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Open AccessArticle

Algorithm to Determine the Knee Point on Capacity Fade Curves of Lithium-Ion Cells

Center for Advanced Life Cycle Engineering (CALCE), University of Maryland, College Park, MD 20742, USA
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Energies 2019, 12(15), 2910; https://doi.org/10.3390/en12152910
Received: 9 May 2019 / Revised: 24 July 2019 / Accepted: 26 July 2019 / Published: 29 July 2019
(This article belongs to the Section Energy Storage and Application)
Lithium-ion batteries typically exhibit a transition to a more rapid capacity fade trend when subjected to extended charge–discharge cycles and storage conditions. The identification of the knee point can be valuable to identify the more severe degradation trend, and to provide guidance when scheduling battery replacements and planning secondary uses of the battery. However, a concise and repeatable determination of a knee point has not been documented. This paper provides a definition of the knee point which can be used as a degradation metric, and develops an algorithm to identify it. The algorithm is implemented on various data cases, and the results indicate that the approach provides repeatable knee point identification. View Full-Text
Keywords: lithium-ion batteries; capacity fade; algorithm; knee point identification; slope-changing ratio lithium-ion batteries; capacity fade; algorithm; knee point identification; slope-changing ratio
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MDPI and ACS Style

Diao, W.; Saxena, S.; Han, B.; Pecht, M. Algorithm to Determine the Knee Point on Capacity Fade Curves of Lithium-Ion Cells. Energies 2019, 12, 2910.

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