CN-122001041-A - Battery cell information cloud management method, device and storage medium of energy storage system

CN122001041ACN 122001041 ACN122001041 ACN 122001041ACN-122001041-A

Abstract

A battery core information cloud management method, equipment and storage medium of an energy storage system relate to the technical field of battery core management and comprise the steps of constructing a multi-layer digital twin model corresponding to a physical energy storage system, carrying out at least two-stage progressive feature extraction and information aggregation on battery core sensing data along a data acquisition path of the physical energy storage system to generate multi-granularity situation data for updating node states of different layers of the digital twin model, and providing interactive visual service linked with the digital twin model. The method solves the problem of interaction passivity, and realizes active, accurate and intelligent exploration and positioning of mass battery cells.

Inventors

Zhu Ruida
ZHANG HUI
DU MINGYU
TAN SHUAISHUAI
CHENG CHAOLONG
LI TANXIN

Assignees

深能源(深圳)创新技术有限公司
深圳市盛路物联通讯技术有限公司
深能北方能源控股有限公司

Dates

Publication Date: 20260508
Application Date: 20260120

Claims (10)

1. The battery cell information cloud management method of the energy storage system is characterized by comprising the following steps of: Constructing a multi-layer digital twin model corresponding to a physical energy storage system, wherein the multi-layer digital twin model can map the hierarchical organization structure and the spatial position relation of an electric core in the physical energy storage system; Performing at least two-stage progressive feature extraction and information aggregation on the cell sensing data along a data acquisition path of the physical energy storage system to generate multi-granularity situation data for updating node states of different levels of the digital twin model; and providing an interactive visual service linked with the digital twin model, wherein the service at least supports navigation based on a spatial structure of the digital twin model and supports condition screening based on multi-dimensional attributes of the battery cells, and target positioning and information penetration are performed in the digital twin model.
2. The method of claim 1, wherein the performing at least two-stage progressive feature extraction and information aggregation on the cell sensing data along the data collection path of the physical energy storage system comprises: Processing the original cell sensing data at a first-stage processing node to generate first-stage characteristic data containing cell individual dynamic characteristics and local group consistency indexes; Fusing the first-level characteristic data from a plurality of first-level processing nodes at a second-level processing node higher than the first-level processing node to generate second-level regional situation data containing spatial distribution visual information and regional cluster statistical summaries; and uploading the second-level regional situation data to a cloud end for driving dynamic update of the digital twin model.
3. The method of claim 2, wherein the first level processing nodes are deployed at a battery pack or battery cluster level and the second level processing nodes are deployed at a container or energy storage unit level.
4. The method of claim 2, wherein the individual dynamic features in the first level feature data at least comprise real-time deviation of cell voltage or temperature from the average value of the local population, and voltage or temperature change trend values calculated based on time series, and the local population consistency index at least comprises voltage extreme differences or standard deviations.
5. The method of claim 2, wherein generating the spatial distribution visualization information comprises: And mapping key feature values in the first-level feature data into visual variables based on predefined cell space coordinates, and rendering on a base map of a corresponding physical structure to generate a thermodynamic diagram.
6. The method of claim 1, wherein the performing object localization and information penetration in the digital twin model based on conditional screening of cell multi-dimensional properties comprises: Providing a configurable filter, allowing a user to set query conditions related to the real-time state, historical performance trend and spatial location attribute of the battery cell in a combined manner; according to the query conditions, searching the matched cell entities in the digital twin model in real time; in the visual interface, the retrieved cell entities are synchronously highlighted in each hierarchical structure view to which the cell entities belong, and the cell entities support to drill down from the highlighting position to acquire associated full-dimension data.
7. The method according to claim 1 or 6, characterized in that the method further comprises: And responding to the selection of the user to the historical time point, and calling and reproducing the state snapshot of the digital twin model at the corresponding historical moment so as to support the interactive investigation analysis of the historical event.
8. The utility model provides an electric core information high in clouds management device of energy storage system which characterized in that includes: The construction module is used for constructing a multi-layer digital twin model corresponding to the physical energy storage system, and the multi-layer digital twin model can map the hierarchical organization structure and the spatial position relation of the battery cells in the physical energy storage system; The aggregation module is used for carrying out at least two-stage progressive feature extraction and information aggregation on the battery cell sensing data along a data acquisition path of the physical energy storage system so as to generate multi-granularity situation data for updating the node states of different levels of the digital twin model; The system comprises a providing module, a processing module and a processing module, wherein the providing module is used for providing interactive visualization service linked with the digital twin model, and the service at least supports navigation based on a spatial structure of the digital twin model and supports condition screening based on multi-dimensional attributes of a battery cell, and target positioning and information penetration are performed in the digital twin model.
9. The battery cell information cloud management device of the energy storage system is characterized by comprising a processor, a memory and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the computer program to realize the steps of the method according to any one of claims 1 to 7.
10. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method according to any one of claims 1 to 7.

