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Life prediction of lithium ion batteries for electric vehicles based on gas production behavior model

  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Lithium ion battery as a kind of new energy is a promising energy storage medium for electric and hybrid electric vehicles with their characteristics of lightness and high energy density. However, some accidents about battery fire or explosion remind us to focus on their reliability and safety issues. Thus, life prediction as the essential part should be considered during the design phrase of batteries to guarantee the safety and reliability level. In this paper, a new life prediction method based on gas production model of batteries has been proposed. Firstly, based on analysis result of actual gas production mechanism, types of chemical reactions existed in batteries can be determined. Then, through theoretical analysis of these chemical reactions combined with capacity change of battery, the whole gas behavior is divided into two stages. It includes the initial solid electrolyte interface formation stage and the stage of solid electrolyte interface being severely damaged and repaired. Gas production equation of each stage has been constructed. Based on these gas equations, quantitative relationship between the battery capacity and the characteristics of gas production is investigated. With a suitable end-of-life criterion, the application-oriented life prediction model for lithium ion batteries is established. Finally, the verification procedure is presented based on actual test data to validate our method and its advantages. This paper aims to achieve deeper understanding gas behavior of lithium ion batteries and further develop corresponding life prediction method to provide a theoretical basis for future design improvement.

Original languageEnglish
Title of host publicationProceedings - 2017 International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2017
EditorsWei Guo, Jose Valente de Oliveira, Chuan Li, Yun Bai, Ping Ding, Juanjuan Shi
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages275-280
Number of pages6
ISBN (Electronic)9781509040209
DOIs
StatePublished - 9 Dec 2017
Event2017 International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2017 - Shanghai, China
Duration: 16 Aug 201718 Aug 2017

Publication series

NameProceedings - 2017 International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2017
Volume2017-December

Conference

Conference2017 International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2017
Country/TerritoryChina
CityShanghai
Period16/08/1718/08/17

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Capacity
  • Electric vehicle
  • Gas production model
  • Life prediction
  • Lithium ion battery

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