State-of-charge estimation for lithium-ion batteries under various operating conditions using an equivalent circuit model

This paper describes a state-of-charge estimation methodology for lithium-ion batteries in hybrid electric vehicles. The proposed methodology is intended for SOC estimation under various operating conditions including changes in temperature, driving mode or power duty. The suggested methodology consists of a recursive estimator and employs an equivalent circuit as the electrochemical cell model. Model parameters are estimated by parameter map on experimental cell data with various temperatures and current conditions. The parameter map is developed by a least sum square error estimation method based on nonlinear programming. An adaptive estimator is employed and is based on the combination of current integration and battery model based estimation. The proposed SOC estimation methodology is demonstrated with experimental LiB pack data under various driving schedules with low and ambient temperature and sensor failure cases. Our results show that the proposed methodology is appropriate for estimating SOC under various conditions.

► Lithium-ion battery is modeled for various conditions by equivalent circuit model.
► Model parameters are estimated by adaptive method based on nonlinear programming.
► SOC estimation method is a combination of current integration and model based method.
► Developed method is demonstrated under various conditions and sensor failure cases.