Title: Modeling strategy for progressive failure prediction in lithium-ion batteries under mechanical abuse

Abstract

The prediction for the internal failure of lithium-ion batteries (LIBs) under external mechanical abuse loading remains a challenge for safe design. This paper systematically studies the modeling approach for progressive failure simulation and short-circuit prediction. Hemispherical indentation experiments are conducted on a battery specimen containing 5 representative sandwich (RS) layers to examine the deformation and progressive failure behavior of battery components. Three different models, viz, a high-fidelity detailed model, an intermediate homogenized model and a fully homogenized model, are developed and employed to simulate the progressive failure in a multi-layer battery specimen. The simulation results obtained using the three models all correlate well with experimental phenomena, capturing the overall stress-strain response and ultimate failure of the battery structure. The numerical results can help us understand the failure behavior and the mechanism for mechanical abuse-induced short circuit in LIBs. The feasibility of the three models for use in progressive failure prediction is compared by analyzing the capability of the models in predicting the critical failure events, the computational efficiency of the models, and the feasibility to implement coupled mechanical-electrochemical-thermal simulations. The results of this work provide useful insights on practical choices for the modeling strategy and safety design of LIBs undermore » mechanical abuse conditions.« less

Authors:

Yin, Hanfeng ^[1]; Ma, Shuai ^[1]; Li, Honggang ^[2]; Wen, Cuilin ^[1]; Santhanagopalan, Shriram ^[3]; Zhang, Chao  ^[2]

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+ Show Author Affiliations

1. Hunan University, Changsha (China)
2. Northwestern Polytechnical University (China)
3. National Renewable Energy Lab. (NREL), Golden, CO (United States)

Publication Date:

Mon Dec 28 00:00:00 EST 2020

Research Org.:

National Renewable Energy Lab. (NREL), Golden, CO (United States)

Sponsoring Org.:

USDOE Office of Energy Efficiency and Renewable Energy (EERE), Transportation Office. Vehicle Technologies Office

OSTI Identifier:

1764943

Report Number(s):

NREL/JA-5700-76871
Journal ID: ISSN 2590-1168; MainId:10515;UUID:13ee0818-5c9b-4542-8e4b-458efb045aca;MainAdminID:19295

Grant/Contract Number:  

AC36-08GO28308

Resource Type:

Accepted Manuscript

Journal Name:

eTransportation

Additional Journal Information:

Journal Volume: 7; Journal ID: ISSN 2590-1168

Publisher:

Elsevier

Country of Publication:

United States

Language:

English

Subject:

33 ADVANCED PROPULSION SYSTEMS; 25 ENERGY STORAGE; finite element analysis; high-fidelity detailed model; homogenized model; lithium-ion batteries; mechanical failure behavior