Title :
Li-ion battery parameter estimation for state of charge
Author :
Xidong Tang ; Xiaofeng Mao ; Jian Lin ; Koch, B.
Author_Institution :
Global R&D, Gen. Motors, Warren, MI, USA
fDate :
June 29 2011-July 1 2011
Abstract :
Battery state of charge (SOC) is a critical parameter for the control of propulsion systems in plug-in hybrid electric vehicles (PHEV) and electric vehicles (EV). As SOC is not measureable during vehicle operation, an onboard adaptive algorithm is developed in this paper. The algorithm estimates six electrical parameters for Li-ion batteries and provides a reliable SOC based on one of the estimated battery parameters, i.e. open circuit voltage (OCV). Simulation and vehicle validation results show good robustness and adaptation of the algorithm with high computational efficiency and low implementation cost.
Keywords :
battery powered vehicles; hybrid electric vehicles; lithium; secondary cells; Li; Li-ion battery parameter estimation; OCV; PHEV; SOC; high computational efficiency; onboard adaptive algorithm; open circuit voltage; plug-in hybrid electric vehicles; propulsion systems control; Batteries; Battery charge measurement; Estimation; Hysteresis; Integrated circuit modeling; Parameter estimation; System-on-a-chip;
Conference_Titel :
American Control Conference (ACC), 2011
Conference_Location :
San Francisco, CA
Print_ISBN :
978-1-4577-0080-4
DOI :
10.1109/ACC.2011.5990963