Multi-type tiered battery management method, system, apparatus, and storage medium

By establishing an independent communication link for each battery cluster, performing state of charge calculation and power optimization allocation, the problem of system performance degradation caused by battery differences in the collaborative management of tiered batteries is solved, achieving refined monitoring and improved safety.

CN122246316APending Publication Date: 2026-06-19SHENZHEN YILANCO ELECTRIC CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
SHENZHEN YILANCO ELECTRIC CO LTD
Filing Date
2026-05-19
Publication Date
2026-06-19

AI Technical Summary

⚠Technical Problem

Existing tiered battery collaborative management schemes ignore the significant differences between battery clusters, leading to a decrease in the overall available capacity of the system, accelerated degradation of individual battery cells, safety hazards, and impact on the economy and reliability of energy storage systems.

⚗Method used

By establishing an independent communication link for each battery cluster, performing state of charge calculation and power optimization allocation, and generating personalized control commands, refined monitoring and balanced management of the battery clusters can be achieved.

🎯Benefits of technology

It improves the overall available capacity and balancing efficiency of the system, ensures safety, and enhances the economy and response accuracy of the energy storage system in peak-valley arbitrage and frequency regulation applications.

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Abstract

This application provides a method, system, device, and storage medium for managing multiple types of cascaded batteries. The method includes: polling battery clusters connected to each energy storage converter sequentially using a communication protocol through an energy management system to establish an independent communication link with each battery cluster; periodically collecting the operating status data of the battery clusters uploaded by each energy storage converter based on the independent communication link, and performing state of charge (SOC) calculation to obtain real-time SOC values; when the statistical dispersion exceeds a preset dispersion threshold, calculating the individual deviation of each SOC value from a preset balancing benchmark, and integrating all individual deviations to obtain a personalized power bias set; combining all real-time SOC values ​​with the personalized power bias set to perform power optimization allocation, generating and issuing independent control commands to each energy storage converter to complete SOC balancing management. This application can flexibly adjust the power allocation strategy according to the real-time status.
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