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- W4362501507 abstract "This work aims to improve the accuracy of state of charge estimation for lithium-ion battery, as well as to accurately estimate state of health. This study presents a piecewise forgetting factor recursive least squares method based on integral separation with a second-order resistor-capacitor model and uses a novel adaptive filter based on error covariance correction on the conventional dual extended Kalman filter. The experiments show that the error of SOC estimation is less than 0.61% and the error of SOH is less than 0.09% under different complex conditions, the proposed method can effectively improve the estimation accuracy and robustness." @default.
- W4362501507 created "2023-04-05" @default.
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- W4362501507 date "2022-12-09" @default.
- W4362501507 modified "2023-10-16" @default.
- W4362501507 title "Joint State of Charge and State of Health Estimation of Lithium-ion Battery Using Improved Adaptive Dual Extended Kalman Filter Based on Piecewise Forgetting Factor Recursive Least Squares" @default.
- W4362501507 doi "https://doi.org/10.1109/spies55999.2022.10082478" @default.
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