A Multi-timescale Kalman Filter-Based Estimator of Li-Ion Battery Parameters Including Adaptive Coupling of State-of-Charge and Capacity Estimation
IEEE Transactions on Control Systems Technology, Vol. 31, No. 2, pp. 692-7062023The paper deals with coupled, state and parameter estimation for lithium-ion batteries described by an equivalent circuit model including polarization dynamics. Since the model parameters depend on the battery state-of-charge and temperature operating point, as well as on the battery state-of-health, all states and parameters need to be estimated simultaneously for an accurate overall estimation during the battery lifetime. The proposed estimation algorithm is structured in two timescales: (i) slow-scale, Sigma-point Kalman filter-based estimation of battery capacity and (ii) fast-scale, Dual Extended Kalman filter-based estimation of state-of-charge and model parameters. A particular emphasis is on adaptive parameterization of state-of-charge and capacity estimators, which provides robust coupling between two timescales and ensures favorable convergence as well as robust capacity tracking in conditions of state-of-charge and model parameters estimation errors. In support of estimation accuracy analysis, an algebraic observability analysis of impedance parameters is conducted. Also, by introducing an observability index calculated in each simulation timestep, a comparison of degrees of observability of different impedance parameter subsets is allowed for. The proposed estimation algorithm is verified both by simulation and experimentally for an electric scooter Li-NMC battery pack. energy storage; hybrid and electric vehicles; Kalman filtering
Cited by 12
▾
-
[1]
Estimating state of charge of lithium-ion battery using an adaptive fractional-order Kalman-unscented particle filter🔗
Journal of Energy Storage, 2025
-
-
-
[4]
A Data-Driven DAE-CNN-BiLSTM-Attention Prediction Model for the State of Health of Lithium-Ion Batteries🔗
International Conference on Information and Software Technologies, 2024
-
[5]
A comprehensive review of hybrid battery state of charge estimation: Exploring physics-aware AI-based approaches🔗
Journal of Energy Storage, 2024
-
[6]
Model-Based State-of-Charge Estimation of 28 V LiFePO
4
Aircraft Battery🔗
SAE International Journal of Electrified Vehicles, 2024
-
-
[8]
Adaptive Observer based Simultaneous Estimation of Model Parameters and State-of-Charge of Lithium-ion Battery🔗
IEEE India Conference, 2023
-
[9]
An improved fractional‐order state estimation algorithm based on an unscented particle filter for state of charge estimation of lithium‐ion batteries with adaptive estimations of unknown parameters🔗
International journal of circuit theory and applications, 2023
-
[10]
State of charge estimation for the vanadium redox flow battery based on the Sage–Husa adaptive extended Kalman filter🔗
International journal of circuit theory and applications, 2023
-
[11]
An improved long short‐term memory based on global optimization square root extended Kalman smoothing algorithm for collaborative state of charge and state of energy estimation of lithium‐ion batteries🔗
International journal of circuit theory and applications, 2023
-
IEEE Transactions on Control Systems Technology, Vol. 31, No. 2, pp. 692-706
2023
Cited by 12
▾
-
[1] Estimating state of charge of lithium-ion battery using an adaptive fractional-order Kalman-unscented particle filter🔗Journal of Energy Storage, 2025
-
[4] A Data-Driven DAE-CNN-BiLSTM-Attention Prediction Model for the State of Health of Lithium-Ion Batteries🔗International Conference on Information and Software Technologies, 2024
-
[5] A comprehensive review of hybrid battery state of charge estimation: Exploring physics-aware AI-based approaches🔗Journal of Energy Storage, 2024
-
[6] Model-Based State-of-Charge Estimation of 28 V LiFePO 4 Aircraft Battery🔗SAE International Journal of Electrified Vehicles, 2024
-
[8] Adaptive Observer based Simultaneous Estimation of Model Parameters and State-of-Charge of Lithium-ion Battery🔗IEEE India Conference, 2023
-
[9] An improved fractional‐order state estimation algorithm based on an unscented particle filter for state of charge estimation of lithium‐ion batteries with adaptive estimations of unknown parameters🔗International journal of circuit theory and applications, 2023
-
[10] State of charge estimation for the vanadium redox flow battery based on the Sage–Husa adaptive extended Kalman filter🔗International journal of circuit theory and applications, 2023
-
[11] An improved long short‐term memory based on global optimization square root extended Kalman smoothing algorithm for collaborative state of charge and state of energy estimation of lithium‐ion batteries🔗International journal of circuit theory and applications, 2023