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

[0114] Determine 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 according to the first judgment result;

[0115] At the first time node, repeatedly determine at least one battery cell in an abnormal heating state and its corresponding at least one target coolant flow rate among the plurality of battery cells according to the plurality of first battery parameter sets, a preset first heat mapping relationship, and a preset first flow rate mapping relationship; and determine at least one valve opening corresponding to the at least one target coolant flow rate, where the coolant flow rate is associated with the valve opening; and generate at least one control signal according to the at least one valve opening; and send the at least one control signal to at least one of the coolant inlet and outlet valves 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 a preset temperature value is less than the preset threshold.

[0117] Exemplarily, set the target time period to be from 9:00 - 9:30, and the first preset value to be 10 minutes. At 9:55 (the first time node), it is detected that the absolute value of the temperature difference of battery cell 5 is greater than the preset threshold. At this time, calculate the time interval between 9:55 and 9:30 to be 25 minutes, which is greater than the first preset value of 10 minutes. Then the controller sends a first message to the monitoring module, instructing the monitoring module to send the operating parameters of the plurality of battery cells during 9:20 - 9:50 (the second time period); and assume that through analysis, it is found that battery cell 5 is in an abnormal heating state during 9:20 - 9:50, calculate the second coolant flow rate to be 15 L / min, and the corresponding second valve opening to be 0.8 (assumed relative value). Furthermore, generate a second control message based on the second valve opening of 0.8 and send it to the coolant inlet and outlet valve corresponding to the second battery cell (i.e., battery cell 5). Finally, at a second time node later than 9:55, such as at 10:00, it is detected again that the absolute value of the difference between the temperatures of all battery cells and the preset temperature value is less than the preset threshold.

[0118] Exemplarily, if the absolute value of the temperature difference of the battery unit 5 is detected to be greater than the preset threshold at 9:40 (the first time node), the time interval between 9:40 and 9:30 is calculated to be 10 minutes at this time, which is equal to the first preset value of 10 minutes. Then, since the time interval is too small and the operating parameters of the energy storage battery change little, there is no need to re-acquire the battery parameter set. The operations of determining the battery unit in an abnormal heating state according to multiple first battery parameter sets, the preset first heat mapping relationship, and the preset first flow rate mapping relationship, and determining the corresponding coolant flow rate and valve opening and sending a control signal are repeatedly executed. For example, recalculate the current operating parameters of each battery unit, determine that the battery unit 5 is still in an abnormal heating state, re-determine the appropriate coolant flow rate and valve opening, and send a control signal to adjust the coolant inlet and outlet valves. Finally, at the second time node, such as 9:45, it is detected that the absolute value of the difference between the temperatures of all battery units and the preset temperature value is less than the preset threshold.

[0119] It can be seen that in this embodiment, based on the battery operating parameters, the controller monitors the voltage and current of the battery in real time, obtains the working state of the battery, including parameters such as charge and discharge state, power output, and battery health status, and uses the coupling relationship between these parameters and the coolant flow rate to dynamically adjust the coolant flow rate. At the same time, by setting an independent coolant flow control valve, different coolant flow rates can be provided for the corresponding battery areas, achieving the balance and optimization of the battery temperature, improving the flexibility and economy of the system, reducing energy loss, and enhancing the efficiency of the energy storage system.

[0120] Please refer to Figure 5 , Figure 5 which is the step flow chart of an intelligent control method for coolant flow rate provided by an embodiment of the present application. As Figure 5 shown, the method includes the following steps:

[0121] Step S501, periodically receive the battery parameter set sent by the monitoring module.

[0122] In a possible embodiment, before the step of 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, and a single reference battery parameter set includes multiple battery operating parameters of the corresponding battery unit in the historical period; establishing a first heat mapping relationship according to the multiple reference battery sets, and the first heat mapping relationship is represented by the following formula (1): Q = f(V, I, T, R, C, SOC, SOH, t); where Q is the heat generation of the battery unit, V is the voltage of the battery unit, I is the current of the battery unit, T is the temperature of the battery unit, R is the internal resistance of the battery unit, C is the charge and discharge cycle times of the battery unit, SOC is the state of charge of the battery unit, SOH is the health state of the battery unit, t is the operating period of the battery unit, and f is the functional relationship.

