On-board real-time state-of-charge estimators of hybrid electric vehicles Ni-MH battery

In this research is developed and implemented in MATLAB simulation environment two real-time estimators, such as an Unscented Kalman Filter (UKF) and a sliding mode observer (SMO). The intent is to use these estimators to estimate the state-of-charge (SOC) of a generic nickel - metal hydride (Ni-MH) battery integrated in the battery management system (BMS) structure of hybrid electric vehicles (HEVs). The novelty of this paper is that the proposed estimators can be tailored to estimate the battery SOC of different chemistries, and also could be extended to detect and estimate the severity of battery faults. The preliminary results obtained in this research are encouraging and reveal the effectiveness of the real-time implementation of the proposed estimators.