Python Battery Mathematical Modelling (PyBaMM)

Sulzer, Valentin; Marquis, Scott G.; Timms, Robert; Martin, Randall V.; Chapman, S. Jon

doi:10.1149/osf.io/67ckj

Cited by 17 publications

(11 citation statements)

References 6 publications

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“…Presently, we generate a larger domain parametrically and introduce continuous tab boundary conditions for the current. The open source software PyBaMM is used for the electrochemistry 15,16 described by porous electrode theory, using the model of Doyle, Fuller and Newman (DFN) 17,18 and OpenPNM is used for the global current and thermal transport. 19 It is assumed that charge transport in the current collectors is one-dimensional along the spiral length, whereas charge transport in the electrodes and separator is one-dimensional in the direction normal to the current collectors (radially).…”

Section: Methodsmentioning

confidence: 99%

Communication—Prediction of Thermal Issues for Larger Format 4680 Cylindrical Cells and Their Mitigation with Enhanced Current Collection

Tranter

Timms

Shearing

et al. 2020

J. Electrochem. Soc.

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The paper numerically explores the electrochemical and thermal behaviour of a larger format 4680 cylindrical cell recently proposed by Tesla and explains the need to go "tabless." An idealized spiral geometry is used for 2D simulations with the traditional tab-based current collection method and a new continuous current collection method compared. The new design is found to mitigate the ohmic losses experienced around the "jelly-roll" current collectors which are significant for the traditional tabbed case, thus leading to higher efficiency and capacity and reduced heat production.

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Section: Methodsmentioning

confidence: 99%

Communication—Prediction of Thermal Issues for Larger Format 4680 Cylindrical Cells and Their Mitigation with Enhanced Current Collection

Tranter

Timms

Shearing

et al. 2020

J. Electrochem. Soc.

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“…To integrate the AD into the solution of an ODE system, the ODE solver should be compatible to these AD packages and the operations and functions in the ODE solver should be included in the computational graph of the AD packages. There are several modules satisfying these requirements such as the torchdiffeq 29 for Pytorch, the DifferentialEquations 30 for ForwardDiff and the PyBaMM 31 for Jax. In this work, we use the ForwardDiff and DifferentialEquations in the Julia language since they provides various differentiable ODE solvers that could handle various non-stiff and stiff problems.…”

Section: Automatic Differentiationmentioning

confidence: 99%

Evaluation of the degree of rate control via automatic differentiation

2022

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The degree of rate control (DRC) quantitatively identifies the kinetically relevant (sometimes known as rate‐limiting) steps of a complex reaction network. This concept relies on derivatives which are commonly implemented numerically, for example, with finite differences (FDs). Numerical derivatives are tedious to implement, and can be problematic, and unstable or unreliable. In this study, we demonstrate the use of automatic differentiation (AD) in the evaluation of the DRC. AD libraries are increasingly available through modern machine learning frameworks. Compared with the FDs, AD provides solutions with higher accuracy with lower computational cost. We demonstrate applications in steady‐state and transient kinetics. Furthermore, we illustrate a hybrid local‐global sensitivity analysis method, the distributed evaluation of local sensitivity analysis, to assess the importance of kinetic parameters over an uncertain space. This method also benefits from AD to obtain high‐quality results efficiently.

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“…Numerical simulations of the full model were performed using the commercial software COMSOL [7], while the reduced models were implemented in the opensource battery modeling package PyBaMM (Python Battery Mathematical Modelling) [37]. All simulations were performed on a desktop computer (i5 processor, 2.1GHz) with 16Gb of RAM.…”

Section: Comparison Of Modelsmentioning

confidence: 99%

Asymptotic Reduction of a Lithium-Ion Pouch Cell Model

Timms¹,

Marquis²,

Sulzer³

et al. 2021

SIAM J. Appl. Math.

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A three-dimensional model of a single-layer lithium-ion pouch cell is presented which couples conventional porous electrode theory describing cell electrochemical behavior with an energy balance describing cell thermal behavior. Asymptotic analysis of the model is carried out by exploiting the small aspect ratio typical of pouch cell designs. The analysis reveals the scaling that results in a distinguished limit and highlights the role played by the electrical conductivities of the current collectors. The resulting model comprises a collection of one-dimensional models for the through-cell electrochemical behavior which are coupled via two-dimensional problems for the Ohmic and thermal behavior in the planar current collectors. A further limit is identified which reduces the problem to a single volume-averaged through-cell model, greatly reducing the computational complexity. Numerical simulations are presented which illustrate and validate the asymptotic results.

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Python Battery Mathematical Modelling (PyBaMM)

Cited by 17 publications

References 6 publications

Communication—Prediction of Thermal Issues for Larger Format 4680 Cylindrical Cells and Their Mitigation with Enhanced Current Collection

Communication—Prediction of Thermal Issues for Larger Format 4680 Cylindrical Cells and Their Mitigation with Enhanced Current Collection

Evaluation of the degree of rate control via automatic differentiation

Asymptotic Reduction of a Lithium-Ion Pouch Cell Model

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