TY - GEN
T1 - Lithium iron phosphate intelligent SOC prediction for efficient electric vehicle
AU - Toha, Siti Fauziah
AU - Faeza, Nor Hazima
AU - Azubair, Nor Aziah Mohd
AU - Hanisa, Nizam
AU - Hassan, Mohd Khair
AU - Ibrahim, Babul Salam K
PY - 2014/1/1
Y1 - 2014/1/1
N2 - This paper presents modelling techniques for Lithium Iron Phosphate (LiFePO4) battery in an electric vehicle. Artificial intelligence techniques namely multi-layered perceptron neural network (MLPNN) and Elman recurrent neural network are devised to estimate the energy remained in the battery bank which referred to state of charge (SOC). The New European Driving Cycle (NEDC) test data is used to excite the cells in driving cycle-based conditions under varied temperature range [0-55]0C. Accurate SOC prediction is a key function for satisfactory implementation of Battery Supervisory System (BSS). It is demonstrated that artificial intelligence methods can be effectively used with highly accurate results. The accuracy of the modeling results is demonstrated through validation and correlation tests.
AB - This paper presents modelling techniques for Lithium Iron Phosphate (LiFePO4) battery in an electric vehicle. Artificial intelligence techniques namely multi-layered perceptron neural network (MLPNN) and Elman recurrent neural network are devised to estimate the energy remained in the battery bank which referred to state of charge (SOC). The New European Driving Cycle (NEDC) test data is used to excite the cells in driving cycle-based conditions under varied temperature range [0-55]0C. Accurate SOC prediction is a key function for satisfactory implementation of Battery Supervisory System (BSS). It is demonstrated that artificial intelligence methods can be effectively used with highly accurate results. The accuracy of the modeling results is demonstrated through validation and correlation tests.
KW - Elman recurrent neural network and battery supervisory system (BSS)
KW - Lithium iron phosphate
KW - Multi-layered perceptron neural network (MLPNN)
KW - State of charge (SOC)
UR - https://www.scopus.com/pages/publications/84896274159
U2 - 10.4028/www.scientific.net/AMR.875-877.1613
DO - 10.4028/www.scientific.net/AMR.875-877.1613
M3 - Conference proceeding
AN - SCOPUS:84896274159
SN - 9783037859933
T3 - Advanced Materials Research
SP - 1613
EP - 1619
BT - Material Research and Applications
PB - Trans Tech Publications
T2 - 2012 International Conference on Advanced Material and Manufacturing Science
Y2 - 20 December 2012 through 21 December 2012
ER -