A Novel Coupled Electro-thermal-aging Model for Simultaneous SOC, SOH, and Parameter Estimation of Lithium-ion Batteries

Reliable estimation of the state of charge (SOC) and state of Health (SOH) is critical for battery management systems (BMSs) to ensure the safety of lithium-ion batteries (LIBs). Efforts in this paper seek to simultaneously estimate SOC and SOH of LIBs along with internal parameter (Ohmic-resistance) by introducing a novel coupled electro-thermal-aging model. First, a SOH-coupled non-linear model is proposed by coupling the SOH with SOC dynamics. The SOH, SOC, and equivalent circuit model (ECM) are integrated with the thermal model of LiFePO4/graphite battery to develop the coupled electro-thermal-aging model. The proposed model's parameters vary with SOH, SOC, and temperature to account for their dependence on internal degradation. An extended Kalman filter (EKF) is employed to simultaneously estimate the SOC and SOH of the battery. In addition, to estimate internal resistance via an EKF, we also introduced a second model by representing the time-varying resistance as one of the states. Numerical and experimental results are put forward to validate the proposed nonlinear coupled electro-thermal-aging model.