Abstract: Energy storage batteries are able to smooth renewable energy output, enhance power system flexibility, and address peak-demand scenarios. They play a pivotal role in promoting the development of renewable energy, thereby mitigating the dual pressures of environmental pollution and energy scarcity. Currently, lithium-ion batteries dominate the market, featuring high energy density characteristics. Emerging energy storage batteries are also thriving, with vanadium redox flow batteries offering high safety advantages, and liquid metal batteries boasting an ultra-long cycle life, which have an important application prospect in the field of power energy storage. Modeling and state estimation for energy storage batteries are crucial for enhancing the performance of energy storage battery systems, ensuring safety, and optimizing maintenance efficiency. Therefore, this paper provides a comprehensive review of the modeling and state estimation for lithium-ion batteries, vanadium redox flow batteries, and liquid metal batteries. Firstly, it introduces the overall framework of state estimation for energy storage batteries, providing a comprehensive overview of experiment-based, model-based, and data-driven methods. It summarizes the definitions of State of Charge（SOC）, State of Health（SOH）, and Remaining Useful Life（RUL）. Subsequently, starting from the principles, the paper summarizes the internal workings, model construction, state estimation, and battery management processes of different energy storage battery systems.Finally, the paper conducts a horizontal comparison and summary of the main working characteristics of different energy storage battery systems, aiming to provide insights for the selection and development of energy storage batteries.