Thermal management energy efficiency grade determination method and device, electronic equipment and storage medium

Abstract

The invention provides a thermal management energy efficiency grade determination method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining the temperature data of an energy storage container, the operation condition data of the energy storage container, the control parameters of thermal management equipment, and the energy consumption data of the thermal management equipment, and determining the energy consumption of the thermal management equipment according to the temperature data of the energy storage container and the power of the operation condition; determining a thermal management energy efficiency score according to the operation time of the operation condition, the control parameters of the thermal management equipment and the energy consumption data of the thermal management equipment; and determining a target thermal management energy efficiency level according to the thermal management energy efficiency score and a corresponding relationship between the thermal management energy efficiency score and the thermal management energy efficiency level. According to the method, the thermal management energy efficiency score is determined by acquiring the temperature data and the operation condition data of the energy storage container and the control parameters and the energy consumption data of the thermal management equipment, energy efficiency evaluation is comprehensively performed on the thermal management system through the data, and the energy efficiency of the thermal management system can be accurately and comprehensively evaluated compared with only consideration of a single factor.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of thermal management technology, and in particular to a method, device, electronic device and storage medium for determining a thermal management energy efficiency level. Background Art

[0002] With the global emphasis on and development of renewable energy, energy storage power stations are increasingly being used. Energy storage power stations play a vital role in the power system, for example, in smoothing out the intermittent nature of renewable energy generation, improving the stability of the power system, and achieving load regulation.

[0003] Among the many components of an energy storage power station, the thermal management system cannot be ignored. The thermal management system is crucial to ensuring the efficient and stable operation of the energy storage power station. This is because the energy storage equipment in the energy storage power station will generate heat during the charging and discharging process. If the heat cannot be effectively managed, it will have a serious impact on the performance and safety of the energy storage equipment. For example, excessively high temperatures may reduce the service life of the energy storage equipment, reduce the charging and discharging efficiency, and even cause safety accidents. Therefore, the thermal management system plays a vital role in the energy storage power station, and its operating energy efficiency is directly related to the safety, stability and economy of the energy storage power station. How to evaluate the energy efficiency of the thermal management system is particularly important. Summary of the invention

[0004] In view of the above problems, a method, device, electronic device and storage medium for determining a thermal management energy efficiency level are proposed to overcome the above problems or at least partially solve the above problems, including:

[0005] In a first aspect, an embodiment of the present application provides a method for determining a thermal management energy efficiency level, which is applied to an energy storage power station, wherein the energy storage power station includes a plurality of energy storage containers, and the energy storage containers include a thermal management device. The method includes:

[0006] Acquire temperature data of any of the energy storage containers, operating condition data of the energy storage container, control parameters of the thermal management device, and energy consumption data of the thermal management device, wherein the operating condition data includes the power of the operating condition and the operating time of the operating condition;

[0007] Determining a thermal management energy efficiency score according to the temperature data of the energy storage container, the power of the operating condition, the operating time of the operating condition, the control parameters of the thermal management device, and the energy consumption data of the thermal management device;

[0008] A target thermal management energy efficiency level is determined according to the thermal management energy efficiency score and a preset correspondence relationship between the thermal management energy efficiency score and the thermal management energy efficiency level.

[0009] Optionally, the energy storage power station is divided into at least one level of cabin level, cluster level and module level, the cabin level is divided based on the energy storage container, the cluster level is divided based on the battery cluster, and the module level is divided based on the battery module, wherein the energy storage container includes at least one battery cluster, and the battery cluster includes a plurality of battery modules;

[0010] The obtaining of the temperature data of the energy storage container comprises:

[0011] Setting weight values ​​for the cabin level, the cluster level, and the module level;

[0012] Setting a thermal management evaluation index and a strategy for obtaining a thermal management evaluation index value for the cabin level, the cluster level, and the module level;

[0013] Setting weight values ​​for the cabin-level thermal management evaluation index, the cluster-level thermal management evaluation index, and the module-level thermal management evaluation index;

[0014] Determine the thermal management evaluation index value of the cabin level according to the thermal management evaluation index value acquisition strategy of the cabin level, determine the thermal management evaluation index value of the cluster level according to the thermal management evaluation index value acquisition strategy of the cluster level, and determine the thermal management evaluation index value of the module level according to the thermal management evaluation index value acquisition strategy of the module level;

[0015] The temperature data of the energy storage container is determined according to the thermal management evaluation index value of the cabin level, the thermal management evaluation index value of the cluster level, the thermal management evaluation index value of the module level, the weight value of the thermal management evaluation index of the cabin level, the weight value of the thermal management evaluation index of the cluster level, the weight value of the thermal management evaluation index of the module level, the weight value of the cabin level, the weight value of the cluster level and the weight value of the module level.

[0016] Optionally, the thermal management device includes an air conditioner and an exhaust fan;

[0017] The obtaining of the energy consumption data of the thermal management device comprises:

[0018] Obtaining power data and operating time of the air conditioner and the exhaust fan;

[0019] Determining energy consumption data of the air conditioner according to the power data and operating time of the air conditioner;

[0020] Determining energy consumption data of the exhaust fan according to the power data and operating time of the exhaust fan;

[0021] The energy consumption data of the thermal management device is determined according to the energy consumption data of the air conditioner and the energy consumption data of the exhaust fan.

[0022] Optionally, the thermal management device includes a liquid cooling system;

[0023] The obtaining of the energy consumption data of the thermal management device comprises:

[0024] Obtaining power data and operating time of the liquid cooling system;

[0025] Determining energy consumption data of the liquid cooling system according to the power data and operating time of the liquid cooling system;

[0026] The energy consumption data of the thermal management device is determined according to the energy consumption data of the liquid cooling system and the energy consumption data of the exhaust fan.

[0027] Optionally, determining the thermal management energy efficiency score according to the temperature data of the energy storage container, the power of the operating condition, the operating time of the operating condition, the control parameters of the thermal management device, and the energy consumption data of the thermal management device includes:

[0028] The temperature data of the energy storage container, the power of the operating condition, the operating time of the operating condition, the control parameters of the thermal management device and the energy consumption data of the thermal management device are input into a pre-generated thermal management energy efficiency model to obtain a thermal management energy efficiency score.

[0029] Optionally, after the step of determining a target thermal management energy efficiency level according to the thermal management energy efficiency score and a preset correspondence between the thermal management energy efficiency score and the thermal management energy efficiency level, the method includes:

[0030] When the target thermal management energy efficiency level is low energy efficiency, determining whether the thermal management evaluation index value of the cabin level, the thermal management evaluation index value of the cluster level, and the thermal management evaluation index value of the module level are abnormal;

[0031] In the event that the thermal management evaluation index value is abnormal, the control parameters of the thermal management device are adjusted.

[0032] Optionally, adjusting the control parameters of the thermal management device includes:

[0033] The control parameters of the air conditioner are adjusted, wherein the control parameters of the air conditioner include at least temperature and air volume.

[0034] Optionally, the cooling system includes a cooling medium;

[0035] The adjusting of the control parameters of the thermal management device comprises:

[0036] The control parameters of the liquid cooling system are adjusted, wherein the control parameters of the liquid cooling system include at least the temperature of the cooling medium, the flow rate of the cooling medium and the flow velocity of the cooling medium.

[0037] Optionally, before the step of acquiring the temperature data of any of the energy storage containers, the operating condition data of the energy storage containers, the control parameters of the thermal management device, and the energy consumption data of the thermal management device, the method includes:

[0038] Pre-constructing a three-dimensional temperature field of the energy storage container;

[0039] Obtaining the stable duration of the three-dimensional temperature field;

[0040] Determining whether the temperature distribution of the three-dimensional temperature field is in a stable state according to the stability time of the three-dimensional temperature field;

[0041] When the temperature distribution of the three-dimensional temperature field is in a stable state, determining that the operating condition of the energy storage container has not changed;

[0042] When the operating condition of the energy storage container does not change, the step of acquiring the temperature data of the energy storage container and the energy consumption data of the thermal management device is performed according to a first preset cycle.

