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

Journal Article · 27 September 2019 · Journal of Electrochemical Energy Conversion and Storage

DOI: https://doi.org/10.1115/1.4044156 · OSTI ID:1575257

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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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)

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.

• Research Organization: Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
• Sponsoring Organization: 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)
• Grant/Contract Number: AC04-94AL85000; NA0003525
• OSTI ID: 1575257
• Report Number(s): SAND-2019-5455J; 675548
• Journal Information: Journal of Electrochemical Energy Conversion and Storage, Vol. 17, Issue 1; ISSN 2381-6872
• Publisher: ASMECopyright Statement
• Country of Publication: United States
• Language: English