Charge and Health State Estimation of Lithium-Ion Battery in More Electric Aircraft Considering Electro-Thermal-Coupled Factors

Accurate state estimation of lithium-ion batteries is crucial for aviation safety, yet remains challenging due to temperature-dependent parameter drift and complex electro-thermal coupling effects. This paper proposes an Extended Kalman Filter (EKF) framework integrated with electro-thermal coupled modeling for State of Charge (SOC) and State of Health (SOH) estimation in more electric aircraft battery. By establishing a second-order RC electrical model combined with a lumped-parameter thermal model with online parameter identification, we construct hierarchical state-space equations to address multi-time-scale polarization dynamics. Adaptive noise covariance adjustment enhances robustness under dynamic operating conditions. Finally, experimental verification is conducted under the conditions of HPPC, DST, FUDS and CC-CV. The electro-thermal co-simulation framework significantly reduces temperature-induced estimation errors through real-time parameter updates. This study provides a high-precision state awareness solution for more electric aircraft battery management systems under stringent operational constraints.