Method for energy storage system battery management optimization and battery safety management system

Abstract

The application provides a method for energy storage system battery management optimization and a battery safety management system. The method establishes a battery alarm threshold parameter estimation algorithm model, takes the specifications, cell types and running conditions of the energy storage system as the input of the alarm threshold parameter estimation algorithm model, calculates and generates new alarm threshold parameters to replace the original alarm threshold parameters in the battery management system of the energy storage system, and monitors and manages the energy storage system based on the new alarm threshold parameters. The method for energy storage system battery management optimization can establish a battery alarm threshold parameter estimation algorithm model, calculate and generate new alarm threshold parameters for the battery management system, thereby optimizing and adjusting the alarm threshold parameters of the energy storage system, achieving good matching of the cell characteristics, and facilitating the safe operation of the energy storage system.

Description

Technical Field

[0001] This invention relates to the field of power energy storage technology, and in particular to a method for optimizing battery management in energy storage systems. Furthermore, this invention also relates to a battery safety management system. Background Technology

[0002] In energy storage systems using chemical batteries, the battery system consists of modules formed by parallel and series connections of battery cells. One to n modules form a battery box, and m battery boxes form a battery cluster. Depending on the energy storage product, each product contains 1 to a battery clusters. Within the energy storage system, a Battery Management System (BMS) is responsible for safety monitoring and protection throughout the battery's entire lifespan.

[0003] During the operation of the energy storage system, the BMS monitors various real-time data and alarm thresholds of the battery cells, identifies the current safety fault level of the battery system, and takes corresponding safety measures based on the fault level. For example, when different levels of alarms are issued, the system may take the following actions: do not take any action; control the system to shut down and automatically resume operation after the alarm is cleared; or allow the system to resume operation after manual confirmation following fault recovery.

[0004] Existing energy storage systems are generally required to have a lifespan of over 10 years. Throughout the entire lifespan of the energy storage system, the alarm judgment of the Battery Management System (BMS) plays a crucial role in the safety of the battery cells. However, during the entire lifespan of the energy storage system, as the characteristics of the battery cells change, cell consistency and cell capacity will change. The alarm threshold parameters of the BMS cannot be automatically adjusted and must be adjusted by maintenance personnel based on experience. This can lead to potential safety hazards. Untimely adjustment of alarm threshold parameters can result in system faults not being detected and judged in a timely manner, and manually set parameters may not be optimally matched to the current state of the battery cells. Summary of the Invention

[0005] In view of this, the present invention aims to propose a method for optimizing battery management in energy storage systems, so as to optimize the alarm threshold parameters of the battery management system in energy storage systems in a timely manner, thereby facilitating the safe operation of energy storage systems.

[0006] To achieve the above objectives, the technical solution of the present invention is implemented as follows:

[0007] A method for optimizing battery management in an energy storage system involves establishing a pre-estimation model for alarm threshold parameters of the battery. Information data regarding the specifications, cell type, and operating status of the energy storage system are used as input to this model to calculate and generate new alarm threshold parameters that cover the existing alarm threshold parameters in the battery management system of the energy storage system. The battery management system then monitors and manages the energy storage system based on these new alarm threshold parameters.

[0008] Furthermore, the data of the alarm threshold parameter prediction algorithm model is stored in the EMS controller of the energy storage system; the EMS controller is connected to the cloud data platform and receives updates to the alarm threshold parameter prediction algorithm model from the cloud data platform.

[0009] Furthermore, the operational information data includes at least the operating time and number of charge / discharge cycles of the energy storage system.

[0010] Furthermore, the alarm threshold parameters include at least one of the following: module voltage, charging current, discharging current, charging cell temperature, cell temperature difference, insulation resistance, cell voltage, module temperature difference, and discharge cell temperature alarm upper and lower limits and hysteresis values.

[0011] Furthermore, the battery management system is configured as a primary BMS and a secondary BMS; the primary BMS is used for collecting information on the cell's voltage, temperature, SOC, and SOH, as well as data processing within the module.

[0012] The secondary BMS is used for data statistics, alarm threshold judgment and monitoring of the battery cluster. The alarm threshold parameter is located in the secondary BMS. The secondary BMS monitors the operation of the battery cluster based on the alarm threshold parameter and issues corresponding alarm actions.