[0043] Optionally, the energy storage container includes a temperature measurement point;

[0044] The pre-construction of the three-dimensional temperature field of the energy storage container includes:

[0045] Acquire the design data of the energy storage container, the arrangement data of the temperature measuring points, and acquire the temperature data of the temperature measuring points through the temperature measuring points;

[0046] A three-dimensional temperature field of the energy storage container is constructed according to the design data of the energy storage container, the arrangement data of the temperature measurement points and the temperature data.

[0047] Optionally, after the step of judging whether the temperature distribution of the three-dimensional temperature field is in a stable state according to the stable duration of the three-dimensional temperature field, the method includes:

[0048] When the temperature distribution of the three-dimensional temperature field is in an unstable state, determining that the operating condition of the energy storage container has changed;

[0049] When the operating condition of the energy storage container changes, the step of acquiring the temperature data of the energy storage container and the energy consumption data of the thermal management device is performed according to a second preset cycle, wherein the second preset cycle is shorter than the first preset cycle.

[0050] Optionally, the battery module includes a battery cell;

[0051] The cabin-level thermal management evaluation indicators include at least the temperature optimal time coverage, the average maximum temperature difference, the high temperature limit exceeding time ratio, the low temperature limit exceeding time ratio and the stable time of the three-dimensional temperature field;

[0052] The cluster-level thermal management evaluation index at least includes the temperature optimal time coverage, the average maximum temperature difference, the high temperature limit exceeding time, the low temperature limit exceeding time, the stable time of the three-dimensional temperature field, the maximum value of the mean square error of the average temperature of the battery module, and the average value of the mean square error of the average temperature of the battery module;

[0053] The module-level thermal management evaluation indicators include at least the temperature optimal time coverage, the average maximum temperature difference, the high temperature limit exceeding time, the low temperature limit exceeding time, the stable time of the three-dimensional temperature field, the maximum value of the mean square deviation of the average temperature of the battery cell, and the average value of the mean square deviation of the average temperature of the battery cell.

[0054] In a second aspect, an embodiment of the present application provides a device for determining a thermal management energy efficiency level, which is applied to an energy storage power station, wherein the energy storage power station includes a plurality of energy storage containers, and the energy storage containers include a thermal management device, and the device includes:

[0055] A data acquisition module, used to acquire the temperature data of any of the energy storage containers, the operating condition data of the energy storage containers, the control parameters of the thermal management device, and the energy consumption data of the thermal management device, wherein the operating condition data includes the power of the operating condition and the operating time of the operating condition;

[0056] A thermal management energy efficiency evaluation score determination module, used to determine a thermal management energy efficiency score according to the temperature data of the energy storage container, the power of the operating condition, the operating time of the operating condition, the control parameters of the thermal management device and the energy consumption data of the thermal management device;

[0057] The thermal management energy efficiency evaluation level determination module is used to determine the target thermal management energy efficiency level according to the thermal management energy efficiency score and the preset corresponding relationship between the thermal management energy efficiency score and the thermal management energy efficiency level.

[0058] In a third aspect, an embodiment of the present application further provides an electronic device, comprising: a processor; and a memory for storing instructions executable by the processor, wherein the processor is configured to execute the instructions to implement any of the thermal management energy efficiency level determination methods described above.

[0059] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium. When the instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute any of the thermal management energy efficiency level determination methods described above.

[0060] In an embodiment of the present application, the temperature data of any energy storage container, the operating condition data of the energy storage container, the control parameters of the thermal management device, and the energy consumption data of the thermal management device are obtained, wherein the operating condition data includes the power of the operating condition and the operating time of the operating condition. The thermal management energy efficiency score is determined according to the temperature data of the energy storage container, the power of the operating condition, the operating time of the operating condition, the control parameters of the thermal management device, and the energy consumption data of the thermal management device; the target thermal management energy efficiency level is determined according to the correspondence between the thermal management energy efficiency score and the preset thermal management energy efficiency score and the thermal management energy efficiency level. The present application determines the thermal management energy efficiency score by obtaining the temperature data of the energy storage container, the operating condition data (including the power and operating time of the operating condition), the control parameters of the thermal management device, and the energy consumption data. By integrating these multi-source data to evaluate the energy efficiency of the thermal management system, it can more accurately and comprehensively measure the energy efficiency level of the thermal management system compared to considering only a single factor (for example, only considering energy consumption). In addition, the present application determines the target thermal management energy efficiency level according to the correspondence between the thermal management energy efficiency score and the preset thermal management energy efficiency score and the thermal management energy efficiency level. This precise grading method helps to make a detailed division of the energy efficiency status of the thermal management system. Different energy efficiency levels can provide users with a clear reference to understand the level of energy efficiency performance of the thermal management system, such as whether it is high, medium or low efficiency, thereby providing a basis for subsequent decision-making (for example: adjustment of control parameters of thermal management equipment, etc.).

[0061] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present application. Also, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0063] Figure 1 It is a flowchart of the steps of a method for determining a thermal management energy efficiency level provided in an embodiment of the present application;

[0064] Figure 2It is a schematic diagram of a process for evaluating and optimizing the operation energy efficiency of a thermal management system of an energy storage power station provided in an embodiment of the present application;

[0065] Figure 3 is a device block diagram of a device for determining a thermal management energy efficiency level provided in an embodiment of the present application;

[0066] Figure 4 It is a structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0067] The exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present application and to fully convey the scope of the present application to those skilled in the art.

[0068] In conjunction with the accompanying drawings, a method, device, electronic device and storage medium for determining a thermal management energy efficiency level provided in an embodiment of the present application are described in detail through specific embodiments and their application scenarios.

[0069] Figure 1 is a flowchart of a method for determining a thermal management energy efficiency level provided in an embodiment of the present application. Figure 1 As shown, the method includes:

[0070] Step 101, obtaining temperature data of any energy storage container, operating condition data of the energy storage container, control parameters of a thermal management device, and energy consumption data of the thermal management device, wherein the operating condition data includes the power of the operating condition and the operating time of the operating condition.

[0071] Step 102, determining a thermal management energy efficiency score according to the temperature data of the energy storage container, the power of the operating condition, the operating time of the operating condition, the control parameters of the thermal management device, and the energy consumption data of the thermal management device.

[0072] Step 103: determining a target thermal management energy efficiency level according to the thermal management energy efficiency score and a preset correspondence relationship between the thermal management energy efficiency score and the thermal management energy efficiency level.

[0073] In some embodiments of the present application, the operating conditions of the energy storage container include charging and discharging. When the operating condition of the energy storage container is charging, the power of the operating condition is the charging power, and the operating time of the operating condition is the charging operating time. When the operating condition of the energy storage container is discharging, the power of the operating condition is the discharging power, and the operating time of the operating condition is the discharging operating time.

[0074] The energy storage power station includes several energy storage containers. Taking an energy storage container as an example, the temperature data of the energy storage container, the operating condition data of the energy storage container, the control parameters of the thermal management equipment, and the energy consumption data of the thermal management equipment are obtained, wherein the operating condition data includes the power of the operating condition and the operating time of the operating condition. In addition, in order to ensure the accuracy and reliability of the data, the acquired data can also be cleaned, screened, and outliers removed, and other data preprocessing operations can be performed.

