Physics Based Modeling Tools for Next-Generation Lithium Ion Battery Performance and Lifetime

Award Information
Agency: Department of Defense
Branch: Missile Defense Agency
Contract: HQ0147-12-C-7163
Agency Tracking Number: B2-1855
Amount: $993,559.00
Phase: Phase II
Program: STTR
Awards Year: 2012
Solicitation Year: 2010
Solicitation Topic Code: MDA10-T004
Solicitation Number: 2010.B
Small Business Information
215 Wynn Dr., 5th Floor, Huntsville, AL, -
DUNS: 185169620
HUBZone Owned: N
Woman Owned: Y
Socially and Economically Disadvantaged: N
Principal Investigator
 J. Cole
 (256) 726-4852
Business Contact
 Deborah Phipps
Title: Contracts Manager
Phone: (256) 726-4884
Research Institution
 Washington University in St. Louis
 Connie Motoki
 1 Brookings Dr. Campus Bx 1054
275 N. Skinker Bldg, Ste 220
St. Louis, MO, 63130-
 (314) 935-9443
 Nonprofit college or university
The MDA is developing the Precision Tracking Space System and other satellite based systems that could benefit from ongoing developments in advanced materials for lithium ion batteries. Unfortunately, the applications driving much of that battery research have less abusive operational cycles than the frequent cycling, and sporadic pulse loads to deep discharge, of MDA satellite applications. Physics based models of battery performance and degradation for promising material chemistries are desired to help screen candidates that can meet calendar and active life requirements under abusive orbital mission profiles, and to support and improve accelerated life testing for earlier insertion. In Phase I, CFDRC and our partner Washington University in Saint Louis developed and validated fast, predictive electrochemical models to aid in screening next-generation lithium ion batteries for MDA applications. The models included variable lithium diffusivity in the active material particles, improving predictive capabilities for promising materials, and detailed treatment of interfacial film formation that reduces battery capacity and/or rate. During Phase II, we will incorporate additional degradation mechanisms and material property models. Model parameters will be extracted from and validated against laboratory cycling data, then the models will be applied to estimate battery life cycles and analyze/improve testing protocols.

* Information listed above is at the time of submission. *

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