[0013] Furthermore, the alarm threshold parameters include first-level alarm threshold parameters, second-level alarm threshold parameters, and third-level alarm threshold parameters, and the alarm severity corresponding to each level of alarm threshold parameter increases progressively.

[0014] Compared with the prior art, the present invention has the following advantages:

[0015] The present invention provides a method for optimizing battery management in energy storage systems. By establishing a pre-estimation algorithm model for battery alarm threshold parameters, and using this algorithm model and relevant information data of the energy storage system, new alarm threshold parameters are calculated and generated for use by the battery management system. This allows for the optimization and adjustment of the alarm threshold parameters of the energy storage system, achieving a good match with the characteristics of the battery cells and facilitating the safe operation of the energy storage system.

[0016] In addition, an EMS controller is set up in the battery management system of the battery safety management system. The EMS controller stores and calculates the alarm threshold parameters of the battery management system and accepts the updated data of the alarm threshold parameter prediction algorithm model from the cloud data platform. Based on big data, an algorithm model more suitable for the current operation of the energy storage system can be obtained, thereby generating alarm threshold parameters that are more matched with the battery characteristics, which helps to improve the operating status of the energy storage system.

[0017] In addition, the present invention also provides a battery safety management system, including an energy storage system and a battery management system disposed in the energy storage system; the battery safety management system further includes an EMS controller communicatively connected to the battery management system, the EMS controller having an energy storage system information storage unit, a BMS alarm threshold storage module, a battery prediction algorithm model storage module, and a calculation module; the energy storage system information storage unit is used to store information data on the specifications, cell type, and operating status of the energy storage system; the BMS alarm threshold storage module is used to store alarm threshold parameters of the battery management system; the battery prediction algorithm model storage module is used to store adjustment calculation model data of the alarm threshold parameters;

[0018] The calculation module generates new alarm threshold parameters based on the adjustment calculation model and the information data in the energy storage system information storage unit, and stores them in the BMS alarm threshold storage module; the battery management system obtains the alarm threshold parameters in the BMS alarm threshold storage module to overwrite the original alarm threshold parameters.

[0019] Furthermore, the energy storage system information storage unit includes a basic information storage module and an operation information storage module. The basic information storage module is used to store information data on the specifications and cell types of the energy storage system, and the operation information storage module is used to store information data on the operation status of the energy storage system.

[0020] Furthermore, the EMS controller is configured with an external communication port, through which the EMS controller communicates with the outside world to update the data in the battery prediction algorithm model storage module.

[0021] Furthermore, the energy storage system is equipped with an energy storage converter, which is controlled by the EMS controller to perform charging and discharging operations on the energy storage system.

[0022] Compared with the prior art, the present invention has the following advantages:

[0023] The battery safety management system of the present invention includes an EMS controller for the battery management system. The EMS controller stores and calculates and adjusts the alarm threshold parameters of the battery management system. It can adjust the alarm threshold parameters in a timely manner according to the performance and operating status of the energy storage system, thereby optimizing the configuration of the alarm threshold parameters of the battery management system in the energy storage system and facilitating the safe operation of the energy storage system.

[0024] Furthermore, based on basic information such as the specifications, power, and cell type of the energy storage system, as well as operational information such as the operating time and number of charge / discharge cycles of the energy storage system, the alarm threshold parameters of the energy storage system can be optimized and adjusted. This not only allows for successful calculation with the support of the battery prediction algorithm model storage module of the EMS controller, but also improves the optimization response speed and enhances the flexibility of adjusting the alarm threshold parameters of the energy storage system. Attached Figure Description

[0025] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments and descriptions of the invention are for explaining the invention. The directional terms used, such as front / back, up / down, etc., are only used to indicate relative positional relationships and do not constitute an improper limitation of the invention. In the drawings:

[0026] Figure 1 This is a flowchart illustrating the steps of the method for optimizing battery management in an energy storage system according to Embodiment 1 of the present invention.

