Publication:
Fast capacity and internal resistance estimation method for second-life batteries from electric vehicles

Date

2023

Director

Publisher

Elsevier
Acceso abierto / Sarbide irekia
Artículo / Artikulua
Versión publicada / Argitaratu den bertsioa

Project identifier

European Commission/Horizon 2020 Framework Programme/774094openaire
AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-111262RB-I00/ES/recolecta
Gobierno de Navarra/0011-1411-2022-000039

Abstract

The success of second-life (SL) Li-ion batteries from electric vehicles is still conditioned by their technical and economic viability. The knowledge of the internal parameters of retired batteries at the repurposing stage is key to ensure their adequate operation and to enlarge SL lifetime. However, traditional characterization methods require long testing times and specific equipment, which result in high costs that may jeopardize the economic viability of SL. In the seek of optimizing the repurposing stage, this contribution proposes a novel fast characterization method that allows to estimate capacity and internal resistance at various state of charge for reused cells, modules and battery packs. Three estimation models are proposed. The first of them is based on measurements of AC resistance, the second on DC resistance and the third combines both resistance types. These models are validated in 506 cells, 203 modules and 3 battery packs from different Nissan Leaf vehicles. The results achieved are satisfactory, with mean absolute percentage errors (MAPE) below 2.5% at cell and module level in capacity prediction and lower than 2.4% in resistance estimation. Considering battery pack level, MAPE is below 4.2% and 1.8% in capacity and resistance estimation respectively. With the proposed method, testing times are reduced from more than one day to 2 min per cell, while energy consumption is lowered from 1.4 kWh to 1 Wh. In short, this study contributes to the reduction of repurposing procedures and costs, and ultimately to the success of SL batteries business model.

Description

Keywords

Characterization, Electric vehicle, Energy storage, Lithium-ion battery, Second-life battery

Department

Ingeniería Eléctrica, Electrónica y de Comunicación / Institute of Smart Cities - ISC / Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren

Faculty/School

Degree

Doctorate program

item.page.cita

Braco, E., San Martín, I., Sanchis, P., & Ursúa, A. (2023). Fast capacity and internal resistance estimation method for second-life batteries from electric vehicles. Applied Energy, 329, 120235. https://doi.org/10.1016/j.apenergy.2022.120235

item.page.rights

© 2022 The Author(s). This is an open access article under the CC BY license.

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