[0123] In a possible embodiment, before periodically receiving the set of battery parameters sent by the monitoring module, the method further includes: establishing a reference flow rate mapping relationship according to the first heat mapping relationship, where the reference flow rate mapping relationship is used to characterize the corresponding relationship between the coolant flow rate, the heat generation amount of the battery cell, and the current instantaneous state; coupling the reference flow rate mapping relationship according to the multiple battery operating parameters to obtain the first flow rate mapping relationship, and the first flow rate mapping relationship is represented by the following formula: q = K 1 V + K 2 I + K 3 T + K 4 R + K 5 C + K 6 SOC + K 7 SOH + q b ; where q is the coolant flow rate of the battery cell, and K 1 -K 7 are respectively the weight coefficients of the multiple battery operating parameters, and q b is a constant term representing the system base coolant flow rate.

[0124] Among them, the first heat mapping relationship is used to characterize the corresponding relationship between the heat generation amount of the battery cell in different time periods and the multiple battery operating parameters, and the first flow rate mapping relationship is used to characterize the corresponding relationship between the coolant flow rate of the battery cell at different time nodes and the multiple battery operating parameters.

[0125] Step S502, after receiving the set of battery parameters each time, determine the battery cells with abnormal heat generation and their corresponding target coolant flow rates according to the set of battery parameters, the first heat mapping relationship, and the first flow rate mapping relationship.

[0126] In a possible embodiment, the determining the battery cells with abnormal heat generation and their corresponding target coolant flow rates according to the set of battery parameters, the first heat mapping relationship, and the first flow rate mapping relationship includes: performing the following operations for each battery cell among the multiple battery cells to determine at least one battery cell in an abnormal heat generation state and its corresponding at least one target coolant flow rate: determining the reference heat generation amount of the battery cell in the target time period according to 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 amount is outside the preset heat generation amount interval, determining that the battery cell is in the abnormal heat generation state; obtaining the multiple 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 according to the multiple 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 unit.

[0128] Among them, the correlation between the coolant flow rate and the valve opening can be expressed by the following formula: D = f(q); where D represents the valve opening of the coolant inlet and outlet, q represents the coolant flow rate of the battery unit, and f is the functional relationship.

[0129] Step S504: Detect whether the temperatures of multiple battery units are balanced.

[0130] Specifically, if so, execute Step S501, and if not, execute Step S505.

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

[0132] Furthermore, after Step S505 is executed, continue to execute Step S504 to continuously detect whether the temperatures of multiple battery units are balanced.

[0133] In a possible embodiment, the re-determining the battery unit with abnormal heat generation and its corresponding valve opening, and sending a control signal to the battery unit 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 battery unit among the multiple battery units and the preset temperature value is greater than the preset threshold; judging whether the time interval between the first time node and the end time node of the target period is greater than a first preset value to obtain a first judgment result; performing different coolant flow rate regulation operations according to the first judgment result to achieve detecting at a second time node that the absolute value of the difference between the temperature of any one battery unit among the multiple battery units and the preset temperature value is less than the preset threshold, and the second time node is later than the first time node.

[0134] It can be understood that when it is detected at a certain time node that there are battery units with too high or too low temperatures, it is necessary to re-detect the abnormal heat generation of the battery units. However, due to various factors, such as battery unit performance, electrical connection relationship, etc., the time interval between the time node when the temperature imbalance is detected and the target time corresponding to the battery parameter set collected in this detection may be too large or too small. Therefore, it is necessary to adopt different methods based on the size of the time interval to re-determine the battery unit with abnormal heat generation and its corresponding valve opening and adjust the coolant flow rate, so as to differentially process the temperature imbalance in different situations, and then be able to achieve more intelligent and efficient adjustment of the coolant flow rate for the energy storage system.

