电池(电)
荷电状态
计算机科学
锂离子电池
汽车工程
锂(药物)
电压
健康状况
估计
功率(物理)
电动汽车
电气工程
可靠性工程
工程类
系统工程
内分泌学
物理
医学
量子力学
作者
Muhammad Umair Ali,Amad Zafar,Sarvar Hussain Nengroo,Sadam Hussain,Muhammad Junaid Alvi,Hee‐Je Kim
出处
期刊:Energies
[Multidisciplinary Digital Publishing Institute]
日期:2019-01-30
卷期号:12 (3): 446-446
被引量:346
摘要
Energy storage system (ESS) technology is still the logjam for the electric vehicle (EV) industry. Lithium-ion (Li-ion) batteries have attracted considerable attention in the EV industry owing to their high energy density, lifespan, nominal voltage, power density, and cost. In EVs, a smart battery management system (BMS) is one of the essential components; it not only measures the states of battery accurately, but also ensures safe operation and prolongs the battery life. The accurate estimation of the state of charge (SOC) of a Li-ion battery is a very challenging task because the Li-ion battery is a highly time variant, non-linear, and complex electrochemical system. This paper explains the workings of a Li-ion battery, provides the main features of a smart BMS, and comprehensively reviews its SOC estimation methods. These SOC estimation methods have been classified into four main categories depending on their nature. A critical explanation, including their merits, limitations, and their estimation errors from other studies, is provided. Some recommendations depending on the development of technology are suggested to improve the online estimation.
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