Modelling the degradation process of lithium-ion batteries when operating at erratic state-of-charge swing ranges

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2017 4th International Conference on Control, Decision and Information Technologies (CoDIT)
2017 4th International Conference on Control, Decision and Information Technologies (CoDIT)

Abstract

Manufacturers of lithium-ion batteries inform capacity degradation for regular, symmetrical charge/discharge cycles, which is clearly problematic in real life applications where charge/discharge cycles are hardly regular. In this context, this paper presents a methodology that can model the degradation of lithium-ion batteries when these are charged and discharged erratically. The proposed methodology can model degradation of a lithium-ion battery type subject to erratic charge/discharge cycles where degradation data under symmetrical charge/discharge cycles (namely, under a standard protocol) has been provided by the manufacturer. To do so we use the concepts of (i) SOC swing, (ii) average swing range and (iii) Coulombic efficiency to model the degradation process in a simple manner through interpolation techniques. We use both deterministic and Monte Carlo simulations to obtain capacity degradation as a function of the number of cycles.

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Manufacturers of lithium-ion batteries inform capacity degradation for regular, symmetrical charge/discharge cycles, which is clearly problematic in real life applications where charge/discharge cycles are hardly regular. In this context, this paper presents a methodology that can model the degradation of lithium-ion batteries when these are charged and discharged erratically. The proposed methodology can model degradation of a lithium-ion battery type subject to erratic charge/discharge cycles where degradation data under symmetrical charge/discharge cycles (namely, under a standard protocol) has been provided by the manufacturer. To do so we use the concepts of (i) SOC swing, (ii) average swing range and (iii) Coulombic efficiency to model the degradation process in a simple manner through interpolation techniques. We use both deterministic and Monte Carlo simulations to obtain capacity degradation as a function of the number of cycles.

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