Abstract : Lithium-ion batteries have a very important role to play in the transition to a sustainable future. But despite the current widespread use of batteries, many of the phenomena involved in their functioning are not well understood. Mathematical models can be a fundamental tool to understand batteries and enable better design and management. In this minisymposium we will discuss the latest advances in the development and analysis of continuum models for lithium-ion batteries, with a particular focus on homogenised models and their applications to real-world problems. This minisymposium is part of the ECMI Special Interest Group on Sustainable Energies and Materials.
[03631] Asymptotic methods for lithium-ion battery models
Format : Talk at Waseda University
Author(s) :
Ferran Brosa Planella (University of Warwick)
Abstract : Lithium-ion batteries have become an essential in our lives, and to develop better and safer batteries we need accurate and fast models. Current models are often posed in an ad hoc way, which usually leads to inconsistencies. In this talk we will provide an overview of battery modelling, and show how asymptotic methods can help us obtain simple and consistent models that help us design and manage the next generation of batteries.
[05237] Topology Optimization for Li-ion batteries
Format : Talk at Waseda University
Author(s) :
Thomas Roy (Lawrence Livermore National Laboratory)
Hanyu Li (Lawrence Livermore National Laboratory)
Nicholas Brady (Lawrence Livermore National Laboratory)
Giovanna Bucci (Lawrence Livermore National Laboratory)
Tiras Lin (Lawrence Livermore National Laboratory)
Daniel Tortorelli (Lawrence Livermore National Laboratory)
Marcus Worsley (Lawrence Livermore National Laboratory)
Abstract : Typical porous electrodes are homogeneous, stochastic collections of small-scale particles offering few opportunities for engineering higher performance. To leverage recent breakthroughs in advanced and additive manufacturing, we use topology optimization to design electrodes for energy storage devices. Energy density is maximized, leading to non-trivial geometries that outperform monolithic electrodes. These geometries facilitate ionic transport and lead to better electrode utilization. We consider simultaneous optimization of cathode and anode, which can lead to interdigitated designs. LLNL-ABS-847750
[04263] Homogenisation and Modelling of a Silicon nanowire Li-ion battery anode
Format : Talk at Waseda University
Author(s) :
Emma Elizabeth Greenbank (MACSI, University of Limerick)
Michael Vynnycky (MACSI, University of Limerick)
Doireann O'Kiely (MACSI, University of Limerick)
Abstract : We consider a battery anode composed of an array of copper nanowires, coated with Li-carrying copper silicide and surrounded by Li-alloying electrolyte. This anode design alleviates degradation arising from extreme volumetric changes of silicon during lithiation. The governing equations for the electric and concentration fields inside the nanowire array structure are homogenised, and solutions of the homogenised problem are used to predict the transport of lithium through the anode.
[02731] A continuum model for lithium plating and dendrite formation in lithium-ion batteries.
Format : Talk at Waseda University
Author(s) :
Smita Sahu (University of Portsmouth)
Abstract : This work presents a novel physics-based model for lithium plating and dendrite formation in lithium-ion batteries. The formation of Li metal is an undesirable side-effect of fast charging and a primary contributor to cell degradation and failure. The model distinguishes between three types of plated Li metal, namely: (a) Li metal plated within the pores of the solid electrolyte interphase (assumed to be electronically connected to the anode and therefore recoverable); (b) dendrites protruding outside the SEI that remain electronically connected (and are therefore dangerous, potentially leading to a short circuit), and (c) electronically disconnected/“dead” Li metal outside the SEI contributing to capacity fade. The model is validated against two independent experiments. First, measurements of: (i) the cell voltage and current during a constant-current–constant-voltage charge and subsequent discharge, and (ii) the Li metal intensities (derived from operando NMR) which directly quantifies the time-resolved quantity of Li metal in the cell during use. Second, against voltage measurements during galvanostatic discharge at a range of C-rates and temperatures. Favourable agreement is demonstrated throughout; particularly in terms of the proportions of reversible and irreversible plating. We also demonstrate that the model reproduces the well-documented trends of being more prevalent at increased C-rate and/or decreased temperature.
[04505] Simulation and analysis of space charge layers in a solid electrolyte
Format : Talk at Waseda University
Author(s) :
Laura Marie Keane (York University)
Iain Moyles (York University)
Abstract : We consider the zero-charge flux equilibrium problem in a solid electrolyte. We introduce an auxiliary variable to remove singularities from the domain, facilitating robust numerical simulations. We use asymptotic reduction to uncover the true width of the boundary layer of the electrolyte. Exploiting the asymptotic regimes, we generate a nonuniform discretization grid enabling more computationally efficient simulations without sacrificing accuracy as we focus computational power in regions where the solution changes more rapidly.
[03112] Machine Learning of Electrochemistry Battery Models
Format : Talk at Waseda University
Author(s) :
Brian Wetton (University of British Columbia)
Maricela Best-Mckay (University of British Columbia)
Abstract : We present a surrogate modeling approach that uses synthetic data generated by an electrochemical model to approximate Li-ion battery dynamics using a Deep Neural Network. Our approach uses the Pseudo-Two Dimensional model and a well defined use-cycle, fit to a Network of convolution type for the particle concentrations. The Network is able to accurately predict future behaviour. Extensions to initial State of Charge correction and the identification of a State of Health parameter are given.
[05150] Parameterisation of reduced-order battery models from non-invasive characterisation
Format : Talk at Waseda University
Author(s) :
Nicola Courtier (University of Oxford)
Ross Drummond (University of Sheffield)
David Howey (University of Oxford)
Abstract : Robust parameterisation methods exist for equivalent circuit models of batteries but, to understand the underlying processes and battery design, electrochemical models are needed. Progress is limited by a lack of robust parameterisation methods for nonlinear systems of differential equations, containing parameters which are unidentifiable from non-invasive measurements. Reduced-order modelling offers a pathway to systematically estimate lumped parameters from data using prediction-error minimisation. Furthermore, we apply the measure-moment approach to optimisation to estimate optimal charging profiles.
[05185] Early prediction of battery remaining useful life using AI and physics
Format : Online Talk on Zoom
Author(s) :
Edwin Khoo (Institute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR))
Abstract : Accurate prediction of the remaining useful life (RUL) of a lithium-ion battery (LIB) using early cycle data aids in scheduling predictive maintenance, avoiding catastrophic failure during operation and optimizing battery manufacturing. In this talk, we discuss our recent work in building a hybrid deep learning model that combines physics-informed features with statistical features to achieve better generalization performance in early RUL prediction when benchmarked against several AI models. If time permits, we will also discuss our recent parametric study of LIB capacity fade using a cell OCV model.