[0075] The thermal management energy efficiency score is determined based on the temperature data of the energy storage container, the power of the operating conditions, the operating time of the operating conditions, the control parameters of the thermal management equipment, and the energy consumption data of the thermal management equipment.

[0076] The correspondence between the thermal management energy efficiency score and the thermal management energy efficiency level can be set in advance. For example, the correspondence between the thermal management energy efficiency score and the thermal management energy efficiency level can be: Thermal management energy efficiency score 0-20: low energy efficiency level. Thermal management energy efficiency score 21-50: medium energy efficiency level. Thermal management energy efficiency score 51-80: high energy efficiency level. Thermal management energy efficiency score 81-100: extremely high energy efficiency level.

[0077] After determining the thermal management energy efficiency score, it can be determined in which thermal management energy efficiency score interval the thermal management energy efficiency score falls, and then the target thermal management energy efficiency level is determined. For example: if the thermal management energy efficiency score is 18, it is in the thermal management energy efficiency score range of 0-20, corresponding to the low energy efficiency level, so the target thermal management energy efficiency level is the low energy efficiency level.

[0078] This application determines the thermal management energy efficiency score by obtaining the temperature data, operating condition data (including the power and operating time of the operating condition), control parameters of the thermal management equipment, and energy consumption data of the energy storage container. By integrating these multi-source data to evaluate the energy efficiency of the thermal management system, it can more accurately measure the energy efficiency level of the thermal management system compared to considering only a single factor (for example, only considering energy consumption). In addition, this application determines the target thermal management energy efficiency level based on the thermal management energy efficiency score and the correspondence between the preset thermal management energy efficiency score and the thermal management energy efficiency level. This precise grading method helps to make a detailed division of the energy efficiency status of the thermal management system. Different energy efficiency levels can provide users with a clear reference to understand the level of energy efficiency performance of the thermal management system, such as high efficiency, medium efficiency, or low efficiency, thereby providing a basis for subsequent decisions (for example, adjustment of thermal management equipment control parameters, etc.).

[0079] Furthermore, in some embodiments of the present application, the step of “obtaining temperature data of the energy storage container” in step 101 may also include the following steps:

[0080] Sub-step 11, setting weight values ​​for cabin level, cluster level and module level.

[0081] In some embodiments of the present application, the energy storage power station is divided into at least one level of cabin level, cluster level and module level. The cabin level is divided based on the energy storage container, the cluster level is divided based on the battery cluster, and the module level is divided based on the battery module. An energy storage power station includes several energy storage containers, an energy storage container includes at least one battery cluster, a battery cluster includes several battery modules, and a battery module includes several battery cells.

[0082] After completing the hierarchical division of the energy storage power station, weight values ​​are assigned to the cabin level, cluster level, and module level. For example, considering that the closer the level is to the battery cell, the greater the impact on thermal management, the module level is set to a relatively high weight value because the module level is closest to the battery cell. The weight values ​​of the cabin level, cluster level, and module level can be 0.2, 0.3, and 0.5, respectively.

[0083] Sub-step 12, setting thermal management evaluation indicators and thermal management evaluation indicator value acquisition strategies for cabin level, cluster level and module level.

[0084] In some embodiments of the present application, Figure 2 As shown, according to the three remote points (telemetry, telesignaling, and remote control), thermal management evaluation indicators and strategies for obtaining thermal management evaluation indicator values ​​are set for cabin level, cluster level, and module level respectively.

[0085] Among them, the cabin-level thermal management evaluation indicators include at least the temperature optimal time coverage, the average maximum temperature difference, the high temperature exceeding the limit time ratio, the low temperature exceeding the limit time ratio and the stability time of the three-dimensional temperature field.

[0086] The cluster-level thermal management evaluation indicators include at least the temperature optimal time coverage, the average maximum temperature difference, the high temperature limit exceeding time, the low temperature limit exceeding time, the stability time of the three-dimensional temperature field, the maximum value of the mean square deviation of the average temperature of the battery module, and the average value of the mean square deviation of the average temperature of the battery module.

[0087] The module-level thermal management evaluation indicators include at least the temperature optimal time coverage, the average maximum temperature difference, the high temperature limit exceeding time, the low temperature limit exceeding time, the stable time of the three-dimensional temperature field, the maximum value of the mean square deviation of the average temperature of the battery cell, and the average value of the mean square deviation of the average temperature of the battery cell.

[0088] The strategy for obtaining the value of the temperature optimal time coverage is as follows: determine the maximum temperature and the minimum temperature from the temperature data collected from all temperature measurement points at the cabin level / cluster level / module level. Obtain the duration of the maximum temperature and the minimum temperature in the preset optimal operating temperature range. The value of the temperature optimal time coverage = the duration of the maximum temperature and the minimum temperature in the preset optimal operating temperature range / total operating time*100%, where the total operating time can be the operating time at the cabin level / cluster level / module level.

[0089] Taking the cabin class as an example, assuming that the preset optimal operating temperature range is 20-30 degrees Celsius, the total operating time is 720 hours, of which the maximum and minimum temperatures are within the optimal operating temperature range for 500 hours, then the cabin class temperature optimal time coverage value is 500 / 720 * 100% ≈ 69.4%.

[0090] The strategy for obtaining the average maximum temperature difference value is: the sum of the maximum temperature differences in each hour at the cabin level / cluster level / module level / number of hours. For example, within 24 hours a day, the maximum temperature differences in each hour at the cabin level are 5, 6, 4, ..., 7 degrees Celsius, respectively. The average maximum temperature difference value at the cabin level is (5+6+4+...+7) / 24≈5.5 degrees Celsius.

[0091] The strategy for obtaining the high temperature limit-exceeding duration ratio value is: high temperature limit-exceeding duration / total operating time*100%, where the high temperature limit-exceeding duration refers to the duration that the temperature at the cabin level / cluster level / module level exceeds the preset high temperature threshold.

[0092] The strategy for obtaining the low temperature limit exceeding time ratio value is: low temperature limit exceeding time / total operating time*100%, where the low temperature limit exceeding time refers to the time when the temperature at the cabin level / cluster level / module level is lower than the preset low temperature threshold.

[0093] The strategy for obtaining the stable duration value of the three-dimensional temperature field is as follows: obtain the temperature data collected by all temperature measuring points at the cabin level / cluster level / module level. Determine the maximum temperature and the minimum temperature from the temperature data collected by all temperature measuring points. Obtain the time from the beginning of the change of the maximum temperature and the minimum temperature to the stable state, or the time from the beginning of the change of the maximum temperature and the minimum temperature to the fluctuation range less than the preset value, where the preset value can be 0.2 degrees Celsius or 0.1 degrees Celsius. The time from the beginning of the change of the maximum temperature and the minimum temperature to the stable state, or the time from the beginning of the change of the maximum temperature and the minimum temperature to the fluctuation range less than the preset value both represent the stable duration of the three-dimensional temperature field at the cabin level / cluster level / module level.

[0094] The strategy for obtaining the maximum value of the mean square deviation of the average temperature of the battery module is as follows: obtain the average temperature of each battery module within each hour. Calculate the average temperature of all battery modules based on the average temperature of each battery module and the number of battery modules. Calculate the mean square deviation based on the average temperature of each battery module, the average temperature of all battery modules and the number of battery modules to obtain the mean square deviation of the average temperature. Obtain temperature data for multiple hours over a period of time (for example, one day, one week, or one month). For each hour of temperature data, calculate its mean square deviation of the average temperature, and then determine the maximum value of the mean square deviation of the average temperature of the battery module from these multiple mean square deviations of the average temperature.

