State of charge and state of health estimation based on dual nonlinear adaptive observer and hysteresis model of lithium-ion battery

Accurate estimation of state of health (SOH) and state of charge (SOC) can provide a basis for regular operation and fault diagnosis of batteries, which is of great significance for electric vehicles. In this paper, a dual nonlinear adaptive observer (DNLAO) is presented to realize the joint estimation of SOC and SOH. Considering that the battery hysteresis characteristics impact the estimation, an equivalent circuit model including the hysteresis characteristic is established, and the model equations with uncertainties are analyzed. In designing observers, the Takagi–Sugeno fuzzy model is introduced to reduce the model complexity, and adaptive parameters are added to connect the observed output with measured output to reduce the model uncertainty and improve estimation accuracy. The proposed observer convergence is proved based on the Lyapunov equation. The simulation results show that the SOC estimation error and the SOH estimation error by DNLAO are lower than those of a dual extended Kalman filter. DNLAO has high estimation accuracy and fast convergence speed on SOC and SOH joint estimation, and can achieve long-term SOH estimation.