Battery management method based on cloud-side combination and energy storage system

Abstract

The invention discloses a battery management method based on cloud-side combination and an energy storage system, and belongs to the technical field of computers. According to the technical scheme provided by the embodiment of the invention, the first edge computing device and the second edge computing device are determined from the plurality of edge computing devices, and the plurality of reference temperature management strategies and the plurality of reference charging and discharging management strategies are acquired by using the first edge computing device and the second edge computing device. And in combination with a battery pack parameter set of a target energy storage device, the plurality of reference temperature management strategies and the plurality of reference charge and discharge management strategies, determining a target temperature management strategy and a target charge and discharge management strategy of the target energy storage device. And the target energy storage device is managed by using the target temperature management strategy and the target charging and discharging management strategy, so that the operation stability of the target energy storage device is improved, and effective management of the target energy storage device is realized.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a battery management method and energy storage system based on cloud-edge integration. Background Art

[0002] With the continuous growth of energy demand and the widespread application of renewable energy (such as solar energy, wind energy, etc.), energy storage devices are becoming increasingly important in energy systems. The battery pack in the energy storage device is a key component, and its performance, life and safety directly affect the efficiency of the entire energy storage system. Effective battery management is of great significance in ensuring the stable operation of the energy storage device, improving energy utilization efficiency and ensuring equipment safety.

[0003] Therefore, how to effectively manage energy storage systems has become a hot topic of research. Summary of the invention

[0004] The embodiment of the present application provides a battery management method and energy storage system based on cloud-edge integration, which can effectively manage the energy storage system. The technical solution is as follows: On the one hand, a battery management method based on cloud-edge integration is provided, which is executed by a server, and the method includes: Determine a first edge computing device and a second edge computing device from a plurality of edge computing devices, wherein the battery management credibility of the first edge computing device and the second edge computing device are both higher than a credibility threshold, the first edge computing device is used to manage the temperature of a battery pack of an energy storage device, and the second edge computing device is used to manage the charging and discharging power of the battery pack; Acquire a battery pack parameter set of multiple battery packs of a target energy storage device and send the battery pack parameter set to the first edge computing device and the second edge computing device, so that the first edge computing device determines multiple reference temperature management strategies for the target energy storage device based on the battery pack parameter set, and the second edge computing device determines multiple reference charge and discharge management strategies for the target energy storage device based on the battery pack parameter set, wherein the battery pack parameter set includes battery pack parameters of each of the battery packs, and the battery pack parameters include operating parameters and attribute parameters; Obtain multiple reference temperature management strategies returned by the first edge computing device and multiple reference charge and discharge management strategies returned by the second edge computing device; Based on the battery pack parameter set, the multiple reference temperature management strategies and the multiple reference charge and discharge management strategies, a target temperature management strategy and a target charge and discharge management strategy of the target energy storage device are determined, and the target energy storage device is managed based on the target temperature management strategy and the target charge and discharge management strategy.

[0005] In one aspect, an energy storage system is provided, the system comprising: a device determination module, configured to determine a first edge computing device and a second edge computing device from a plurality of edge computing devices, wherein the battery management credibility of the first edge computing device and the second edge computing device are both higher than a credibility threshold, the first edge computing device is configured to manage the temperature of a battery pack of an energy storage device, and the second edge computing device is configured to manage the charge and discharge power of the battery pack; a parameter acquisition module, configured to acquire a battery pack parameter set of multiple battery packs of a target energy storage device and send the battery pack parameter set to the first edge computing device and the second edge computing device, so that the first edge computing device determines multiple reference temperature management strategies for the target energy storage device based on the battery pack parameter set, and the second edge computing device determines multiple reference charge and discharge management strategies for the target energy storage device based on the battery pack parameter set, wherein the battery pack parameter set includes battery pack parameters of each of the battery packs, and the battery pack parameters include operating parameters and attribute parameters; A strategy acquisition module, used to acquire multiple reference temperature management strategies returned by the first edge computing device and multiple reference charge and discharge management strategies returned by the second edge computing device; A management module is used to determine a target temperature management strategy and a target charge and discharge management strategy of the target energy storage device based on the battery pack parameter set, the multiple reference temperature management strategies and the multiple reference charge and discharge management strategies, and manage the target energy storage device based on the target temperature management strategy and the target charge and discharge management strategy.

[0006] In one possible implementation, the device determination module is used to obtain a set of device screening parameters for the multiple edge computing devices, the set of device screening parameters including historical device management policies of each of the edge computing devices, a set of historical battery pack parameters corresponding to the historical device management policies, and historical management evaluation data; based on the set of device screening parameters, determine multiple candidate edge computing devices from the multiple edge computing devices, the battery management credibility of the multiple candidate edge computing devices all being higher than the credibility threshold; determine the first edge computing device and the second edge computing device from the multiple candidate edge computing devices.

[0007] In one possible implementation, the device determination module is used to determine the first management credibility and the second management credibility of each of the edge computing devices based on the device screening parameter set, wherein the first management credibility is determined based on historical management evaluation data, and the second management credibility is determined based on historical device management policies and corresponding historical battery pack parameter sets; based on the first management credibility and the second management credibility of each of the edge computing devices, the battery management credibility of each of the edge computing devices is determined; and the edge computing devices whose battery management credibility is greater than or equal to the credibility threshold among the multiple edge computing devices are determined as candidate edge computing devices to obtain the multiple candidate edge computing devices.

[0008] In one possible implementation, the device determination module is used to determine the historical temperature management evaluation data and the historical charge and discharge management evaluation data of each of the multiple candidate edge computing devices from the historical management evaluation data of the multiple candidate edge computing devices; based on the historical temperature management evaluation data and the historical charge and discharge management evaluation data of each of the candidate edge computing devices, the multiple candidate edge computing devices are divided into a first device group and a second device group, the edge computing devices in the first device group are edge computing devices with good temperature management evaluation effects indicated by the temperature management evaluation data, and the edge computing devices in the second device group are edge computing devices with good charge and discharge management evaluation effects indicated by the charge and discharge management evaluation data; based on the historical device management strategy of each of the edge computing devices and the historical battery pack parameter set corresponding to the historical device management strategy, the first edge computing device is determined from the first device group, and the second edge computing device is determined from the second device group.

[0009] In a possible implementation, the method in which the first edge computing device determines multiple reference temperature management strategies for the target energy storage device based on the battery pack parameter set includes: The first edge computing device obtains battery pack parameters of each of the battery packs from the battery pack parameter set; the first edge computing device determines a plurality of first initial management strategies based on operating parameters in the battery pack parameters of each of the battery packs; the first edge computing device determines a plurality of first reference management strategies from the plurality of first initial management strategies based on attribute parameters in the battery pack parameters of each of the battery packs, the first reference management strategy being a first initial management strategy that matches the attribute parameters; the first edge computing device determines a temperature management strategy in the plurality of first reference management strategies as the plurality of reference temperature management strategies; The method for the second edge computing device to determine multiple reference charge and discharge management strategies for the target energy storage device based on the battery pack parameter set includes: The second edge computing device obtains the battery pack parameters of each of the battery packs from the battery pack parameter set; the second edge computing device determines a plurality of second initial management strategies based on the operating parameters in the battery pack parameters of each of the battery packs; the second edge computing device determines a plurality of second reference management strategies from the plurality of second initial management strategies based on the attribute parameters in the battery pack parameters of each of the battery packs, the second reference management strategy being a second initial management strategy that matches the attribute parameters; the second edge computing device determines the charge and discharge management strategy among the plurality of second reference management strategies as the plurality of reference charge and discharge management strategies.

[0010] In a possible implementation, the first edge computing device determines a plurality of first initial management strategies based on operating parameters in the battery pack parameters of each of the battery packs, including: The first edge computing device determines a first battery pack management strategy for each battery pack and a first energy storage device management strategy for the target energy storage device based on the working parameters of each battery pack; the first edge computing device determines the multiple first initial management strategies based on the first battery pack management strategy for each battery pack and the first energy storage device management strategy for the target energy storage device; the second edge computing device determines multiple second initial management strategies based on the working parameters in the battery pack parameters of each battery pack, including: the second edge computing device determines a second battery pack management strategy for each battery pack and a second energy storage device management strategy for the target energy storage device based on the working parameters of each battery pack; the second edge computing device determines the multiple second initial management strategies based on the second battery pack management strategy for each battery pack and the second energy storage device management strategy for the target energy storage device.

[0011] In a possible implementation, the management module is used to determine the first estimated effect parameter, the second estimated effect parameter and the first risk parameter of each of the reference temperature management strategies based on the battery pack parameter set and the multiple reference temperature management strategies, wherein the first estimated effect parameter is used to indicate the temperature management effect of the target energy storage device after executing the corresponding reference temperature management strategy, and the second estimated effect parameter is used to indicate the temperature management effect of each of the battery packs after executing the corresponding reference temperature management strategy; based on the battery pack parameter set and the multiple reference charge and discharge management strategies, determine the third estimated effect parameter, the fourth estimated effect parameter and the first risk parameter of each of the reference charge and discharge management strategies. The second risk parameter, the third estimated effect parameter is used to represent the charge and discharge management effect of the target energy storage device after executing the corresponding reference charge and discharge management strategy, and the fourth estimated effect parameter is used to represent the charge and discharge management effect of each of the battery packs after executing the corresponding reference charge and discharge management strategy; based on the first estimated effect parameter, the second estimated effect parameter and the first risk parameter of each of the reference temperature management strategies, the target temperature management strategy is determined from the multiple reference temperature management strategies; based on the third estimated effect parameter, the fourth estimated effect parameter and the second risk parameter of each of the reference charge and discharge management strategies, the target charge and discharge management strategy is determined from the multiple reference charge and discharge management strategies.

