Predictive Models of Li-ion Battery Lifetime: NREL (National Renewable Energy Laboratory)

Kandler Smith, Eric Wood, Shriram Santhanagopalan, Gi-Heon Kim, Ying Shi, Ahmad Pesaran, Gi-Heon Kim

Research output: NRELPresentation

Abstract

It remains an open question how best to predict real-world battery lifetime based on accelerated calendar and cycle aging data from the laboratory. Multiple degradation mechanisms due to (electro)chemical, thermal, and mechanical coupled phenomena influence Li-ion battery lifetime, each with different dependence on time, cycling and thermal environment. The standardization of life predictive models would benefit the industry by reducing test time and streamlining development of system controls.
Original languageAmerican English
Number of pages24
StatePublished - 2015

Publication series

NamePresented at the Advanced Automotive & Industrial/Stationary Battery Conference, 15-19 June 2015, Detroit, Michigan

NREL Publication Number

  • NREL/PR-5400-64622

Keywords

  • battery
  • battery life
  • CRADAS
  • life predictive model

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