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Lithium-Ion Battery Degradation Indicators Via Incremental Capacity Analysis

Author:
Anseán González, DavidUniovi authority; García Fernández, Víctor ManuelUniovi authority; González Vega, ManuelaUniovi authority; Blanco Viejo, Cecilio JoséUniovi authority; Viera Pérez, Juan CarlosUniovi authority; Fernández Pulido, YoanaUniovi authority; Sánchez Ramos, LucianoUniovi authority
Subject:

Battery degradation modes

Incremental capacity (IC) analysis

Lithium-ion battery (LIB)

Lookup tables

Publication date:
2019-05
Publisher version:
http://dx.doi.org/10.1109/TIA.2019.2891213
Citación:
IEEE Transactions on Industry Applications, 55(3) (2019); doi:10.1109/TIA.2019.2891213
Descripción física:
p. 2992-3002
Abstract:

Abstract—Lithium-ion battery (LIB)degradation originates from complex mechanisms, usually interacting simultaneously in various degrees of intensity. Due to its complexity, to date, identifying battery aging mechanisms remains challenging. Recent improvements in battery degradation identification have been developed,including validated, in situ incremental capacity (IC) and peak area (PA) analysis. Due to their in situ and non-destructive nature, IC and PA implementation is feasible in on-board battery management systems (BMSs). Despite their advantages, the understanding and applicability of IC and PA techniques is not straightforward, as it requires both electrochemical and material science backgrounds. However, BMS design teams are mainly integrated by electrical engineers and may not include battery scientists. Aiming to bridge gaps in knowledge between electrical engineering and battery science toward battery degradation identification, here we present a systematic approach consisting in a set of lookup tables generated from IC and PA techniques. The lookup tables provide a simple, yet reliable, tool for the evaluation of LIB degradation modes. Various real-life examples of cell degradation are also presented to illustrate and validate the use of the proposed approach. This study exemplifies the use of lookup tables providing a simple, fast, and accurate automated estimation of LIB degradation modes to be implemented in BMSs.

Abstract—Lithium-ion battery (LIB)degradation originates from complex mechanisms, usually interacting simultaneously in various degrees of intensity. Due to its complexity, to date, identifying battery aging mechanisms remains challenging. Recent improvements in battery degradation identification have been developed,including validated, in situ incremental capacity (IC) and peak area (PA) analysis. Due to their in situ and non-destructive nature, IC and PA implementation is feasible in on-board battery management systems (BMSs). Despite their advantages, the understanding and applicability of IC and PA techniques is not straightforward, as it requires both electrochemical and material science backgrounds. However, BMS design teams are mainly integrated by electrical engineers and may not include battery scientists. Aiming to bridge gaps in knowledge between electrical engineering and battery science toward battery degradation identification, here we present a systematic approach consisting in a set of lookup tables generated from IC and PA techniques. The lookup tables provide a simple, yet reliable, tool for the evaluation of LIB degradation modes. Various real-life examples of cell degradation are also presented to illustrate and validate the use of the proposed approach. This study exemplifies the use of lookup tables providing a simple, fast, and accurate automated estimation of LIB degradation modes to be implemented in BMSs.

URI:
http://hdl.handle.net/10651/56927
ISSN:
0093-9994
DOI:
10.1109/TIA.2019.2891213
Patrocinado por:

This work was supported in part by the Science and Innovation Ministry and in part by FEDER, under Projects DPI2013-046541-R, TIN2014-56967-R, TEC2016-80700-R (AEI/FEDER, UE), and TIN2017-84804-R

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