Title : Sodium-ion battery energy storage system: Modeling, data-driven state estimation and applications
Abstract:
Sodium-ion battery energy storage systems (SIB-ESSs) have emerged as a transformative and strategically important alternative to conventional lithium-ion battery technologies. This growing interest is primarily driven by the widespread availability and low cost of sodium resources, which offer a sustainable pathway for large-scale energy storage deployment. Unlike lithium, sodium is abundantly distributed across the Earth’s crust and seawater, significantly reducing concerns associated with resource scarcity, geopolitical dependence, and raw material price volatility. These intrinsic advantages position sodium-ion batteries as highly promising candidates for grid-scale energy storage, renewable energy integration, and future low-carbon power systems.
As the global energy sector accelerates its transition toward carbon neutrality and renewable electricity generation, the development of advanced sodium-ion battery energy storage systems requires a comprehensive and multidisciplinary framework. In particular, achieving high safety, long cycle life, and reliable operation under complex working conditions demands the integration of electrochemical modeling, intelligent battery management, and system-level optimization. Accurate multi-scale models are essential for understanding sodium-ion transport mechanisms, electrode interface evolution, thermal behavior, and degradation pathways during long-term operation. Such models provide the theoretical foundation for predicting battery aging, performance decay, and safety risks.
At the same time, intelligent state estimation technologies play a pivotal role in enabling real-time monitoring and adaptive control of sodium-ion battery systems. Advanced algorithms combining physics-based models, data-driven learning, and artificial intelligence techniques can significantly improve the estimation accuracy of key battery states, including state of charge (SOC), state of health (SOH), state of energy (SOE), and remaining useful life (RUL). These capabilities are particularly important for large-scale energy storage applications, where operational reliability and fault diagnosis are critical for maintaining grid stability and economic efficiency.
Furthermore, strategic deployment of sodium-ion battery energy storage systems must consider application scenarios, lifecycle economics, thermal management, and integration with renewable energy resources such as wind and solar power. Through coordinated advances in materials science, battery management systems, digital intelligence, and power system engineering, sodium-ion battery technologies are expected to become a cornerstone of next-generation sustainable energy infrastructure.
