arXiv subjects

Ganesh Madabattula

Publications and source records attributed to Ganesh Madabattula.

3 recordsLinked to original sources

arXiv2026

Battery Recycling: Mechanistic Modelling of LiCoO$_2$ Leaching with Coupled Diffusion-Reaction Kinetics and Film Passivation

We developed a new mechanistic model for lithium and cobalt recovery during acidic-reductive leaching from LiCoO$_2$. The system considers HCl as an acid and H$_2$O$_2$ as a reducing agent. The model tracks conversion of LCO, the particle radius, the acid, H$_2$O$_2$, formation-dissolution dynamics of Co$_3$O$_4$ film, the film thickness, recovery of lithium and cobalt, and moles of O$_2$. We introduced the film passivation effects for reduced recovery in the absence of H$_2$O$_2$. We validated the model against the experimental data of recovered Li and Co reported in literature at three acid concentrations (0.5 M, 1.5 M, and 2.5 M) and four H$_2$O$_2$ concentrations (0%, 0.2%, 0.4%, and 0.6% (v/v)). The model works reasonably well at 0.5 M and 1.5 M HCl for the 0% and 0.6% concentrations of H$_2$O$_2$. At 2.5 M HCl, the model over-predicts the data in the presence of H$_2$O$_2$, while it works well at 0% H$_2$O$_2$. We suggest pathways for further improvements in the model. The comprehensive mechanistic modelling framework for the leaching with a full list of the equations, the parameters, and the variables, reported for the first time, can be extended to other cathode chemistries and acid-reductive leaching systems.

physics.chem-ph↗

arXiv2026

Linking Calendar and Cycle Ageing in Lithium-Ion Batteries through Consistent Parameterisation of an Electrochemical-Thermal-Degradation Model

Parameterisation of coupled degradation mechanisms in lithium-ion batteries is a major challenge. Interactions between the mechanisms depend on usage conditions: C-rate, rest state-of-charge (SoC), depth-of-discharge (DoD) and temperature. This work presents a framework to consistently parameterise key degradation modes--solid-electrolyte interphase (SEI) growth, lithium plating, and active material loss in both electrodes--using insights derived from degradation mode analysis data. The work predicts capacity fade trajectories of a NMC-based lithium-ion cell under both calendar and combined calendar-cyclic ageing, using a P2D electrochemical-thermal-degradation model. The work predicts state-of-health (SoH), remaining-useful-life (RUL) and internal degradation modes of the cell--under 81 combinations of temperature (10$^o$C, 25$^o$C, 40$^o$C), C-rate (0.1 C, 0.3 C and 1.0 C), rest SoC (10%, 60%, and 100%) and DoD (50%, 70%, and 90%)--using PyBaMM. The predicted cycle-life varies between 0.8 to 14 years to reach 75% of SoH. The work provides mechanistic insights into competing effects between calendar and cyclic ageing, during cycling. The model demonstrates sub-linear, linear, and sup-linear/accelerated capacity fade based on the usage conditions. The simulated dataset for all the cases is made available.

cond-mat.mtrl-sci↗

arXiv2022

Lithium-ion battery degradation: how to model it

Predicting lithium-ion battery degradation is worth billions to the global automotive, aviation and energy storage industries, to improve performance and safety and reduce warranty liabilities. However, very few published models of battery degradation explicitly consider the interactions between more than two degradation mechanisms, and none do so within a single electrode. In this paper, the first published attempt to directly couple more than two degradation mechanisms in the negative electrode is reported. The results are used to map different pathways through the complicated path dependent and non-linear degradation space. Four degradation mechanisms are coupled in PyBaMM, an open source modelling environment uniquely developed to allow new physics to be implemented and explored quickly and easily. Crucially it is possible to see 'inside' the model and observe the consequences of the different patterns of degradation, such as loss of lithium inventory and loss of active material. For the same cell, five different pathways that can result in end-of-life have already been found, depending on how the cell is used. Such information would enable a product designer to either extend life or predict life based upon the usage pattern. However, parameterization of the degradation models remains as a major challenge, and requires the attention of the international battery community.

physics.chem-ph↗