[0012] In a possible implementation, the operating parameters include operating temperature, operating current, operating voltage, remaining power, number of cycles and charge and discharge power, and the attribute parameters include electrolyte type, electrode type and battery pack connection relationship. The management module is used to determine the first estimated effect parameter of each reference temperature management strategy based on the operating temperature, electrolyte type, electrode type, battery pack connection relationship and the multiple reference temperature management strategies of each battery pack in the battery pack parameter set; determine the second estimated effect parameter of each reference temperature management strategy based on the operating temperature, operating current, operating voltage, remaining power, number of cycles, charge and discharge power of each battery pack in the battery pack parameter set and the multiple reference temperature management strategies; determine the first risk parameter of each reference temperature management strategy based on the operating temperature, operating current, operating voltage, charge and discharge power, electrolyte type, electrode type and the multiple reference temperature management strategies of each battery pack in the battery pack parameter set; The management module is used to determine the third estimated effect parameter of each reference charge and discharge management strategy based on the charge and discharge power, electrolyte type, electrode type, battery pack connection relationship of each battery pack in the battery pack parameter set and the multiple reference charge and discharge management strategies; determine the fourth estimated effect parameter of each reference charge and discharge management strategy based on the operating temperature, operating current, operating voltage, charge and discharge power of each battery pack in the battery pack parameter set and the multiple reference charge and discharge management strategies; determine the second risk parameter of each reference charge and discharge management strategy based on the operating temperature, operating current, operating voltage, electrolyte type, electrode type of each battery pack in the battery pack parameter set and the multiple reference charge and discharge management strategies.

[0013] In a possible implementation, the management module is used to fuse the first estimated effect parameter and the second estimated effect parameter of each of the reference temperature management strategies to obtain the first target estimated effect parameter of each of the reference temperature management strategies; fuse the first target estimated effect parameter of each of the reference temperature management strategies with the first risk parameter of each of the reference temperature management strategies to obtain the first target strategy evaluation score of each of the reference temperature management strategies; determine the reference temperature management strategy with the highest first target strategy evaluation score among the multiple reference temperature management strategies as the target temperature management strategy; The management module is used to fuse the third estimated effect parameter and the fourth estimated effect parameter of each of the reference charge and discharge management strategies to obtain the second target estimated effect parameter of each of the reference charge and discharge management strategies; fuse the second target estimated effect parameter of each of the reference charge and discharge management strategies with the second risk parameter of each of the reference charge and discharge management strategies to obtain the second target strategy evaluation score of each of the reference charge and discharge management strategies; and determine the reference charge and discharge management strategy with the highest second target strategy evaluation score among the multiple reference charge and discharge management strategies as the target charge and discharge management strategy.

[0014] On the one hand, a server is provided, which includes one or more processors and one or more memories, wherein at least one computer program is stored in the one or more memories, and the computer program is loaded and executed by the one or more processors to implement the battery management method based on cloud-edge integration.

[0015] On the one hand, a computer-readable storage medium is provided, in which at least one computer program is stored. The computer program is loaded and executed by a processor to implement the battery management method based on cloud-edge integration.

[0016] On the one hand, a computer program product or computer program is provided, which includes a program code, which is stored in a computer-readable storage medium. A processor of a server reads the program code from the computer-readable storage medium, and the processor executes the program code, so that the server executes the above-mentioned cloud-edge combined battery management method.

[0017] Through the technical solution provided in the embodiment of the present application, a first edge computing device and a second edge computing device are determined from multiple edge computing devices, and the first edge computing device and the second edge computing device are used to obtain multiple reference temperature management strategies and multiple reference charge and discharge management strategies. Combined with the battery pack parameter set of the target energy storage device, the multiple reference temperature management strategies and the multiple reference charge and discharge management strategies, the target temperature management strategy and the target charge and discharge management strategy of the target energy storage device are determined. The target temperature management strategy and the target charge and discharge management strategy are used to manage the target energy storage device, thereby improving the operating stability of the target energy storage device and achieving effective management of the target energy storage device. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0019] Figure 1 It is a schematic diagram of an implementation environment of a battery management method based on cloud-edge integration provided in an embodiment of the present application; Figure 2 This is a flow chart of a battery management method based on cloud-edge integration provided in an embodiment of the present application; Figure 3 It is a flow chart of another battery management method based on cloud-edge integration provided in an embodiment of the present application; Figure 4 is a structural schematic diagram of an energy storage system provided in an embodiment of the present application; Figure 5 It is a structural diagram of a server provided in an embodiment of the present application. DETAILED DESCRIPTION

[0020] In order to make the objectives, technical solutions and advantages of the present application clearer, the implementation methods of the present application will be further described in detail below with reference to the accompanying drawings.

[0021] In this application, the terms "first", "second", etc. are used to distinguish identical or similar items with basically the same effects and functions. It should be understood that there is no logical or temporal dependency between "first", "second", and "nth", nor is there any limitation on quantity and execution order.

[0022] Energy storage device: Energy storage device is a device that can store energy and release it when needed. It plays a vital role in energy management and utilization, especially in the application of renewable energy. Energy storage device can solve the temporal or local differences between energy supply and demand.

[0023] Cloud-edge integration: Cloud-edge integration refers to the combination of cloud computing and edge computing, which enables more efficient and intelligent computing services by processing and analyzing data between the cloud and edge devices. This combination can give full play to the powerful computing power of cloud computing and the low latency and high bandwidth advantages of edge computing, providing users with a better service experience.

[0024] Artificial Intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain better results.

[0025] Machine Learning (ML) is a multi-disciplinary subject involving probability theory, statistics, approximation theory, convex analysis, algorithm complexity theory and other disciplines. It specializes in studying how computers simulate or implement human learning behavior to acquire new knowledge or skills and reorganize existing knowledge sub-models to continuously improve their performance. Machine learning is the core of artificial intelligence and the fundamental way to make computers intelligent. Its applications are spread across all areas of artificial intelligence. Machine learning and deep learning usually include artificial neural networks, belief networks, reinforcement learning, transfer learning, inductive learning, and teaching learning.

[0026] Normalization: Mapping sequences with different value ranges to the interval (0, 1) makes data processing easier. In some cases, the normalized values ​​can be directly implemented as probabilities.

[0027] Embedded Coding: Embedded coding mathematically represents a correspondence, that is, mapping data in X space to Y space through a function F, where the function F is an injective function, and the mapping result is structural preservation. The injective function indicates that the data after mapping is uniquely corresponding to the data before mapping, and structural preservation indicates that the size relationship of the data before mapping is the same as the size relationship of the data after mapping. For example, there are data X1 and X2 before mapping, and after mapping, Y1 corresponding to X1 and Y2 corresponding to X2 are obtained. If the data X1 before mapping is greater than X2, then correspondingly, the data Y1 after mapping is greater than Y2. For words, it means mapping the words to another space to facilitate subsequent machine learning and processing.

[0028] Attention weight: It can indicate the importance of a certain data in the training or prediction process. Importance indicates the influence of input data on output data. Data with high importance has a higher corresponding attention weight value, and data with low importance has a lower corresponding attention weight value. In different scenarios, the importance of data is different. The process of training the attention weight of the model is also the process of determining the importance of data.

[0029] After introducing some terms involved in the embodiments of the present application, the application scenarios of the embodiments of the present application are introduced below. Figure 1 is a schematic diagram of an implementation environment of a thermal management strategy optimization method for an energy storage device provided in an embodiment of the present application, see Figure 1 The technical solution provided in the embodiment of the present application can be applied in an energy storage device 100, and the energy storage device 100 includes: Battery 110: As a key technology route for new energy storage, batteries play a key role in improving the utilization rate of renewable energy and ensuring the safety and stability of the power system. Lithium batteries are the most commonly used energy storage batteries on the market and are widely recognized for their high efficiency and long life.

[0030] Thermal management system 120: By adjusting the temperature of the energy storage system, it ensures that it operates in an optimal temperature environment, prolongs the service life of the battery, and improves the overall performance of the system. Bidirectional energy storage converter (PCS, Power Conversion System) 130: It can convert the AC power of the power grid into the DC power required by the battery, and can also convert the DC power stored in the battery into AC power for use in the power grid.

[0031] Energy Management System (EMS) 140: Responsible for collecting, processing and analyzing data from various parts of the energy storage system to ensure the safe and efficient operation of the energy storage system.

[0032] Battery Management System (BMS) 150: The main function is to improve the utilization efficiency of the battery, prevent overcharging and discharging of the battery, and fully ensure the safe operation of the energy storage system.

[0033] After introducing the implementation environment of the embodiment of the present application, the battery management method based on cloud-edge integration provided by the embodiment of the present application is described below. Figure 2 This is a flow chart of a battery management method based on cloud-edge integration provided in an embodiment of the present application, see Figure 2 Taking the execution subject as a server of an energy storage system as an example, the method includes the following steps.

[0034] 201. The server determines a first edge computing device and a second edge computing device from a plurality of edge computing devices.

[0035] Among them, the battery management credibility of the first edge computing device and the second edge computing device are both higher than the credibility threshold, the first edge computing device is used to manage the temperature of the battery pack of the energy storage device, and the second edge computing device is used to manage the charge and discharge power of the battery pack. The credibility threshold is set by the technician according to the actual situation, and the embodiment of the present application does not limit this. The first edge computing device and the second edge computing device both belong to an edge computing device cluster. Different edge computing devices in the edge computing device cluster are deployed in different areas to directly control different energy storage devices. The above-described acquisition of the first edge computing device refers to screening out a first edge computing device for temperature management of the battery pack from a plurality of edge computing devices. Correspondingly, the above-described acquisition of the second edge computing device refers to screening out a second edge computing device for charge and discharge power management of the battery pack from a plurality of edge computing devices. In the embodiment of the present application, the "cloud" in the cloud-edge combination refers to the server, and the "edge" refers to the edge computing device.

