Simultaneous State And Parameter Estimation Of Lithium-Ion Battery: An Observer Based Approach

State of charge (SOC) and state of health (SOH) estimation along with parameter identification of a Lithium-ion battery (LIB) are the primary steps towards the development of an efficient battery management system (BMS). In this paper, first, a novel nonlinear state space representation of the electric circuit model (ECM) of LIB, with SOC-varying electrical parameters, is presented as a switched system, i.e., for both charging and discharging cycles. A non-linear observer (NLO) is designed to simultaneously estimate the SOC and SOC-varying internal parameters of the ECM. Second, the proposed state space representation is extended to include the change in ECM parameters with degradation due to temperature, ageing, capacity loss, and high C-rates such that the NLO can be used to estimate core temperature, surface temperature, and SOH along with SOC and time-varying parameters. The uniform ultimate boundedness (UUB) of the NLO's state estimation error is guaranteed using Lyapunov stability analysis. Numerical simulation results are also presented to corroborate the efficacy of modeling and simultaneous estimation scheme.