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Lithium-ion batteries play a vital role in a society more and more affected by the spectre of climate change: hence the need of lowering CO2 emissions and reducing the fossil fuel consumption. At the moment, lithium-ion batteries appear as the ideal candidates for this challenge but further research and development is required to understand their behaviour, predict their issues and therefore improve their performance. In this regard, mathematical modelling and numerical simulation have become standard techniques in lithium-ion battery research and development and have proven to be highly useful in supporting experimental work and increasing the predictability of model-based life expectancy.
This study focuses on the electrochemical ageing reactions at the anode, especially on the topic of lithium plating and its interaction with the solid electrolyte interface (SEI). The purpose of this work is a deeper understanding of these degradation processes through the construction of refined modelling frameworks and the analysis of simulations carried out over a wide range of operating conditions. The governing equations are implemented in the in-house multiphysics software package DENIS, while the electrochemistry model is based on the use of the open-source chemical kinetics code CANTERA.
The development, parameterisation and experimental validation of a comprehensive pseudo-three-dimensional multiphysics model of a commercial lithium-ion cell with blend cathode and graphite anode is presented. This model is able to describe and simulate both multiscale heat and mass transport and complex electrochemical reaction mechanisms, including also as extra feature the capability of reproducing a composite electrode where multiple active materials are subject to intercalation/deintercalation reaction.
A further extension to include reversible lithium plating process and predict ageing behaviour over a wide range of conditions, with a focus on the high currents and low temperatures particularly interesting for the fast charging topic, follows. This extended model is verified by comparison with published experimental data showing voltage plateau and voltage drop as plating indicators and optionally includes an explicit re-intercalation reaction that is shown to suppress macroscopic plating hints in the specific case of a cell not showing evident plating signs. This model is used to create degradation maps over a wide range of conditions and an in-depth spatiotemporal analysis of the anode behaviour at the mesoscopic and microscopic scales, demonstrating the dynamic and nonlinear interaction between the intercalation and plating reactions.
A deeper outlook on the SEI formation and growth is presented, together with the qualitative description of three different 1D-models with a decreasing level of detail, developed with the purpose of ideally being included in future in more comprehensive multiscale frameworks.
Finally, the extended model is successfully coupled with a previously developed SEI model to result in an original modelling framework able to simulate both degradation processes and their continuous positive feedback.
The measurement of the active material volume fraction in composite electrodes of lithium-ion battery cells is difficult due to the small (sub-micrometer) and irregular structure and multi-component composition of the electrodes, particularly in the case of blend electrodes. State-of-the-art experimental methods such as focused ion beam/scanning electron microscopy (FIB/SEM) and subsequent image analysis require expensive equipment and significant expertise. We present here a simple method for identifying active material volume fractions in single-material and blend electrodes, based on the comparison of experimental equilibrium cell voltage curve (open-circuit voltage as function of charge throughput) with active material half-cell potential curves (half-cell potential as function of lithium stoichiometry). The method requires only (i) low-current cycling data of full cells, (ii) cell opening for measurement of electrode thickness and active electrode area, and (iii) literature half-cell potentials of the active materials. Mathematical optimization is used to identify volume fractions and lithium stoichiometry ranges in which the active materials are cycled. The method is particularly useful for model parameterization of either physicochemical (e.g., pseudo-two-dimensional) models or equivalent circuit models, as it yields a self-consistent set of stoichiometric and structural parameters. The method is demonstrated using a commercial LCO–NCA/graphite pouch cell with blend cathode, but can also be applied to other blends (e.g., graphite–silicon anode).