Individual differentiation intelligent charging and discharging optimization method and system for communication power storage battery

By collecting individual data and using a co-evolutionary reinforcement learning algorithm, a differentiated control strategy model was constructed, which solved the problems of individual battery difference identification and strategy adjustment in communication power supply battery management, realizing intelligent management, extending lifespan and improving power supply reliability.

CN122292591APending Publication Date: 2026-06-26BEIJING KEDONG ELECTRIC POWER CONTROL SYST CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
BEIJING KEDONG ELECTRIC POWER CONTROL SYST CO LTD
Filing Date
2026-03-26
Publication Date
2026-06-26

AI Technical Summary

Technical Problem

In current communication power supply battery management, individual cell differences are ignored, resulting in high-performance batteries not being able to fully realize their potential, while low-performance batteries are prone to accelerated aging due to overcharging and over-discharging. Furthermore, it is difficult to accurately identify individual cell differences and dynamically adjust strategies, which poses risks of communication interruption and shortened lifespan.

Method used

By collecting individual data, we construct the state of charge, category, and anomaly flags. Using a co-evolutionary reinforcement learning algorithm, we determine the comprehensive reward function, construct a differentiated control strategy model, and output the optimal charging and discharging strategy to achieve individual-differentiated intelligent charging and discharging optimization.

Benefits of technology

It accurately identifies individual unit performance differences, dynamically adapts charging and discharging strategies, extends lifespan, reduces operation and maintenance costs, improves power supply reliability and security, reduces the risk of communication interruption, and optimizes overall performance.

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Abstract

This invention proposes a method and system for individualized intelligent charging and discharging optimization of communication power batteries. The method includes collecting data from all individual battery cells; determining the state of charge, category, and anomaly indicators of each battery cell based on this data; constructing individual cell state features using these features and a co-evolutionary reinforcement learning algorithm; determining a comprehensive reward function for each battery cell based on these features; performing online strategy optimization based on the reward function to construct a differentiated control strategy model for each battery cell; inputting real-time data from each battery cell into the differentiated control strategy model; and outputting the optimal charging and discharging strategy for each battery cell to implement individualized intelligent charging and discharging optimization of the communication power battery. This invention improves the accuracy of individual battery state perception, extends the battery's lifespan, and enhances the reliability of charging and discharging.
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Citation Information

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