[0135] Please refer toFigure 6 , Figure 6 is the flowchart of steps of another intelligent control method for coolant flow rate provided by an embodiment of the present application. As shown in Figure 6 , this method is a sub-step for step S505 in Figure 5 , and this method includes the following steps:

[0136] Step S601: Detect that the temperatures of multiple battery cells are unbalanced, and determine the time interval between the current time node and the end time node of the target period.

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

[0138] Specifically, if not, then execute step S603; and if so, then execute step S604.

[0139] Step S603: Based on the first battery parameter set again, determine the battery cell with abnormal heat generation and its corresponding valve opening degree, and generate a control signal according to the valve opening degree and send the control signal to the battery cell.

[0140] Exemplarily, set the target period from 9:00 - 9:30, and the first preset value is 10 minutes. At 9:40 (the first time node), it is detected that the absolute value of the temperature difference of battery cell 5 is greater than the preset threshold. At this time, calculate the time interval between 9:40 and 9:30 as 10 minutes, which is equal to the first preset value of 10 minutes. Then repeat the operation of determining the battery cell in the abnormal heat generation state according to multiple first battery parameter sets, the preset first heat mapping relationship, and the preset first flow rate mapping relationship, and determining the corresponding coolant flow rate, valve opening degree, and sending the control signal. For example, recalculate the current operating parameters of each battery cell, determine that battery cell 5 is still in the abnormal heat generation state, re-determine the appropriate coolant flow rate and valve opening degree, and send a control signal to adjust the coolant inlet and outlet valves.

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

[0142] Wherein, the first message is used to instruct the monitoring module to send multiple second battery parameter sets to the controller. A single second battery parameter set includes multiple battery operating parameters of the corresponding battery cell within the second period, and the second period 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 heat generation and its corresponding second coolant flow rate according to the second battery parameter set, the first heat mapping relationship, and the first flow rate mapping relationship.

[0145] In a possible embodiment, determining the second battery cell with abnormal heating and its corresponding second coolant flow rate according to 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 multiple battery cells to determine the second battery cell with abnormal heating and its corresponding second coolant flow rate: determining a reference heating value of the battery cell within the target time period according to 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 heating value is outside a preset heating value range, determining that the battery cell is the second battery cell; obtaining multiple 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 according to the multiple target battery operating parameters and the first flow rate mapping relationship.

[0146] Step S607, determining a second valve opening corresponding to a second coolant flow rate, and generating a second control signal based on the second valve opening and sending the second control signal to the coolant inlet and outlet valves corresponding to the second battery unit.

[0147] Exemplarily, the target time period is set from 9:00-9:30, and the first preset value is 10 minutes. At 9:55 (the first time node), it is detected that the absolute value of the temperature difference of the battery cell 5 is greater than the preset threshold. At this time, 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 a first message 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 it is found through analysis that the battery cell 5 is in an abnormal heating state from 9:20 to 9:50, the second coolant flow rate is calculated to be 15L / min, and the corresponding second valve opening is 0.8 (the assumed relative value), and then the second control information is generated based on the second valve opening of 0.8, and sent to the coolant inlet and outlet valves corresponding to the second battery cell (i.e., battery cell 5).

[0148] It can be seen that in this embodiment, different schemes are used based on different time intervals to re-determine the abnormally hot battery cells and adjust the coolant flow rate, which can adapt to different battery operating conditions. For example, in an energy storage system with strict requirements on battery temperature stability, when it is found that the first regulation is not effective, a second regulation is quickly performed based on the same target period data, which can quickly respond to and stabilize the battery temperature. For example, in an electric vehicle energy storage system, the operating conditions are constantly changing during vehicle driving and the working state of the battery also changes accordingly. When a second coolant flow rate regulation is required, the use of new target period data can better adapt to the changes, which is conducive to improving the accuracy and effectiveness of coolant flow rate regulation.

[0149] Please refer to Figure 7 , Figure 7 which is an application scenario diagram of an intelligent control method for coolant flow rate provided by an embodiment of the present application. As shown in Figure 7 , this application scenario diagram is an actual application scenario diagram of an energy storage system. The energy storage system includes a controller 710, a monitoring module 720, a battery unit 730, a cooling module 740, and a coolant storage tank 750.

