Published October 15, 2017 | Version v1
Journal article

Li-ion battery capacity cycling fading dynamics cognition: A stochastic approach

  • 1. Science and Technology on Reliability and Environmental Engineering Laboratory (China)
  • 2. School of Reliability and Systems Engineering, Beihang University (China)
  • 3. Department of Mechanical & Industrial Engineering, University of Toronto (Canada)
  • 4. School of Aeronautic Science and Engineering, Beihang University (China)
  • 5. Contemporary Amperex Technology Co., Limited, Ningde, Fujian Province (China)

Description

Li-ion batteries have been commercially used for many years in small portable devices and electrical vehicles. Here, a five-state nonhomogeneous Markov chain model is introduced, which can assist to saving time and costs incurred by large amounts of cycling life tests with various cell formulations in battery design stage. The model is designed to have five states that belong to three phases: storage phase, active phase, and absorbing phase. The storage phase has one storage state that could be transformed into the third active state; the active phase is comprised of a stable state, an inherent unstable state, and a state that is transformed from the storage phase; the absorbing phase, which is converted from the active phase. The verification results suggest that the proposed model provides an accurate and effective way to cognizing the capacity cycling fading dynamics of various Li-ion batteries with different anode materials even under different working conditions (The cognition accuracy of R-Square can reach 0.999). Furthermore, this method would be a promising way to evaluate the features and performance of Li-ion batteries made of different formulations in the design stage, which could provide valuable information for battery manufacturers to accelerate battery design process. - Highlights: • A model linked to physicochemical fading process of Li-ion battery is proposed. • The model describes battery capacity fading as a nonhomogeneous Markov chain. • The model can cognize capacity fading dynamics with different anode materials. • Nonlinear features within cycling fading dynamics can be depicted by the model. • This approach can describe batteries under different working conditions.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.energy.2017.06.167

Additional details

Identifiers

DOI
10.1016/j.energy.2017.06.167;
PII
S0360-5442(17)31162-3;

Publishing Information

Journal Title
Energy (Oxford)
Journal Volume
137
Journal Issue
Complete
Journal Page Range
p. 251-259
ISSN
0360-5442
CODEN
ENEYDS

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
49065355
Subject category
S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
Descriptors DEI
ANODES; LITHIUM ION BATTERIES; MARKOV PROCESS; NONLINEAR PROBLEMS; WORKING CONDITIONS
Descriptors DEC
ELECTRIC BATTERIES; ELECTROCHEMICAL CELLS; ELECTRODES; ENERGY STORAGE SYSTEMS; ENERGY SYSTEMS; STOCHASTIC PROCESSES

Optional Information

Copyright
Copyright (c) 2017 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.