Abstract
This article introduces an efficient modeling approach based on the Wiener structure to reinforce the capacity of classical equivalent circuit models (ECMs) in capturing the nonlinearities of lithium-ion (Li-ion) batteries. The proposed block-oriented modeling architecture is composed of a simple linear ECM followed by a static output nonlinearity block, which helps achieving a superior nonlinear mapping property while maintaining the real-time efficiency. The observability of the established battery model is analytically proven. This article also introduces an efficient parameter estimator based on extended-kernel iterative recursive least squares algorithm for real-time estimation of the parameters of the proposed Wiener model. The proposed approach is applied for state-of-charge (SoC) estimation of 3.4-Ah 3.6-V nickel-manganese-cobalt-based Li-ion cells using the extended Kalman filter (EKF). The results show about 1.5% improvement in SoC estimation accuracy compared with the EKF algorithm based on the second-order ECM. A series of real-time tests are also carried out to demonstrate the computational efficiency of the proposed method.
Original language | English |
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Journal | I E E E Transactions on Industrial Electronics |
Volume | 69 |
Issue number | 4 |
Pages (from-to) | 3743-3751 |
Number of pages | 9 |
ISSN | 0278-0046 |
DOIs | |
Publication status | Published - Apr 2022 |
Keywords
- Equivalent circuit model (ECM)
- Wiener model
- extended Kalman filter (EKF)
- least squares
- lithium-ion (Li-ion) battery
- state of charge (SoC)