[0150] Among them, the energy storage system includes a plurality of battery units 730 and a plurality of cooling modules 740. Each cooling module 740 is closely attached to the lower end surface of the battery unit 730 for cooling the battery unit. Among them, the cooling module 740 includes a pipeline 741, a coolant inlet valve 742, and a coolant outlet valve 743. The pipeline 741 is respectively connected to the coolant storage tank 750 through the coolant inlet valve 742 and the coolant outlet valve 743. Cold water in the coolant storage tank 750 is introduced into the pipeline 741 of the cooling module through the coolant outlet valve 743 to cool the battery unit 730, and, through the coolant outlet valve 743, the cold water in the pipeline 741 of the cooling module is drained back to realize water circulation.

[0151] Among them, the monitoring module 720 is respectively connected to a plurality of battery units 730. The monitoring module 720 is used to obtain a plurality of battery operation parameters of the battery unit 730 during a target period and perform preliminary processing to form a battery parameter set; and, to send the plurality of battery parameter sets to the controller 710.

[0152] Among them, the controller 710 is respectively connected to the monitoring module 720, the coolant inlet valve 742, and the coolant outlet valve 743. The controller 710 is used to perform data interaction with the monitoring module 720 and receive the battery parameter set corresponding to the battery unit 730 sent by the monitoring module 720; and, according to the received battery parameter set, based on a preset first heat mapping relationship and a first flow rate mapping relationship, analyze and determine the battery unit in an abnormal heating state and its corresponding target coolant flow rate, and then determine the opening degrees of the corresponding coolant inlet valve 742 and / or coolant outlet valve 743, generate a control signal and send it to the corresponding valve to realize intelligent control of the coolant flow rate.

[0153] It can be seen that in this embodiment, through the connection and information interaction between various parts of the entire energy storage system, the state of the battery unit can be monitored in real time, and for different parameter differences of the batteries, the coolant flow rate in the corresponding battery area can be adjusted separately, which is beneficial to improving the temperature uniformity between the batteries, ensuring that the energy storage battery pack operates within a suitable temperature range, and is beneficial to improving the performance and lifespan of the energy storage battery.

[0154] Please refer to Figure 8 , Figure 8Schematic diagram of functional modules of an intelligent coolant flow rate control device 8 provided by an embodiment of the present application, as Figure 8 shown, the intelligent coolant flow rate control device 8 includes the following units:

[0155] A receiving unit 801, configured to receive a plurality of first battery parameter sets sent by the monitoring module, and a single first battery parameter set includes a plurality of battery operation parameters of the corresponding battery unit within a target period;

[0156] A first determination unit 802, configured to determine at least one battery unit in an abnormal heating state and its corresponding at least one target coolant flow rate among the plurality of battery units according to 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 generation amount of the battery unit at different times and the plurality of battery operation parameters, and the first flow rate mapping relationship is used to characterize the correspondence between the coolant flow rate of the battery unit at different time nodes and the plurality of battery operation parameters;

[0157] A second determination unit 803, configured to determine at least one valve opening corresponding to the at least one target coolant flow rate, and the coolant flow rate is associated with the valve opening;

[0158] A sending unit 804, configured to generate at least one control signal according to the at least one valve opening; and send the at least one control signal to at least one of the coolant inlet and outlet valves corresponding to the at least one battery unit;

[0159] A detection unit 805, configured to detect that the absolute value of the difference between the temperature of any one of the plurality of battery units 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 among the plurality of battery cells according to 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 battery cell among the plurality of battery cells to determine the at least one battery cell in the abnormal heating state and its corresponding at least one target coolant flow rate: determining a reference heat generation amount of the battery cell during the target period according to 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 amount is outside a preset heat generation amount interval, 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 termination time node of the target period; and determining the target coolant flow rate corresponding to the battery cell according to the plurality of target battery operating parameters and the first flow rate mapping relationship.

