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Title: Predictive Models of Li-ion Battery Lifetime

Conference ·
OSTI ID:1225318

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.

Research Organization:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V)
DOE Contract Number:
AC36-08GO28308
OSTI ID:
1225318
Report Number(s):
NREL/PR-5400-64622
Resource Relation:
Conference: Advanced Automotive Battery Conference;Detroit, MI; -
Country of Publication:
United States
Language:
English