[0036] 202. The server obtains a battery pack parameter set of multiple battery packs of the target energy storage device and sends the battery pack parameter set to the first edge computing device and the second edge computing device, so that the first edge computing device determines multiple reference temperature management strategies for the target energy storage device based on the battery pack parameter set, and the second edge computing device determines multiple reference charge and discharge management strategies for the target energy storage device based on the battery pack parameter set.

[0037] Among them, the battery pack parameter set includes battery pack parameters of each battery pack, and the battery pack parameters include operating parameters and attribute parameters. Multiple reference temperature management strategies are strategies for the first edge computing device to manage the temperature of the target energy storage device. Managing the temperature of the target energy storage device means controlling the heat dissipation component of the target energy storage device according to the operating conditions of the target energy storage device, so that the temperature of the target energy storage device can be kept stable, thereby improving the stability of the target energy storage device. The temperature management strategy provides a temperature control method under different circumstances. Multiple reference charge and discharge management strategies are strategies for the second edge computing device to manage the charge and discharge power of the target energy storage device. Managing the charge and discharge power of the target energy storage device means controlling the energy storage component of the target energy storage device according to the operating conditions of the target energy storage device, so that the energy storage component of the target energy storage device can be kept stable, thereby improving the stability of the target energy storage device. The charge and discharge management strategy provides a charge and discharge power control method under different circumstances.

[0038] 203. The server obtains multiple reference temperature management strategies returned by the first edge computing device and multiple reference charge and discharge management strategies returned by the second edge computing device.

[0039] 204. The server determines a target temperature management strategy and a target charge and discharge management strategy of the target energy storage device based on the battery pack parameter set, the multiple reference temperature management strategies, and the multiple reference charge and discharge management strategies.

[0040] The target temperature management strategy refers to the temperature management strategy ultimately used to manage the target energy storage device, and the target charge and discharge management strategy refers to the charge and discharge management strategy ultimately used to manage the target energy storage device.

[0041] 205. The server manages the target energy storage device based on the target temperature management strategy and the target charge and discharge management strategy.

[0042] Through the technical solution provided in the embodiment of the present application, a first edge computing device and a second edge computing device are determined from multiple edge computing devices, and the first edge computing device and the second edge computing device are used to obtain multiple reference temperature management strategies and multiple reference charge and discharge management strategies. Combined with the battery pack parameter set of the target energy storage device, the multiple reference temperature management strategies and the multiple reference charge and discharge management strategies, the target temperature management strategy and the target charge and discharge management strategy of the target energy storage device are determined. The target temperature management strategy and the target charge and discharge management strategy are used to manage the target energy storage device, thereby improving the operating stability of the target energy storage device and achieving effective management of the target energy storage device.

[0043] The above steps 201-205 are a brief introduction to the battery management method based on cloud-edge integration provided in the embodiment of the present application. The following will combine some examples to more clearly explain the battery management method based on cloud-edge integration provided in the embodiment of the present application. Figure 3 Taking the execution subject as a server as an example, the method includes the following steps.

[0044] 301. The server determines multiple edge computing devices.

[0045] The plurality of edge computing devices belong to a selected edge computing device cluster, and different edge computing devices in the edge computing device cluster are deployed in different areas for directly controlling different energy storage devices. In the embodiment of the present application, the "cloud" in the cloud-edge combination refers to the server, and the "edge" refers to the edge computing device.

[0046] In one possible implementation, the server determines a plurality of initial edge computing devices, where the plurality of initial edge computing devices are edge computing devices that are currently online. The server determines the plurality of edge computing devices from the plurality of initial edge computing devices, where the plurality of edge computing devices are initial edge computing devices whose activity levels are greater than or equal to an activity level threshold.

[0047] Among them, the activity level of the edge computing device is used to represent at least one of the online time of the edge computing device, the number of times it is called, and the management time of the energy storage device. The activity level threshold is set by technical personnel according to actual conditions, and the embodiments of the present application do not limit this.

[0048] For example, the server determines multiple initial edge computing devices that are currently online. The server obtains at least one of the online duration, the number of times it is called, and the energy storage device management duration of each initial edge computing device. The server determines the activity level of each initial edge computing device based on at least one of the online duration, the number of times it is called, and the energy storage device management duration of each initial edge computing device. The server determines the initial edge computing device whose activity level is greater than or equal to the activity level threshold among the multiple initial edge computing devices as an edge computing device to obtain the multiple edge computing devices.

[0049] 302. The server determines a first edge computing device and a second edge computing device from a plurality of edge computing devices.

[0050] Among them, the battery management credibility of the first edge computing device and the second edge computing device are both higher than the credibility threshold, the first edge computing device is used to manage the temperature of the battery pack of the energy storage device, and the second edge computing device is used to manage the charge and discharge power of the battery pack. The credibility threshold is set by the technical personnel according to the actual situation, and the embodiment of the present application does not limit this. The first edge computing device and the second edge computing device are different edge computing devices, and the first edge computing device and the second edge computing device both belong to the edge computing device cluster. The above-described acquisition of the first edge computing device refers to screening out a first edge computing device for temperature management of the battery pack from a plurality of edge computing devices, and accordingly, the above-described acquisition of the second edge computing device refers to screening out a second edge computing device for charge and discharge power management of the battery pack from a plurality of edge computing devices.

[0051] In a possible implementation, the server obtains a set of device screening parameters for the multiple edge computing devices, the set of device screening parameters including the historical device management policies of each edge computing device, the set of historical battery pack parameters corresponding to the historical device management policies, and the historical management evaluation data. Based on the set of device screening parameters, the server determines multiple candidate edge computing devices from the multiple edge computing devices, and the battery management credibility of the multiple candidate edge computing devices is higher than the credibility threshold. The server determines the first edge computing device and the second edge computing device from the multiple candidate edge computing devices.

[0052] The historical device management strategy includes the strategy of the edge computing device when managing the energy storage device in history. The historical battery pack parameter set refers to the battery pack parameter set of the energy storage device when the energy storage device is managed using the corresponding historical device management strategy. The management evaluation data is used to represent the evaluation of the historical device management strategy by the management personnel or downstream users after the historical device management strategy is adopted.

[0053] In order to explain the above implementation more clearly, the above implementation will be explained in several parts below.

[0054] In the first part, the server obtains a set of device screening parameters for the multiple edge computing devices, where the set of device screening parameters includes a historical device management strategy for each edge computing device, a historical battery pack parameter set corresponding to the historical device management strategy, and historical management evaluation data.

[0055] In a possible implementation, the server sends a parameter acquisition request to the multiple edge computing devices, where the parameter acquisition request is used to request to acquire a device screening parameter set of the multiple edge computing devices. The server acquires the device screening parameter set returned by the multiple edge computing devices.

[0056] In the second part, the server determines multiple candidate edge computing devices from the multiple edge computing devices based on the device screening parameter set.

[0057] In one possible implementation, the server determines the first management credibility and the second management credibility of each edge computing device based on the device screening parameter set, the first management credibility is determined based on historical management evaluation data, and the second management credibility is determined based on historical device management policies and corresponding historical battery pack parameter sets. The server determines the battery management credibility of each edge computing device based on the first management credibility and the second management credibility of each edge computing device. The server determines the edge computing device whose battery management credibility is greater than or equal to the credibility threshold among the multiple edge computing devices as a candidate edge computing device, and obtains the multiple candidate edge computing devices.

[0058] For example, the server inputs the historical management evaluation data of each edge computing device into the first credibility determination model, and extracts the features of the historical management evaluation data of each edge computing device through the first credibility determination model to obtain the management evaluation features of each edge computing device. The server maps the management evaluation features of each edge computing device through the first credibility determination model to obtain the first management credibility of each edge computing device. The server inputs the historical device management strategy of each edge computing device and the corresponding historical battery pack parameter set into the second credibility determination model, and extracts the features of the historical device management strategy of each edge computing device and the corresponding historical battery pack parameter set through the second credibility determination model to obtain the historical device management strategy features and historical battery pack parameter set features of each edge computing device. The server determines the matching degree between the historical device management strategy of each edge computing device and the corresponding historical battery pack parameter set based on the historical device management strategy features and historical battery pack parameter set features of each edge computing device through the second credibility determination model, and determines the matching degree as the second management credibility of each edge computing device. The server weightedly fuses the first management credibility and the second management credibility of each edge computing device to obtain the battery management credibility of each edge computing device. The server determines, among the multiple edge computing devices, an edge computing device whose battery management credibility is greater than or equal to the credibility threshold as a candidate edge computing device, and obtains the multiple candidate edge computing devices.

[0059] The weight for weighting the first management credibility and the second management credibility is provided by each edge computing device, and the embodiment of the present application does not limit this. The first credibility determination model is a regression model, and the second credibility determination model is a matching model. The embodiment of the present application does not limit the type and result of the first credibility determination model and the second credibility determination model.

[0060] Part three: The server determines the first edge computing device and the second edge computing device from the multiple candidate edge computing devices.

[0061] In a possible implementation, the server determines the historical temperature management evaluation data and the historical charge and discharge management evaluation data of each candidate edge computing device from the historical management evaluation data of the multiple candidate edge computing devices. Based on the historical temperature management evaluation data and the historical charge and discharge management evaluation data of each candidate edge computing device, the server divides the multiple candidate edge computing devices into a first device group and a second device group. The edge computing devices in the first device group are edge computing devices with good temperature management evaluation effects as indicated by the temperature management evaluation data, and the edge computing devices in the second device group are edge computing devices with good charge and discharge management evaluation effects as indicated by the charge and discharge management evaluation data. Based on the historical device management policies of each edge computing device and the historical battery pack parameter set corresponding to the historical device management policies, the server determines the first edge computing device from the first device group and determines the second edge computing device from the second device group.

[0062] Among them, the historical management evaluation data includes data for evaluating the management of multiple dimensions of edge computing devices. For example, in an embodiment of the present application, the historical management evaluation data includes at least historical temperature management evaluation data and historical charge and discharge management evaluation data. The historical temperature management evaluation data is used to represent the evaluation of the edge computing device management temperature, and the historical charge and discharge management evaluation parameters are used to represent the evaluation of the edge computing device management charge and discharge power.