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

[0162] In one embodiment, performing different coolant flow rate regulation operations according to the first judgment result includes: determining, according to the first judgment result, that the time interval between the first time node and the end time node of the target period is greater than the first preset value; sending a first message to the monitoring module, the first message being used to instruct the monitoring module to send multiple sets of second battery parameters to the controller, and a single set of second battery parameters includes multiple battery operation parameters of the corresponding battery unit within a second period, and the second period is earlier than the first time node; determining, according to the received multiple sets of second battery parameters, the first heat mapping relationship, and the first flow rate mapping relationship, the second battery unit in the abnormal heating state and its corresponding second coolant flow rate within the second period; and determining the second valve opening corresponding to the second coolant flow rate; and generating a second control signal according to the second valve opening; and sending the second control signal to the coolant inlet and outlet valve corresponding to the second battery unit; detecting, at the second time node, that the absolute value of the difference between the temperature of any one of the multiple battery units and the preset temperature value is less than the preset threshold value.

[0163] In one embodiment, the method further includes: determining, according to the first judgment result, that the time interval between the first time node and the end time node of the target period is less than or equal to the first preset value; repeating, at the first time node, determining, according to the multiple sets of first battery parameters, the preset first heat mapping relationship, and the preset first flow rate mapping relationship, at least one battery unit in the abnormal heating state among the multiple battery units and its corresponding at least one target coolant flow rate; and determining at least one valve opening corresponding to the at least one target coolant flow rate, the coolant flow rate being associated with the valve opening; and generating at least one control signal according to the at least one valve opening; and sending the at least one control signal to at least one of the coolant inlet and outlet valves corresponding to the at least one battery unit; detecting, at the second time node, that the absolute value of the difference between the temperature of any one of the multiple battery units and the preset temperature value is less than the preset threshold value.

[0164] In one embodiment, the multiple battery operating parameters at least include voltage, current, temperature, internal resistance, number of charge and discharge cycles, state of charge (SOC), and state of health (SOH). Before receiving the multiple first battery parameter sets sent by the monitoring module, the method further includes: receiving the multiple reference battery parameter sets sent by the monitoring module, where a single reference battery parameter set includes multiple battery operating parameters of the corresponding battery cell within a historical period; establishing the first heat mapping relationship according to the multiple reference battery sets, and the first heat mapping relationship is represented 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 and 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 a functional relationship.

[0165] In one embodiment, the method further includes: establishing a reference flow rate mapping relationship according to the first heat mapping relationship, where the reference flow rate mapping relationship is used to characterize the corresponding relationship between the coolant flow rate and the heat generation and the current instantaneous state of the battery cell; coupling the reference flow rate mapping relationship according to the multiple battery operating parameters to obtain the first flow rate mapping relationship, and the first flow rate mapping relationship is represented by the following formula: q = K 1 V + K 2 I + K 3 T + K 4 R + K 5 C + K 6 SOC + K 7 SOH + q b ; where q is the coolant flow rate of the battery cell, K 1 -K 7 are respectively the weight coefficients of the multiple battery operating parameters, and q b is a constant term representing the system base coolant flow rate.

[0166] It can be understood that since the method embodiment and the device embodiment are different presentation forms of the same technical concept, the content of the method embodiment part in this application should be synchronously adapted to the device embodiment part, and will not be elaborated here.

[0167] It can be seen that the controller of the device determines the battery cells in an abnormal heating state by obtaining parameters such as the voltage, current, temperature, internal resistance, and battery health status of the battery, and uses the mapping relationship between these parameters and the heat release amount. Based on the coupling relationship between the parameters and the coolant flow rate, the coolant flow rate of the battery cells with abnormal heating is dynamically adjusted. At the same time, by setting an independent coolant flow control valve, different coolant flow rates can be provided for the corresponding battery areas, achieving the balance and optimization of the battery temperature, improving the flexibility and economy of the system, reducing energy loss, and enhancing the thermal management efficiency.

[0168] In addition, the embodiment of the present application also provides a computer storage medium, which stores a computer program that can be loaded and executed by a processor and is used for the intelligent control method of the coolant flow rate as described above. The computer-readable storage medium includes, for example: various media that can store program codes such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical discs.

[0169] It should be noted that, for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the present application is not limited by the described action sequence, because according to the present application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the present application.

