liionpack: A Python package for simulating packs of batteries with PyBaMM

Journal Article · 20 February 2022 · Journal of Open Source Software

DOI: https://doi.org/10.21105/joss.04051 · OSTI ID:1847507

Tranter, Thomas G.  ^[1]; Timms, Robert  ^[2]; Sulzer, Valentin  ^[3]; Planella, Ferran Brosa  ^[4]; Wiggins, Gavin M.  ^[5]; Karra, Suryanarayana Vikrant  ^[5]; Agarwal, Priyanshu  ^[6]; Chopra, Saransh  ^[7]; Allu, Srikanth  ^[5]; Shearing, Paul R.  ^[1]; Brett, Dan J. L.  ^[1]

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1. Univ. College London (United Kingdom); The Faraday Institution, OX (United Kingdom)
2. The Faraday Institution, OX (United Kingdom); Univ. of Oxford (United Kingdom)
3. Carnegie Mellon Univ., Pittsburgh, PA (United States)
4. The Faraday Institution, OX (United Kingdom); Univ. of Warwick, Coventry (United Kingdom)
5. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
6. Symbiosis International University, Lavale (India)
7. Univ. of Delhi (India)

Electrification of transport and other energy intensive activities is of growing importance as it provides an underpinning method to reduce carbon emissions. With an increase in reliance on renewable sources of energy and a reduction in the use of more predictable fossil fuels in both stationary and mobile applications, energy storage will play a pivotal role and batteries are currently the most widely adopted and versatile form. Therefore, understanding how batteries work, how they degrade, and how to optimize and manage their operation at large scales is critical to achieving emission reduction targets. The electric vehicle (EV) industry requires a considerable number of batteries even for a single vehicle, sometimes numbering in the thousands if smaller cells are used, and the dynamics and degradation of these systems, as well as large stationary power systems, is not that well understood. As increases in the efficiency of a single battery become diminishing for standard commercially available chemistries, gains made at the system level become more important and can potentially be realised more quickly compared with developing new chemistries. Mathematical models and simulations provide a way to address these challenging questions and can aid the engineer and designers of batteries and battery management systems to provide longer lasting and more efficient energy storage systems.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: Faraday Institution; USDOE Office of Electricity Delivery and Energy Reliability (OE)
• Grant/Contract Number: AC05-00OR22725
• OSTI ID: 1847507
• Journal Information: Journal of Open Source Software, Journal Name: Journal of Open Source Software Journal Issue: 70 Vol. 7; ISSN 2475-9066
• Publisher: Open Source Initiative - NumFOCUSCopyright Statement
• Country of Publication: United States
• Language: English