TY - JOUR
T1 - Simultaneous state and logarithmic parameter estimation of lithium-ion batteries using UKF
AU - Baba, Atsushi
AU - Adachi, Shuichi
PY - 2013
Y1 - 2013
N2 - A rechargeable battery is one of the key technologies in hybrid electric vehicles (HEVs) and electric vehicles (EVs). Although it is important to know the states and parameters of the battery to maximize its efficiency and safety, there are still some difficulties in estimating them. This paper focuses on the simultaneous state and parameter estimation of the battery. The estimation often suffers from poor numerical stability, and to address this issue, simultaneous state and "logarithmic" parameter estimation of batteries is proposed and implemented. This approach is verified by performing a series of simulations under an EV operating environment.
AB - A rechargeable battery is one of the key technologies in hybrid electric vehicles (HEVs) and electric vehicles (EVs). Although it is important to know the states and parameters of the battery to maximize its efficiency and safety, there are still some difficulties in estimating them. This paper focuses on the simultaneous state and parameter estimation of the battery. The estimation often suffers from poor numerical stability, and to address this issue, simultaneous state and "logarithmic" parameter estimation of batteries is proposed and implemented. This approach is verified by performing a series of simulations under an EV operating environment.
KW - Battery
KW - Electric vehicle (EV)
KW - Lognormal distribution
KW - Simultaneous state and parameter estimation
KW - Unscented Kalman filter
KW - Warburg impedance
UR - http://www.scopus.com/inward/record.url?scp=84891816587&partnerID=8YFLogxK
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U2 - 10.1541/ieejias.133.1139
DO - 10.1541/ieejias.133.1139
M3 - Article
AN - SCOPUS:84891816587
VL - 133
SP - 1139
EP - 1147
JO - IEEJ Transactions on Industry Applications
JF - IEEJ Transactions on Industry Applications
SN - 0913-6339
IS - 12
ER -