Description

Battery cell information cloud management method, device and storage medium of energy storage system Technical Field The application belongs to the technical field of battery management, and particularly relates to a battery cell information cloud management method, equipment and a storage medium of an energy storage system. Background The monitoring system of the current large-scale energy storage power station faces three core bottlenecks, namely firstly, fragmentation of information presentation, disconnection of hierarchical and spatial structures of a data interface and a physical system, difficulty in cognition of operation and maintenance personnel, low positioning efficiency, secondly, flat and extensive data processing, direct cloud loading of massive low-value original data, waste of bandwidth storage, incapability of improving multi-granularity situation information serving different hierarchical decisions, weak early warning and root cause analysis capability, and finally, passive stiffness of user interaction, lack of multi-dimensional active exploration and intelligent screening tools based on space, attribute, trend and the like, and difficulty in converting massive data into effective insight. The prior art can not meet the requirement of the gigawatt-level energy storage system on upgrading from passive monitoring to active intelligent treatment. Disclosure of Invention In view of the above, the embodiment of the application provides a battery cell information cloud management method, equipment and a storage medium of an energy storage system, which solve the problem of information fragmentation by constructing a digital twin model of a mapping physical structure, solve the problem of rough data processing by carrying out at least two-stage progressive feature extraction and aggregation along a data path, realize high-efficiency extraction and layering utilization of data values, remarkably lighten system load, and solve the problem of interaction and passive by providing a visual service which is linked with the twin model and supports space navigation and multidimensional screening, thereby realizing active, accurate and intelligent exploration and positioning of massive battery cells. The embodiment of the application provides a battery cell information cloud management method of an energy storage system, which comprises the following steps: Constructing a multi-layer digital twin model corresponding to a physical energy storage system, wherein the multi-layer digital twin model can map the hierarchical organization structure and the spatial position relation of an electric core in the physical energy storage system; Performing at least two-stage progressive feature extraction and information aggregation on the cell sensing data along a data acquisition path of the physical energy storage system to generate multi-granularity situation data for updating node states of different levels of the digital twin model; and providing an interactive visual service linked with the digital twin model, wherein the service at least supports navigation based on a spatial structure of the digital twin model and supports condition screening based on multi-dimensional attributes of the battery cells, and target positioning and information penetration are performed in the digital twin model. In an embodiment, the performing at least two-stage progressive feature extraction and information aggregation on the battery cell sensing data along the data acquisition path of the physical energy storage system includes: Processing the original cell sensing data at a first-stage processing node to generate first-stage characteristic data containing cell individual dynamic characteristics and local group consistency indexes; Fusing the first-level characteristic data from a plurality of first-level processing nodes at a second-level processing node higher than the first-level processing node to generate second-level regional situation data containing spatial distribution visual information and regional cluster statistical summaries; and uploading the second-level regional situation data to a cloud end for driving dynamic update of the digital twin model. In one embodiment, the first level processing nodes are deployed at the battery pack or battery cluster level and the second level processing nodes are deployed at the container or energy storage unit level. In an embodiment, the individual dynamic characteristics in the first-level characteristic data at least comprise real-time deviation of the voltage or the temperature of the battery cell relative to the average value of the local group and a voltage or temperature change trend value calculated based on time sequence, and the local group consistency index at least comprises a voltage polar difference or a standard deviation. In an embodiment, generating the spatial distribution visualization information includes: And mapping key feature values in the first-level f