Energy storage battery systems applied to stratospheric airships exhibit significant parameter inconsistencies due to environmental influences. Moreover, to achieve efficient and rapid data transmission, the system can only transmit critical information parameters to the ground station, which poses substantial challenges for state estimation. To address this, this paper proposes a joint estimation approach for State of Charge (SOC) and State of Health (SOH) based on the collected data. Firstly, recognizing the shortcomings in conventional definitions of battery pack SOC and SOH, the study improves their calculation methods by using the minimum remaining capacity and minimum rechargeable capacity of individual cells within the pack as the current battery pack capacity. Secondly, the battery pack inconsistency model based on the Rint model is established and integrated with the previously developed battery pack model to construct a framework for joint SOC and SOH estimation using the Dual Adaptive Extended Kalman Filter (DAEKF). Finally, based on the experimental data, not only the estimation methods for SOC and SOH are refined, but also short-term and long-term simulation verification are carried out. In particular, combined with the typical working conditions of the stratospheric airship, the simulation results of multiple cycles show that the MSE of the jointly estimated SOC is < 0.5% and the RMSE is < 7%, the MSE < 0.0014% and the RMSE < 0.36% for SOH. Accurate SOC-SOH co-estimation can provide crucial guidance for flight strategy formulation and path planning of stratospheric airships.
CHENG et al. (Sun,) studied this question.