[0063] For example, the server determines the historical temperature management evaluation data and the historical charge and discharge management evaluation data of each candidate edge computing device from the historical management evaluation data of the multiple candidate edge computing devices. Based on the historical temperature management evaluation data and the historical charge and discharge management evaluation data of each candidate edge computing device, the server determines the historical temperature management score and the historical charge and discharge management score of each candidate edge computing device, the historical temperature management score is positively correlated with the temperature management evaluation effect, and the historical charge and discharge management score is positively correlated with the charge and discharge management evaluation effect. The server divides the top N candidate edge computing devices with the highest historical temperature management scores among the multiple candidate edge computing devices into the first device group, and divides the top M candidate edge computing devices with the highest historical charge and discharge management scores among the multiple candidate edge computing devices into the second device group, where N and M are both positive integers. The server determines the comprehensive management evaluation score of each edge computing device based on the historical device management strategy of each edge computing device and the historical battery pack parameter set corresponding to the historical device management strategy, and the comprehensive management score is positively correlated with the comprehensive management evaluation effect. The server merges the historical temperature management scores and the comprehensive management evaluation scores of the N candidate edge computing devices in the first device group to obtain the first device screening scores of the N candidate edge computing devices in the first device group. The server determines the candidate edge computing device with the highest first device screening score among the N candidate edge computing devices as the first edge computing device. The server merges the historical charge and discharge management scores and the comprehensive management evaluation scores of the M candidate edge computing devices in the second device group to obtain the second device screening scores of the M candidate edge computing devices in the second device group. The server determines the candidate edge computing device with the highest second device screening score among the M candidate edge computing devices as the second edge computing device.

[0064] Among them, the above-mentioned server determines the comprehensive management evaluation score of each edge computing device based on the historical device management policy of each edge computing device and the historical battery pack parameter set corresponding to the historical device management policy. In fact, it is based on the historical device management policy of each edge computing device and the historical battery pack parameter set corresponding to the historical device management policy. The degree of matching between the historical device management policy of each edge computing device and the corresponding historical battery pack parameter set is determined, and the matching degree is mapped into a comprehensive management evaluation score. The method of determining the matching degree belongs to the same inventive concept as the description in the above second part. The implementation process refers to the relevant description in the above second part, which will not be repeated here.

[0065] 303. The server obtains a battery pack parameter set of multiple battery packs of the target energy storage device and sends the battery pack parameter set to the first edge computing device and the second edge computing device, so that the first edge computing device determines multiple reference temperature management strategies for the target energy storage device based on the battery pack parameter set, and the second edge computing device determines multiple reference charge and discharge management strategies for the target energy storage device based on the battery pack parameter set.

[0066] Among them, the target energy storage device is the energy storage device to be managed, and the target energy storage device includes multiple battery packs. The battery pack parameter set includes battery pack parameters of each battery pack, and the battery pack parameters include operating parameters and attribute parameters. Multiple reference temperature management strategies are strategies for the first edge computing device to manage the temperature of the target energy storage device. Managing the temperature of the target energy storage device means controlling the heat dissipation component of the target energy storage device according to the operating conditions of the target energy storage device, so that the temperature of the target energy storage device can be kept stable, thereby improving the stability of the target energy storage device. The temperature management strategy provides a temperature control method under different conditions. Multiple reference charge and discharge management strategies are strategies for the second edge computing device to manage the charge and discharge power of the target energy storage device. Managing the charge and discharge power of the target energy storage device means controlling the energy storage component of the target energy storage device according to the operating conditions of the target energy storage device, so that the energy storage component of the target energy storage device can be kept stable, thereby improving the stability of the target energy storage device. The charge and discharge management strategy provides a charge and discharge power control method under different conditions.

[0067] In order to explain the above step 303 more clearly, the manner in which the first edge computing device determines multiple reference temperature management strategies for the target energy storage device in the above step 303 is explained below.

[0068] In a possible implementation, the first edge computing device obtains battery pack parameters of each battery pack from the battery pack parameter set. The first edge computing device determines a plurality of first initial management strategies based on the operating parameters in the battery pack parameters of each battery pack. The first edge computing device determines a plurality of first reference management strategies from the plurality of first initial management strategies based on the attribute parameters in the battery pack parameters of each battery pack, and the first reference management strategy is a first initial management strategy that matches the attribute parameters. The first edge computing device determines a temperature management strategy from the plurality of first reference management strategies as the plurality of reference temperature management strategies.

[0069] In order to explain the above implementation more clearly, the above implementation will be explained in several parts below.

[0070] In the first part, the first edge computing device obtains the battery pack parameters of each battery pack from the battery pack parameter set.

[0071] In a possible implementation, the first edge computing device unpacks the battery pack parameter set to obtain battery pack parameters of each battery pack.

[0072] In the second part, the first edge computing device determines multiple first initial management strategies based on the operating parameters in the battery pack parameters of each battery pack.

[0073] In a possible implementation, the first edge computing device determines a first battery pack management strategy for each battery pack and a first energy storage device management strategy for the target energy storage device based on operating parameters of each battery pack. The first edge computing device determines the multiple first initial management strategies based on the first battery pack management strategy for each battery pack and the first energy storage device management strategy for the target energy storage device.

[0074] Among them, the first battery pack management strategy refers to a strategy for managing the battery pack, and the first energy storage device management strategy refers to a strategy for overall management of the target energy storage device. In an embodiment of the present application, the first initial management strategy is a fusion management strategy, that is, it includes both a strategy for managing the battery pack and a strategy for overall management of the target energy storage device. In some embodiments, the operating parameters include operating temperature, operating current, operating voltage, remaining power, number of cycles, and charge and discharge power.

[0075] For example, for any battery pack among multiple battery packs of the target energy storage device, the first edge computing device inputs the working parameters of the battery pack into the first local management strategy determination model, extracts features of the working parameters of the battery pack through the first local management strategy determination model, and obtains the first battery pack working feature of the battery pack. The first edge computing device performs multiple rounds of iterative decoding based on the first battery pack working feature of the battery pack through the first local management strategy determination model to obtain the first battery pack management policy of the battery pack. The first edge computing device inputs the working parameters of the battery pack into the first global management strategy determination model, extracts features of the working parameters of each battery pack through the first global management strategy determination model, and obtains the first energy storage device working feature of the target energy storage device. The first edge computing device performs multiple rounds of iterative decoding based on the first energy storage device working feature of the target energy storage device through the first global management strategy determination model to obtain the first energy storage device management policy of the target energy storage device. The first edge computing device performs policy regeneration based on the first battery pack management policies of the multiple battery packs and the first energy storage device management policy of the target energy storage device to obtain the multiple first initial management policies.

[0076] Among them, the first local management strategy determination model and the first global management strategy determination model are both models with strategy generation capabilities. From another perspective, the first local management strategy determination model and the first global management strategy determination model are generative models from sequence (feature) to sequence (strategy). In the embodiment of the present application, the first local management strategy determination model and the first global management strategy determination model are both models obtained by training based on the BERT model. The feature extraction process uses the encoder of the BERT model, and the process of decoding the features uses the decoder of the BERT model. In addition, the above-mentioned strategy regeneration can be achieved through a pre-trained fine-tuned first large language model, that is, the first edge computing device inputs the first battery pack management strategy of the multiple battery packs, the first energy storage device management strategy of the target energy storage device, and the first prompt text template into the first large language model, and the strategy is regenerated through the first large language model to obtain the multiple first initial management strategies. The first prompt text template is used to prompt the strategy regeneration. The form of the first prompt text template is set by the technician according to the actual situation, and the embodiment of the present application does not limit this.

[0077] Part three: The first edge computing device determines multiple first reference management strategies from the multiple first initial management strategies based on the attribute parameters in the battery pack parameters of each battery pack.

[0078] Among them, the property parameters include electrolyte type, electrode type and battery pack connection relationship.

[0079] In a possible implementation, the first edge computing device determines the degree of match between the target energy storage device and the multiple first initial management strategies based on the attribute parameters in the battery pack parameters of each battery pack. The first edge computing device determines the first initial management strategy among the multiple first initial management strategies whose degree of match with the target energy storage device is greater than or equal to a matching degree threshold as the first reference management strategy.

[0080] For example, the first edge computing device performs feature extraction on the attribute parameters in the battery pack parameters of each battery pack to obtain the attribute characteristics of multiple battery packs in the target energy storage device. The first edge computing device performs feature extraction on the multiple first initial management strategies to obtain the first management strategy characteristics of each initial first initial management strategy. The first edge computing device determines the degree of match between the target energy storage device and the multiple first initial management strategies based on the attribute characteristics of the multiple battery packs in the target energy storage device and the first management strategy characteristics of each initial first initial management strategy. The first edge computing device determines the first initial management strategy among the multiple first initial management strategies whose degree of match with the target energy storage device is greater than or equal to a matching degree threshold as the first reference management strategy.

[0081] Part 4: The first edge computing device determines the temperature management strategy among the multiple first reference management strategies as the multiple reference temperature management strategies.

[0082] In a possible implementation, the first edge computing device disassembles the multiple first reference strategies to obtain the multiple reference temperature management strategies.

[0083] In order to explain the above step 303 more clearly, the manner in which the second edge computing device determines multiple reference charge and discharge management strategies for the target energy storage device in the above step 303 is explained below.

[0084] In a possible implementation, the second edge computing device obtains the battery pack parameters of each battery pack from the battery pack parameter set. The second edge computing device determines a plurality of second initial management strategies based on the operating parameters in the battery pack parameters of each battery pack. The second edge computing device determines a plurality of second reference management strategies from the plurality of second initial management strategies based on the attribute parameters in the battery pack parameters of each battery pack, and the second reference management strategy is a second initial management strategy that matches the attribute parameters. The second edge computing device determines the charge and discharge management strategy in the plurality of second reference management strategies as the plurality of reference charge and discharge management strategies.