[0095] The strategy for obtaining the average value of the mean square deviation of the average temperature of the battery module is as follows: obtain the average temperature of each battery module within each hour. Calculate the average temperature of all battery modules based on the average temperature of each battery module and the number of battery modules. Calculate the mean square deviation based on the average temperature of each battery module, the average temperature of all battery modules and the number of battery modules to obtain the mean square deviation of the average temperature. Obtain temperature data for multiple hours over a period of time (for example, one day, one week, or one month). Calculate the mean square deviation of the average temperature for each hour of temperature data. Averaging the mean square deviation of the average temperature of all hours and the number of hours, calculate the average value of the mean square deviation of the average temperature of the battery module.

[0096] The strategy for obtaining the maximum value of the mean square deviation of the average temperature of the battery cell is as follows: obtain the average temperature of each battery cell within each hour. Averaging the average temperature of each battery cell and the number of battery cells, calculate the average temperature of all battery cells. Calculate the mean square deviation based on the average temperature of each battery cell, the average temperature of all battery cells, and the number of battery cells to obtain the mean square deviation of the average temperature. Obtain temperature data for multiple hours over a period of time (for example, one day, one week, or one month). For each hour of temperature data, calculate its mean square deviation of the average temperature, and then determine the maximum value of the mean square deviation of the average temperature of the battery cell from these multiple mean square deviations of the average temperature.

[0097] The strategy for obtaining the average value of the mean square deviation of the average temperature of the battery cell is as follows: obtain the average temperature of each battery cell within each hour. Calculate the average temperature of all battery cells based on the average temperature of each battery cell and the number of battery modules. Calculate the mean square deviation based on the average temperature of each battery cell, the average temperature of all battery cells and the number of battery cells to obtain the mean square deviation of the average temperature. Obtain temperature data for multiple hours over a period of time (for example, one day, one week, or one month). Calculate the mean square deviation of the average temperature for each hour of temperature data. Averaging the mean square deviation of the average temperature of all hours and the number of hours, calculate the average value of the mean square deviation of the average temperature of the battery cell.

[0098] Sub-step 13, setting weight values ​​for the cabin-level thermal management evaluation index, the cluster-level thermal management evaluation index, and the module-level thermal management evaluation index.

[0099] In some embodiments of the present application, weight values ​​are respectively assigned to the thermal management evaluation indicators at the cabin level, the thermal management evaluation indicators at the cluster level, and the thermal management evaluation indicators at the module level. For example, for the thermal management evaluation indicators at the cabin level, weight values ​​can be assigned to these thermal management evaluation indicators according to their importance. For the thermal management evaluation indicators at the cluster level, weight values ​​can be assigned to these thermal management evaluation indicators according to their importance. For the thermal management evaluation indicators at the module level, weight values ​​can be assigned to these thermal management evaluation indicators according to their importance. Among them, when assigning weight values ​​to the thermal management evaluation indicators at the module level, the weight value of the temperature optimal time coverage can be set to 0.3, the weight value of the average maximum temperature difference can be set to 0.2, and so on.

[0100] Sub-step 14, respectively determining the thermal management evaluation index values ​​of the cabin level according to the thermal management evaluation index value acquisition strategy of the cabin level, determining the thermal management evaluation index values ​​of the cluster level according to the thermal management evaluation index value acquisition strategy of the cluster level, and determining the thermal management evaluation index values ​​of the module level according to the thermal management evaluation index value acquisition strategy of the module level.

[0101] In some embodiments of the present application, the values ​​of each thermal management evaluation index at the cabin level are calculated according to the acquisition strategy of each thermal management evaluation index value at the cabin level. The values ​​of each thermal management evaluation index at the cluster level are calculated according to the acquisition strategy of each thermal management evaluation index value at the cluster level. The values ​​of each thermal management evaluation index at the module level are calculated according to the acquisition strategy of each thermal management evaluation index value at the module level.

[0102] Sub-step 15, determining the temperature data of the energy storage container according to the thermal management evaluation index value of the cabin level, the thermal management evaluation index value of the cluster level, the thermal management evaluation index value of the module level, the weight value of the thermal management evaluation index of the cabin level, the weight value of the thermal management evaluation index of the cluster level, the weight value of the thermal management evaluation index of the module level, the weight value of the cabin level, the weight value of the cluster level and the weight value of the module level.

[0103] In some embodiments of the present application, for any level among the cabin level, cluster level, and module level, a value is calculated by weighted averaging the thermal management evaluation index value calculated at this level and the weight value corresponding to each thermal management evaluation index. Each level corresponds to a value, and there are three values ​​in total for cabin level, cluster level, and module level. Then, these three values ​​and the weight values ​​of the levels corresponding to these three values ​​are weighted averaged to obtain a total value, which is the temperature data of the energy storage container.

[0104] The present application divides the energy storage power station into at least one level of cabin level, cluster level and module level, and sets multiple refined thermal management evaluation indicators for the cabin level, cluster level and module level, so as to comprehensively and deeply evaluate the thermal management energy efficiency of the thermal management system at different levels. It not only improves the accuracy and comprehensiveness of the energy efficiency evaluation of the thermal management system under different charging and discharging conditions, but also enables the staff to quickly locate the temperature abnormal area, for example: timely discover the location where the average maximum temperature difference in the energy storage container is too large, so as to optimize it in a targeted manner and improve the uniformity and stability of thermal management.

[0105] Furthermore, in some embodiments of the present application, the step of “obtaining energy consumption data of a thermal management device” in step 101 may also include the following steps:

[0106] Sub-step 21, obtaining power data and operating time of the air conditioner and exhaust fan.

[0107] Sub-step 22, determining the energy consumption data of the air conditioner according to the power data and the operating time of the air conditioner.

[0108] Sub-step 23, determining the energy consumption data of the exhaust fan according to the power data and operating time of the exhaust fan.

[0109] Sub-step 24, determining the energy consumption data of the thermal management device according to the energy consumption data of the air conditioner and the energy consumption data of the exhaust fan.

[0110] In some embodiments of the present application, the energy consumption data of the thermal management device is the amount of electricity consumed by the thermal management device. When the control mode of thermal management in the energy storage container is air cooling, the thermal management devices are air conditioners and exhaust fans, and the energy consumption data of the thermal management device are the energy consumption data of the air conditioners and the energy consumption data of the exhaust fans. It should be noted that in the embodiments of the present application, the energy consumption data of the thermal management device can also be obtained in real time on a daily basis.

[0111] The specific implementation process of obtaining the energy consumption data of the thermal management device is: install power sensors on the air conditioner and exhaust fan respectively. The power sensor can obtain the power data and operating time of the air conditioner and exhaust fan respectively. The energy consumption data of the air conditioner can be obtained by multiplying the power data and operating time of the air conditioner. The energy consumption data of the exhaust fan can be obtained by multiplying the power data and operating time of the exhaust fan. The energy consumption data of the exhaust fan can be obtained by adding the energy consumption data of the air conditioner and the energy consumption data of the exhaust fan. For example: if the power data of the air conditioner is P1 and the operating time is T1; the power data of the exhaust fan is P2 and the operating time is T2, then the energy consumption data of the thermal management device = P1*T1+P2*T2.

[0112] Furthermore, in some embodiments of the present application, the step of “obtaining energy consumption data of a thermal management device” in step 101 may also include the following steps:

[0113] Sub-step 31, obtaining power data and operating time of the liquid cooling system.

[0114] Sub-step 32, determining energy consumption data of the liquid cooling system according to the power data and operating time of the liquid cooling system.

[0115] Sub-step 33, determining the energy consumption data of the thermal management device according to the energy consumption data of the liquid cooling system and the energy consumption data of the exhaust fan.

[0116] In some embodiments of the present application, when the control method of thermal management in the energy storage container is liquid cooling, the thermal management equipment is a liquid cooling system and an exhaust fan, and the energy consumption data of the thermal management equipment is the energy consumption data of the liquid cooling system and the energy consumption data of the exhaust fan.

