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Title: Models for Battery Reliability and Lifetime

Abstract

Models describing battery degradation physics are needed to more accurately understand how battery usage and next-generation battery designs can be optimized for performance and lifetime. Such lifetime models may also reduce the cost of battery aging experiments and shorten the time required to validate battery lifetime. Models for chemical degradation and mechanical stress are reviewed. Experimental analysis of aging data from a commercial iron-phosphate lithium-ion (Li-ion) cell elucidates the relative importance of several mechanical stress-induced degradation mechanisms.

Authors:
; ; ; ; ;
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy Vehicle Technologies Office
OSTI Identifier:
1128611
Report Number(s):
NREL/CP-5400-57746
DOE Contract Number:
AC36-08GO28308
Resource Type:
Conference
Resource Relation:
Conference: Presented at the Battery Congress 2013, 15-16 April 2013, Ann Arbor, Michigan
Country of Publication:
United States
Language:
English
Subject:
25 ENERGY STORAGE; 33 ADVANCED PROPULSION SYSTEMS; BATTERY; RELIABILITY; LITHIUM; LI-ION; FATIGUE; MODEL; PREDICTIVE; BATTERY OWNERSHIP MODEL; BOM; SECOND USE; ENERGY STORAGE; Transportation

Citation Formats

Smith, K., Wood, E., Santhanagopalan, S., Kim, G. H., Neubauer, J., and Pesaran, A. Models for Battery Reliability and Lifetime. United States: N. p., 2014. Web.
Smith, K., Wood, E., Santhanagopalan, S., Kim, G. H., Neubauer, J., & Pesaran, A. Models for Battery Reliability and Lifetime. United States.
Smith, K., Wood, E., Santhanagopalan, S., Kim, G. H., Neubauer, J., and Pesaran, A. Sat . "Models for Battery Reliability and Lifetime". United States. doi:. https://www.osti.gov/servlets/purl/1128611.
@article{osti_1128611,
title = {Models for Battery Reliability and Lifetime},
author = {Smith, K. and Wood, E. and Santhanagopalan, S. and Kim, G. H. and Neubauer, J. and Pesaran, A.},
abstractNote = {Models describing battery degradation physics are needed to more accurately understand how battery usage and next-generation battery designs can be optimized for performance and lifetime. Such lifetime models may also reduce the cost of battery aging experiments and shorten the time required to validate battery lifetime. Models for chemical degradation and mechanical stress are reviewed. Experimental analysis of aging data from a commercial iron-phosphate lithium-ion (Li-ion) cell elucidates the relative importance of several mechanical stress-induced degradation mechanisms.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sat Mar 01 00:00:00 EST 2014},
month = {Sat Mar 01 00:00:00 EST 2014}
}

Conference:
Other availability
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  • This presentation discusses models for battery reliability and lifetime and the Battery Ownership Model.
  • Predictive models of capacity and power fade must consider a multiplicity of degradation modes experienced by Li-ion batteries in the automotive environment. Lacking accurate models and tests, lifetime uncertainty must presently be absorbed by overdesign and excess warranty costs. To reduce these costs and extend life, degradation models are under development that predict lifetime more accurately and with less test data. The lifetime models provide engineering feedback for cell, pack and system designs and are being incorporated into real-time control strategies.
  • Predictive models of Li-ion battery reliability must consider a multiplicity of electrochemical, thermal and mechanical degradation modes experienced by batteries in application environments. Complicating matters, Li-ion batteries can experience several path dependent degradation trajectories dependent on storage and cycling history of the application environment. Rates of degradation are controlled by factors such as temperature history, electrochemical operating window, and charge/discharge rate. Lacking accurate models and tests, lifetime uncertainty must be absorbed by overdesign and warranty costs. Degradation models are needed that predict lifetime more accurately and with less test data. Models should also provide engineering feedback for next generation batterymore » designs. This presentation reviews both multi-dimensional physical models and simpler, lumped surrogate models of battery electrochemical and mechanical degradation. Models are compared with cell- and pack-level aging data from commercial Li-ion chemistries. The analysis elucidates the relative importance of electrochemical and mechanical stress-induced degradation mechanisms in real-world operating environments. Opportunities for extending the lifetime of commercial battery systems are explored.« less
  • 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.