TY - GEN
T1 - Pruning LS-SVM based battery model for electric vehicles
AU - Lei, Xiao
AU - Chan, C. C.
AU - Liu, Kaipei
AU - Ma, Li
PY - 2007/8
Y1 - 2007/8
N2 - This paper presents a new method to estimate the battery state of charge (SOC) in electric vehicles (EVs). The key of the proposed method is to establish the relationship of the SOC to the battery current, voltage and temperature by using least squares support vector machine (LS-SVM). For ease of practical application, the pruning procedure is developed to reduce the number of support vectors in terms of their significance. The results show that the proposed method can simulate the battery dynamics for the accurate estimation of the SOC in EVs.
AB - This paper presents a new method to estimate the battery state of charge (SOC) in electric vehicles (EVs). The key of the proposed method is to establish the relationship of the SOC to the battery current, voltage and temperature by using least squares support vector machine (LS-SVM). For ease of practical application, the pruning procedure is developed to reduce the number of support vectors in terms of their significance. The results show that the proposed method can simulate the battery dynamics for the accurate estimation of the SOC in EVs.
UR - http://www.scopus.com/inward/record.url?scp=38049010014&partnerID=8YFLogxK
U2 - 10.1109/ICNC.2007.584
DO - 10.1109/ICNC.2007.584
M3 - Conference article published in proceeding or book
AN - SCOPUS:38049010014
SN - 0769528759
SN - 9780769528755
T3 - Proceedings - Third International Conference on Natural Computation, ICNC 2007
SP - 333
EP - 337
BT - Proceedings - Third International Conference on Natural Computation, ICNC 2007
T2 - 3rd International Conference on Natural Computation, ICNC 2007
Y2 - 24 August 2007 through 27 August 2007
ER -