[0117] The specific implementation process of obtaining the energy consumption data of the thermal management device is as follows: obtaining the power data and operating time of the liquid cooling system. Multiplying the power data and operating time of the liquid cooling system can obtain the energy consumption data of the liquid cooling system. Adding the energy consumption data of the liquid cooling system and the energy consumption data of the exhaust fan can obtain the energy consumption data of the thermal management device.

[0118] By accurately calculating the energy consumption of each thermal management device, the present application can pinpoint links with excessive energy consumption, and provide strong data support for reducing the energy consumption of thermal management equipment. For example, it can be clear whether the energy consumption of air conditioners, exhaust fans, or liquid cooling system-related equipment is too high, so that corresponding energy-saving measures can be taken, such as adjusting the air conditioning temperature and air volume, to effectively reduce the energy consumption of the thermal management system and save operating costs.

[0119] Furthermore, in some embodiments of the present application, step 102 may also include the following steps:

[0120] Sub-step 41, inputting the temperature data of the energy storage container, the power of the operating condition, the operating time of the operating condition, the control parameters of the thermal management device and the energy consumption data of the thermal management device into a pre-generated thermal management energy efficiency model to obtain a thermal management energy efficiency score.

[0121] In some embodiments of the present application, a training sample data set is obtained in advance, and the training sample data set includes several groups of data and a thermal management energy efficiency score corresponding to each group of data, wherein each group of data includes temperature data of the energy storage container, power of the operating condition, operating time of the operating condition, control parameters of the thermal management device, and energy consumption data of the thermal management device.

[0122] The initial model is trained using the training sample data set, and the initial model that has completed the training is the thermal management energy efficiency model. In addition, in the process of training the initial model using the training sample data set, the parameters of the initial model can be continuously adjusted so that the thermal management energy efficiency score output by the initial model is consistent with the thermal management energy efficiency score included in the training sample data set, which can further improve the accuracy and adaptability of the thermal management energy efficiency model.

[0123] The generated thermal management energy efficiency model is a scoring model that can score the thermal management energy efficiency based on the temperature data of the energy storage container, the power of the operating conditions, the operating time of the operating conditions, the control parameters of the thermal management equipment, and the energy consumption data of the thermal management equipment to obtain a thermal management energy efficiency score.

[0124] The acquired temperature data of the energy storage container, the power of the operating condition, the operating time of the operating condition, the control parameters of the thermal management equipment and the energy consumption data of the thermal management equipment are used as inputs to the pre-generated thermal management energy efficiency model, and are input into the thermal management energy efficiency model. The thermal management energy efficiency model can automatically output the thermal management energy efficiency score.

[0125] Furthermore, in some embodiments of the present application, the following steps may be included after step 103:

[0126] Step 104 , when the target thermal management energy efficiency level is low energy efficiency, determine whether the cabin-level thermal management evaluation index value, the cluster-level thermal management evaluation index value, and the module-level thermal management evaluation index value are abnormal.

[0127] Step 105: When there is an abnormal value of the thermal management evaluation index, adjust the control parameters of the thermal management device.

[0128] In some embodiments of the present application, Figure 2 As shown, when the target thermal management energy efficiency level is low energy efficiency, it is further analyzed whether the thermal management evaluation index values ​​at the cabin level, the thermal management evaluation index values ​​at the cluster level, and the thermal management evaluation index values ​​at the module level are abnormal.

[0129] If there are abnormal thermal management evaluation index values ​​among the cabin-level thermal management evaluation index values, the cluster-level thermal management evaluation index values, and the module-level thermal management evaluation index values, the control parameters of the thermal management device are adjusted.

[0130] Furthermore, after adjusting the control parameters of the thermal management equipment, it is also possible to track and evaluate the abnormal thermal management evaluation indicators, compare the thermal management evaluation indicators before and after optimization, and evaluate the improvement effect. Based on the evaluation and improvement results, the evaluation methods and optimization measures are continuously improved to achieve continuous improvement of the thermal management system.

[0131] This application analyzes whether the values ​​of thermal management evaluation indicators at each level are abnormal when the target thermal management energy efficiency level is low. If there are abnormal values ​​of thermal management evaluation indicators, the control parameters of the thermal management equipment are adjusted to ensure that the energy consumption of the thermal management equipment is balanced with the thermal management effect, and the economy is optimized, thereby increasing the service life of the battery, saving the cost of using the battery, and reducing the power consumption of the thermal management equipment. In addition, this application forms a complete closed loop from simulation, calculation, modeling, training, evaluation, review, analysis to solution, realizing the continuous optimization and intelligent and efficient operation of the thermal management system, thereby significantly improving the operating efficiency and stability of the energy storage power station and reducing operating costs.

[0132] Furthermore, in some embodiments of the present application, step 105 may also include the following steps:

[0133] Sub-step 51, adjusting the control parameters of the air conditioner, wherein the control parameters of the air conditioner include at least temperature and air volume.

[0134] In some embodiments of the present application, when the thermal management control method in the energy storage container is air cooling, the control parameters of the air conditioner can be adjusted, specifically, the temperature and air volume of the air conditioner can be adjusted.

[0135] Furthermore, in some embodiments of the present application, step 105 may also include the following steps:

[0136] Sub-step 52, adjusting the control parameters of the liquid cooling system, wherein the control parameters of the liquid cooling system at least include the temperature of the cooling medium, the flow rate of the cooling medium and the flow velocity of the cooling medium.

[0137] In some embodiments of the present application, when the thermal management control method in the energy storage container is liquid cooling, the control parameters of the liquid cooling system can be adjusted, specifically, the temperature of the cooling medium, the flow rate of the cooling medium and the flow rate of the cooling medium can be adjusted, wherein the cooling medium can be a coolant.

[0138] Furthermore, in some embodiments of the present application, the following steps may be included before step 101:

[0139] Step 1011, pre-constructing the three-dimensional temperature field of the energy storage container.

[0140] Step 1012, obtaining the stable duration of the three-dimensional temperature field.

[0141] Step 1013, judging whether the temperature distribution of the three-dimensional temperature field is in a stable state according to the stable duration of the three-dimensional temperature field.

[0142] Step 1014: when the temperature distribution of the three-dimensional temperature field is in a stable state, determine that the operating condition of the energy storage container has not changed.

[0143] Step 1015, when the operating condition of the energy storage container has not changed, the step of acquiring the temperature data of the energy storage container and the energy consumption data of the thermal management device is performed according to the first preset cycle.

[0144] In some embodiments of the present application, the three-dimensional temperature field refers to the temperature distribution in three-dimensional space.

[0145] like Figure 2 As shown, a three-dimensional temperature field in the energy storage container is pre-constructed, wherein the specific construction process of the three-dimensional temperature field in the energy storage container can refer to sub-steps 61 and 62, which will not be described in detail here.

[0146] After completing the construction of the three-dimensional temperature field in the energy storage container, the stable duration of the three-dimensional temperature field is obtained, wherein the specific implementation process of obtaining the stable duration of the three-dimensional temperature field in the energy storage container is: obtaining the temperature data collected by all temperature measuring points in the energy storage container. Determine the maximum temperature and the minimum temperature from the temperature data collected by all temperature measuring points. Obtain the time from the beginning of the change of the maximum temperature and the minimum temperature to the stable state, or the time from the beginning of the change of the maximum temperature and the minimum temperature to the fluctuation range less than the preset value, wherein the preset value can be 0.2 degrees Celsius or 0.1 degrees Celsius. The time from the beginning of the change of the maximum temperature and the minimum temperature to the stable state, or the time from the beginning of the change of the maximum temperature and the minimum temperature to the fluctuation range less than the preset value both represent the stable duration of the three-dimensional temperature field.