[0170] In several embodiments provided by the present application, it should be understood that the disclosed methods, devices, and systems can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for example, the division of the units is only a logical function division, and there can be other division methods in actual implementation; for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed mutual coupling or direct coupling or communication connection can be through some interfaces, and the indirect coupling or communication connection of the device or unit can be in an electrical, mechanical, or other form.

[0171] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0172] In addition, in each embodiment of the present invention, each functional unit can be integrated into one processing unit, or each unit can be physically included separately, or two or more units can be integrated into one unit. The above integrated unit can be implemented in the form of hardware, or in the form of a hardware plus software functional unit.

[0173] The above integrated unit implemented in the form of a software functional unit can be stored in a computer-readable storage medium. The above software functional unit stored in a storage medium includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute some steps of the methods described in each embodiment of the present invention. The foregoing storage medium includes: USB flash drive, mobile hard disk, magnetic disk, optical disk, volatile memory, or non-volatile memory. Among them, 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 (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct rambus random access memory (DRRAM), etc., all of which are various media that can store program code.

[0174] In the above embodiments, the descriptions of each embodiment have their own emphases. For parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0175] The above has introduced the embodiments of the present application in detail. Specific examples are used in this text to elaborate on the principle and implementation manner of the present application. The description of the above embodiments is only used to help understand the method and its core idea of the present application; at the same time, for those of ordinary skill in the art, according to the idea of the present application, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present application.

[0176] Although the present application is disclosed as above, the present application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions without departing from the spirit and scope of the present application, and can make various changes and modifications, including combinations of the above different functions and implementation steps, including software and hardware implementation manners, which are all within the protection scope of the present application.

Claims

1. A coolant flow rate intelligent control method, characterized in that: A controller applied to an energy storage system, wherein the energy storage system further comprises a monitoring module, an energy storage battery pack and a plurality of coolant inlet and outlet valves, wherein the monitoring module is connected to the energy storage battery pack, the energy storage battery pack comprises a plurality of battery cells, the plurality of battery cells are correspondingly connected to the plurality of coolant inlet and outlet valves, the controller is respectively connected to the monitoring module and the plurality of coolant inlet and outlet valves, and the method comprises: receiving a plurality of first battery parameter sets sent by the monitoring module, wherein a single first battery parameter set includes a plurality of battery operating parameters of a corresponding battery unit within a target time period; 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 according to the plurality of first battery parameter sets, the preset first heat mapping relationship, and the preset first flow rate mapping relationship, 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, 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 nodes and the plurality of battery operating parameters; Determining at least one valve opening corresponding to the at least one target coolant flow rate, the coolant flow rate being associated with the valve opening; Generate at least one control signal according to the at least one valve opening; and send the at least one control signal to at least one coolant inlet and outlet valve corresponding to the at least one battery cell; It is detected 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 smaller than a preset threshold.

2. The method according to claim 1, characterized in that The determining, according to 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 includes: Performing the following operations for each of the plurality of battery cells to determine at least one battery cell in an abnormal heating state and at least one corresponding target coolant flow rate: Determine a reference heating value of the battery cell within the target time period according to a first battery parameter set corresponding to the currently processed battery cell and the first heat mapping relationship; If it is determined that the reference heating value is outside the preset heating value range, it is determined that the battery unit is in the abnormal heating state; Acquire a plurality of target battery operating parameters corresponding to the battery unit at the end time node of the target time period; The target coolant flow rate corresponding to the battery unit is determined according to the plurality of target battery operating parameters and the first flow rate mapping relationship.

3. The method according to claim 1 or 2, characterized in that: The method further comprises: 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 value; It is detected at a first time node that the absolute value of the difference between the temperature of at least one battery cell among 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; Different coolant flow rate control operations are performed according to the first judgment result to achieve that at a second time node, it is detected 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.

