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Pulse Voltammetry Tools for Accurate and Rapid Analysis of Batteries

Award Information
Agency: Department of Defense
Branch: Army
Contract: W911NF-19-C-0084
Agency Tracking Number: A2-7845
Amount: $999,957.00
Phase: Phase II
Program: STTR
Solicitation Topic Code: A152-092
Solicitation Number: 15.2
Solicitation Year: 2015
Award Year: 2019
Award Start Date (Proposal Award Date): 2019-08-13
Award End Date (Contract End Date): 2021-08-01
Small Business Information
701 McMillian Way NW Suite D
Huntsville, AL 35806
United States
DUNS: 185169620
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 James V Cole
 Technical Fellow
 (256) 726-4800
Business Contact
 Tanu Singhal
Phone: (256) 726-4800
Research Institution
 Purdue University
 Lindsey Peabody Lindsey Peabody
155 S. Grant Street Young Hall - 715
West Lafayette, IN 47906
United States

 (765) 494-6204
 Nonprofit College or University

Pulse voltammetry techniques, coupled with model-based analysis tools, provide a number of advantages for quantitative analysis of electrochemically active materials that govern the performance of batteries and fuel cells. In prior Phase I and II research, CFD Research developed and validated computational models in software that reads voltammogram data from laboratory instruments; predicts the response of multistep electrochemical mechanisms from entire square wave voltammograms; and determines reaction kinetic parameters with statistical uncertainty quantification and mechanism discrimination. The analysis package was extended to address porous fuel cell and battery electrode applications. During this Phase II, we will partner with Purdue University to further develop and validate the analysis tools through battery characterization in support of the Hybrid-on-Hybrid Tactical UAS concept demonstration project. The team will use pulse voltammetry, related electrochemical measurement techniques, and complementary physical analysis to identify charge and discharge rate controlling processes for H2-TUAS batteries, quantify corresponding model parameters, and produce models for degradation during operational duty cycles including fast charge. The approach will be validated through applying and testing the resulting models for custom battery cell design, optimizing fast charging protocols, and generating compact models of state of charge and health for use in battery management systems.

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

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