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

Journal Article · · Journal of Electrochemical Energy Conversion and Storage
DOI:https://doi.org/10.1115/1.4044156· OSTI ID:1454680
 [1];  [2];  [3];  [3];  [4];  [3];  [5]
  1. Department of Chemical Engineering, University of Washington, Seattle, WA 98195
  2. Department of Chemical Engineering, Indian Institute of Technology Hyderabad, Kandi, Sangareddy 502285, Telangana, India
  3. Sandia National Laboratories, Albuquerque, NM 87185
  4. Department of Energy Science and Engineering, Indian Institute of Technology Bombay, Powai 400076, Mumbai, Maharashtra, India
  5. Department of Chemical Engineering, University of Washington, Seattle, WA 98195; Pacific Northwest National Laboratory, Richland, WA 99354

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 Laboratories (SNL-NM), Albuquerque, NM (United States)
Sponsoring Organization:
USDOE Office of Electricity Delivery and Energy Reliability (OE), Power Systems Engineering Research and Development (R&D) (OE-10)
DOE Contract Number:
AC04-94AL85000
OSTI ID:
1454680
Report Number(s):
SAND--2018-2540J; 661289
Journal Information:
Journal of Electrochemical Energy Conversion and Storage, Journal Name: Journal of Electrochemical Energy Conversion and Storage Journal Issue: 1 Vol. 17; ISSN 2381-6872
Publisher:
ASME
Country of Publication:
United States
Language:
English

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