A novel bias compensation recursive least square‐multiple weighted dual extended Kalman filtering method for accurate state‐of‐charge and state‐of‐health co‐estimation of lithium‐ion batteries.
(2021)
Journal Article
QIAO, J., WANG, S., YU, C., SHI, W. and FERNANDEZ, C. 2021. A novel bias compensation recursive least square-multiple weighted dual extended Kalman filtering method for accurate state-of-charge and state-of-health co-estimation of lithium-ion batteries. International journal of circuit theory and applications [online], 49(11), pages 3879-3893. Available from: https://doi.org/10.1002/cta.3115
Abstract - State-of-charge and state-of-health of power lithium-ion batteries are two important state parameters for battery management system monitoring. To accurately estimate the state-of-charge and state-of-health of in real time, the ternary lit... Read More about A novel bias compensation recursive least square‐multiple weighted dual extended Kalman filtering method for accurate state‐of‐charge and state‐of‐health co‐estimation of lithium‐ion batteries..