[0027] Figure 2 This is a schematic diagram of the system configuration of the battery safety management system described in Embodiment 2 of the present invention;

[0028] Figure 3 This is a schematic diagram of the internal structure of the EMS controller according to an embodiment of the present invention;

[0029] Explanation of reference numerals in the attached figures:

[0030] 1. EMS controller; 10. Energy storage system information storage unit; 11. BMS alarm threshold storage module; 101. Basic information storage module; 102. Operation information storage module; 12. Battery prediction algorithm model storage module; 13. External communication port; 14. Calculation module; 15. External devices;

[0031] 2. Energy storage system;

[0032] 3. Cloud data platform; 30. Communication network;

[0033] 4. Energy storage converter; 5. Battery management system;

[0034] 601. Level 1 alarm threshold parameters; 602. Level 2 alarm threshold parameters; 603. Level 3 alarm threshold parameters. Detailed Implementation

[0035] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0036] In the description of this invention, it should be noted that the terms "installation," "connection," "connection," and "connector" should be interpreted broadly. For example, a connection can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or it can be a connection within two components. Those skilled in the art can understand the specific meaning of the above terms in this invention in light of the specific circumstances. Furthermore, the energy storage converter mentioned in this invention refers to a PCS (Power Conversion System); EMS refers to an energy management system; and an EMS controller refers to an edge controller used for the control and management of the energy management system.

[0037] The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0038] Example 1

[0039] This embodiment relates to a method for optimizing battery management in an energy storage system. It can optimize and adjust the alarm threshold parameters of the energy storage system to achieve a good match with the characteristics of the battery cells, thus facilitating the safe operation of the energy storage system. An exemplary procedure is as follows: Figure 1 As shown.

[0040] Overall, this method first establishes a pre-estimation model for battery alarm threshold parameters. Information on the specifications, cell type, and operating status of energy storage system 2 is used as input to this model to calculate and generate new alarm threshold parameters, thus overriding the existing alarm threshold parameters in the battery management system 5 of energy storage system 2. The battery management system 5 then monitors and manages energy storage system 2 based on these new alarm threshold parameters.

[0041] Specifically, an EMS controller 1 can be configured for the energy storage system 2 to work in conjunction with the battery management system 5 of the energy storage system 2, monitor the operating status of the battery management system 5, and collect battery-related data collected by the battery management system 5. At this time, the data of the alarm threshold parameter prediction algorithm model can be stored in the EMS controller 1; simultaneously, the EMS controller 1 is connected to the cloud data platform 3 and receives updated data from the cloud data platform 3 on the alarm threshold parameter prediction algorithm model, thereby continuously updating and optimizing the model.

[0042] By accepting updated data from the alarm threshold parameter prediction algorithm model from the cloud data platform 3, an algorithm model more suitable for the current operating conditions of the energy storage system 2 can be obtained based on big data, thereby generating alarm threshold parameters that are more matched with battery characteristics, which helps to improve the operating status of the energy storage system 2.

[0043] When establishing or updating the alarm threshold parameter prediction algorithm model, it is necessary to make corresponding configurations based on the relevant data of the operation status of energy storage system 2. This operation status information data should at least include the running time and number of charge and discharge cycles of energy storage system 2, so as to better match the operation status of energy storage system 2.

[0044] The alarm threshold parameters mentioned above can include various cell parameters such as module voltage, charging current, discharging current, charging cell temperature, cell temperature difference, insulation resistance, cell voltage, module temperature difference, and discharging cell temperature, and further include the alarm upper and lower limits and hysteresis values ​​of these parameters, thereby realizing comprehensive monitoring and alarm control of the energy storage system 2.

[0045] In the configuration of the battery management system 5, the battery management system 5 of this embodiment is set up with two levels, including a primary BMS and a secondary BMS. The primary BMS is used for the collection of information on the voltage, temperature, SOC, and SOH of the battery cells, as well as data processing within the module; the secondary BMS is used for data statistics of the battery cluster, judgment and monitoring of data alarm thresholds. The alarm threshold parameters are located in the secondary BMS. The secondary BMS monitors the operation of the battery cluster based on the alarm threshold parameters and issues corresponding alarm actions.

[0046] Furthermore, the aforementioned alarm threshold parameters are set in three levels: Level 1 alarm threshold parameter 601, Level 2 alarm threshold parameter 602, and Level 3 alarm threshold parameter 603; and the alarm severity corresponding to each level of alarm threshold parameter increases progressively. In response to the triggering of alarm threshold parameters at different levels, the battery management system 5 can take corresponding warning or protective actions against the energy storage system 2.

