Development and Verification of a Diagnostic Technology for Waste Battery Deterioration Factors

Author:

Jung Sunghun1ORCID,Seo Joon Kyo2,Jang Il‐Chan2,Kim Jihun2,Shim Jae‐Hyun3,Woo Jung‐Je2ORCID

Affiliation:

1. Faculty of Smart Vehicle System Engineering Chosun University 101, Chosundae 2-gil, Dong-gu Gwangju 61452 Republic of Korea

2. Gwangju Clean Energy Research Center Korea Institute of Energy Research 25, Samso-ro 270 beon-gil, Buk-gu Gwangju 61003 Republic of Korea

3. Faculty of Battery Science and Engineering Dongshin University 67, Dongsindae-gil Naju-si Jeollanam-do 58245 Republic of Korea

Abstract

AbstractWe defined four major deterioration factors (electrolyte loss (EL), lithium loss (LL), lithium precipitation (LP), and compound deterioration (CD)). Then, we derived eleven key performance indicators (KPIs) for comparative analysis. After that, we fabricated three deteriorated cells for each of three deterioration factors (EL, LL, and LP) and one cell with CD (for verification) with four individual (dis)charging experiment manuals. The two major contributions of this study are the performance of 1) trend analysis to determine a suitable diagnostic metric by inspecting the eleven KPIs and 2) comparison analysis of and to verify the effectiveness of utilizing as a real‐time deterioration diagnostic factor using a concept of model‐in‐the‐loop simulation. The results show that 1) has the most conspicuous trendline tendency among the eleven comparison targets for all four major deterioration factors, and 2) the angle difference between the two trends of and lies within a minimum of 9° and a maximum of 43° (with a sscale on the x‐axis and a scale on the y‐axis for a clear trend line analysis). From this, we can conclude that the trendline‐based real‐time deterioration analysis employing may be practically applicable to a limited extent.

Publisher

Wiley

Subject

Physical and Theoretical Chemistry,Atomic and Molecular Physics, and Optics

Reference36 articles.

1. Cost Projection of State of the Art Lithium-Ion Batteries for Electric Vehicles Up to 2030

2. Mechanistic investigation of silicon-graphite/LiNi0.8Mn0.1Co0.1O2 commercial cells for non-intrusive diagnosis and prognosis

3. Online capacity estimation of lithium-ion batteries with deep long short-term memory networks

4. International Energy Agency “Global EV Outlook 2022” can be found underhttps://iea.blob.core.windows.net/assets/e0d2081d-487d–4818-8c59-69b638969f9e/GlobalElectricVehicleOutlook2022.pdf 2022(accessed 1 August 2023).

5. Hyundai Motor Group “Hyundai Motor Group Signs MOU with CPS Energy and OCI Solar Power” can be found under http://www.hyundai motorgroup.com/news/CONT0000000000001638 2021(accessed 1 August 2023).

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