TY - JOUR
T1 - An Overview and Comparison of Online Implementable SOC Estimation Methods for Lithium-Ion Battery
AU - Meng, Jinhao
AU - Ricco, Mattia
AU - Luo, Guangzhao
AU - Swierczynski, Maciej Jozef
AU - Stroe, Daniel-Ioan
AU - Stroe, Ana-Irina
AU - Teodorescu, Remus
PY - 2018/3
Y1 - 2018/3
N2 - With the popularity of Electrical Vehicles (EVs), Lithium-ion battery industry is developing rapidly. To ensure the battery safe usage and to reduce its average lifecycle cost, an accurate State of Charge (SOC) tracking algorithms for real-time implementation are required for different applications. Many SOC estimation methods have been proposed in the literature. However, only a few of them consider the real-time applicability. This paper reviews recently proposed online SOC estimation methods and classifies them into five categories. Their principal features are illustrated, and the main pros and cons are provided. The SOC estimation methods are compared and discussed in terms of accuracy, robustness, and computation burden. Afterward, as the most popular type of model based SOC estimation algorithms, seven nonlinear filters existing in literature are compared in terms of their accuracy and execution time as a reference for online implementation.
AB - With the popularity of Electrical Vehicles (EVs), Lithium-ion battery industry is developing rapidly. To ensure the battery safe usage and to reduce its average lifecycle cost, an accurate State of Charge (SOC) tracking algorithms for real-time implementation are required for different applications. Many SOC estimation methods have been proposed in the literature. However, only a few of them consider the real-time applicability. This paper reviews recently proposed online SOC estimation methods and classifies them into five categories. Their principal features are illustrated, and the main pros and cons are provided. The SOC estimation methods are compared and discussed in terms of accuracy, robustness, and computation burden. Afterward, as the most popular type of model based SOC estimation algorithms, seven nonlinear filters existing in literature are compared in terms of their accuracy and execution time as a reference for online implementation.
KW - Comparison
KW - lithium-ion battery
KW - nonlinear filter
KW - online implementation
KW - state ofcharge (SOC) estimation
UR - http://www.scopus.com/inward/record.url?scp=85035114823&partnerID=8YFLogxK
U2 - 10.1109/TIA.2017.2775179
DO - 10.1109/TIA.2017.2775179
M3 - Journal article
SN - 0093-9994
VL - 54
SP - 1583
EP - 1591
JO - I E E E Transactions on Industry Applications
JF - I E E E Transactions on Industry Applications
IS - 2
ER -