[0147] For example: in an energy storage container, the maximum temperature of the temperature data collected by all temperature measuring points is 25 degrees, and the minimum temperature is 20 degrees. The maximum and minimum temperature values ​​are basically unchanged, or the change is very small. Up to this moment, the duration in between is the duration for the three-dimensional temperature field to reach stability, that is, the stability duration of the three-dimensional temperature field.

[0148] The obtained stable time of the three-dimensional temperature field is compared with a preset time threshold. If the stable time of the three-dimensional temperature field is less than the preset time threshold, it is determined that the temperature distribution of the three-dimensional temperature field is in an unstable state.

[0149] If the stability time of the three-dimensional temperature field is greater than or equal to the preset time threshold, it is determined that the temperature distribution of the three-dimensional temperature field is in a stable state. When the temperature distribution of the three-dimensional temperature field is in a stable state, it is determined that the operating condition of the energy storage container has not changed. When the operating condition of the energy storage container has not changed, the step of obtaining the temperature data of the energy storage container and the energy consumption data of the thermal management device is performed according to the first preset period, wherein the first preset period can be 1 minute.

[0150] The present application ensures that the temperature data of the energy storage container and the energy consumption data of the thermal management device can be obtained in a timely and accurate manner under stable working conditions by executing the step of obtaining the temperature data of the energy storage container and the energy consumption data of the thermal management device according to the first preset cycle when the operating conditions of the energy storage container have not changed.

[0151] Furthermore, in some embodiments of the present application, step 1011 may also include the following steps:

[0152] Sub-step 61, obtaining design data of the energy storage container, arrangement data of the temperature measuring points, and obtaining temperature data of the temperature measuring points through the temperature measuring points.

[0153] Sub-step 62, constructing a three-dimensional temperature field of the energy storage container according to the design data of the energy storage container, the arrangement data of the temperature measurement points, and the temperature data.

[0154] In some embodiments of the present application, the design data of the energy storage container includes at least the structure (e.g., shape, size), material (e.g., properties of insulation material), and spatial layout (e.g., placement of equipment). The layout data of the temperature measurement points are the distribution positions of the temperature measurement points. For example, the energy storage container is a rectangular parallelepiped, and the interior is composed of multiple battery clusters and battery modules. The temperature measurement points are distributed at key positions in the energy storage container, such as near heat sources, vents, etc.

[0155] The design data of the energy storage container, the arrangement data of the temperature measuring points, and the temperature data of the temperature measuring points obtained by the temperature measuring points are obtained. Furthermore, a three-dimensional temperature field in the energy storage container is constructed based on the design data of the energy storage container, the arrangement data of the temperature measuring points, and the temperature data of the temperature measuring points. That is, the three-dimensional temperature field refers to the distribution of the temperature measuring points in the three-dimensional space of the energy storage container, and the temperature values ​​between different temperature measuring points are calculated by temperature diffusion and differential algorithms, so as to map all temperature values ​​to various positions of the entire energy storage container.

[0156] This application achieves accurate simulation of the three-dimensional temperature field through core elements such as the structure, material, spatial layout and distribution of temperature measurement points within the energy storage container. It can simulate the temperature distribution inside the energy storage container more realistically and accurately, provide a reliable basis for subsequent evaluation and optimization, and help to discover potential thermal management problems in advance.

[0157] Furthermore, in some embodiments of the present application, the following steps may be included after step 1013:

[0158] Step 1016: When the temperature distribution of the three-dimensional temperature field is in an unstable state, determine whether the operating condition of the energy storage container has changed.

[0159] Step 1017, when the operating condition of the energy storage container changes, the step of obtaining the temperature data of the energy storage container and the energy consumption data of the thermal management device is performed according to a second preset cycle, wherein the second preset cycle is shorter than the first preset cycle.

[0160] In some embodiments of the present application, when the temperature distribution of the three-dimensional temperature field is in an unstable state, it is determined that the operating condition of the energy storage container has changed. When the operating condition of the energy storage container has changed, the step of acquiring the temperature data of the energy storage container and the energy consumption data of the thermal management device is performed according to a second preset period, wherein the second preset period may be 10 seconds.

[0161] The present application ensures that the temperature data of the energy storage container and the energy consumption data of the thermal management device can be obtained in a timely and accurate manner when the operating condition is switched, by executing the step of obtaining the temperature data of the energy storage container and the energy consumption data of the thermal management device according to the second preset cycle when the operating condition of the energy storage container changes, so as to capture the rapid changes in temperature and energy consumption in a timely manner.

[0162] Corresponding to the method provided in the above-mentioned embodiment of the method for determining the thermal management energy efficiency level of the present application, see Figure 3 , the present application also provides a device block diagram of a device for determining a thermal management energy efficiency level. In this embodiment, the device includes:

[0163] The data acquisition module 301 is used to acquire the temperature data of any energy storage container, the operating condition data of the energy storage container, the control parameters of the thermal management device, and the energy consumption data of the thermal management device, wherein the operating condition data includes the power of the operating condition and the operating time of the operating condition;

[0164] The thermal management energy efficiency evaluation score determination module 302 is used to determine the thermal management energy efficiency score according to the temperature data of the energy storage container, the power of the operating condition, the operating time of the operating condition, the control parameters of the thermal management device and the energy consumption data of the thermal management device;

[0165] The thermal management energy efficiency evaluation level determination module 303 is used to determine the target thermal management energy efficiency level according to the thermal management energy efficiency score and the preset correspondence between the thermal management energy efficiency score and the thermal management energy efficiency level.

[0166] Optionally, the energy storage power station is divided into at least one level of cabin level, cluster level and module level, the cabin level is divided based on the energy storage container, the cluster level is divided based on the battery cluster, and the module level is divided based on the battery module, wherein the energy storage container includes at least one battery cluster, and the battery cluster includes a plurality of battery modules;

[0167] The data acquisition module 301 includes:

[0168] The hierarchical weight value is assigned to the submodule, which is used to set the weight value for the cabin level, cluster level and module level;

[0169] The evaluation index setting submodule is used to set the thermal management evaluation index and the acquisition strategy of the thermal management evaluation index value for the cabin level, cluster level and module level;

[0170] The evaluation index weight value is assigned to the submodule, which is used to set the weight value for the thermal management evaluation index of the cabin level, the thermal management evaluation index of the cluster level and the thermal management evaluation index of the module level;

[0171] An evaluation index numerical calculation submodule, used to determine the thermal management evaluation index value of the cabin level according to the thermal management evaluation index value acquisition strategy of the cabin level, determine the thermal management evaluation index value of the cluster level according to the thermal management evaluation index value acquisition strategy of the cluster level, and determine the thermal management evaluation index value of the module level according to the thermal management evaluation index value acquisition strategy of the module level;

[0172] The temperature data calculation submodule of the energy storage container is used to determine the temperature data of the energy storage container according to the thermal management evaluation index value of the cabin level, the thermal management evaluation index value of the cluster level, the thermal management evaluation index value of the module level, the weight value of the thermal management evaluation index of the cabin level, the weight value of the thermal management evaluation index of the cluster level, the weight value of the thermal management evaluation index of the module level, the weight value of the cabin level, the weight value of the cluster level and the weight value of the module level.