4. The method according to claim 3, characterized in that The performing different coolant flow rate control operations according to the first judgment result includes: Determine, according to the first judgment result, that the time interval between the first time node and the end time node of the target period is greater than the first preset value; Sending first information to the monitoring module, wherein the first information is used to instruct the monitoring module to send a plurality of second battery parameter sets to the controller, wherein a single second battery parameter set includes a plurality of battery operating parameters of a corresponding battery unit in a second time period, and the second time period is earlier than the first time node; Determine the second battery unit in the abnormal heating state and its corresponding second coolant flow rate in the second time period according to the received multiple second battery parameter sets, the first heat mapping relationship and the first flow rate mapping relationship; and determine the second valve opening corresponding to the second coolant flow rate; and, generating a second control signal according to the second valve opening; and sending the second control signal 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 a preset temperature value is less than the preset threshold.

5. The method according to claim 4, characterized in that The method further comprises: Determine, according to the first judgment result, that the time interval between the first time node and the end time node of the target period is less than or equal to the first preset value; Repeating at the first time node, determining at least one battery cell in the plurality of battery cells that is in an abnormally hot state and at least one target coolant flow rate corresponding thereto according to the plurality of first battery parameter sets, the preset first heat mapping relationship, and the preset first flow rate mapping relationship; and determining at least one valve opening corresponding to the at least one target coolant flow rate, the coolant flow rate being associated with the valve opening; and generating at least one control signal according to the at least one valve opening; and sending the at least one control signal to at least one coolant inlet and 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 a preset temperature value is less than the preset threshold.

6. The method according to any one of claims 2 to 4, characterized in that: The multiple battery operating parameters include at least voltage, current, temperature, internal resistance, number of charge and discharge cycles, state of charge SOC and state of health SOH. Before receiving the multiple first battery parameter sets sent by the monitoring module, the method further includes: receiving a plurality of reference battery parameter sets sent by the monitoring module, wherein a single reference battery parameter set includes a plurality of battery operating parameters of a corresponding battery unit within a historical period; The first heat mapping relationship is established according to the multiple reference battery sets, and the first heat mapping relationship is expressed by the following formula (1): Q = f(V,I,T,R,C,SOC,SOH,t); Among them, 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 and 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 functional relationship.

7. The method according to claim 6, characterized in that The method further comprises: Establishing a reference flow rate mapping relationship according to the first heat mapping relationship, wherein the reference flow rate mapping relationship is used to characterize the corresponding relationship between the coolant flow rate and the heat generation of the battery unit and the current instantaneous state; The reference flow rate mapping relationship is coupled according to the multiple battery operation parameters to obtain the first flow rate mapping relationship, and the first flow rate mapping relationship is expressed by the following formula: q=K1V+K2I+K3T+K4R+K5C+K6SOC+K7SOH+q b ; Wherein, q is the coolant flow rate of the battery unit, K1-K7 are the weight coefficients of the multiple battery operating parameters, q b is a constant term representing the base coolant flow rate of the system.

8. A coolant flow rate intelligent control device, characterized in that: A controller applied to an energy storage system, wherein the energy storage system further comprises a monitoring module, an energy storage battery pack and a plurality of coolant inlet and outlet valves, wherein the monitoring module is connected to the energy storage battery pack, the energy storage battery pack comprises a plurality of battery cells, the plurality of battery cells are correspondingly connected to the plurality of coolant inlet and outlet valves, the controller is respectively connected to the monitoring module and the plurality of coolant inlet and outlet valves, and the device comprises: A receiving unit, configured to receive a plurality of first battery parameter sets sent by the monitoring module, wherein a single first battery parameter set includes a plurality of battery operating parameters of a corresponding battery unit within a target time period; A first determination unit, configured to determine at least one battery cell in an abnormally heated state among the plurality of battery cells and at least one corresponding target coolant flow rate thereof according to the plurality of first battery parameter sets, a preset first heat mapping relationship, and a preset first flow rate mapping relationship, 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, 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 nodes and the plurality of battery operating parameters; A second determination unit, configured 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 sending unit, configured to generate at least one control signal according to the at least one valve opening; and send the at least one control signal to at least one coolant inlet and 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 value.

9. An electronic device, characterized in that: The method comprises 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, and the programs include instructions for executing the steps in any one of the methods of claims 1 to 7.

10. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: The computer program / instructions are executed by a processor to implement the steps of the method according to any one of claims 1 to 7.

Images