[0085] In order to explain the above implementation more clearly, the above implementation will be explained in several parts below.

[0086] In the first part, the second edge computing device obtains the battery pack parameters of each battery pack from the battery pack parameter set.

[0087] In a possible implementation, the second edge computing device unpacks the battery pack parameter set to obtain battery pack parameters of each battery pack.

[0088] The second part, the second edge computing device determines multiple second initial management strategies based on the operating parameters in the battery pack parameters of each battery pack.

[0089] In one possible implementation, the second edge computing device determines the second battery pack management strategy for each battery pack and the second energy storage device management strategy for the target energy storage device based on the operating parameters of each battery pack. The second edge computing device determines the multiple second initial management strategies based on the second battery pack management strategy for each battery pack and the second energy storage device management strategy for the target energy storage device.

[0090] Among them, the second battery pack management strategy refers to a strategy for managing the battery pack, and the second energy storage device management strategy refers to a strategy for overall management of the target energy storage device. In the embodiment of the present application, the second initial management strategy is a fusion management strategy, that is, it includes both a strategy for managing the battery pack and a strategy for overall management of the target energy storage device.

[0091] For example, for any battery pack among the multiple battery packs of the target energy storage device, the second edge computing device inputs the working parameters of the battery pack into the second local management strategy determination model, and extracts the features of the working parameters of the battery pack through the second local management strategy determination model to obtain the second battery pack working feature of the battery pack. The second edge computing device performs multiple rounds of iterative decoding based on the second battery pack working feature of the battery pack through the second local management strategy determination model to obtain the second battery pack management strategy of the battery pack. The second edge computing device inputs the working parameters of the battery pack into the second global management strategy determination model, and extracts the features of the working parameters of each battery pack through the second global management strategy determination model to obtain the second energy storage device working feature of the target energy storage device. The second edge computing device performs multiple rounds of iterative decoding based on the second energy storage device working feature of the target energy storage device through the second global management strategy determination model to obtain the second energy storage device management strategy of the target energy storage device. The second edge computing device performs multiple rounds of iterative decoding based on the second energy storage device working feature of the target energy storage device through the second global management strategy determination model to obtain the second energy storage device management strategy of the target energy storage device. The second edge computing device regenerates the policy based on the second battery pack management policy of the multiple battery packs and the second energy storage device management policy of the target energy storage device to obtain the multiple second initial management policies.

[0092] Among them, the second local management strategy determination model and the second global management strategy determination model are both models with strategy generation capabilities. From another perspective, the second local management strategy determination model and the second global management strategy determination model are generative models from sequence (feature) to sequence (strategy). In the embodiment of the present application, the second local management strategy determination model and the second global management strategy determination model are both models trained based on the BERT model. The feature extraction process uses the encoder of the BERT model, and the feature decoding process uses the decoder of the BERT model. In addition, the second local management strategy determination model and the first local management strategy determination model are respectively trained by the second edge computing device and the first edge computing device using different data sets; the second global management strategy determination model and the first global management strategy determination model are also respectively trained by the second edge computing device and the first edge computing device using different data sets. In addition, the above-mentioned policy regeneration can be achieved through a pre-trained and fine-tuned second largest language model, that is, the second edge computing device inputs the second battery pack management strategy of the multiple battery packs, the second energy storage device management strategy of the target energy storage device, and the second prompt text template into the second largest language model, and performs policy regeneration through the second largest language model to obtain the multiple second initial management strategies. The second prompt text template is used to prompt policy regeneration. The form of the second prompt text template is set by technical personnel according to actual conditions, and the embodiments of the present application are not limited to this.

[0093] Part three: The second edge computing device determines multiple second reference management strategies from the multiple second initial management strategies based on the attribute parameters in the battery pack parameters of each battery pack.

[0094] In a possible implementation, the second edge computing device determines the degree of match between the target energy storage device and the plurality of second initial management strategies based on the attribute parameters in the battery pack parameters of each battery pack. The second edge computing device determines the second initial management strategy among the plurality of second initial management strategies, whose degree of match with the target energy storage device is greater than or equal to a matching degree threshold, as the second reference management strategy.

[0095] For example, the second edge computing device performs feature extraction on the attribute parameters in the battery pack parameters of each battery pack to obtain the attribute characteristics of multiple battery packs in the target energy storage device. The second edge computing device performs feature extraction on the multiple second initial management strategies to obtain the first management strategy characteristics of each initial second initial management strategy. The second edge computing device determines the degree of match between the target energy storage device and the multiple second initial management strategies based on the attribute characteristics of the multiple battery packs in the target energy storage device and the first management strategy characteristics of each initial second initial management strategy. The second edge computing device determines the second initial management strategy among the multiple second initial management strategies whose degree of match with the target energy storage device is greater than or equal to the matching degree threshold as the second reference management strategy.

[0096] Part 4: The second edge computing device determines the charge and discharge management strategy among the multiple second reference management strategies as the multiple reference charge and discharge management strategies.

[0097] In a possible implementation, the second edge computing device disassembles the multiple second reference strategies to obtain the multiple reference charge and discharge management strategies.

[0098] 304. The server obtains multiple reference temperature management strategies returned by the first edge computing device and multiple reference charge and discharge management strategies returned by the second edge computing device.

[0099] 305. The server determines a target temperature management strategy and a target charge and discharge management strategy of the target energy storage device based on the battery pack parameter set, the multiple reference temperature management strategies, and the multiple reference charge and discharge management strategies.

[0100] The target temperature management strategy refers to the temperature management strategy ultimately used to manage the target energy storage device, and the target charge and discharge management strategy refers to the charge and discharge management strategy ultimately used to manage the target energy storage device.

[0101] In a possible implementation, the server determines the first estimated effect parameter, the second estimated effect parameter, and the first risk parameter of each reference temperature management strategy based on the battery pack parameter set and the multiple reference temperature management strategies, the first estimated effect parameter is used to indicate the temperature management effect of the target energy storage device after the corresponding reference temperature management strategy is executed, and the second estimated effect parameter is used to indicate the temperature management effect of each battery pack after the corresponding reference temperature management strategy is executed. The server determines the third estimated effect parameter, the fourth estimated effect parameter, and the second risk parameter of each reference charge and discharge management strategy based on the battery pack parameter set and the multiple reference charge and discharge management strategies, the third estimated effect parameter is used to indicate the charge and discharge management effect of the target energy storage device after the corresponding reference charge and discharge management strategy is executed, and the fourth estimated effect parameter is used to indicate the charge and discharge management effect of each battery pack after the corresponding reference charge and discharge management strategy is executed. The server determines the target temperature management strategy from the multiple reference temperature management strategies based on the first estimated effect parameter, the second estimated effect parameter, and the first risk parameter of each reference temperature management strategy. The server determines the target charge and discharge management strategy from the multiple reference charge and discharge management strategies based on the third estimated effect parameter, the fourth estimated effect parameter, and the second risk parameter of each reference charge and discharge management strategy.

[0102] In order to explain the above implementation more clearly, the above implementation will be explained in several parts below.

[0103] In the first part, the server determines a first estimated effect parameter, a second estimated effect parameter and a first risk parameter of each reference temperature management strategy based on the battery pack parameter set and the multiple reference temperature management strategies.

[0104] In a possible implementation, the operating parameters include operating temperature, operating current, operating voltage, remaining power, number of cycles, and charge and discharge power, and the attribute parameters include electrolyte type, electrode type, and battery pack connection relationship. The server determines the first estimated effect parameter of each reference temperature management strategy based on the operating temperature, electrolyte type, electrode type, battery pack connection relationship, and the multiple reference temperature management strategies of each battery pack in the battery pack parameter set. The server determines the second estimated effect parameter of each reference temperature management strategy based on the operating temperature, operating current, operating voltage, remaining power, number of cycles, charge and discharge power, and the multiple reference temperature management strategies of each battery pack in the battery pack parameter set. The server determines the first risk parameter of each reference temperature management strategy based on the operating temperature, operating current, operating voltage, charge and discharge power, electrolyte type, electrode type, and the multiple reference temperature management strategies of each battery pack in the battery pack parameter set.

[0105] For example, the server inputs the operating temperature, electrolyte type, electrode type, battery pack connection relationship and the multiple reference temperature management strategies of each battery pack in the battery pack parameter set into the first evaluation model, and extracts the features of the operating temperature, electrolyte type, electrode type, battery pack connection relationship and the multiple reference temperature management strategies of each battery pack through the first evaluation model to obtain the first evaluation feature of each reference temperature management strategy. The server fully connects and normalizes the first evaluation feature of each reference temperature management strategy through the first evaluation model to obtain the first estimated effect parameter of each reference temperature management strategy. The server inputs the operating temperature, operating current, operating voltage, remaining power, number of cycles, charge and discharge power and the multiple reference temperature management strategies of each battery pack in the battery pack parameter set into the second evaluation model, and extracts the features of the operating temperature, operating current, operating voltage, remaining power, number of cycles, charge and discharge power and the multiple reference temperature management strategies of each battery pack through the second evaluation model to obtain the second evaluation feature of each reference temperature management strategy. The server fully connects and normalizes the second evaluation feature of each reference temperature management strategy through the second evaluation model to obtain the second estimated effect parameter of each reference temperature management strategy. The server inputs the operating temperature, operating current, operating voltage, charge and discharge power, electrolyte type, electrode type and the multiple reference temperature management strategies of each battery pack in the battery pack parameter set into the first risk assessment model, and extracts the features of the operating temperature, operating current, operating voltage, charge and discharge power, electrolyte type, electrode type and the multiple reference temperature management strategies of each battery pack through the first risk assessment model to obtain the first risk feature of each reference temperature management strategy. The server fully connects and normalizes the first risk features of each reference temperature management strategy through the first risk assessment model to obtain the first risk parameter of each reference temperature management strategy.