[0173] Optionally, the thermal management device includes an air conditioner and an exhaust fan;

[0174] The data acquisition module 301 includes:

[0175] A first power and operating time acquisition submodule, used to acquire power data and operating time of the air conditioner and the exhaust fan;

[0176] The air conditioner energy consumption calculation submodule is used to determine the energy consumption data of the air conditioner according to the power data and operation time of the air conditioner;

[0177] The first exhaust fan energy consumption calculation submodule is used to determine the energy consumption data of the exhaust fan according to the power data and operation time of the exhaust fan;

[0178] The first thermal management device energy consumption data calculation submodule is used to determine the energy consumption data of the thermal management device according to the energy consumption data of the air conditioner and the energy consumption data of the exhaust fan.

[0179] Optionally, the thermal management device includes a liquid cooling system;

[0180] The data acquisition module 301 includes:

[0181] Get power data and operating hours of liquid cooling systems;

[0182] A second power and operating time acquisition submodule is used to determine energy consumption data of the liquid cooling system according to the power data and operating time of the liquid cooling system;

[0183] The second thermal management device energy consumption data calculation submodule is used to determine the energy consumption data of the thermal management device according to the energy consumption data of the liquid cooling system and the energy consumption data of the exhaust fan.

[0184] Optionally, the thermal management energy efficiency evaluation score determination module 302 includes:

[0185] The thermal management energy efficiency model processing submodule is used to input the temperature data of the energy storage container, the power of the operating conditions, the operating time of the operating conditions, the control parameters of the thermal management equipment and the energy consumption data of the thermal management equipment into a pre-generated thermal management energy efficiency model to obtain a thermal management energy efficiency score.

[0186] Optionally, the device comprises:

[0187] An abnormality analysis module, used to determine whether the thermal management evaluation index values ​​at the cabin level, the cluster level, and the module level are abnormal when the target thermal management energy efficiency level is low energy efficiency;

[0188] The thermal management device control parameter optimization module is used to adjust the control parameters of the thermal management device when there are abnormal values ​​of the thermal management evaluation indicators.

[0189] Optionally, the thermal management device control parameter optimization module includes:

[0190] The air conditioning control parameter adjustment submodule is used to adjust the control parameters of the air conditioning, wherein the control parameters of the air conditioning include at least temperature and air volume.

[0191] Optionally, the cooling system includes a cooling medium;

[0192] The thermal management equipment control parameter optimization module includes:

[0193] The liquid cooling system control parameter adjustment submodule is used to adjust the control parameters of the liquid cooling system, wherein the control parameters of the liquid cooling system at least include the temperature of the cooling medium, the flow rate of the cooling medium and the flow rate of the cooling medium.

[0194] Optionally, the device comprises:

[0195] A three-dimensional temperature field construction module is used to pre-construct the three-dimensional temperature field of the energy storage container;

[0196] A three-dimensional temperature field stable time acquisition module is used to obtain the stable time of the three-dimensional temperature field;

[0197] A temperature distribution judgment module is used to judge whether the temperature distribution of the three-dimensional temperature field is in a stable state according to the stability time of the three-dimensional temperature field;

[0198] A first operating condition determination module, used to determine that the operating condition of the energy storage container has not changed when the temperature distribution of the three-dimensional temperature field is in a stable state;

[0199] The first data acquisition strategy determination module is used to execute the step of acquiring the temperature data of the energy storage container and the energy consumption data of the thermal management device according to the first preset cycle when the operating condition of the energy storage container does not change.

[0200] Optionally, the energy storage container includes a temperature measurement point;

[0201] The 3D temperature field building module includes:

[0202] The energy storage container related data acquisition submodule is used to obtain the design data of the energy storage container, the layout data of the temperature measuring points, and obtain the temperature data of the temperature measuring points through the temperature measuring points;

[0203] The three-dimensional temperature field construction submodule is used to construct the three-dimensional temperature field of the energy storage container according to the design data of the energy storage container, the layout data of the temperature measurement points and the temperature data.

[0204] Optionally, the device comprises:

[0205] A second operating condition determination module is used to determine whether the operating condition of the energy storage container has changed when the temperature distribution of the three-dimensional temperature field is in an unstable state;

[0206] The second data acquisition strategy determination module is used to execute the step of acquiring the temperature data of the energy storage container and the energy consumption data of the thermal management device according to a second preset cycle when the operating conditions of the energy storage container change, wherein the second preset cycle is smaller than the first preset cycle.

[0207] Optionally, the battery module includes a battery cell;

[0208] The cabin-level thermal management evaluation indicators include at least the temperature optimal time coverage, the average maximum temperature difference, the high temperature exceeding limit time ratio, the low temperature exceeding limit time ratio and the stable time of the three-dimensional temperature field;

[0209] The cluster-level thermal management evaluation indicators include at least the temperature optimal time coverage, the average maximum temperature difference, the high temperature limit exceeding time, the low temperature limit exceeding time, the stability time of the three-dimensional temperature field, the maximum value of the mean square error of the average temperature of the battery module, and the average value of the mean square error of the average temperature of the battery module;

[0210] The module-level thermal management evaluation indicators include at least the temperature optimal time coverage, the average maximum temperature difference, the high temperature limit exceeding time, the low temperature limit exceeding time, the stable time of the three-dimensional temperature field, the maximum value of the mean square deviation of the average temperature of the battery cell, and the average value of the mean square deviation of the average temperature of the battery cell.

[0211] Figure 4 This is a structural diagram of an electronic device M00 provided in an embodiment of the present application. In the diagram, the electronic device M00 includes a processor M01 and a memory M02. The memory M02 stores programs or instructions that can be run on the processor M01. When the program or instructions are executed by the processor M01, the various steps of the above-mentioned thermal management energy efficiency level determination method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, they will not be repeated here.

[0212] In an embodiment of the present application, the memory M02 may be used to store software programs and various data. The memory M02 may mainly include a first storage area for storing programs or instructions and a second storage area for storing data, wherein the first storage area may store an operating system, an application program or instructions required for at least one function (such as a sound playback function, an image playback function, etc.), etc. In addition, the memory M02 may include a volatile memory or a non-volatile memory, or the memory M02 may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), a static random access memory (SRAM), a dynamic random access memory (DRAM), a synchronous dynamic random access memory (SDRAM), a double data rate synchronous dynamic random access memory (DDRSDRAM), an enhanced synchronous dynamic random access memory (ESDRAM), a synchronous link dynamic random access memory (SLDRAM) and a direct memory bus random access memory (DRRAM). The memory M02 in the embodiment of the present application includes but is not limited to these and any other suitable types of memories.

[0213] The processor M01 may include one or more processing units; optionally, the processor M01 integrates an application processor and a modem processor, wherein the application processor mainly processes operations related to an operating system, a user interface, and application programs, and the modem processor mainly processes wireless communication signals, such as a baseband processor. It is understandable that the modem processor may not be integrated into the processor M01.

[0214] An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, each process of the above-mentioned thermal management energy efficiency level determination method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0215] The processor is the processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.

[0216] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned thermal management energy efficiency level determination method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0217] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the relevant technology, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, a disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0218] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

Claims

1. A method for determining a thermal management energy efficiency level, characterized in that: Applied to an energy storage power station, wherein the energy storage power station includes a plurality of energy storage containers, and the energy storage containers include a thermal management device, and the method includes: Acquire temperature data of any of the energy storage containers, operating condition data of the energy storage container, control parameters of the thermal management device, and energy consumption data of the thermal management device, wherein the operating condition data includes the power of the operating condition and the operating time of the operating condition; Determining a thermal management energy efficiency score according to the temperature data of the energy storage container, the power of the operating condition, the operating time of the operating condition, the control parameters of the thermal management device, and the energy consumption data of the thermal management device; A target thermal management energy efficiency level is determined according to the thermal management energy efficiency score and a preset correspondence relationship between the thermal management energy efficiency score and the thermal management energy efficiency level.

