How can BMS maximize asset value with the support of AI?

As AI technology rapidly penetrates physical sectors such as industrial manufacturing, energy, and transportation, the lithium battery industry is experiencing a value transformation driven by algorithms.

For decades, Battery Management Systems (BMS) have been hardware-centric, with control strategies fixed at the factory. Safety thresholds, balancing logic, and lifespan management were confined within preset frameworks, making it difficult to adapt to the dynamic changes throughout a battery's lifecycle.

With the deep integration of cloud computing, machine learning, and big data, Battery Management Systems (BMS) have transcended the physical limitations of hardware, evolving from passive battery protection to proactive asset management.

In this industrial wave of AI and lithium battery integration, Youdan Technology has taken the lead in completing its deployment and implementation.

Centered on "keeping lithium batteries always online," Udan Technology has developed an integrated "edge-cloud-intelligence" iBMS technical architecture. This architecture incorporates AI capabilities across the entire process of data collection, status analysis, strategy optimization, and operation and maintenance management. It has been extensively applied in various scenarios, including industrial and commercial energy storage, battery swapping for two-wheeled vehicles, and construction machinery, establishing a development path characterized by technological differentiation and diverse application scenarios.