Advanced Models and Controls for Prediction and Extension of Battery Lifetime (Presentation)

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Description

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.

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25 p.

Creation Information

Smith, K.; Wood, E.; Santhanagopalan, S.; Kim, G. & Pesaran, A. February 1, 2014.

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Description

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.

Physical Description

25 p.

Source

  • Presented at the 2014 Large Lithium Ion Battery Technology & Application Symposia Advanced Automotive Battery Conference, 4 - 6 February 2014, Atlanta, Georgia; Related Information: NREL (National Renewable Energy Laboratory)

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  • Report No.: NREL/PR-5400-61037
  • Grant Number: AC36-08GO28308
  • Office of Scientific & Technical Information Report Number: 1114881
  • Archival Resource Key: ark:/67531/metadc871298

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Creation Date

  • February 1, 2014

Added to The UNT Digital Library

  • Sept. 16, 2016, 12:32 a.m.

Description Last Updated

  • April 4, 2017, 3:27 p.m.

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Smith, K.; Wood, E.; Santhanagopalan, S.; Kim, G. & Pesaran, A. Advanced Models and Controls for Prediction and Extension of Battery Lifetime (Presentation), article, February 1, 2014; Golden, Colorado. (digital.library.unt.edu/ark:/67531/metadc871298/: accessed August 20, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.