Abstract
Battery energy storage and management systems constitute an enabling technology for more sustainable transportation and power grid systems. On the one hand, emerging materials and chemistries of batteries are being actively synthesized to continually improve their energy density, power density, cycle life, charging rate, etc. On the other hand, advanced battery management systems (BMSs) are being intensively developed to guarantee the safety, reliability, efficiency, and cost-effectiveness of batteries in realistic operations, as well as their integration with mechatronics. Owing to their multi-physics nature, designing high-performance batteries and their management systems requires multidisciplinary approaches, with an ever-increasing synergy of electrochemi- cal, material, mechatronics, computer, and control disciplines.
Highlights
Accurate battery SOC estimation is vital for safe, highefficiency, and cost-effective battery operations, through effectively avoiding over-charge and over-discharge
In ‘‘State of charge estimation of battery energy storage systems based on adaptive unscented Kalman Filter with a noise statistics estimator,’’ by Peng et al, based on a noise statistical estimator, a new SOC estimation approach using adaptive unscented kalman filtering (AUKF) is developed
In ‘‘Real-time estimation of battery state of charge with metabolic grey model and LabVIEW platform,’’ by Zheng et al, the authors develop a battery SOC estimation method for electric vehicles based on a grey model
Summary
Accurate battery SOC estimation is vital for safe, highefficiency, and cost-effective battery operations, through effectively avoiding over-charge and over-discharge. The overarching purpose of this Special Section on ‘‘Battery energy storage and management systems’’ is to collect and illustrate the recent results of research and development endeavors to advance the research fields of batteries, their management systems, and their integration into smart grids and electrified vehicles. It is believed that these articles impressively demonstrate stateof-the-art characterization, modeling, state estimation, and control methods of battery systems.
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