Lithium-ion batteries are unanimously considered to be the standard electric power source for many applications, including electrified vehicles, such as plug-in hybrid electric vehicles (PHEV), electric vehicles (EV), and hybrid electric vehicles (HEV). Accordingly, optimal battery management is a relevant issue in automatic control practice. The Battery Management System (BMS) has to: (1) ensure that the battery is appropriately used when meeting the demand for electrical power; and (2) guarantee feasible and safe operation.\u00a0A battery\u2019s energy and power strongly depend on the battery\u2019s state. In particular, the residual energy is related to the cell\u2019s State-of-Charge (SoC) as well as to the battery\u2019s age, and is the reason why the performance of lithium-ion batteries degrades with time and use. As the direct measurement of SoC and State-of-Health (SoH) is unavailable in real-time applications, a key task for the BMS is to provide an accurate estimation of the battery\u2019s state. This is required in order to achieve high battery efficiency, avoid damage, predict the Remaining Useful Life (RUL), and potentially slow the rate of deterioration.\u00a0This Special Issue will focus on the analysis, design, implementation, and validation of strategies for the estimation of the state of lithium-ion cells and, more generally, algorithms for the management of lithium-ion batteries. Studies that employ recently developed data-driven approaches will also be welcome.
\nKeywords: battery management system; lithium-ion batteries; state estimation; battery aging; state-of-charge estimation; state-of-health estimation; remaining useful life prediction; data-driven estimation.<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"template":"","format":"standard","topic":[130,597,449,632,559,467,472,567,563,572,616,617,604],"country":[55],"nsj_language":[57],"class_list":["post-1763","call_for_papers","type-call_for_papers","status-publish","format-standard","hentry","topic-chemical-material-sciences-en","topic-data-sensing-and-analysis","topic-energy-efficiency","topic-energy-storage","topic-industrial-engineering","topic-industry-4-0","topic-life-cycle-assessment","topic-methodology","topic-modeling","topic-monitoring","topic-performance-evaluation","topic-performance-based-design","topic-process-modeling-and-simulation","country-switzerland","nsj_language-english"],"acf":[],"yoast_head":"\n