  This work investigates the real-time estimation of the state-of-charge (SoC)
of Lithium-ion (Li-ion) cells for reliable, safe and efficient utilization. A
novel attractive ellipsoid based sliding-mode observer (AESMO) algorithm is
designed to estimate the SoC in real-time. The algorithm utilizes standard
equivalent circuit model of a Li-ion cell and provides reliable and efficient
SoC estimate in the presence of bounded uncertainties in the battery parameters
as well as exogenous disturbances. The theoretical framework of the observer
design is not limited to the SoC estimation problem of Li-ion cell but
applicable to a wider class of nonlinear systems with both matched and
mismatched uncertainties. The main advantage of the proposed observer is to
provide a fast and optimal SoC estimate based on minimization over the
uncertainty bound. The proposed method is experimentally tested and evaluated
using the hybrid pulse power characterization test (HPPC)and urban dynamometer
driving schedule (UDDS) test data, which demonstrate its effectiveness and
feasibility.

Systems and Control;Systems and Control;Optimization and Control