The Extended Kalman Filter as been shown to be highly effective in estimating the battery State of Charge, however its performance strongly depends on battery model accuracy and on precise knowledge of the battery model parameters. This work investigates the correlation between inaccuracies in the battery model and the resulting error in the State of Charge estimation using the Extended Kalman Filter.
Impact of Parameter Estimation Accuracy on State of Charge Estimation Using Extended Kalman Filter / Grilli, M.; Guaitini, J.; Orcioni, S.; Conti, M.. - 1369:(2025), pp. 466-473. ( International Conference on Applications in Electronics Pervading Industry, Environment and Society, APPLEPIES 2024 Turin 19 - 20 September 2024) [10.1007/978-3-031-84100-2_55].
Impact of Parameter Estimation Accuracy on State of Charge Estimation Using Extended Kalman Filter
Orcioni S.;Conti M.
2025-01-01
Abstract
The Extended Kalman Filter as been shown to be highly effective in estimating the battery State of Charge, however its performance strongly depends on battery model accuracy and on precise knowledge of the battery model parameters. This work investigates the correlation between inaccuracies in the battery model and the resulting error in the State of Charge estimation using the Extended Kalman Filter.| File | Dimensione | Formato | |
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Applepies_Kalman_revised.pdf
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