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Title: Battery Capacity Fading Estimation Using a Force-Based Incremental Capacity Analysis

Traditionally health monitoring techniques in lithium-ion batteries rely on voltage and current measurements. A novel method of using a mechanical rather than electrical signal in the incremental capacity analysis (ICA) method is introduced in this paper. This method derives the incremental capacity curves based onmeasured force (ICF) instead of voltage (ICV). The force ismeasured on the surface of a cell under compression in a fixture that replicates a battery pack assembly and preloading. The analysis is performed on data collected from cycling encased prismatic Lithium-ion Nickel-Manganese-Cobalt Oxide (NMC) cells. For the NMC chemistry, the ICF method can complement or replace the ICV method for the following reasons. The identified ICV peaks are centered around 40% of state of charge (SOC) while the peaks of the ICF method are centered around 70% of SOC indicating that the ICF can be used more often because it is more likely that an electric vehicle (EV) or a plug-in hybrid electric vehicle (PHEV) will traverse the 70% SOC range than the 40% SOC. In addition the Signal to Noise ratio (SNR) of the force signal is four times larger than the voltage signal using laboratory grade sensors. The proposed ICF method is shown tomore » achieve 0.42% accuracy in capacity estimation during a low C-rate constant current discharge. Future work will investigate the application of the capacity estimation technique under charging and operation under high C-rates by addressing the transient behavior of force so that an online methodology for capacity estimation is developed.« less
Authors:
 [1] ;  [2] ;  [1] ;  [1]
  1. Univ. of Michigan, Ann Arbor, MI (United States). Department of Mechanical Engineering
  2. Southwest Research Institute, Ann Arbor, MI (United States). Ann Arbor Technical Center
Publication Date:
Grant/Contract Number:
AR0000269
Type:
Accepted Manuscript
Journal Name:
Journal of the Electrochemical Society
Additional Journal Information:
Journal Volume: 163; Journal Issue: 8; Journal ID: ISSN 0013-4651
Publisher:
The Electrochemical Society
Research Org:
General Electric Company, Boston, MA (United States)
Sponsoring Org:
USDOE Advanced Research Projects Agency - Energy (ARPA-E)
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; 25 ENERGY STORAGE; Capacity estimation; Force; Incremental capacity analysis; State of health; Stress
OSTI Identifier:
1437279

Samad, Nassim A., Kim, Youngki, Siegel, Jason B., and Stefanopoulou, Anna G.. Battery Capacity Fading Estimation Using a Force-Based Incremental Capacity Analysis. United States: N. p., Web. doi:10.1149/2.0511608jes.
Samad, Nassim A., Kim, Youngki, Siegel, Jason B., & Stefanopoulou, Anna G.. Battery Capacity Fading Estimation Using a Force-Based Incremental Capacity Analysis. United States. doi:10.1149/2.0511608jes.
Samad, Nassim A., Kim, Youngki, Siegel, Jason B., and Stefanopoulou, Anna G.. 2016. "Battery Capacity Fading Estimation Using a Force-Based Incremental Capacity Analysis". United States. doi:10.1149/2.0511608jes. https://www.osti.gov/servlets/purl/1437279.
@article{osti_1437279,
title = {Battery Capacity Fading Estimation Using a Force-Based Incremental Capacity Analysis},
author = {Samad, Nassim A. and Kim, Youngki and Siegel, Jason B. and Stefanopoulou, Anna G.},
abstractNote = {Traditionally health monitoring techniques in lithium-ion batteries rely on voltage and current measurements. A novel method of using a mechanical rather than electrical signal in the incremental capacity analysis (ICA) method is introduced in this paper. This method derives the incremental capacity curves based onmeasured force (ICF) instead of voltage (ICV). The force ismeasured on the surface of a cell under compression in a fixture that replicates a battery pack assembly and preloading. The analysis is performed on data collected from cycling encased prismatic Lithium-ion Nickel-Manganese-Cobalt Oxide (NMC) cells. For the NMC chemistry, the ICF method can complement or replace the ICV method for the following reasons. The identified ICV peaks are centered around 40% of state of charge (SOC) while the peaks of the ICF method are centered around 70% of SOC indicating that the ICF can be used more often because it is more likely that an electric vehicle (EV) or a plug-in hybrid electric vehicle (PHEV) will traverse the 70% SOC range than the 40% SOC. In addition the Signal to Noise ratio (SNR) of the force signal is four times larger than the voltage signal using laboratory grade sensors. The proposed ICF method is shown to achieve 0.42% accuracy in capacity estimation during a low C-rate constant current discharge. Future work will investigate the application of the capacity estimation technique under charging and operation under high C-rates by addressing the transient behavior of force so that an online methodology for capacity estimation is developed.},
doi = {10.1149/2.0511608jes},
journal = {Journal of the Electrochemical Society},
number = 8,
volume = 163,
place = {United States},
year = {2016},
month = {5}
}