[0047] In summary, the method for optimizing battery management in an energy storage system according to the present invention establishes a pre-estimation algorithm model for battery alarm threshold parameters, and uses this algorithm model and relevant information data of the energy storage system 2 to calculate and generate new alarm threshold parameters for use by the battery management system 5. This allows for the optimization and adjustment of the alarm threshold parameters of the energy storage system 2, achieving a good match with the characteristics of the battery cells and facilitating the safe operation of the energy storage system 2.

[0048] Example 2

[0049] This embodiment relates to a battery safety management system, which facilitates timely optimization of alarm threshold parameters of the battery management system 5 in the energy storage system 2, thereby promoting the safe operation of the energy storage system 2; an exemplary system configuration of this battery safety management system is as follows: Figure 2 and Figure 3 As shown.

[0050] Overall, the battery safety management system includes an energy storage system 2 and a battery management system 5 located within the energy storage system 2. The battery safety management system also includes an EMS controller 1 that is communicatively connected to the battery management system 5. The EMS controller 1 includes an energy storage system information storage unit 10, a BMS alarm threshold storage module 11, a battery pre-calculation model storage module 12, and a calculation module 14. The energy storage system information storage unit 10 stores information data about the specifications, cell types, and operating status of the energy storage system 2. The BMS alarm threshold storage module 11 stores alarm threshold parameters of the battery management system 5. The battery pre-calculation model storage module 12 stores adjustment calculation model data for the alarm threshold parameters. The calculation module 14 generates new alarm threshold parameters based on the adjustment calculation model and the information data in the energy storage system information storage unit 10, and stores them in the BMS alarm threshold storage module 11. The battery management system 5 retrieves the alarm threshold parameters from the BMS alarm threshold storage module 11 to overwrite the existing alarm threshold parameters.

[0051] Based on the above design concept, the specific implementation scheme of this embodiment will be described in detail below.

[0052] like Figure 3 As shown, the energy storage system information storage unit 10 includes a basic information storage module 101 and an operation information storage module 102. The basic information storage module 101 stores information data regarding the specifications and cell types of the energy storage system 2, while the operation information storage module 102 stores information data regarding the operation status of the energy storage system 2. Furthermore, the aforementioned operation status information data should at least include basic information such as the operating time and number of charge / discharge cycles of the energy storage system 2, in order to provide an accurate basis for determining new alarm threshold parameters.

[0053] Based on the basic information of the energy storage system 2, such as its specifications, power, and cell type, as well as its operating information such as its operating time and number of charge / discharge cycles, the alarm threshold parameters of the energy storage system 2 can be optimized and adjusted. This not only allows for successful calculation with the support of the battery pre-estimation model storage module 12 of the EMS controller 1, but also improves the optimization response speed and enhances the flexibility of adjusting the alarm threshold parameters of the energy storage system 2.

[0054] Furthermore, the battery management system 5 in this embodiment has two levels, including a primary BMS and a secondary BMS. The primary BMS is used for collecting information on the voltage, temperature, SOC, and SOH of the battery cells, as well as data processing within the module. The secondary BMS is used for data statistics of the battery cluster, data alarm threshold judgment and monitoring, with alarm threshold parameters located within the secondary BMS. The battery management system 5 is configured in two levels to separately collect state data of the battery cells in the energy storage system 2 and monitor alarm judgment, thereby improving the operational performance of the battery management system 5.

[0055] The alarm threshold parameters mentioned above are set in the secondary BMS, and the alarm threshold parameters in the secondary BMS are read and updated from the BMS alarm threshold storage module 11 in the EMS controller 1. For example... Figure 2 and combined Figure 3 As shown, the alarm threshold parameters in this embodiment include a first-level alarm threshold parameter 601, a second-level alarm threshold parameter 602, and a third-level alarm threshold parameter 603, with the alarm severity corresponding to each level increasing progressively. Configuring the alarm threshold parameters to three levels with progressively increasing alarm severity allows for timely implementation of appropriate control and protection measures based on the alarm severity of the energy storage system 2.

