4.8 Article

Capacity-loss diagnostic and life-time prediction in lithium-ion batteries: Part 1. Development of a capacity-loss diagnostic method based on open-circuit voltage analysis

Journal

JOURNAL OF POWER SOURCES
Volume 301, Issue -, Pages 187-193

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.jpowsour.2015.09.110

Keywords

Lithium-ion battery; Capacity-loss diagnostic; Life-time prediction; Open-circuit voltage

Funding

  1. International (Regional) Cooperation and Exchange Program (NSFC) [51361130153]
  2. International (Regional) Cooperation and Exchange Program (EPSRC) [EP/L001063/1]
  3. Research and Development of Application Technology Plan Project in Heilongjiang Province of China [GA13A202]
  4. EPSRC [EP/L001063/1] Funding Source: UKRI
  5. Engineering and Physical Sciences Research Council [EP/L001063/1] Funding Source: researchfish

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Effective capacity-loss diagnosis and life-time prediction are the foundations of battery second-use technology and will play an important role in the development of the new energy industry. Of the two, the capacity-loss diagnostic, as a precondition of the life-time prediction, needs to be studied first. Performing a capacity-loss diagnosis for an aging cell consists of finding the decisive degradation mechanisms for the cell's capacity degradation. Because a cell's capacity just equals the span of the open-circuit voltage (OCV), when suspect degradation mechanisms affect a cell's capacity, they will leave corresponding and particular clues in the OCV curve. Taking a cell's OCV as the diagnostic indicator, a multi-mechanistic and non-destructive diagnostic method is developed in this paper. To establish an unambiguous relationship between OCV changes and the combinations of the decisive mechanisms, all the possible OCV changes under various aging situations are systematically analyzed based on a novel simultaneous coordinate system, in which the effects of each suspect capacity-loss mechanism on the OCV curve can be clearly represented. As a summary of the analysis results, a straightforward diagnostic flowchart is presented. By following the flowchart, an aging cell can be diagnosed within three steps by observation of the OCV changes. (C) 2015 Elsevier B.V. All rights reserved.

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