This paper deals with the problem of the identification of lithium cell parameters to be correlated with the cell level of aging. Three identical Lithium-Cobalt-Oxide (LCO) commercial cells at three different State-of-Life (SOL) values are experimentally tested, and two parameter estimations are applied, focusing on the cell internal resistance, which appears significantly sensitive to different cell aging levels. After displaying how the single cells under study can be calibrated through an off-line procedure by means of equivalent electrical circuit approach, the development of a voltage-current based algorithm to be applied on-line and capable of estimating an 'equivalent internal resistance' to be correlated with cell SOL is proposed. The robustness and the online applicability of the algorithm is tested on different realistic scenarios, as well as different State-of-Charge levels. Results confirm the capability of the proposed algorithm to be potentially applied for the online State-of-Life estimation for lithium cells.

Voltage-current based algorithm for the on-line estimation of equivalent internal resistance of Lithium-Cobalt-Oxide cells at different aging levels

Ceraolo M.;Lutzemberger G.;Scarpelli C.;
2023-01-01

Abstract

This paper deals with the problem of the identification of lithium cell parameters to be correlated with the cell level of aging. Three identical Lithium-Cobalt-Oxide (LCO) commercial cells at three different State-of-Life (SOL) values are experimentally tested, and two parameter estimations are applied, focusing on the cell internal resistance, which appears significantly sensitive to different cell aging levels. After displaying how the single cells under study can be calibrated through an off-line procedure by means of equivalent electrical circuit approach, the development of a voltage-current based algorithm to be applied on-line and capable of estimating an 'equivalent internal resistance' to be correlated with cell SOL is proposed. The robustness and the online applicability of the algorithm is tested on different realistic scenarios, as well as different State-of-Charge levels. Results confirm the capability of the proposed algorithm to be potentially applied for the online State-of-Life estimation for lithium cells.
2023
979-8-3503-4743-2
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1199809
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