Title: Open Data, Models, and Codes for Vanadium Redox Batch Cell Systems: A Systems Approach Using Zero-Dimensional Models

Abstract

Abstract In this paper, we study, analyze, and validate some important zero-dimensional physics-based models for vanadium redox batch cell (VRBC) systems and formulate an adequate physics-based model that can predict the battery performance accurately. In the model formulation process, a systems approach to multiple parameters estimation has been conducted using VRBC systems at low C-rates (~C/30). In this batch cell system, the effect of ions' crossover through the membrane is dominant, and therefore, the capacity loss phenomena can be explicitly observed. Paradoxically, this means that using the batch system might be a better approach for identifying a more suitable model describing the effect of ions transport. Next, we propose an efficient systems approach, which enables to help understand the battery performance quickly by estimating all parameters of the battery system. Finally, open source codes, executable files, and experimental data are provided to enable people's access to robust and accurate models and optimizers. In battery simulations, different models and optimizers describing the same systems produce different values of the estimated parameters. Providing an open access platform can accelerate the process to arrive at robust models and optimizers by continuous modification from the users' side.

Authors:

Lee, Seong Beom ^[1]; Mitra, Kishalay ^[2]; Pratt, Harry D. ^[3]; Anderson, Travis M. ^[3]; Ramadesigan, Venkatasailanathan ^[4]; Chalamala, Babu R. ^[3]; Subramanian, Venkat R. ^[5]

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+ Show Author Affiliations

1. Univ. of Washington, Seattle, WA (United States)
2. Indian Inst. of Technology (IIT), Telangana (India)
3. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
4. Indian Inst. of Technology (IIT), Mumbai (India)
5. Univ. of Washington, Seattle, WA (United States); Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

Publication Date:

Fri Sep 27 00:00:00 EDT 2019

Research Org.:

Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Sponsoring Org.:

USDOE Office of Electricity (OE); USDOE National Nuclear Security Administration (NNSA); USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V)

OSTI Identifier:

1575257

Report Number(s):

SAND-2019-5455J
Journal ID: ISSN 2381-6872; 675548

Grant/Contract Number:  

AC04-94AL85000; NA0003525

Resource Type:

Accepted Manuscript

Journal Name:

Journal of Electrochemical Energy Conversion and Storage

Additional Journal Information:

Journal Volume: 17; Journal Issue: 1; Journal ID: ISSN 2381-6872

Publisher:

ASME

Country of Publication:

United States

Language:

English

Subject:

25 ENERGY STORAGE; laboratory-scale batch cell; a systems approach; optimization; capacity loss; an open source platform; parameter estimation; executable files