The storage battery serves as the core backup power source in the DC power system of substations, with its health directly impacting the reliability and stability of the power system. However, traditional battery management relies on manual periodic testing, lacking real-time monitoring capabilities and thereby making it challenging to promptly identify potential failures. This paper presents a storage battery intelligent management system based on big data analysis and intelligent control technologies, examining multiple cases of DC power system faults and risks identified through its application. By collecting battery data on voltage, internal resistance, and temperature, the system establishes a capacity estimation model and predicts battery health status. Additionally, it achieves intelligent charging management, addressing challenges in open-circuit voltage measurement and open-circuit fault prevention, thereby enhancing the safety and efficiency of battery group power supply management and advancing the digitalization and intelligence of power systems.