TY - GEN
T1 - State of charge estimation of lithium-ion battery using Kalman filters
AU - Baba, Atsushi
AU - Adachi, Shuichi
PY - 2012/12/1
Y1 - 2012/12/1
N2 - In this paper we propose an accurate state of charge (SOC) estimation method for a lithium-ion battery for hybrid electric vehicle (HEV) and electric vehicles (EV) use. Although it is important to accurately determine the SOC of a battery to achieve maximum efficiency and safety, none of the existing methods has achieved this perfectly. To address this issue, a model-based approach using a cascaded combination of two Kalman filters, 'Series Kalman Filters,' is proposed and implemented. Its validity is verified by performing a series of simulations under a basic HEV operating environment.
AB - In this paper we propose an accurate state of charge (SOC) estimation method for a lithium-ion battery for hybrid electric vehicle (HEV) and electric vehicles (EV) use. Although it is important to accurately determine the SOC of a battery to achieve maximum efficiency and safety, none of the existing methods has achieved this perfectly. To address this issue, a model-based approach using a cascaded combination of two Kalman filters, 'Series Kalman Filters,' is proposed and implemented. Its validity is verified by performing a series of simulations under a basic HEV operating environment.
UR - http://www.scopus.com/inward/record.url?scp=84873189235&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84873189235&partnerID=8YFLogxK
U2 - 10.1109/CCA.2012.6402456
DO - 10.1109/CCA.2012.6402456
M3 - Conference contribution
AN - SCOPUS:84873189235
SN - 9781467345033
T3 - Proceedings of the IEEE International Conference on Control Applications
SP - 409
EP - 414
BT - 2012 IEEE International Conference on Control Applications, CCA 2012
T2 - 2012 IEEE International Conference on Control Applications, CCA 2012
Y2 - 3 October 2012 through 5 October 2012
ER -