[0056] Specifically, the alarm severity increases progressively with each level: Level 1 alarm threshold parameter 601, Level 2 alarm threshold parameter 602, and Level 3 alarm threshold parameter 603. Each alarm level has alarm judgment threshold parameters for various parameters. These threshold parameters typically include: upper / lower limit / hysteresis value for group terminal voltage alarm, overcurrent alarm value / hysteresis value for charging current, overcurrent alarm value / hysteresis value for discharging current, upper / lower limit / hysteresis value for charging cell overtemperature alarm, individual cell temperature difference alarm limit, low insulation resistance alarm value, upper / lower limit / hysteresis value for individual cell voltage alarm, upper / lower limit / hysteresis value for module temperature difference alarm, and upper / lower limit / hysteresis value for discharging cell temperature alarm, etc.

[0057] During the operation of energy storage system 2, battery management system 5 monitors various real-time data and alarm thresholds of each cell, identifies the current safety fault level of energy storage system 2, and takes corresponding safety measures based on the fault level. For example, when the first-level alarm threshold parameter 601 is triggered and an alarm is issued, generally no action is taken; when the second-level alarm threshold parameter 602 is triggered and an alarm is issued, the system generally shuts down and automatically resumes operation after the alarm is cleared; when the third-level alarm threshold parameter 603 is triggered and an alarm is issued, the system generally trips, and fault recovery requires manual confirmation before the system can be manually restarted.

[0058] In addition, the energy storage system 2 is equipped with an energy storage converter 4, which is controlled by the EMS controller 1 to perform charging and discharging operations on the energy storage system 2. The energy storage converter 4 within the energy storage system 2 controls the charging and discharging state of the system and can promptly execute charging / discharging restrictions when an alarm level reaches a corresponding level. When a relevant alarm occurs, the energy storage converter 4 can also be controlled to fully charge / discharge each cell in the energy storage system 2, or to restrict charging / discharging of the system 2.

[0059] like Figure 2 As shown, the EMS controller 1 is equipped with an external communication port 13. The EMS controller 1 connects to an external communication source via this port to adjust the data in the battery prediction algorithm model storage module 12. Configuring the external communication port 13 on the EMS controller 1 enables connection between the EMS controller 1 and an external data platform or read / write device, facilitating timely updates and adjustments to the model data in the battery prediction algorithm model storage module 12. The external device 15 can be a laptop or other device used for reading and writing relevant parameter data to the EMS controller 1.

[0060] Furthermore, a cloud data platform 3 can be set up, and the EMS controller 1 can be connected to the cloud data platform 3 via a communication network 30. Using the cloud data platform 3, a large amount of operational data information of the energy storage system 2 can be stored. This allows for continuous optimization of the alarm threshold parameter adjustment calculation model based on artificial intelligence algorithms, thus providing the most suitable adjustment calculation model for different energy storage systems 2. Through the cell lifespan prediction algorithm of the big data cloud platform, and by integrating factors such as system operating conditions and user habits, the optimal alarm threshold parameters for the current energy storage system 2 are comprehensively derived, demonstrating good operational performance.

[0061] The battery safety management system of this embodiment can include only one energy storage system 2, or it can include multiple energy storage systems 2. In this embodiment, the battery safety management system includes multiple energy storage systems 2, and the battery management system 5 of each energy storage system 2 is communicatively connected to the EMS controller 1. By configuring one EMS controller 1 for multiple energy storage systems 2, the system can simultaneously manage and monitor the operation of multiple energy storage systems 2, and adjust the alarm threshold parameters of each energy storage system 2 in a timely manner based on its operating status, thereby achieving safe and stable operation of each energy storage system 2.

[0062] In summary, the battery safety management system of this embodiment includes an EMS controller 1 for the battery management system 5. The EMS controller 1 stores and calculates the alarm threshold parameters of the battery management system 5, and can adjust the alarm threshold parameters in a timely manner according to the performance and operating status of the energy storage system 2. This optimizes the configuration of the alarm threshold parameters of the battery management system 5 in the energy storage system 2, which is beneficial to the safe operation of the energy storage system 2.

[0063] The dynamic optimization method for alarm threshold parameters in the battery management system 5 can automatically optimize the system during operation based on an artificial intelligence algorithm model. This allows for real-time determination of the optimal alarm threshold parameter matching as operating conditions, load habits, grid characteristics, and cell lifespan change, and the system is then updated and optimized in real time based on the battery safety management system of this invention. Implementing the above process in the EMS controller 1 improves the optimization response speed and provides more flexible configuration and use of alarm threshold parameters.

