电极
等效电路
国家(计算机科学)
材料科学
电荷(物理)
电气工程
光电子学
分析化学(期刊)
化学
物理
电压
计算机科学
工程类
物理化学
算法
色谱法
量子力学
作者
Iker Lopetegi,Sergio Fernández,Gregory L. Plett,M. Scott Trimboli,Unai Iraola
标识
DOI:10.1149/1945-7111/ade297
摘要
Abstract To prolong battery lifetime and maximize performance, battery management systems (BMSs) need to estimate internal variables that are related to battery aging. For that, accurate battery models that can represent internal variables that are not directly measurable are required. However, most present BMSs use equivalent-circuit models (ECMs or EQMs) for state of charge (SOC) and state of health (SOH) estimation. These models are not able to predict these aging-related variables, and therefore, they cannot be used to limit battery degradation. In this paper, we propose a method for electrode-level SOC (eSOC) and electrode-level SOH (eSOH) estimation using an electrode-level ECM (eECM), which can describe both electrodes' potentials, giving valuable information for aging prevention. The method produces state of lithiation (SOL) and potential estimates of both electrodes, and updates the eSOH parameters to maintain estimation accuracy through the lifetime of the battery. Furthermore, the eSOH parameter estimates are used to obtain degradation mode information, which could be used to improve state estimation, health diagnosis and prognosis.
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