Guidelines for the Characterization of the Internal Impedance of Lithium-Ion Batteries in PHM Algorithms
Open accessAbstract
This article aims to describe the most important aspects to consider when using the concept of internal impedance in algorithms that focus on characterizing the degradation of lithium-ion (Li-ion) batteries. The first part of the article provides a literature review that will help the reader understand the concept of electrochemical impedance spectroscopy (EIS) and how Li-ion batteries can be represented through electrochemical or empirical models, in order to interpret the outcome of typical discharge and/or degradation tests on Li-ion batteries. The second part of the manuscript shows the obtained results of an accelerated degradation experiment performed under controlled conditions on a Li-ion cell. Results show that changes observed on the EIS test can be linked to battery degradation. This knowledge may be of great value when implementing algorithms aimed to predict the End-of-Life (EoL) of the battery in terms of temperature, voltage, and discharge current measurements. The purpose of this article is to introduce the reader to several types of Li-ion battery models, and show how the internal impedance of a Li-ion battery is a dynamic parameter that depends on different factors; and then, illustrate how the EIS can be used to obtain an equivalent circuit model and how the different electronic components vary with the use given to the battery.
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Cites
Ageing mechanisms in lithium-ion batteries
Vetter, J., Novák, P., Wagner, M. R., Veit, C., Möller, K.-C., Besenhard, J. O., Winter, M., Wohlfahrt-Mehrens, M., Vogler, C., & Hammouche, A. (2005) · Journal of Power Sources · doi:10.1016/j.jpowsour.2005.01.006 · Cited by 3,987 · see citing works
Prognostics methods for battery health monitoring using a bayesian framework
Saha, B., Goebel, K., Poll, S., & Christophersen, J. (2009) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2008.2005965 · Cited by 831 · see citing works
Zou, Y., Hu, X., Ma, H., & Li, S. E. (2014) · Journal of Power Sources · doi:10.1016/j.jpowsour.2014.09.146 · Cited by 723 · see citing works
Capacity fade study of lithium-ion batteries cycled at high discharge rates
Ning, G., Haran, B., & Popov, B. N. (2003) · Journal of Power Sources · doi:10.1016/s0378-7753(03)00029-6 · Cited by 616 · see citing works
Cycle Life Modeling of Lithium-Ion Batteries
Ning, G., & Popov, B. N. (2004) · Journal of The Electrochemical Society · doi:10.1149/1.1787631 · Cited by 479 · see citing works
Mathematical modeling of the capacity fade of Li-ion cells
Ramadass, P., Haran, B., White, R. E., & Popov, B. N. (2003) · Journal of Power Sources · doi:10.1016/s0378-7753(03)00531-7 · Cited by 446 · see citing works
Characterizing aging effects of lithium ion batteries by impedance spectroscopy
Tröltzsch, U., Kanoun, O., & Tränkler, H.-R. (2006) · Electrochimica Acta · doi:10.1016/j.electacta.2005.02.148 · Cited by 427 · see citing works
A generalized cycle life model of rechargeable Li-ion batteries
Ning, G., White, R. E., & Popov, B. N. (2005) · Electrochimica Acta · doi:10.1016/j.electacta.2005.06.033 · Cited by 373 · see citing works
Dynamic modelling of lead/acid batteries using impedance spectroscopy for parameter identification
Mauracher, P., & Karden, E. (1997) · Journal of Power Sources · doi:10.1016/s0378-7753(97)02498-1 · Cited by 224 · see citing works
Olivares, B. E., Cerda, M. A., Orchard, M. E., & Silva, J. F. (2012) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2012.2215142 · Cited by 217 · see citing works
Self-citationA new SOH prediction concept for the power lithium-ion battery used on HEVs
Dai, H., Xuezhe, W., & Zechang, S. (2009) · IEEE Vehicle Power and Propulsion Conference (VPPC) · doi:10.1109/vppc.2009.5289654 · Cited by 205 · see citing works
Impedance Observer for a Li-Ion Battery Using Kalman Filter
Vinh, D., Forgez, C., Benkara, K. E. K., & Friedrich, G. (2009) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2009.2028572 · Cited by 179 · see citing works
Parameter Estimation and Life Modeling of Lithium-Ion Cells
Santhanagopalan, S., Zhang, Q., Kumaresan, K., et al. (2008) · Journal of The Electrochemical Society · doi:10.1149/1.2839630 · Cited by 173 · see citing works
Electrochemistry-based Battery Modeling for Prognostics
Daigle, M. J., & Kulkarni, C. S. (2013) · Annual Conference of the PHM Society · doi:10.36001/phmconf.2013.v5i1.2252 · Cited by 122 · see citing works
Electrochemical impedance spectroscopy for online battery monitoring - power electronics control
Koch, R., Kühn, R., Zilberman, I., et al. (2014) · European Conference on Power Electronics and Applications · doi:10.1109/epe.2014.6910907 · Cited by 57 · see citing works
State of health aware charge management in hybrid electrical energy storage systems
Xie, Q., Lin, X., Wang, Y., Pedram, M., Shin, D., & Chang, N. (2012) · doi:10.5555/2492708.2492970 · Cited by 50 · see citing works
An Analytical Model for Predicting the Remaining Battery Capacity of Lithium-Ion Batteries
Peng, R., & Pedram, M. (2003) · Design, Automation, and Test in Europe · doi:10.5555/789083.1022894 · Cited by 42 · see citing works
Study on correlation with SOH and EIS model of Li-ion battery
Wang, H., He, L., Jian-hua, S., et al. (2011) · doi:10.1109/ifost.2011.6021018 · Cited by 27 · see citing works
An analytical model for predicting the remaining battery capacity of lithium-ion batteries
Rong, P., & Pedram, M. (2003) · Design, Automation, and Test in Europe · doi:10.1109/date.2003.1253775 · Cited by 27 · see citing works
State of health aware charge management in hybrid electrical energy storage systems
Xie, Q., Lin, X., Wang, Y., Pedram, M., Shin, D., & Chang, N. (2012) · Design, Automation, and Test in Europe · doi:10.1109/date.2012.6176652 · Cited by 25 · see citing works
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Background
- Authors
- Pérez, A., Benavides, M., Rozas, H., Seria, S., & Orchard, M.
- Affiliations
- University of Chile (CL)
- Venue
- International Journal of Prognostics and Health Management
- Publisher
- PHM Society
- Published
- 2020-11-20
- Volume
- 9
- Issue
- 3
- ISSN
- 2153-2648 (ISSN-L)
- OpenAlex
- W3136515962
- Cited by
- 16
- References
- 20
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 1 · 2023: 4 · 2021: 4 · 2020: 2 · 2019: 1 · 2018: 1
- FWCI
- 0.92
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- other-oa
- Locations
- International Journal of Prognostics and Health Management (publishedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Universidad de Chile (submittedVersion)
- Funders
- Universidad de Costa Rica (1170044)
- Comisión Nacional de Investigación Científica y Tecnológica (FB0008, 1170044)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Advanced Battery Technologies Research
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Battery Materials
- Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Reliability and Maintenance Optimization
- Keywords
- lithium-ion batteries, internal impedance, electrochemical impedance spectroscopy, battery degradation, prognostics and health management, end-of-life prediction, equivalent circuit model, battery model, accelerated degradation testing
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