A comprehensive review of state-of-charge and state-of-health estimation for lithium-ion battery energy storage systems

With the gradual transformation of energy industries around the world, the trend of industrial reform led by clean energy has become increasingly apparent. As a critical link in the new energy industry chain, lithium-ion (Li-ion) battery energy storage system plays an irreplaceable role. Accurate estimation of Li-ion battery states, especially state of charge (SOC) and state of health (SOH), is the core to realize the safe and efficient utilization of energy storage systems. This paper presents a systematic and comprehensive evaluation and summary of the most advanced Li-ion battery state estimation methods proposed in the past 3 years, focusing on analyzing data-driven state estimation algorithms. At the same time, the latest Li-ion battery data sets and data selection methods are analyzed, and future research trends and possible challenges are proposed. This review will provide a valuable reference for future academic research in Li-ion battery state estimation.