[0106] In the second part, the server determines the third estimated effect parameter, the fourth estimated effect parameter and the second risk parameter of each reference charge and discharge management strategy based on the battery pack parameter set and the multiple reference charge and discharge management strategies.

[0107] In one possible implementation, the server determines the third estimated effect parameter of each reference charge and discharge management strategy based on the charge and discharge power, electrolyte type, electrode type, battery pack connection relationship of each battery pack in the battery pack parameter set, and the multiple reference charge and discharge management strategies. The server determines the fourth estimated effect parameter of each reference charge and discharge management strategy based on the operating temperature, operating current, operating voltage, charge and discharge power of each battery pack in the battery pack parameter set, and the multiple reference charge and discharge management strategies. The server determines the second risk parameter of each reference charge and discharge management strategy based on the operating temperature, operating current, operating voltage, electrolyte type, electrode type of each battery pack in the battery pack parameter set, and the multiple reference charge and discharge management strategies.

[0108] For example, the server inputs the charge and discharge power, electrolyte type, electrode type, battery pack connection relationship and the multiple reference charge and discharge management strategies of each battery pack in the battery pack parameter set into the third evaluation model, and extracts the features of the charge and discharge power, electrolyte type, electrode type, battery pack connection relationship and the multiple reference charge and discharge management strategies of each battery pack through the third evaluation model to obtain the third evaluation feature of each reference charge and discharge management strategy. The server fully connects and normalizes the third evaluation feature of each reference charge and discharge management strategy through the third evaluation model to obtain the third estimated effect parameter of each reference charge and discharge management strategy. The server inputs the operating temperature, operating current, operating voltage, charge and discharge power and the multiple reference charge and discharge management strategies of each battery pack in the battery pack parameter set into the fourth evaluation model, and extracts the features of the operating temperature, operating current, operating voltage, charge and discharge power and the multiple reference charge and discharge management strategies of each battery pack through the fourth evaluation model to obtain the fourth evaluation feature of each reference charge and discharge management strategy. The server uses the fourth evaluation model to fully connect and normalize the fourth evaluation features of each reference charge and discharge management strategy to obtain the fourth estimated effect parameters of each reference charge and discharge management strategy. The server inputs the operating temperature, operating current, operating voltage, electrolyte type, electrode type and multiple reference charge and discharge management strategies of each battery pack in the battery pack parameter set into the second risk assessment model, and extracts the operating temperature, operating current, operating voltage, electrolyte type, electrode type and multiple reference charge and discharge management strategies of each battery pack through the second risk assessment model to obtain the second risk features of each reference charge and discharge management strategy. The server uses the second risk assessment model to fully connect and normalize the second risk features of each reference charge and discharge management strategy to obtain the second risk parameters of each reference charge and discharge management strategy.

[0109] Part three: The server determines the target temperature management strategy from the multiple reference temperature management strategies based on the first estimated effect parameter, the second estimated effect parameter and the first risk parameter of each reference temperature management strategy.

[0110] In a possible implementation, the server fuses the first estimated effect parameter and the second estimated effect parameter of each reference temperature management strategy to obtain the first target estimated effect parameter of each reference temperature management strategy. The server fuses the first target estimated effect parameter of each reference temperature management strategy with the first risk parameter of each reference temperature management strategy to obtain the first target strategy evaluation score of each reference temperature management strategy. The server determines the reference temperature management strategy with the highest first target strategy evaluation score among the multiple reference temperature management strategies as the target temperature management strategy.

[0111] In the fourth part, the server determines the target charge and discharge management strategy from the multiple reference charge and discharge management strategies based on the third estimated effect parameter, the fourth estimated effect parameter and the second risk parameter of each reference charge and discharge management strategy.

[0112] In a possible implementation, the server fuses the third estimated effect parameter and the fourth estimated effect parameter of each reference charge and discharge management strategy to obtain the second target estimated effect parameter of each reference charge and discharge management strategy. The server fuses the second target estimated effect parameter of each reference charge and discharge management strategy with the second risk parameter of each reference charge and discharge management strategy to obtain the second target strategy evaluation score of each reference charge and discharge management strategy. The server determines the reference charge and discharge management strategy with the highest second target strategy evaluation score among the multiple reference charge and discharge management strategies as the target charge and discharge management strategy.

[0113] 306. The server manages the target energy storage device based on the target temperature management strategy and the target charge and discharge management strategy.

[0114] In a possible implementation, the server sends the target temperature management strategy and the target charge and discharge management strategy to the target energy storage device, so that the target energy storage device operates based on the target temperature management strategy and the target charge and discharge management strategy, thereby achieving management of the target energy storage device.

[0115] All the above optional technical solutions can be arbitrarily combined to form optional embodiments of the present application, which will not be described one by one here.

[0116] Through the technical solution provided in the embodiment of the present application, a first edge computing device and a second edge computing device are determined from multiple edge computing devices, and the first edge computing device and the second edge computing device are used to obtain multiple reference temperature management strategies and multiple reference charge and discharge management strategies. Combined with the battery pack parameter set of the target energy storage device, the multiple reference temperature management strategies and the multiple reference charge and discharge management strategies, the target temperature management strategy and the target charge and discharge management strategy of the target energy storage device are determined. The target temperature management strategy and the target charge and discharge management strategy are used to manage the target energy storage device, thereby improving the operating stability of the target energy storage device and achieving effective management of the target energy storage device.

[0117] Figure 4 is a schematic diagram of the structure of an energy storage system provided in an embodiment of the present application, see Figure 4 The system includes: a device determination module 401, a parameter acquisition module 402, a strategy acquisition module 403 and a management module 404.

[0118] The device determination module 401 is used to determine a first edge computing device and a second edge computing device from multiple edge computing devices, the battery management credibility of the first edge computing device and the second edge computing device are both higher than the credibility threshold, the first edge computing device is used to manage the temperature of the battery pack of the energy storage device, and the second edge computing device is used to manage the charging and discharging power of the battery pack.

[0119] The parameter acquisition module 402 is used to obtain a battery pack parameter set of multiple battery packs of a target energy storage device and send the battery pack parameter set to the first edge computing device and the second edge computing device, so that the first edge computing device determines multiple reference temperature management strategies for the target energy storage device based on the battery pack parameter set, and the second edge computing device determines multiple reference charge and discharge management strategies for the target energy storage device based on the battery pack parameter set. The battery pack parameter set includes battery pack parameters of each of the battery packs, and the battery pack parameters include operating parameters and attribute parameters.

[0120] The strategy acquisition module 403 is used to acquire multiple reference temperature management strategies returned by the first edge computing device and multiple reference charge and discharge management strategies returned by the second edge computing device.

[0121] The management module 404 is used to determine the target temperature management strategy and the target charge and discharge management strategy of the target energy storage device based on the battery pack parameter set, the multiple reference temperature management strategies and the multiple reference charge and discharge management strategies, and manage the target energy storage device based on the target temperature management strategy and the target charge and discharge management strategy.

[0122] In a possible implementation, the device determination module 401 is used to obtain a device screening parameter set of the multiple edge computing devices, the device screening parameter set including the historical device management strategy of each edge computing device, the historical battery pack parameter set corresponding to the historical device management strategy, and the historical management evaluation data. Based on the device screening parameter set, multiple candidate edge computing devices are determined from the multiple edge computing devices, and the battery management credibility of the multiple candidate edge computing devices is higher than the credibility threshold. The first edge computing device and the second edge computing device are determined from the multiple candidate edge computing devices.

[0123] In one possible implementation, the device determination module 401 is used to determine the first management credibility and the second management credibility of each edge computing device based on the device screening parameter set, wherein the first management credibility is determined based on historical management evaluation data, and the second management credibility is determined based on historical device management policies and corresponding historical battery pack parameter sets. Based on the first management credibility and the second management credibility of each edge computing device, the battery management credibility of each edge computing device is determined. The edge computing device whose battery management credibility is greater than or equal to the credibility threshold among the multiple edge computing devices is determined as a candidate edge computing device, and the multiple candidate edge computing devices are obtained.

[0124] In a possible implementation, the device determination module 401 is used to determine the historical temperature management evaluation data and historical charge and discharge management evaluation data of each candidate edge computing device from the historical management evaluation data of the multiple candidate edge computing devices. Based on the historical temperature management evaluation data and historical charge and discharge management evaluation data of each candidate edge computing device, the multiple candidate edge computing devices are divided into a first device group and a second device group, the edge computing devices in the first device group are edge computing devices with good temperature management evaluation effects indicated by the temperature management evaluation data, and the edge computing devices in the second device group are edge computing devices with good charge and discharge management evaluation effects indicated by the charge and discharge management evaluation data. Based on the historical device management strategies of each edge computing device and the historical battery pack parameter set corresponding to the historical device management strategies, the first edge computing device is determined from the first device group, and the second edge computing device is determined from the second device group.

[0125] In a possible implementation, the method for the first edge computing device to determine multiple reference temperature management strategies for the target energy storage device based on the battery pack parameter set includes: The first edge computing device obtains the battery pack parameters of each of the battery packs from the battery pack parameter set. The first edge computing device determines a plurality of first initial management strategies based on the operating parameters in the battery pack parameters of each of the battery packs. The first edge computing device determines a plurality of first reference management strategies from the plurality of first initial management strategies based on the attribute parameters in the battery pack parameters of each of the battery packs, the first reference management strategy being a first initial management strategy that matches the attribute parameters. The first edge computing device determines a temperature management strategy from the plurality of first reference management strategies as the plurality of reference temperature management strategies.

