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Modeling of Lithium-Ion Cell Performance

Award Information
Agency: Department of Defense
Branch: Missile Defense Agency
Contract: HQ0147-13-C-7167
Agency Tracking Number: B2-1860
Amount: $999,515.00
Phase: Phase II
Program: STTR
Solicitation Topic Code: MDA10-T004
Solicitation Number: 2010.B
Solicitation Year: 2010
Award Year: 2013
Award Start Date (Proposal Award Date): 2013-03-22
Award End Date (Contract End Date): 2015-03-21
Small Business Information
12744 San Fernando Road Building 3
Sylmar, CA -
United States
DUNS: 071628460
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Hiroshi Nakahara
 Director of Battery Development
 (818) 833-2016
Business Contact
 Alex Fay
Title: Business Development Manager
Phone: (818) 833-2029
Research Institution
 University of South Carolina
 Ralph White
Dept of Chemical Engineering 301 South Main Street
Columbia, SC 29208-
United States

 (803) 777-3270
 Nonprofit College or University

Quallion LLC proposes to continue development of its reference electrode technology into a commercial scale prototype and partner with the University of South Carolina to develop a life prediction model for cells cycled at high depths of discharge. In Phase II, Quallion will refine its reference electrode design based on lessons learned in Phase I, incorporate a reference electrode into commercial satellite cell designs, and build prototype cells with reference electrode for testing to validate their performance and to generate data for the modeling effort. Quallion will also build cells using the current 72Ah commercial cell design utilizing the new Gen2 chemistry and perform life testing on these cells at 60% DOD. The modeling effort will evaluate two methods of predicting capacity fade, one based on operational capacity checks and the other on on-line monitoring of parameters during cycling. Parameters will include data gathered by the reference electrode. Phase II will develop long-term cycling data on test regimes and further develop the model capability for prediction of cycle life under different test regimes and DODs.

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

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