[0064] By dynamically optimizing and adjusting the alarm threshold parameters of energy storage system 2, the best match with the characteristics of the battery cells can be achieved, which can improve the safety of battery cell operation and extend the battery cell life. Furthermore, it can help reduce the occurrence of safety accidents in energy storage system 2, extend the system life, and thus increase user benefits.

[0065] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for optimizing battery management in an energy storage system, characterized in that: A battery alarm threshold parameter prediction model and a battery safety management system are established. The battery safety management system includes an energy storage system (2), a battery management system (5) located in the energy storage system (2), and an EMS controller (1) that is communicatively connected to the battery management system (5). The data of the alarm threshold parameter prediction model is stored in the EMS controller (1). The EMS controller (1) is provided with an energy storage system information storage unit (10), a BMS alarm threshold storage module (11), a battery prediction model storage module (12), and a calculation module (14). The specifications, cell type, and operating status of the energy storage system (2) are used as input to the alarm threshold parameter estimation model to calculate and generate new alarm threshold parameters to cover the original alarm threshold parameters in the battery management system (5); the battery management system (5) monitors and manages the energy storage system (2) based on the new alarm threshold parameters. The battery management system (5) is configured as a primary BMS and a secondary BMS; the primary BMS is used for the collection of information on the voltage, temperature, SOC, and SOH of the battery cells, as well as data processing within the module; The secondary BMS is used for data statistics, data alarm threshold judgment and monitoring of the battery cluster. The alarm threshold parameter is located in the secondary BMS. The secondary BMS monitors the operation of the battery cluster based on the alarm threshold parameter and issues corresponding alarm actions. The energy storage system information storage unit (10) is used to store information data on the specifications, cell type, and operating status of the energy storage system (2); the BMS alarm threshold storage module (11) is used to store alarm threshold parameters of the battery management system (5); the battery pre-calculation model storage module (12) is used to store adjustment calculation model data of the alarm threshold parameters; The calculation module (14) generates new alarm threshold parameters based on the adjustment calculation model and the information data in the energy storage system information storage unit (10), and stores them in the BMS alarm threshold storage module (11); the battery management system (5) obtains the alarm threshold parameters in the BMS alarm threshold storage module (11) to overwrite the original alarm threshold parameters.

2. The method for optimizing battery management in an energy storage system according to claim 1, characterized in that: The EMS controller (1) is connected to the cloud data platform (3) and receives updates from the cloud data platform (3) to the alarm threshold parameter prediction algorithm model.

3. The method for optimizing battery management in an energy storage system according to claim 1, characterized in that: The operational information data includes at least the operating time and number of charge / discharge cycles of the energy storage system (2).

4. The method for optimizing battery management in an energy storage system according to claim 1, characterized in that: The alarm threshold parameters include at least one of the following: module voltage, charging current, discharging current, charging cell temperature, cell temperature difference, insulation resistance, cell voltage, module temperature difference, and discharge cell temperature alarm upper and lower limits and hysteresis values.

5. The method for optimizing battery management in an energy storage system according to any one of claims 1 to 4, characterized in that: The alarm threshold parameters include a first-level alarm threshold parameter (601), a second-level alarm threshold parameter (602), and a third-level alarm threshold parameter (603), and the alarm severity corresponding to each level of alarm threshold parameter increases progressively.

6. The method for optimizing battery management in an energy storage system according to claim 5, characterized in that: The energy storage system information storage unit (10) includes a basic information storage module (101) and an operation information storage module (102). The basic information storage module (101) is used to store information data on the specifications and cell types of the energy storage system (2), and the operation information storage module (102) is used to store information data on the operation status of the energy storage system (2).

7. The method for optimizing battery management in an energy storage system according to claim 6, characterized in that: The EMS controller (1) is equipped with an external communication port (13). The EMS controller (1) communicates with the outside through the external communication port (13) to update the data in the battery prediction algorithm model storage module (12).

8. The method for optimizing battery management in an energy storage system according to claim 6, characterized in that: The energy storage system (2) is equipped with an energy storage converter (4), which is controlled by the EMS controller (1) and performs charging and discharging operations on the energy storage system (2).

Images