Comprehensive Modeling of Temperature-Dependent Degradation Mechanisms in Lithium Iron Phosphate Batteries

Schimpe, Michael; von Kuepach, M. E.; Naumann, M.; Hesse, H. C.; Smith, Kandler A.; Jossen, A.

doi:10.1149/2.1181714jes

Comprehensive Modeling of Temperature-Dependent Degradation Mechanisms in Lithium Iron Phosphate Batteries

Journal Article · Fri Jan 12 00:00:00 EST 2018 · Journal of the Electrochemical Society

DOI:https://doi.org/10.1149/2.1181714jes· OSTI ID:1421782

^[1]; von Kuepach, M. E. ^[1]; Naumann, M. ^[1]; Hesse, H. C. ^[1]; ^[2]; Jossen, A. ^[1]

Technical Univ. of Munich (TUM), Munich (Germany)
National Renewable Energy Lab. (NREL), Golden, CO (United States)

For reliable lifetime predictions of lithium-ion batteries, models for cell degradation are required. A comprehensive semi-empirical model based on a reduced set of internal cell parameters and physically justified degradation functions for the capacity loss is developed and presented for a commercial lithium iron phosphate/graphite cell. One calendar and several cycle aging effects are modeled separately. Emphasis is placed on the varying degradation at different temperatures. Degradation mechanisms for cycle aging at high and low temperatures as well as the increased cycling degradation at high state of charge are calculated separately. For parameterization, a lifetime test study is conducted including storage and cycle tests. Additionally, the model is validated through a dynamic current profile based on real-world application in a stationary energy storage system revealing the accuracy. Tests for validation are continued for up to 114 days after the longest parametrization tests. In conclusion, the model error for the cell capacity loss in the application-based tests is at the end of testing below 1% of the original cell capacity and the maximum relative model error is below 21%.

View Accepted Manuscript (DOE)

Research Organization:: National Renewable Energy Laboratory (NREL), Golden, CO (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V)

Grant/Contract Number:: AC36-08GO28308

OSTI ID:: 1421782

Report Number(s):: NREL/JA--5400-70616

Journal Information:: Journal of the Electrochemical Society, Journal Name: Journal of the Electrochemical Society Journal Issue: 2 Vol. 165; ISSN 0013-4651

Publisher:: The Electrochemical SocietyCopyright Statement

Country of Publication:: United States

Language:: English

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Battery health prediction under generalized conditions using a Gaussian process transition model Richardson, Robert R.; Osborne, Michael A.; Howey, David A. arXiv https://doi.org/10.48550/arxiv.1807.06350	text	January 2018
Assessment of residential battery storage systems and operation strategies considering battery aging Förstl, Markus; Azuatalam, Donald; Chapman, Archie International Journal of Energy Research, Vol. 44, Issue 2 https://doi.org/10.1002/er.4770	journal	November 2019
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Fast charging of lithium-ion batteries at all temperatures Yang, Xiao-Guang; Zhang, Guangsheng; Ge, Shanhai Proceedings of the National Academy of Sciences, Vol. 115, Issue 28 https://doi.org/10.1073/pnas.1807115115	journal	June 2018
Cycle Life Prediction of Aged Lithium-Ion Batteries from the Fading Trajectory of a Four-Parameter Model Li, Je-Feng; Lin, Chi-Hao; Chen, Kuo-Ching Journal of The Electrochemical Society, Vol. 165, Issue 16 https://doi.org/10.1149/2.0211816jes	journal	January 2018
Review and Performance Comparison of Mechanical-Chemical Degradation Models for Lithium-Ion Batteries Reniers, Jorn M.; Mulder, Grietus; Howey, David A. Journal of The Electrochemical Society, Vol. 166, Issue 14 https://doi.org/10.1149/2.0281914jes	journal	January 2019
Ageing and Efficiency Aware Battery Dispatch for Arbitrage Markets Using Mixed Integer Linear Programming Hesse, Holger; Kumtepeli, Volkan; Schimpe, Michael Energies, Vol. 12, Issue 6 https://doi.org/10.3390/en12060999	journal	March 2019

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