2. The method according to claim 1, characterized in that The energy storage power station is divided into at least one level of cabin level, cluster level and module level, the cabin level is divided based on the energy storage container, the cluster level is divided based on the battery cluster, and the module level is divided based on the battery module, wherein the energy storage container includes at least one battery cluster, and the battery cluster includes a plurality of battery modules; The obtaining of the temperature data of the energy storage container comprises: Setting weight values ​​for the cabin level, the cluster level, and the module level; Setting a thermal management evaluation index and a strategy for obtaining a thermal management evaluation index value for the cabin level, the cluster level, and the module level; Setting weight values ​​for the cabin-level thermal management evaluation index, the cluster-level thermal management evaluation index, and the module-level thermal management evaluation index; Determine the thermal management evaluation index value of the cabin level according to the thermal management evaluation index value acquisition strategy of the cabin level, determine the thermal management evaluation index value of the cluster level according to the thermal management evaluation index value acquisition strategy of the cluster level, and determine the thermal management evaluation index value of the module level according to the thermal management evaluation index value acquisition strategy of the module level; The temperature data of the energy storage container is determined according to the thermal management evaluation index value of the cabin level, the thermal management evaluation index value of the cluster level, the thermal management evaluation index value of the module level, the weight value of the thermal management evaluation index of the cabin level, the weight value of the thermal management evaluation index of the cluster level, the weight value of the thermal management evaluation index of the module level, the weight value of the cabin level, the weight value of the cluster level and the weight value of the module level.

3. The method according to claim 1, characterized in that The thermal management equipment includes an air conditioner and an exhaust fan; The obtaining of energy consumption data of the thermal management device comprises: Obtaining power data and operating time of the air conditioner and the exhaust fan; Determining energy consumption data of the air conditioner according to the power data and operating time of the air conditioner; Determining energy consumption data of the exhaust fan according to the power data and operating time of the exhaust fan; The energy consumption data of the thermal management device is determined according to the energy consumption data of the air conditioner and the energy consumption data of the exhaust fan.

4. The method according to claim 3, characterized in that: The thermal management device includes a liquid cooling system; The obtaining of energy consumption data of the thermal management device comprises: Obtaining power data and operating time of the liquid cooling system; Determining energy consumption data of the liquid cooling system according to the power data and operating time of the liquid cooling system; The energy consumption data of the thermal management device is determined according to the energy consumption data of the liquid cooling system and the energy consumption data of the exhaust fan.

5. The method according to claim 1, characterized in that Determining the thermal management energy efficiency score according to the temperature data of the energy storage container, the power of the operating condition, the operating time of the operating condition, the control parameters of the thermal management device, and the energy consumption data of the thermal management device includes: The temperature data of the energy storage container, the power of the operating condition, the operating time of the operating condition, the control parameters of the thermal management device and the energy consumption data of the thermal management device are input into a pre-generated thermal management energy efficiency model to obtain a thermal management energy efficiency score.

6. The method according to claim 2, characterized in that After the step of determining a target thermal management energy efficiency level according to the thermal management energy efficiency score and a preset correspondence between the thermal management energy efficiency score and the thermal management energy efficiency level, the method includes: When the target thermal management energy efficiency level is low energy efficiency, determining whether the thermal management evaluation index value of the cabin level, the thermal management evaluation index value of the cluster level, and the thermal management evaluation index value of the module level are abnormal; In the event that the thermal management evaluation index value is abnormal, the control parameters of the thermal management device are adjusted.

7. The method according to claim 3, characterized in that The adjusting of the control parameters of the thermal management device comprises: The control parameters of the air conditioner are adjusted, wherein the control parameters of the air conditioner include at least temperature and air volume.

8. The method according to claim 4, characterized in that The cooling system includes a cooling medium; The adjusting of the control parameters of the thermal management device comprises: The control parameters of the liquid cooling system are adjusted, wherein the control parameters of the liquid cooling system include at least the temperature of the cooling medium, the flow rate of the cooling medium and the flow velocity of the cooling medium.

9. The method according to claim 1, characterized in that: Before the step of obtaining the temperature data of any of the energy storage containers, the operating condition data of the energy storage containers, the control parameters of the thermal management device, and the energy consumption data of the thermal management device, the method includes: Pre-constructing a three-dimensional temperature field of the energy storage container; Obtaining the stable duration of the three-dimensional temperature field; Determining whether the temperature distribution of the three-dimensional temperature field is in a stable state according to the stability time of the three-dimensional temperature field; When the temperature distribution of the three-dimensional temperature field is in a stable state, determining that the operating condition of the energy storage container has not changed; When the operating condition of the energy storage container does not change, the step of acquiring the temperature data of the energy storage container and the energy consumption data of the thermal management device is performed according to a first preset cycle.

10. The method according to claim 9, characterized in that The energy storage container includes a temperature measurement point; The pre-construction of the three-dimensional temperature field of the energy storage container includes: Acquire the design data of the energy storage container, the arrangement data of the temperature measuring points, and acquire the temperature data of the temperature measuring points through the temperature measuring points; A three-dimensional temperature field of the energy storage container is constructed according to the design data of the energy storage container, the arrangement data of the temperature measurement points and the temperature data.

11. The method according to claim 9, characterized in that After the step of judging whether the temperature distribution of the three-dimensional temperature field is in a stable state according to the stable duration of the three-dimensional temperature field, the method includes: When the temperature distribution of the three-dimensional temperature field is in an unstable state, determining that the operating condition of the energy storage container has changed; When the operating condition of the energy storage container changes, the step of acquiring the temperature data of the energy storage container and the energy consumption data of the thermal management device is performed according to a second preset cycle, wherein the second preset cycle is shorter than the first preset cycle.

12. The method according to claim 2, characterized in that: The battery module includes a battery cell; The cabin-level thermal management evaluation indicators include at least the temperature optimal time coverage, the average maximum temperature difference, the high temperature limit exceeding time ratio, the low temperature limit exceeding time ratio and the stable time of the three-dimensional temperature field; The cluster-level thermal management evaluation index at least includes the temperature optimal time coverage, the average maximum temperature difference, the high temperature limit exceeding time, the low temperature limit exceeding time, the stable time of the three-dimensional temperature field, the maximum value of the mean square error of the average temperature of the battery module, and the average value of the mean square error of the average temperature of the battery module; The module-level thermal management evaluation indicators include at least the temperature optimal time coverage, the average maximum temperature difference, the high temperature limit exceeding time, the low temperature limit exceeding time, the stable time of the three-dimensional temperature field, the maximum value of the mean square deviation of the average temperature of the battery cell, and the average value of the mean square deviation of the average temperature of the battery cell.

13. A device for determining a thermal management energy efficiency level, characterized in that: Applied to an energy storage power station, wherein the energy storage power station includes a plurality of energy storage containers, the energy storage containers include thermal management equipment, and the device includes: A data acquisition module, used to acquire the temperature data of any of the energy storage containers, the operating condition data of the energy storage containers, the control parameters of the thermal management device, and the energy consumption data of the thermal management device, wherein the operating condition data includes the power of the operating condition and the operating time of the operating condition; A thermal management energy efficiency evaluation score determination module, used to determine a thermal management energy efficiency score according to the temperature data of the energy storage container, the power of the operating condition, the operating time of the operating condition, the control parameters of the thermal management device and the energy consumption data of the thermal management device; The thermal management energy efficiency evaluation level determination module is used to determine the target thermal management energy efficiency level according to the thermal management energy efficiency score and the preset corresponding relationship between the thermal management energy efficiency score and the thermal management energy efficiency level.

14. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the thermal management energy efficiency level determination method according to any one of claims 1 to 12.

15. A storage medium, characterized in that: When the instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the thermal management energy efficiency level determination method according to any one of claims 1 to 12.

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