TY - JOUR
T1 - Online state of charge and model parameter co-estimation based on a novel multi-timescale estimator for vanadium redox flow battery
AU - Wei, Zhongbao
AU - Lim, Tuti Mariana
AU - Skyllas-Kazacos, Maria
AU - Wai, Nyunt
AU - Tseng, King Jet
N1 - Publisher Copyright:
© 2016 Elsevier Ltd.
PY - 2016/6/15
Y1 - 2016/6/15
N2 - A key function of battery management system (BMS) is to provide accurate information of the state of charge (SOC) in real time, and this depends directly on the precise model parameterization. In this paper, a novel multi-timescale estimator is proposed to estimate the model parameters and SOC for vanadium redox flow battery (VRB) in real time. The model parameters and OCV are decoupled and estimated independently, effectively avoiding the possibility of cross interference between them. The analysis of model sensitivity, stability, and precision suggests the necessity of adopting different timescales for each estimator independently. Experiments are conducted to assess the performance of the proposed method. Results reveal that the model parameters are online adapted accurately thus the periodical calibration on them can be avoided. The online estimated terminal voltage and SOC are both benchmarked with the reference values. The proposed multi-timescale estimator has the merits of fast convergence, high precision, and good robustness against the initialization uncertainty, aging states, flow rates, and also battery chemistries.
AB - A key function of battery management system (BMS) is to provide accurate information of the state of charge (SOC) in real time, and this depends directly on the precise model parameterization. In this paper, a novel multi-timescale estimator is proposed to estimate the model parameters and SOC for vanadium redox flow battery (VRB) in real time. The model parameters and OCV are decoupled and estimated independently, effectively avoiding the possibility of cross interference between them. The analysis of model sensitivity, stability, and precision suggests the necessity of adopting different timescales for each estimator independently. Experiments are conducted to assess the performance of the proposed method. Results reveal that the model parameters are online adapted accurately thus the periodical calibration on them can be avoided. The online estimated terminal voltage and SOC are both benchmarked with the reference values. The proposed multi-timescale estimator has the merits of fast convergence, high precision, and good robustness against the initialization uncertainty, aging states, flow rates, and also battery chemistries.
KW - Battery model
KW - Lithium-ion battery
KW - Multi-timescale
KW - Parameters identification
KW - State of charge estimation
KW - Vanadium redox flow battery
UR - http://www.scopus.com/inward/record.url?scp=84961894470&partnerID=8YFLogxK
U2 - 10.1016/j.apenergy.2016.03.103
DO - 10.1016/j.apenergy.2016.03.103
M3 - Article
AN - SCOPUS:84961894470
SN - 0306-2619
VL - 172
SP - 169
EP - 179
JO - Applied Energy
JF - Applied Energy
ER -