Remaining useful life prediction for lithium-ion batteries based on an integrated health indicator-Reference-Cited by-同舟云学术

Remaining useful life prediction for lithium-ion batteries based on an integrated health indicator

Published:2018-09 Issue: Volume:88-90 Page:1189-1194
ISSN:0026-2714
Container-title:Microelectronics Reliability
language:en
Short-container-title:Microelectronics Reliability

Author:

Sun Yongquan,Hao Xueling,Pecht Michael,Zhou Yapeng

Funder

Natural Science Foundation of Heilongjiang Province

University Nursing Program for Young Scholars with Creative Talents

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Surfaces, Coatings and Films,Safety, Risk, Reliability and Quality,Condensed Matter Physics,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials

Reference18 articles.

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2. Capacity fade modelling of lithium-ion battery under cyclic loading conditions;Ashwin;J. Power Sources,2016

3. Capacity prognostics of lithium-ion batteries using EMD denoising and multiple kernel RVM;Zhang;IEEE Access,2017

4. Lithium-ion battery pack state of charge and state of energy estimation algorithms using a hardware-in-the-loop validation;Zhang;IEEE Trans. Power Electron.,2017

5. A novel mechanistic modeling framework for analysis of electrode balancing and degradation modes in commercial lithium-ion cells;Schindler;J. Power Sources,2017

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