[0126] The method for the second edge computing device to determine multiple reference charge and discharge management strategies for the target energy storage device based on the battery pack parameter set includes: The second edge computing device obtains the battery pack parameters of each of the battery packs from the battery pack parameter set. The second edge computing device determines a plurality of second initial management strategies based on the operating parameters in the battery pack parameters of each of the battery packs. The second edge computing device determines a plurality of second reference management strategies from the plurality of second initial management strategies based on the attribute parameters in the battery pack parameters of each of the battery packs, and the second reference management strategy is a second initial management strategy that matches the attribute parameters. The second edge computing device determines the charge and discharge management strategy among the plurality of second reference management strategies as the plurality of reference charge and discharge management strategies.

[0127] In a possible implementation, the first edge computing device determines a plurality of first initial management strategies based on operating parameters in the battery pack parameters of each of the battery packs, including: The first edge computing device determines the first battery pack management strategy of each battery pack and the first energy storage device management strategy of the target energy storage device based on the operating parameters of each battery pack. The first edge computing device determines the multiple first initial management strategies based on the first battery pack management strategy of each battery pack and the first energy storage device management strategy of the target energy storage device. The second edge computing device determines the multiple second initial management strategies based on the operating parameters in the battery pack parameters of each battery pack, including: the second edge computing device determines the second battery pack management strategy of each battery pack and the second energy storage device management strategy of the target energy storage device based on the operating parameters of each battery pack. The second edge computing device determines the multiple second initial management strategies based on the second battery pack management strategy of each battery pack and the second energy storage device management strategy of the target energy storage device.

[0128] In a possible implementation, the management module 404 is used to determine the first estimated effect parameter, the second estimated effect parameter and the first risk parameter of each reference temperature management strategy based on the battery pack parameter set and the multiple reference temperature management strategies, the first estimated effect parameter is used to indicate the temperature management effect of the target energy storage device after the corresponding reference temperature management strategy is executed, and the second estimated effect parameter is used to indicate the temperature management effect of each battery pack after the corresponding reference temperature management strategy is executed. Based on the battery pack parameter set and the multiple reference charge and discharge management strategies, the third estimated effect parameter, the fourth estimated effect parameter and the second risk parameter of each reference charge and discharge management strategy are determined, the third estimated effect parameter is used to indicate the charge and discharge management effect of the target energy storage device after the corresponding reference charge and discharge management strategy is executed, and the fourth estimated effect parameter is used to indicate the charge and discharge management effect of each battery pack after the corresponding reference charge and discharge management strategy is executed. Based on the first estimated effect parameter, the second estimated effect parameter and the first risk parameter of each reference temperature management strategy, the target temperature management strategy is determined from the multiple reference temperature management strategies. The target charge and discharge management strategy is determined from the plurality of reference charge and discharge management strategies based on the third estimated effect parameter, the fourth estimated effect parameter and the second risk parameter of each of the reference temperature management strategies.

[0129] In a possible implementation, the operating parameters include operating temperature, operating current, operating voltage, remaining power, number of cycles, and charge and discharge power, and the attribute parameters include electrolyte type, electrode type, and battery pack connection relationship. The management module 404 is used to determine the first estimated effect parameter of each reference temperature management strategy based on the operating temperature, electrolyte type, electrode type, battery pack connection relationship, and the multiple reference temperature management strategies of each battery pack in the battery pack parameter set. Determine the second estimated effect parameter of each reference temperature management strategy based on the operating temperature, operating current, operating voltage, remaining power, number of cycles, charge and discharge power of each battery pack in the battery pack parameter set, and the multiple reference temperature management strategies. Determine the first risk parameter of each reference temperature management strategy based on the operating temperature, operating current, operating voltage, charge and discharge power, electrolyte type, electrode type, and the multiple reference temperature management strategies of each battery pack in the battery pack parameter set.

[0130] The management module 404 is used to determine the third estimated effect parameter of each reference charge and discharge management strategy based on the charge and discharge power, electrolyte type, electrode type, battery pack connection relationship of each battery pack in the battery pack parameter set and the multiple reference charge and discharge management strategies. The fourth estimated effect parameter of each reference charge and discharge management strategy is determined based on the operating temperature, operating current, operating voltage, charge and discharge power of each battery pack in the battery pack parameter set and the multiple reference charge and discharge management strategies. The second risk parameter of each reference charge and discharge management strategy is determined based on the operating temperature, operating current, operating voltage, electrolyte type, electrode type of each battery pack in the battery pack parameter set and the multiple reference charge and discharge management strategies.

[0131] In a possible implementation, the management module 404 is used to fuse the first estimated effect parameter and the second estimated effect parameter of each reference temperature management strategy to obtain the first target estimated effect parameter of each reference temperature management strategy. The first target estimated effect parameter of each reference temperature management strategy is fused with the first risk parameter of each reference temperature management strategy to obtain the first target strategy evaluation score of each reference temperature management strategy. The reference temperature management strategy with the highest first target strategy evaluation score among the multiple reference temperature management strategies is determined as the target temperature management strategy.

[0132] The management module 404 is used to fuse the third estimated effect parameter and the fourth estimated effect parameter of each reference charge and discharge management strategy to obtain the second target estimated effect parameter of each reference charge and discharge management strategy. The second target estimated effect parameter of each reference charge and discharge management strategy is fused with the second risk parameter of each reference charge and discharge management strategy to obtain the second target strategy evaluation score of each reference charge and discharge management strategy. The reference charge and discharge management strategy with the highest second target strategy evaluation score among the multiple reference charge and discharge management strategies is determined as the target charge and discharge management strategy.

[0133] It should be noted that: the energy storage system provided in the above embodiment only uses the division of the above functional modules as an example when performing model warning. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the energy storage system is divided into different functional modules to complete all or part of the functions described above. In addition, the energy storage system provided in the above embodiment and the battery management method embodiment based on cloud-edge integration belong to the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0134] Through the technical solution provided in the embodiment of the present application, a first edge computing device and a second edge computing device are determined from multiple edge computing devices, and the first edge computing device and the second edge computing device are used to obtain multiple reference temperature management strategies and multiple reference charge and discharge management strategies. Combined with the battery pack parameter set of the target energy storage device, the multiple reference temperature management strategies and the multiple reference charge and discharge management strategies, the target temperature management strategy and the target charge and discharge management strategy of the target energy storage device are determined. The target temperature management strategy and the target charge and discharge management strategy are used to manage the target energy storage device, thereby improving the operating stability of the target energy storage device and achieving effective management of the target energy storage device.

[0135] Figure 5 This is a schematic diagram of the structure of a server provided in an embodiment of the present application. The server 500 may have relatively large differences due to different configurations or performances, and may include one or more processors (Central Processing Units, CPU) 501 and one or more memories 502, wherein at least one computer program is stored in the one or more memories 502, and the at least one computer program is loaded and executed by the one or more processors 501 to implement the methods provided in the above-mentioned various method embodiments. Of course, the server 500 may also have components such as a wired or wireless network interface, a keyboard, and an input and output interface for input and output. The server 500 may also include other components for implementing device functions, which will not be described in detail here.

[0136] In an exemplary embodiment, a computer-readable storage medium is also provided, such as a memory including a computer program, and the computer program can be executed by a processor to complete the cloud-edge-based battery management method in the above embodiment. For example, the computer-readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, etc.

[0137] In an exemplary embodiment, a computer program product or a computer program is also provided, which includes a program code, and the program code is stored in a computer-readable storage medium. The processor of the server reads the program code from the computer-readable storage medium, and the processor executes the program code, so that the server executes the above-mentioned cloud-edge combined battery management method.

[0138] In some embodiments, the computer program involved in the embodiments of the present application may be deployed and executed on one server, or on multiple servers located in one location, or on multiple servers distributed in multiple locations and interconnected by a communication network. Multiple servers distributed in multiple locations and interconnected by a communication network may constitute a blockchain system.

[0139] A person skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware or by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a disk or an optical disk, etc.

[0140] The above are only optional embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A battery management method based on cloud-edge integration, characterized in that: Executed by a server, the method includes: Determine a first edge computing device and a second edge computing device from a plurality of edge computing devices, wherein the battery management credibility of the first edge computing device and the second edge computing device are both higher than a credibility threshold, the first edge computing device is used to manage the temperature of a battery pack of an energy storage device, and the second edge computing device is used to manage the charging and discharging power of the battery pack; Acquire a battery pack parameter set of multiple battery packs of a target energy storage device and send the battery pack parameter set to the first edge computing device and the second edge computing device, so that the first edge computing device determines multiple reference temperature management strategies for the target energy storage device based on the battery pack parameter set, and the second edge computing device determines multiple reference charge and discharge management strategies for the target energy storage device based on the battery pack parameter set, wherein the battery pack parameter set includes battery pack parameters of each of the battery packs, and the battery pack parameters include operating parameters and attribute parameters; Obtain multiple reference temperature management strategies returned by the first edge computing device and multiple reference charge and discharge management strategies returned by the second edge computing device; Based on the battery pack parameter set, the multiple reference temperature management strategies and the multiple reference charge and discharge management strategies, a target temperature management strategy and a target charge and discharge management strategy of the target energy storage device are determined, and the target energy storage device is managed based on the target temperature management strategy and the target charge and discharge management strategy.

2. The method according to claim 1, characterized in that The determining of a first edge computing device and a second edge computing device from a plurality of edge computing devices includes: Acquire a device screening parameter set of the plurality of edge computing devices, the device screening parameter set comprising a historical device management strategy of each of the edge computing devices, a historical battery pack parameter set corresponding to the historical device management strategy, and historical management evaluation data; Based on the device screening parameter set, determine a plurality of candidate edge computing devices from the plurality of edge computing devices, wherein the battery management credibility of the plurality of candidate edge computing devices is higher than the credibility threshold; The first edge computing device and the second edge computing device are determined from the plurality of candidate edge computing devices.

