Systematic mixed adaptive observer and EKF approach to estimate SOC and SOH of lithium-ion battery

One of the main issues with KF-based methods is complication of determining the process noise covariance matrix, which is usually obtained by empirical tuning. Here, by using the adaptive observer designed around an arbitrary operating point of a non-linear system, a novel systematic approach is developed for determining the covariance matrix of the parameter noise in the EKF with the aim of jointly estimating the states and unknown parameters of the system. The proposed mixed adaptive observer and EKF method are applied to a Lithium-Ion battery to simultaneously estimate its state of charge (SOC) and internal resistance as well as the state of health (SOH). The dynamical behaviour of the battery is modelled by using a commonly used RC model and is validated by the real data collected from the battery. The proposed method provides a robust performance against the model uncertainties and shows satisfactory parameter convergence properties. Experimental tests are established to certify the capability and effectiveness of the proposed scheme compared to the conventional EKF. Furthermore, a simulation study is carried out to verify the robustness of the proposed method.