3. The method according to claim 2, characterized in that The determining a plurality of candidate edge computing devices from the plurality of edge computing devices based on the device screening parameter set includes: Based on the device screening parameter set, determine a first management credibility and a second management credibility of each of the edge computing devices, wherein the first management credibility is determined based on historical management evaluation data, and the second management credibility is determined based on historical device management policies and corresponding historical battery pack parameter sets; Determining the battery management credibility of each edge computing device based on the first management credibility and the second management credibility of each edge computing device; An edge computing device whose battery management credibility is greater than or equal to the credibility threshold among the multiple edge computing devices is determined as a candidate edge computing device to obtain the multiple candidate edge computing devices.

4. The method according to claim 2, characterized in that: The determining the first edge computing device and the second edge computing device from the plurality of candidate edge computing devices includes: Determine historical temperature management evaluation data and historical charge and discharge management evaluation data of each of the candidate edge computing devices from the historical management evaluation data of the plurality of candidate edge computing devices; Based on the historical temperature management evaluation data and the historical charge and discharge management evaluation data of each of the candidate edge computing devices, the multiple candidate edge computing devices are divided into a first device group and a second device group, the edge computing devices in the first device group are edge computing devices with good temperature management evaluation effects as indicated by the temperature management evaluation data, and the edge computing devices in the second device group are edge computing devices with good charge and discharge management evaluation effects as indicated by the charge and discharge management evaluation data; Based on the historical device management policies of each of the edge computing devices and the historical battery pack parameter sets corresponding to the historical device management policies, the first edge computing device is determined from the first device group, and the second edge computing device is determined from the second device group.

5. The method according to claim 1, characterized in that The method for the first edge computing device to determine multiple reference temperature management strategies for the target energy storage device based on the battery pack parameter set includes: The first edge computing device acquires the battery pack parameters of each of the battery packs from the battery pack parameter set; The first edge computing device determines a plurality of first initial management strategies based on operating parameters in the battery pack parameters of each of the battery packs; The first edge computing device determines a plurality of first reference management strategies from the plurality of first initial management strategies based on the attribute parameters in the battery pack parameters of each of the battery packs, wherein the first reference management strategy is a first initial management strategy matching the attribute parameters; The first edge computing device determines a temperature management strategy among the plurality of first reference management strategies as the plurality of reference temperature management strategies; The method for the second edge computing device to determine multiple reference charge and discharge management strategies for the target energy storage device based on the battery pack parameter set includes: The second edge computing device obtains the battery pack parameters of each of the battery packs from the battery pack parameter set; The second edge computing device determines a plurality of second initial management strategies based on operating parameters in the battery pack parameters of each of the battery packs; The second edge computing device determines a plurality of second reference management strategies from the plurality of second initial management strategies based on the attribute parameters in the battery pack parameters of each of the battery packs, wherein the second reference management strategies are second initial management strategies matching the attribute parameters; The second edge computing device determines the charge and discharge management strategy among the multiple second reference management strategies as the multiple reference charge and discharge management strategies.

6. The method according to claim 5, characterized in that The first edge computing device determines a plurality of first initial management strategies based on operating parameters in the battery pack parameters of each of the battery packs, including: The first edge computing device determines a first battery pack management strategy for each of the battery packs and a first energy storage device management strategy for the target energy storage device based on operating parameters of each of the battery packs; The first edge computing device determines the plurality of first initial management strategies based on the first battery pack management strategy of each of the battery packs and the first energy storage device management strategy of the target energy storage device; The second edge computing device determines a plurality of second initial management strategies based on the operating parameters in the battery pack parameters of each of the battery packs, including: The second edge computing device determines a second battery pack management strategy for each of the battery packs and a second energy storage device management strategy for the target energy storage device based on the operating parameters of each of the battery packs; The second edge computing device determines the multiple second initial management strategies based on the second battery pack management strategy of each of the battery packs and the second energy storage device management strategy of the target energy storage device.

7. The method according to claim 1, characterized in that The determining, based on the battery pack parameter set, the multiple reference temperature management strategies, and the multiple reference charge and discharge management strategies, a target temperature management strategy and a target charge and discharge management strategy of the target energy storage device includes: Based on the battery pack parameter set and the multiple reference temperature management strategies, determine a first estimated effect parameter, a second estimated effect parameter and a first risk parameter of each of the reference temperature management strategies, wherein the first estimated effect parameter is used to represent the temperature management effect of the target energy storage device after executing the corresponding reference temperature management strategy, and the second estimated effect parameter is used to represent the temperature management effect of each of the battery packs after executing the corresponding reference temperature management strategy; Based on the battery pack parameter set and the multiple reference charge and discharge management strategies, determine the third estimated effect parameter, the fourth estimated effect parameter and the second risk parameter of each of the reference charge and discharge management strategies, the third estimated effect parameter is used to represent the charge and discharge management effect of the target energy storage device after executing the corresponding reference charge and discharge management strategy, and the fourth estimated effect parameter is used to represent the charge and discharge management effect of each of the battery packs after executing the corresponding reference charge and discharge management strategy; Determining the target temperature management strategy from the plurality of reference temperature management strategies based on the first estimated effect parameter, the second estimated effect parameter, and the first risk parameter of each of the reference temperature management strategies; The target charge and discharge management strategy is determined from the plurality of reference charge and discharge management strategies based on the third estimated effect parameter, the fourth estimated effect parameter and the second risk parameter of each of the reference charge and discharge management strategies.

8. The method according to claim 7, characterized in that The operating parameters include operating temperature, operating current, operating voltage, remaining power, number of cycles, and charge and discharge power; the attribute parameters include electrolyte type, electrode type, and battery pack connection relationship; and the first estimated effect parameter, the second estimated effect parameter, and the first risk parameter of each reference temperature management strategy are determined based on the battery pack parameter set and the multiple reference temperature management strategies, including: Determine a first estimated effect parameter of each of the reference temperature management strategies based on the operating temperature, electrolyte type, electrode type, battery pack connection relationship of each of the battery packs in the battery pack parameter set and the multiple reference temperature management strategies; Determine a second estimated effect parameter of each of the reference temperature management strategies based on the operating temperature, operating current, operating voltage, remaining power, number of cycles, charge and discharge power of each of the battery packs in the battery pack parameter set and the multiple reference temperature management strategies; Determine a first risk parameter of each of the reference temperature management strategies based on the operating temperature, operating current, operating voltage, charge and discharge power, electrolyte type, electrode type and the plurality of reference temperature management strategies of each of the battery packs in the battery pack parameter set; The determining, based on the battery pack parameter set, a third estimated effect parameter, a fourth estimated effect parameter, and a second risk parameter of each of the reference charge and discharge management strategies includes: Determine a third estimated effect parameter of each of the reference charge and discharge management strategies based on the charge and discharge power, electrolyte type, electrode type, battery pack connection relationship of each of the battery packs in the battery pack parameter set and the multiple reference charge and discharge management strategies; Determine a fourth estimated effect parameter of each of the reference charge and discharge management strategies based on the operating temperature, operating current, operating voltage, charge and discharge power of each of the battery packs in the battery pack parameter set and the multiple reference charge and discharge management strategies; Based on the operating temperature, operating current, operating voltage, electrolyte type, electrode type and the multiple reference charge and discharge management strategies of each of the battery packs in the battery pack parameter set, a second risk parameter of each of the reference charge and discharge management strategies is determined.

9. The method according to claim 7, characterized in that: The determining the target temperature management strategy from the plurality of reference temperature management strategies based on the first estimated effect parameter, the second estimated effect parameter, and the first risk parameter of each of the reference temperature management strategies comprises: Merging the first estimated effect parameter and the second estimated effect parameter of each of the reference temperature management strategies to obtain the first target estimated effect parameter of each of the reference temperature management strategies; Merging the first target estimated effect parameter of each reference temperature management strategy with the first risk parameter of each reference temperature management strategy to obtain a first target strategy evaluation score of each reference temperature management strategy; Determine the reference temperature management strategy with the highest first target strategy evaluation score among the multiple reference temperature management strategies as the target temperature management strategy; The determining the target charge and discharge management strategy from the plurality of reference charge and discharge management strategies based on the third estimated effect parameter, the fourth estimated effect parameter and the second risk parameter of each of the reference charge and discharge management strategies comprises: The third estimated effect parameter and the fourth estimated effect parameter of each of the reference charge and discharge management strategies are merged to obtain the second target estimated effect parameter of each of the reference charge and discharge management strategies; The second target estimated effect parameter of each of the reference charge and discharge management strategies is integrated with the second risk parameter of each of the reference charge and discharge management strategies to obtain a second target strategy evaluation score of each of the reference charge and discharge management strategies; The reference charge and discharge management strategy with the highest second target strategy evaluation score among the multiple reference charge and discharge management strategies is determined as the target charge and discharge management strategy.

10. An energy storage system, characterized in that: include: a device determination module, configured to determine a first edge computing device and a second edge computing device from a plurality of edge computing devices, wherein the battery management credibility of the first edge computing device and the second edge computing device are both higher than a credibility threshold, the first edge computing device is configured to manage the temperature of a battery pack of an energy storage device, and the second edge computing device is configured to manage the charge and discharge power of the battery pack; a parameter acquisition module, configured to acquire a battery pack parameter set of multiple battery packs of a target energy storage device and send the battery pack parameter set to the first edge computing device and the second edge computing device, so that the first edge computing device determines multiple reference temperature management strategies for the target energy storage device based on the battery pack parameter set, and the second edge computing device determines multiple reference charge and discharge management strategies for the target energy storage device based on the battery pack parameter set, wherein the battery pack parameter set includes battery pack parameters of each of the battery packs, and the battery pack parameters include operating parameters and attribute parameters; A strategy acquisition module, used to acquire multiple reference temperature management strategies returned by the first edge computing device and multiple reference charge and discharge management strategies returned by the second edge computing device; A management module is used to determine a target temperature management strategy and a target charge and discharge management strategy of the target energy storage device based on the battery pack parameter set, the multiple reference temperature management strategies and the multiple reference charge and discharge management strategies, and manage the target energy storage device based on the target temperature management strategy and the target charge and discharge management strategy.

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